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OCTOBER 19-20, 2012 - YMCA University of Science & Technology

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NATIONAL CONFERENCE<br />

ON<br />

TRENDS AND ADVANCES IN MECHANICAL ENGINEERING<br />

TAME <strong>20</strong>12<br />

October <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Chief Patron<br />

H.E. Sh. Jagannath Pahadia Ji<br />

Governor <strong>of</strong> Haryana<br />

Patron<br />

Lt. Gen. (Retd.) K. S. Yadava<br />

PVSM, AVSM,SM,VSM<br />

Vice Chancellor, <strong>YMCA</strong> UST<br />

Co-Patron<br />

Mrs Shimla<br />

Registrar, <strong>YMCA</strong> UST<br />

Conference Chair<br />

Dr. Sandeep Grover<br />

Chairman & Pr<strong>of</strong>essor<br />

Mech. Engg.<br />

Convener<br />

Dr. Raj Kumar<br />

Pr<strong>of</strong>essor<br />

Mech. Engg<br />

Co-Convener<br />

Dr. Navdeep Malhotra<br />

Pr<strong>of</strong>essor<br />

Mech. Engg<br />

Organizing Secretary<br />

Dr. Vikram Singh<br />

Associate Pr<strong>of</strong>essor<br />

Mech. Engg<br />

Chief Editor<br />

Pr<strong>of</strong>. Raj Kumar<br />

Department <strong>of</strong> Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>,<br />

Faridabad, Haryana. 121006<br />

www.ymcaust.ac.in


National Conference on Trends and Advances in Mechanical Engineering<br />

TAME-<strong>20</strong>12<br />

OCT <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

PREFACE<br />

New developments bring change that usher the mankind to a better future. Technological innovations<br />

have reached a stage that incorporates the integration <strong>of</strong> different fields for the holistic developments.<br />

With innumerable specializations in the field <strong>of</strong> mechanical engineering, it becomes obligatory for<br />

pr<strong>of</strong>essionals and researchers to confer and transform their thoughts into more meaningful<br />

developments.<br />

To comply with such dynamic requirements, national conference on Trends and Advances in<br />

Mechanical Engineering (TAME <strong>20</strong>12) is being organised on October <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12. The conference is<br />

aimed at providing a common platform to researchers, industry personnel, academicians, students and<br />

participating pr<strong>of</strong>essionals to interact and discuss about the trends and advances made in the various<br />

areas <strong>of</strong> Mechanical Engineering.<br />

Conference Themes: Suggested themes include, but are not restricted to:<br />

Theme I: Thermal Engineering<br />

Heat Transfer, Fluid Dynamics, Alternative Refrigerants, Thermal Systems, Turbo Machinery,<br />

Renewable Energy, Energy conservation, Refrigeration & A/C<br />

Theme II: Design and Analysis<br />

CAD/CAE, Robotics, Mechatronics, Vibration Analysis, Condition Monitoring, Machine Design and<br />

Dynamics, Mechanisms, Tribology, Fracture Mechanics.<br />

Theme III: Production and Advanced Manufacturing Engineering<br />

CIM, E- Manufacturing, Group <strong>Technology</strong>, Rapid Prototyping and Reverse Engineering, Mechanical<br />

Metallurgy, Welding, Non Conventional Machining, Material testing, Smart Materials, Nano<br />

Materials, Composite Materials, Plastics, Fibre Reinforced Plastics, Flexible Manufacturing Systems.<br />

Theme IV: Industrial Engineering<br />

TQM, JIT, Reliability, Waste Management, Engineering, Concurrent Engineering, Operation<br />

Research, Ergonomics, SCM, ERP, Factories <strong>of</strong> Future, Production, Role <strong>of</strong> Computers in Mechanical<br />

Engineering, Planning and Control.<br />

TAME <strong>20</strong>12 is being organized by Department <strong>of</strong> Mechanical Engineering with ever encouraging<br />

response from the management and whole hearted support from different quarters in the <strong>University</strong> and<br />

outside. The teamwork <strong>of</strong> students and faculty equally would lead to the success <strong>of</strong> conference.<br />

Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad


National Conference on Trends and Advances in Mechanical Engineering<br />

TAME-<strong>20</strong>12<br />

OCT <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

NATIONAL ADVISORY COMMITTEE<br />

Pr<strong>of</strong>. B. John. Davies, Editor in chief, IJAMT, Springer<br />

Pr<strong>of</strong>. Pradeep Kumar, IIT, Roorkee<br />

Pr<strong>of</strong>. S. C Kaushik, IIT, Delhi<br />

Pr<strong>of</strong>. O P Gandhi, IIT, Delhi<br />

Pr<strong>of</strong>. Narendra K. Sharma, IIT Kanpur<br />

Pr<strong>of</strong>. Sunil Pandey, Director, SLIET, Longowal<br />

Pr<strong>of</strong>. S.K Sharma, NIT, Kurkshetra<br />

Pr<strong>of</strong>. H.K Rawal, NIT, Surat<br />

Pr<strong>of</strong>. M D Singh, MNIT, Allahabad<br />

Pr<strong>of</strong>. S. K. Mohapatra, TU, Patiala<br />

Pr<strong>of</strong>. I A Khan, JMI, New Delhi<br />

Pr<strong>of</strong>. Hari Singh, NIT, Kurukshetra<br />

Pr<strong>of</strong>. Keyur Desai, NIT, Surat<br />

Pr<strong>of</strong>. V.P Aggarwal, TU, Patiala<br />

Mr. Raj Bhatia, MD Bony polymers, FBD, President Alumni Association <strong>YMCA</strong> (MOB)<br />

Er. Ravikiran N K, Scientist, ISRO, Bangalore<br />

Dr. B R Ananda Murthy, ISRO, Bangalore<br />

Pr<strong>of</strong>. Dharmender Kumar, GJU, Hissar<br />

Dr. Sona Rani, UIET, K.U., Kurukshetra<br />

Mr. R. M. Mishra, CIPET, Lucknow<br />

Mr. Naveen Sood, MD, VEEGEE Industries, Faridabad<br />

Mr. Sukhdev Singh, Hind Hydraulics, Faridabad<br />

Mr. M.R. Salan, CIHT, Jalandhar<br />

Dr. U. Chandersekhar, Executive Convener RPSI, Bangalore<br />

Dr. A. Selvam, Executive Secretary, FRP Institute, Chennai<br />

Er. Manvinder Singh, MD, Bhiwadi Cylinders<br />

Mr. Praveen Khanna – Promoter <strong>of</strong> Suvidha Engineers<br />

Mr. Ramneek Bawa – Director & CEO <strong>of</strong> DS Construction Ltd.<br />

Mr Ashok Madan – GM (Projects) at HCL Technologies<br />

INTERNAL ADVISORY COMMITTEE<br />

Dr. A. K. Sharma, Pr<strong>of</strong>. and Dean, Engg & Tech.<br />

Dr. Sandeep Grover, Pr<strong>of</strong>. and Chairman, Mech Engg.<br />

Dr. Tilak Raj, Pr<strong>of</strong>essor (Mech. Engg.)<br />

Dr. M. L. Aggarwal, Pr<strong>of</strong>essor (Mech. Engg.)<br />

Dr. Raj Kumar, Pr<strong>of</strong>essor (Mech. Engg.)<br />

Dr. Navdeep Malhotra, Pr<strong>of</strong>essor (Mech. Engg.)<br />

Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad


National Conference on Trends and Advances in Mechanical Engineering<br />

TAME-<strong>20</strong>12<br />

OCT <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Local Organizing Teams for TAME <strong>20</strong>12<br />

S.No Work Domain Team Members<br />

1 Technical Team Pr<strong>of</strong>. Sandeep Grover<br />

Pr<strong>of</strong>. M.L. Aggarwal<br />

Pr<strong>of</strong>. Raj Kumar<br />

Pr<strong>of</strong> Tilak Raj<br />

Pr<strong>of</strong>. Navdeep Malhotra<br />

Dr Vikram Singh<br />

Dr Arvind Gupta<br />

Sh Naresh Yadav<br />

Dr Vikas Kumar<br />

Sh Hari Om<br />

Sh Lakhwinder Singh<br />

Dr NL Mangla<br />

Dr Sanjeev Kumar,<br />

Dr. Sanjeev Goyal<br />

Dr. Rajeev Saha<br />

Dr. Kamal Jangra<br />

Sh. Nikhil Dev<br />

Sh. Rajesh Kumar Attri<br />

Sh. Bhupender Singh<br />

2 Editorial Committee for Souvenir &<br />

Proceedings<br />

3 Registration<br />

&<br />

Dr. Sandeep Grover<br />

Dr. Raj Kumar<br />

Dr. Navdeep Malhotra<br />

Dr. Vikram Singh<br />

Dr. Niranjan Mangla<br />

Dr. Sanjeev Kumar<br />

Dr. Sanjeev Goyal<br />

Dr. Rajeev Saha<br />

Dr. Kamal Jangra<br />

Sh Hari Om<br />

Dr Sanjeev Kumar<br />

Sh Sanjay Kumar<br />

Prize/ Certificate<br />

4 Boarding Lodging & Refreshment Dr Munish Vashishth<br />

Sh Lakhwinder Singh<br />

Sh Mahesh Chand<br />

Sh Bhupinder Singh<br />

Sh Manmohan Kakkar<br />

Sh Sanjay Yadav<br />

Sh Mahinder<br />

Sh Suresh Kumar<br />

5 Event Management(Pre conference Press<br />

meet, Inauguration & Valedictory)<br />

Dr Vikram singh<br />

Dr Sanjeev Goyal<br />

Dr Kamal kumar<br />

6 Printing & Banners Dr Vasdev Malhotra<br />

Sh Surinder Singh<br />

Sh Sanjay Kumar<br />

7 Purchase Sh Naresh Yadav<br />

Sh J.P. Sharma<br />

8 Maintenance & Facelift Sh O.P. Mishra<br />

Sh Anil Kumar, JE<br />

Sh Manmohan Kakkar<br />

Sh Dinesh<br />

9 Session Venue coordinators Sh Mukesh Gupta<br />

Sh Mahesh Chand<br />

10 Technical Session Coordinators Sh Mukesh Gupta<br />

Dr Sanjeev Goyal<br />

Sh Nikhil Dev<br />

Dr Kamal Kumar<br />

Sh O P Mishra<br />

Sh Surinder Singh<br />

Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad


National Conference on Trends and Advances in Mechanical Engineering<br />

TAME-<strong>20</strong>12<br />

OCT <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

ABOUT THE UNIVERSITY<br />

The <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad, erstwhile, '<strong>YMCA</strong><br />

Institute <strong>of</strong> Engineering, the Institute has been granted <strong>University</strong> status since 1st<br />

December, <strong>20</strong>09 (Established by Haryana State Legislative Act No. 21 <strong>of</strong> <strong>20</strong>09 and<br />

recognized by UGC Act <strong>19</strong>56 u/s 22 to Confer Degrees). The <strong>University</strong> has recently<br />

been accorded 12B status by <strong>University</strong> Grant Commission (UGC).<br />

The <strong>University</strong> is situated right on the National Highway No.2 (Mathura Road) 32 Kms.<br />

from the National Capital New Delhi on way to the Taj Mahal, Agra. The <strong>University</strong> has<br />

its own Campus on a plot area <strong>of</strong> <strong>20</strong> acres. It is located in the growing and sprawling<br />

Faridabad Ballabgarh Industrial Complex <strong>of</strong> Haryana. The <strong>University</strong> is well connected<br />

with rail transport from New Delhi.<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong> is a pioneer Institution that has been<br />

providing qualified, trained manpower to the industry since its inception. It has produced<br />

large number <strong>of</strong> entrepreneurs who are actively contributing to the socio – economical<br />

development <strong>of</strong> the country in general and the state <strong>of</strong> Haryana in particular. The<br />

<strong>University</strong> has contributed immensely in the field <strong>of</strong> technical education and plays an<br />

important role in creating highly skilled technical manpower which is employable in an<br />

equally competitive market.<br />

The <strong>University</strong> <strong>of</strong>fers 4-year B.Tech. degree course in six disciplines i.e. Mechanical,<br />

Information <strong>Technology</strong>, Computers, Electronics - Communication, Electrical and<br />

Electronics-Instrumentation & Control.<br />

The <strong>University</strong> also <strong>of</strong>fers Post Graduate courses viz. M.Tech. in Mechanical Engg /<br />

Electrical Engg / Electronics Engg / Computers/ Networking / Information <strong>Technology</strong>,<br />

MBA, MCA, MSc, and Ph.D. in all streams.<br />

Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad


National Conference on Trends and Advances in Mechanical Engineering<br />

TAME-<strong>20</strong>12<br />

OCT <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

ABOUT THE DEPARTMENT<br />

The Department <strong>of</strong> Mechanical Engineering <strong>of</strong>fers courses at UG and PG level. At UG<br />

level, B.Tech. course in Mech. Engg., started in <strong>19</strong>97 has an intake <strong>of</strong> 1<strong>20</strong> students.<br />

M.Tech. programme in Mech. Engg. with specialization in Manufacturing <strong>Technology</strong><br />

and Automation was started from the academic year <strong>20</strong>03-04 and has an intake <strong>of</strong> 18<br />

students. The <strong>University</strong> has started PhD Course since <strong>20</strong>10 and 53 students have<br />

registered themselves for the PhD programme in the department.<br />

The Department <strong>of</strong> Mechanical Engineering has a distinguished record in both<br />

teaching and research. The department was shifted to the new building in January <strong>20</strong>09<br />

with modern facilities and a dedicated technical and <strong>of</strong>fice staff to support the academic<br />

programs and research.<br />

The department is actively engaged in research work in the broad area <strong>of</strong> Design<br />

<strong>of</strong> Mechanical Equipment, Design & Manufacturing, Thermal, Energy conservation,<br />

TQM, Product and Service Quality, Computer Integrated Manufacturing, E-<br />

Manufacturing, Computer Aided Engineering, Just in Time, etc.<br />

The departmental facilities include 16 labs, 3 workshops (Machine Tools,<br />

Refrigeration & Air conditioning, Fabrication & Sheet Metal <strong>Technology</strong>), 8 lecture<br />

halls, 1 conference room and 1 seminar hall with internet connectivity <strong>of</strong> 1Mbps.<br />

The department has highly qualified and experienced faculty including 5<br />

pr<strong>of</strong>essors, 9 Associate pr<strong>of</strong>essors and 16 Assistant Pr<strong>of</strong>essors. 15 <strong>of</strong> the faculty<br />

members are PhD holders with average experience <strong>of</strong> faculty members being<br />

approximately 13years.<br />

The department also sponsors its faculty for short term courses and conferences on<br />

regular basis. During last 3 years, faculty members have published approximately <strong>20</strong>0<br />

papers in various national and international journals and conferences <strong>of</strong> repute.<br />

The department is also highly active in co-curricular and technical activities. Two<br />

<strong>of</strong> its club namely MechNext Club and SAE India <strong>YMCA</strong> Collegiate Club are actively<br />

engaged in practising latest developments in concerned engineering field.<br />

Dr. Sandeep Grover<br />

Pr<strong>of</strong>essor & Chairman<br />

Department <strong>of</strong> Mechanical Engg.<br />

Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad


National Conference on Trends and Advances in Mechanical Engineering<br />

TAME-<strong>20</strong>12<br />

OCT <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

DEPARTMENT OF MECHANICAL ENGINEERING<br />

S. No. Name Designation Qualification<br />

1 Dr. Sandeep Grover Pr<strong>of</strong>essor & Chairman PhD<br />

2 Dr. M.L. Aggarwal Pr<strong>of</strong>essor PhD<br />

3 Dr. Tilak Raj Pr<strong>of</strong>essor PhD<br />

4 Dr. Raj Kumar Pr<strong>of</strong>essor PhD<br />

5 Dr. Navdeep Malhotra Pr<strong>of</strong>essor PhD<br />

6 Mr. Naresh Yadav Workshop Supdt. M.E.<br />

7 Dr. Vikram Singh Associate Pr<strong>of</strong>. PhD<br />

8 Dr. Arvind Gupta Associate Pr<strong>of</strong>. PhD<br />

9 Mr. Hari Om Associate Pr<strong>of</strong>. M.E.<br />

10 Dr. Vikas Turk Associate Pr<strong>of</strong>. PhD<br />

11 Mr. Lakhwinder Singh Associate Pr<strong>of</strong>. M.E.<br />

12 Dr. Niranjan Mangla Associate Pr<strong>of</strong>. PhD<br />

13 Dr. Sanjeev Kumar Associate Pr<strong>of</strong>. PhD<br />

14 Mr. Surinder Raina Associate Pr<strong>of</strong>. M.Tech.<br />

15 Mr. Mukesh Gupta Asst. Pr<strong>of</strong>. M.Tech.<br />

16 Dr. Vasdev Malhotra Asst. Pr<strong>of</strong>. PhD<br />

17 Ms. Sandhya Dixit Asst. Pr<strong>of</strong>. M.Tech.<br />

18 Dr. Sanjeev Goyal Asst. Pr<strong>of</strong>. PhD<br />

<strong>19</strong> Dr. Rajeev Saha Asst. Pr<strong>of</strong>. PhD<br />

<strong>20</strong> Dr. Kamal Jangra Asst. Pr<strong>of</strong>. PhD<br />

21 Mr. Bhaskar Nagar Asst. Pr<strong>of</strong>. M.E.<br />

22 Mr. Nikhil Dev Asst. Pr<strong>of</strong>. M.E.<br />

23 Mr. Rajesh Kumar Attri Asst. Pr<strong>of</strong>. M.Tech.<br />

24 Mr. Krishan Verma Asst. Pr<strong>of</strong>. M.Tech.<br />

25 Mr. Mahesh Chand Asst. Pr<strong>of</strong>. M.E.<br />

26 Mr. Om Prakash Mishra Asst. Pr<strong>of</strong>. M.Tech.<br />

27 Mr. Surender Singh Asst. Pr<strong>of</strong> M.Tech.<br />

28 Mr. Bhupender Singh Asst. Pr<strong>of</strong>. M.Tech.<br />

29 Ms. Shefali Trivedi Asst. Pr<strong>of</strong>. M.Tech.<br />

30 Mr. Sanjay Kumar Asst. Pr<strong>of</strong> M.E.<br />

31 Mr. Manmohan Kakkar Technical Support Staff M.Tech.<br />

32 Mr. Dinesh Arora Support Staff<br />

Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad


MESSAGE<br />

It gives me immense pleasure to note that <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>,<br />

Faridabad is organizing a National Conference on "Trends and advances in<br />

Mechanical Engineering (Tame <strong>20</strong>06)" during October <strong>19</strong>th - <strong>20</strong>th <strong>20</strong>12.<br />

The Conference aims at providing a common platform to researchers, industry<br />

personnel, academicians, pr<strong>of</strong>essionals and other participants to interact and discuss<br />

the latest trends and advances in different fields in Mechanical Engineering, I am sure<br />

that the Conference will enthuse and inspire students and members <strong>of</strong> teaching faculty<br />

to actively participate and gain new insight in this field. I hope the outcomes and<br />

recommendations <strong>of</strong> this Conference will be utilized for promotion <strong>of</strong> research and<br />

development in the relevant field in market and industry and also by the academicians.<br />

I wish the organizers all success for the Conference.<br />

Sh. Dhanpat Singh, IAS,<br />

Principal Secretary to Govt. <strong>of</strong> Haryana,<br />

Technical Education Department,<br />

Room No. 606, 6th Floor,<br />

New Haryana Civil Secretariat Building,<br />

Sector- 17, Chandigarh.


MESSAGE<br />

I am pleased to learn that the Department <strong>of</strong> Mechanical Engineering <strong>of</strong> our <strong>University</strong><br />

is organizing a National Conference on "Trends and Advances in Mechanical<br />

Engineering (TAME <strong>20</strong>12)" during October <strong>19</strong>th - <strong>20</strong>th, <strong>20</strong>12.<br />

In recent years the advancement in Information <strong>Technology</strong> and computer sciences<br />

has brought a sea change in Mechanical Engineering. The integration <strong>of</strong> different<br />

engineering branches has resulted in tremendous technological advances in<br />

Mechanical Engineering. This is a proper time for Indian researchers to meet their<br />

counterparts and discuss various aspects <strong>of</strong> resources and utilization for increased<br />

productivity.<br />

I trust that this conference would also inspire the participants to develop and introduce<br />

new research activities for the future corporate world. These researches will also be <strong>of</strong><br />

great and incredible value to the humankind.<br />

My warm felicitations to the organizers, to all the participating delegates and best<br />

wishes for success <strong>of</strong> the National Conference, TAME <strong>20</strong>12.<br />

Lt. Gen.(Retd.) K.S. Yadava<br />

PVSM, AVSM, SM, VSM<br />

Vice-Chancellor<br />

<strong>YMCA</strong>UST, Faridabad


MESSAGE<br />

It is a matter <strong>of</strong> great and elated feeling that a National Conference on "Trends &<br />

Advances in Mechanical Engineering" is being organized by the Department <strong>of</strong><br />

Mechanical Engineering <strong>of</strong> <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad from<br />

<strong>19</strong>th & <strong>20</strong>th October, <strong>20</strong>12. It is a great stride for the department in the direction <strong>of</strong><br />

achieving excellence in the field <strong>of</strong> mechanical engineering and indeed a proud<br />

moment for all <strong>of</strong> us in the <strong>University</strong>.<br />

Such Conferences provide an opportunity to the scholars and pr<strong>of</strong>essionals who have<br />

propensity towards research, to explore and share the research findings with the<br />

academic fraternity. The organizers have put their best efforts in going in a very<br />

systematic way and out reaching to the researchers countrywide. The result has been<br />

excellent.<br />

More than 150 research papers have been received from far and wide, exhibiting keen<br />

interest in sharing the new trends and advances in the area <strong>of</strong> mechanical<br />

engineering.<br />

The endeavour to bring out the selected papers in the form <strong>of</strong> a souvenir is really<br />

commendable.<br />

I, on behalf <strong>of</strong> the <strong>University</strong> administration and on my own behalf extend a very warm<br />

welcome to all the participants as our esteemed guests to the <strong>University</strong> Campus.<br />

I extend my whole hearted support and best wishes to the organizing Department, coordinators<br />

and participants in their efforts.<br />

I trust that the Conference is going to be a resounding success and provide a vibrant<br />

platform for learning and sharing <strong>of</strong> latest trends in this important area as well as<br />

strengthen the linkage between the academia and industry.<br />

My best wishes<br />

Mrs. Shimla<br />

Registrar<br />

<strong>YMCA</strong>UST, Faridabad


Sr.<br />

No<br />

Proceedings <strong>of</strong> National Conference on Trends and Advances in Mechanical Engineering<br />

TAME-<strong>20</strong>12 OCT <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Paper Title Authors Page<br />

No.<br />

THEME I – THERMAL ENGINEERING<br />

01 Study <strong>of</strong> Solar Water Heaters Based on Exergy Analysis Dilip Johari<br />

Ashok Yadav<br />

02 Green Vehicle: Pollution Control Through Catalytic<br />

Converter and Performance Analysis <strong>of</strong> the same<br />

03 Performance Investigation <strong>of</strong> a Compact Tri-Generation<br />

System Based on Renewable Energy Power Plant Exhaust<br />

Gas Waste Heat Utilization<br />

04 Decomposition <strong>of</strong> Energy Consumption In India: A<br />

Discussion in Context to Index Decomposition Analysis (IDA)<br />

i<br />

Ravi Verma<br />

Pankaj Agarwal<br />

Manish Jain<br />

Dr. Raj Kumar<br />

Anil Kumar<br />

Ponnala Vimal Mosahari<br />

D. Ganeshwar Rao<br />

Rajeev Satsangi<br />

1-8<br />

9-16<br />

17-21<br />

22-26<br />

05 Thermo-Economic Optimization <strong>of</strong> Work Consuming Devices Rajesh Arora 27-34<br />

06 Clean Coal Technologies for Power Generation in India A<br />

near Zero emission plant approach<br />

07 Limitations <strong>of</strong> Energy Utilization <strong>of</strong> Solid Waste due to it’s<br />

Poor Quality<br />

08 A Feasibility Study on Waste Heat Recovery in An IC Engine<br />

Using Electro Turbo Generation<br />

09 Reducing Battery Discharging Rate Using Photo-Electric<br />

Effect<br />

10 Thermodynamic Modelling <strong>of</strong> Ground Source Heat Pump for<br />

Space Heating<br />

Siddhartha<br />

Dr. Navdeep Malhotra<br />

Desh Deepak Johri<br />

Manish Gaur<br />

Sachin Rathod<br />

S.N.Srinivasa Dhaya Prasad<br />

N.Parameshwari<br />

Jeet Kumar Gaur<br />

Abhinav Mittal<br />

Bikash Chandra Maurya<br />

Rajeev Satsangi<br />

Ashok Yadav<br />

Ponnala Vimal Mosahari<br />

11 Alternatives to R134A (CF 3 CH 2 F) Refrigerant- A Review Gaurav<br />

Dr. Raj Kumar<br />

12 A Review <strong>of</strong> Combined Cycle Power Plant Thermodynamic<br />

Cycles<br />

13 A Review on Parabolic Trough Type Solar Collectors:<br />

Innovation, Applications and Thermal Energy Storage<br />

14 Study <strong>of</strong> Flow and Heat Transfer in Plate Fin Heat<br />

Exchanger at Varying Reynold’s Number<br />

15 Performance Improvement <strong>of</strong> a Control Valve Using<br />

Computational Fluid Dynamics<br />

Nikhil Dev<br />

Samsher<br />

S. S. Kachhwaha<br />

Rajesh Attri<br />

35-47<br />

48-54<br />

55-60<br />

61-65<br />

66-72<br />

73-77<br />

78-89<br />

Devander Kumar Lamba 90-99<br />

Pardeep Yadav<br />

Pawan Kumar<br />

K Thanigavelmurugan<br />

N.V. Mahalakshmi<br />

S. Mohan Das<br />

D. Venkatesh<br />

16 CFD Application in Passive Building Designs Ali A. F. Al-Hamadani<br />

S. K. Shukla<br />

Alok K.Dwivedi<br />

17 Energy Audit <strong>of</strong> 250 MW Thermal Power Stations, PTPS,<br />

Panipat<br />

18 Thermodynamic Analysis <strong>of</strong> Ground Source Heat Pump for<br />

Space Heating Using R-22<br />

Vikrant Bhardwaj<br />

Rohit Garg<br />

Mandeep Chahal<br />

Baljeet Singh<br />

Surender Nain<br />

Sanjeev Kumar<br />

Vikrant Bhardwaj<br />

Narender Mann<br />

Parveen Kumar<br />

100-105<br />

106-113<br />

114-1<strong>19</strong><br />

1<strong>20</strong>-125<br />

126-131


Proceedings <strong>of</strong> National Conference on Trends and Advances in Mechanical Engineering<br />

TAME-<strong>20</strong>12 OCT <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

<strong>19</strong> Effect <strong>of</strong> Roughness on Secondary Flow in a Rectilinear<br />

Turbine Cascade<br />

<strong>20</strong> An Overall Evaluation <strong>of</strong> Flow Characteristics and<br />

Performance Parameters <strong>of</strong> Y-Shaped Diffusing Duct with<br />

Same Angle <strong>of</strong> Turn and Different Centerline Length and<br />

Radius <strong>of</strong> Curvature<br />

21 Review <strong>of</strong> Different Technologies in the Solar Absorption<br />

Air-Conditioning Systems<br />

22 Energy Method for Performance Evaluation <strong>of</strong> a Boiler in a<br />

Coal Fired Thermal Power Plant: A Review<br />

23 Shell Side CFD Analysis <strong>of</strong> a Small Shell-and-Tube Heat<br />

Exchanger Considering the Effects <strong>of</strong> Baffle Inclination on<br />

Fluid Flow<br />

24 Performance Based Comparative Analysis <strong>of</strong> Thermal Power<br />

Plant: A Review<br />

25 Exergetic Analysis <strong>of</strong> Combustion Chamber <strong>of</strong> a Combined<br />

Heat and Power System<br />

26 Applications <strong>of</strong> Artificial Neural Network in Solar Thermal<br />

Systems: A Review<br />

27 Thermodynamic Analysis for Improvement in Thermal<br />

Performance <strong>of</strong> A Simple Gas Turbine Cycle Through<br />

Retr<strong>of</strong>itting Techniques (Inlet Air Evaporative Cooling,<br />

Steam Injection and Combined IAC and STIG)<br />

Vinod Kumar Singoria<br />

Deepika Sharma<br />

Dr. Samsher<br />

Netrapal Singh<br />

Abdur Rahim<br />

Md. Islam<br />

Vinod Sehrawat<br />

Tarun Gupta<br />

Dr. Raj Kumar<br />

Mukesh Gupta<br />

Raj Kumar<br />

Abdur Rahim<br />

S.M.Saad Jameel<br />

Manmohan Kakkar<br />

Raj Kumar<br />

Nikhil Dev<br />

Rajesh Attri<br />

Naveen Sharma<br />

Manish Kumar Chauhan<br />

Rajesh Kumar<br />

Shyam Agarwal<br />

R.S. Mishra<br />

132-141<br />

142-152<br />

153-161<br />

162-166<br />

167-173<br />

174-179<br />

180-187<br />

188-<strong>19</strong>4<br />

<strong>19</strong>5-<strong>20</strong>5<br />

28 Time Dependent Analysis <strong>of</strong> Cooling Load Using FDM Sachin Gupta<br />

<strong>20</strong>6-216<br />

Approach<br />

Arvind Gupta<br />

29 Use <strong>of</strong> Biogas for Cooking Purpose in a Technical Institute: A Indraj Singh 217-2<strong>20</strong><br />

View Point<br />

30 CFD Modeling for Pneumatic Conveying Arvind Kumar<br />

D.R. Kaushal<br />

Navneet Kumar<br />

221-227<br />

31 Electronic Waste Management in India Abhinav Kumar Shrivastava<br />

Sorabh<br />

228-233<br />

32 Alternatives <strong>of</strong> Freons Praveen 234-239<br />

33 Waste to Energy: Using MSW <strong>of</strong> Katra Town for Electricity<br />

240-245<br />

Generation<br />

THEME II – DESIGN & ANALYSIS<br />

34 Path Synthesis <strong>of</strong> 4-Bar Linkages with Joint Clearances<br />

Using De Algorithm<br />

35 Stochastic Thermal Buckling Response <strong>of</strong> Laminated<br />

Composite Plate Resting on Elastic Foundation Based on<br />

Micromechanical Model<br />

Sona Rani<br />

Prabhat Shankar<br />

Navdeep Malhotra<br />

Munish Kohli<br />

Ruby Mishra<br />

T.K.Naskar<br />

Sanjib Acharya<br />

Rajiv Kumar<br />

Amit Sharma<br />

Rajesh Kumar<br />

246-257<br />

258-267<br />

36 An Introduction to Structural Health Monitoring: A Smart<br />

Solution<br />

37 Predicting Wind Turbine Design Parameter Using Actuator<br />

Disk Theory as a Rotational Basis<br />

Vikash Kumar<br />

Dr. Sanjeev Kumar<br />

Dr. Vikram Singh<br />

Hari Pal Dhariwal<br />

Barun Kumar Roy<br />

Bhupender Yadav<br />

268-271<br />

272-274<br />

ii


Proceedings <strong>of</strong> National Conference on Trends and Advances in Mechanical Engineering<br />

TAME-<strong>20</strong>12 OCT <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

38 Shape Optimization to Utilize Pressure Difference at Front<br />

and Rear <strong>of</strong> the Body<br />

Amit Chauhan<br />

275-281<br />

Nadish Saini<br />

Shivam<br />

Udit Dureja<br />

Narender Panwar<br />

Amit Chauhan 282-288<br />

39 Investigations <strong>of</strong> the Variation <strong>of</strong> Bush Temperature <strong>of</strong> an<br />

Offset-Halves Journal Bearing Pr<strong>of</strong>ile<br />

40 Navigation Control and Localization <strong>of</strong> Mobile Robot Meghana S<br />

Dr. D.N Drakshayani<br />

41 Fuzzy Control <strong>of</strong> Semi-Active Quarter Car Suspension Devdutt<br />

System with MR Damper<br />

Dr. M.L. Aggarwal<br />

42 Stress Distribution Analysis <strong>of</strong> A Rotating Hyperelastic Vane<br />

with the Finite Element Method<br />

Pratik D Upadhyay<br />

Akshay J Patel<br />

43 Study <strong>of</strong> Uncoiling in Suspension Springs its Effects Kushal A Jolapara<br />

Adhip Puttaraj<br />

Abhishek Chatterjee<br />

44 Factors Affecting the Automatic Rain Sensing Wiper System Rahul Sindhwani<br />

Vasdev Malhotra<br />

45 Failure Analysis and Counter Measure <strong>of</strong> Capacitor Leads Santoshkumar Joshi<br />

Used in Automotive PCBs<br />

Dr. D. N. Shivappa<br />

46 Analysis <strong>of</strong> Brake Spongy Defect in Passenger Vehicle and<br />

Developing the Counter Measures – QI Case Study<br />

Venkatesh Madhyastha<br />

M. Chethan<br />

Dr D N Shivappa<br />

Santosh S Navada<br />

289-295<br />

296-304<br />

305-311<br />

312-321<br />

322-323<br />

324-333<br />

334-346<br />

47 Virtual Reality in Design: User Training and Evaluation: Harish Pungotra 347-355<br />

48 Slab Width Measurement Technique Using Manipulator in Anand S. Srivastava 356-360<br />

Plate Rolling Mill <strong>of</strong> Bhilai Steel Plant (Sail)<br />

Krishna K. Saxena<br />

49 FEM Analysis <strong>of</strong> Copper Using Equal Channel Angular<br />

Pressing<br />

Neeraj Saraswat<br />

Rahul Jain<br />

361-364<br />

Rajnish Saxena<br />

50 Solar Electric Vehicle: A Sustainable Mode <strong>of</strong> Transport Dr Samsher Gautam<br />

Team Solaris<br />

51 Deflection and Stress Analysis <strong>of</strong> Brake Disc Using Finite<br />

Element Method<br />

52 To Eliminate Big End Over Size Rejection by Sizing Plug<br />

Gauge on Connecting Rod Honing Machine: A Case Study<br />

Atul Sharma<br />

M.L. Aggarwal<br />

Aditya Singh<br />

Rajeev Saha<br />

53 Design <strong>of</strong> IIR Band Pass Filter Using Time Domain Approach Ruchika Singh<br />

Munish Vashisht<br />

54 Finite Element Analysis <strong>of</strong> Beam Hasan Zakir Jafri<br />

Pr<strong>of</strong>. I.A. Khan<br />

S.M. Muzakkir<br />

55 Design and Optimisation <strong>of</strong> Robotic Gripper : A Review Vaibhav Raghav<br />

Jitender Kumar<br />

Shailesh S.Senger<br />

THEME III – PRODUCTION ENGINEERING<br />

56 Electrical Discharge Machining <strong>of</strong> Aluminium Metal Matrix<br />

Composites- A Review<br />

Bhaskar Chandra Kandpal<br />

Jatinder Kumar<br />

Hari Singh<br />

365-371<br />

372-376<br />

377-383<br />

384-389<br />

390-396<br />

397-400<br />

401-405<br />

57 Modelling <strong>of</strong> Surface Roughness in WEDM for HSLA Using<br />

Response Surface Methodology<br />

Neeraj Sharma<br />

Kamal Jangra<br />

58 E-Manufacturing Concept: A Review Naveen Virmani<br />

Dr. Rajeev Saha<br />

59 Investigation <strong>of</strong> the Effect <strong>of</strong> Process Parameters on Surface Dharmender<br />

Roughness in Wire Electric Discharge Machining <strong>of</strong> En31 Rajeev Kumar<br />

Tool Steel<br />

Anmol Bhatia<br />

iii<br />

406-412<br />

413-416<br />

417-423


Proceedings <strong>of</strong> National Conference on Trends and Advances in Mechanical Engineering<br />

TAME-<strong>20</strong>12 OCT <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

60 Flexible Manufacturing Systems: Recent Development and<br />

Trends<br />

61 Computer Integrated Manufacturing: A Powerful Technique<br />

for Improving Productivity<br />

62 Influence <strong>of</strong> Drilling Parameters on Thrust Force in Drilling<br />

<strong>of</strong> SiC and Graphite Reinforced Aluminium Matrix<br />

Composites by Step Drill<br />

63 Modelling for Machining Speed in WEDM <strong>of</strong> Wc-5.3%Co<br />

Composite Using Response Surface Methodology<br />

64 Effect <strong>of</strong> Tool Shape on Tensile Strength in Single and<br />

Sequential Double Sided Friction Stir Weld on AA1100<br />

Aluminum Alloy<br />

65 Study <strong>of</strong> Various Mechanical Properties <strong>of</strong> Fiber Reinforced<br />

Cast Iron<br />

66 Application <strong>of</strong> Fiber Reinforced Plastics or Polymers in Civil<br />

Engineering Structures<br />

67 Analysis <strong>of</strong> the Depth <strong>of</strong> Penetration Using Automatic<br />

Robotic Arc Welding System<br />

68 Application <strong>of</strong> Taguchi Method and Grey Relational Analysis<br />

in Optimization <strong>of</strong> Machining Processes: A Review<br />

69 To Study the Effect <strong>of</strong> Polarity and Current During Electric<br />

Discharge Machining <strong>of</strong> Inconel 718 with CuW Powder<br />

Metallurgy Electrode<br />

70 Experimental Evaluations on Surface Quality Improvement<br />

in Aluminium Powder Mixed AEDM <strong>of</strong> Nickel Based Super<br />

Alloy 718 with Cryogenically Treated Copper Electrode<br />

71 Design and Development <strong>of</strong> Cellular Layout for Machining<br />

Axle Housing and Carrier Component<br />

72 Effect <strong>of</strong> Inclusion on Fracture Behavior <strong>of</strong> Viscoelastic<br />

Materials<br />

iv<br />

Neeraj Lamba 424-428<br />

Neeraj Lamba 429-434<br />

A. Muniaraj<br />

435-442<br />

Sushil Lal Das<br />

K. Palanikumar<br />

Kamal Jangra<br />

443-448<br />

Sandeep Grover<br />

Vinod Kumar<br />

449-453<br />

Kamal Jangra<br />

Vikas Kumar<br />

Sanjay Kumar<br />

454-457<br />

Vasdev Malhotra<br />

Vikas Kumar<br />

Meeta Verma 458-462<br />

Anees Ahmed<br />

Dr. Sanjeev Kumar<br />

Ruchika Singh<br />

Parveen Kamboj<br />

Sunil Kumar<br />

Kamal Jangra<br />

Naveen Beri<br />

Harish Pungotra,<br />

Anil Kumar<br />

Anil Kumar<br />

Naveen Beri<br />

Harish Pungotra<br />

Bommireddy G.K<br />

Dr D N Shivappa<br />

Chethan C N<br />

Dharya Partap singh<br />

Varun Chhabra<br />

Mahesh Chand<br />

73 Compound Casting - A Literature Review Rajender Kumar Tayal<br />

Vikram Singh<br />

Sudhir Kumar<br />

Rohit Garg<br />

74 Effect <strong>of</strong> WEDM Parameters on Machinability <strong>of</strong> Nimonic-90 Vinod Kumar<br />

Kamal Jangra<br />

Vikas Kumar<br />

75 Evaluation <strong>of</strong> Electro Discharge Sawing, A Modified Electro<br />

Discharge Machining Process<br />

76 Analysis on the Study <strong>of</strong> Changes In Mechanical Properties<br />

<strong>of</strong> Al6063-SiC<br />

Kalley Harinarayana<br />

T.Raghavender Reddy<br />

Dr.N.Nagabhushana<br />

Ramesh<br />

Dr.B.Balu Naik<br />

Mandeep Singh<br />

Jaspreet Singh<br />

Dipak Narang<br />

Sandhya Dixit<br />

M.L.Aggarwal<br />

Surya Prakash<br />

Dinesh Kumar<br />

Shyam Sunder<br />

Vinod Yadava<br />

463-470<br />

471-475<br />

476-481<br />

482-485<br />

486-494<br />

495-500<br />

501-510<br />

511-516<br />

517-521<br />

522-529<br />

77 Friction Stir Welding <strong>of</strong> Aluminium Alloy and its Tensile<br />

Properties<br />

530-535<br />

78 Investigation and Analysis for The Wrinkling Behaviour <strong>of</strong><br />

536-543<br />

Deep Drawn Die Sheet Metal Component by Using Fast Form<br />

79 Modeling <strong>of</strong> Al-<strong>20</strong>wt.% SiCp Metal Matrix Composite Using<br />

544-549<br />

Surface-Electrical Discharge Diamond Grinding Process<br />

80 Role <strong>of</strong> IT in Manufacturing Sector Amandeep Singh Wadhwa 550-554


Proceedings <strong>of</strong> National Conference on Trends and Advances in Mechanical Engineering<br />

TAME-<strong>20</strong>12 OCT <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

81 Optimizing Surface Roughness <strong>of</strong> High Die Steel H13 in CNC<br />

Milling Using Taguchi Technique<br />

82 A review on Process Parameter Optimization techniques for<br />

Advanced Machining Processes<br />

83 An Analysis <strong>of</strong> Surface Roughness and Machinability <strong>of</strong> Al-<br />

Fe-Si Alloys<br />

84 Machining Characteristics <strong>of</strong> Borosilicate Glass Using<br />

Traveling Wire Electro-Chemical Spark Machining (TW-<br />

ECSM) Process<br />

85 Mechanical Properties <strong>of</strong> Friction Stir Welded Dissimilar<br />

Metals<br />

86 Microstructure and Weldability Evaluation <strong>of</strong> Dissimilar<br />

Metal Joint Using Paste Technique for Buttering Layers<br />

v<br />

Mandeep Chahal<br />

555-559<br />

Vikram Singh<br />

Rohit Garg<br />

Sudhir Kumar<br />

S. Kumar 560-566<br />

Kanwar Pal Sombir Sharma<br />

B. N. Pathak<br />

Arvind Kumar<br />

Basanta Kumar Bhuyan<br />

Vinod Yadava<br />

Ratnesh Kumar Raj Singh<br />

Rajesh Prasad<br />

Sunil Pandey<br />

Dinesh Rathod<br />

Hariom Choudhary<br />

Sunil Pandey<br />

87 Electrical Discharge Grinding (EDG): A Review Ravindra Nath Yadav<br />

Vinod Yadava<br />

88 Effect <strong>of</strong> Ni-<strong>20</strong>mg Treatment <strong>of</strong> Al-2Fe-1V-1Si Alloy on its B. N. Pathak<br />

Microstructure and Mechanical Properties<br />

Dr. K. L. Sahoo<br />

89 Impact <strong>of</strong> Shot Peening and Heat Treatment Process on<br />

Surface Hardening <strong>of</strong> Welded 304l Austenitic Stainless Steel<br />

Dr. M. N. Mishra<br />

Lakhwinder Singh<br />

R.A. Khan<br />

M.L. Aggarwal<br />

90 Sensitive Analysis <strong>of</strong> EDM Process Using Digraph Method Madan Gopal<br />

Naresh Yadav<br />

Bhupender Singh<br />

91 Mathematical Modeling <strong>of</strong> HAZ in Submerged Arc Welding<br />

Process Using Factorial Design Technique<br />

92 Consumption and Manufacturing for the Future Challenges –<br />

The Sustainable Way<br />

93 Finite Element Modelling <strong>of</strong> Tube Hydr<strong>of</strong>orming Process<br />

Using Pure Aluminium (Al 99)<br />

Hari Om<br />

Sunil Pandey<br />

Dinesh Rathod<br />

Subrata Kumar Patra<br />

Tilak Raj<br />

Dhairya Pratap Singh<br />

Jitendra Kumar Verma<br />

Dilip Johari<br />

Avni Khatkar<br />

S.P. Khatkar<br />

94 Nano-materials, Synthesis, Characterization and<br />

Photoluminescent Properties <strong>of</strong> Ca 2 V 2 O 7 : Eu Nanomaterials<br />

95 A Study <strong>of</strong> Recent Trends in Friction Stir Welding Rajan<br />

Shailesh S. Sengar<br />

Jitender Kumar<br />

96 Thermal Modeling and Finite Element Analysis <strong>of</strong> Electro-<br />

Chemical Spark Machining (ECSM)<br />

97 A Detailed Review <strong>of</strong> the Current Research Trends in<br />

Electrical Discharge Machining (EDM)<br />

98 Hardness Improvement <strong>of</strong> Dissimilar metal Stainless Steel<br />

(A304) and Mild Steel by TIG Welding<br />

THEME IV – INDUSTRIAL ENGINEERING<br />

567-570<br />

571-578<br />

579-583<br />

584-589<br />

590-597<br />

598-602<br />

603-607<br />

608-615<br />

616-626<br />

627-632<br />

633-640<br />

641-645<br />

646-649<br />

Gaurav Kumar Sharma 650-656<br />

Audhesh Narayan<br />

Sumit Ganguly 657-669<br />

Rakesh Kumar<br />

Manmeet Shergill<br />

670-675<br />

99 Concurrent Engineering Dr. S.P.Tayal 676-680<br />

100 Implementation <strong>of</strong> NSGA-II to Reduce the Occupational<br />

Health Hazards <strong>of</strong> Workers in Glass Making Industry<br />

Ruchi Chaudhary<br />

Ajit<br />

Manisha Verma<br />

Dr. Rk Srivastava<br />

681-689<br />

101 Study <strong>of</strong> Manual Material Handling Tasks Using Taguchi<br />

Technique<br />

Jaswinder Singh<br />

P Kalra<br />

R S Walia<br />

690-696


Proceedings <strong>of</strong> National Conference on Trends and Advances in Mechanical Engineering<br />

TAME-<strong>20</strong>12 OCT <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

102 Manual Material Handling Tasks Process Optimization<br />

Using Physiological Technique<br />

103 Office Efficiency Enhancement Through TPM : An<br />

Empirical Study<br />

104 Enhancing Productivity by Strategic Improvement in<br />

Throughput-Time on Assembly Line: A Case Study<br />

Jaswinder Singh<br />

P Kalra<br />

R S Walia<br />

Rajender Kumar<br />

Dr. Vikas Kumar<br />

Dr. Sultan Singh<br />

S. K.Gupta<br />

S.K. Gupta<br />

Dr. V.K. Mahna<br />

Dr. R.V. Singh<br />

Rajender Kumar<br />

105 Application <strong>of</strong> Taguchi Method in Process Optimization Shyam Kumar Karna<br />

Dr. Ran Vijay Singh<br />

Dr. Rajeshwar Sahai<br />

106 A Review <strong>of</strong> Literature on Worker Allocation Problem in<br />

FMS<br />

107 To Study the Impementation <strong>of</strong> Parato Analysis in SME<br />

Indian Industries By Using Cause and Effect Diagram: A<br />

Case Study<br />

Lalit Kumar<br />

Mohit Bansal<br />

Sanjeev Goyal<br />

Kailash Attri<br />

Dr. Rajeev Saha<br />

108 Lean Manufacturing System: An Overview Rakesh Kumar<br />

Vikas Kumar<br />

109 Lean Manufacturing: Elements and its Benefits for Rakesh Kumar<br />

Manufacturing Industry<br />

Vikas Kumar<br />

110 Criticality <strong>of</strong> Supply Chain in Indian Auto Industry Dharamvir Mangal<br />

Tarun Gupta<br />

111 Intensity <strong>of</strong> Critical Factors Effecting Technical Institution Victor Gambhir<br />

Evaluation- An ANP Approach<br />

Dr N.C. Wadhwa<br />

112 Effects <strong>of</strong> Road Traffic Noise on Traffic Constable in<br />

Ghaziabad Region<br />

113 Optimization <strong>of</strong> Inventory Model for Decaying Item with<br />

Variable Holding Cost and Power Demand<br />

Dr. Sandeep Grover<br />

Rakesh Mishra<br />

Sachin Rathore ,<br />

Nitin Sharma<br />

D.D.Johri<br />

Z Mallick<br />

Ankit Prakash Tyagi<br />

Rama Kant Pandey<br />

Shivraj Singh<br />

114 Application <strong>of</strong> Graph Theory: A Review Ravi Kalra<br />

Sunil Kumar<br />

Kamal Jangra<br />

115 Evaluation <strong>of</strong> Ideas for Panel Body Assembly by Decision<br />

Matrix<br />

Narender Kumar<br />

Vineet Jain<br />

116 Lean Manufacturing Strategy –A Remedy for Tough Times Naveen Kumar<br />

Dr S.K Sharma<br />

117 Enablers <strong>of</strong> <strong>Technology</strong> Management: An ISM Approach Sarvesh Kumar<br />

Javed Khan<br />

Abid Haleem<br />

118 Establishing Time Standards for Fixing Body Size Panel to<br />

the Chassis in Assembly Line Using MOST<br />

1<strong>19</strong> Establishing Time Standards for Assembly Activity in<br />

Chassis Preparation Area Using MOST<br />

1<strong>20</strong> Metaheuristic Design for Calculating Makespan <strong>of</strong><br />

Comprehensive Scheduling Problems<br />

Vikram K V<br />

Dr. D. N. Shivappa<br />

Jaganur Sangamesh<br />

Harish. H<br />

Dr. D. N. Shivappa<br />

Jaganur Sangamesh<br />

Sunil Kumar<br />

Rajender Kumar Tayal<br />

697-704<br />

705-710<br />

711-717<br />

718-722<br />

723-736<br />

737-741<br />

742-747<br />

748-755<br />

756-758<br />

759764-<br />

765-773<br />

774-781<br />

782-786<br />

787-794<br />

795-800<br />

801-810<br />

811-818<br />

8<strong>19</strong>-826<br />

827-832<br />

vi


Proceedings <strong>of</strong> National Conference on Trends and Advances in Mechanical Engineering<br />

TAME-<strong>20</strong>12 OCT <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

121 An Efficient Approach <strong>of</strong> Good Manufacturing Flexibility by<br />

FMS and RMS With Minimizing the Overall Wastage By JIT<br />

122 Modern Trends, Problems, Solutions and Ethics in<br />

Mechanical Engineering<br />

123 Stratagem Progress <strong>of</strong> Lean Manufacturing Implementation<br />

in Shop Floor<br />

124 Tools and Techniques for Quality Management in<br />

Manufacturing Industries<br />

125 Simulation Based Analysis <strong>of</strong> the Bullwhip Effect Under<br />

Different Information Sharing Strategies<br />

126 Supplier Manufacturer Relationship in Supply Chain<br />

Management: A Review<br />

127 A Generic Model <strong>of</strong> Multi-Echelon Reverse Logistics<br />

Network for Product Returns<br />

128 Supplier Quality Assurance in Supply Chain Management<br />

(SCM)Through Quality Tools and Techniques<br />

129 Critical Issues for Indian Small and Medium Enterprises for<br />

Adopting Knowledge Management<br />

Virender Chahal 833-838<br />

Dr. Niranjan Lal Mangla 839-843<br />

Dharmender Kumar Dr.<br />

Navdeep Malhotra<br />

Mohit Singh<br />

Dr. I.A. Khan<br />

Dr. Sandeep Grover<br />

B.A. Mir<br />

A. Jayant<br />

A. Singh<br />

Vikramjeet Singh<br />

Arvind Jayant<br />

S. Bansal<br />

A.Jayant<br />

P. Gupta<br />

S. K. Garg<br />

P.P. Shah<br />

Dr. R.L. Shrivastava<br />

A. Anand<br />

M. D. Singh<br />

R. Kant<br />

130 JIT Supply Chain Management: An Introduction O P Mishra<br />

Vikas Kumar<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

STUDY OF SOLAR WATER HEATERS BASED ON EXERGY ANALYSIS<br />

Dilip Johari 1 , Ashok Yadav 2 , Ravi Verma 3<br />

1<br />

M.Tech Student, 2 Asst. Pr<strong>of</strong>., Department <strong>of</strong> Mechanical Engineering, Dayalbagh Educational <strong>University</strong>,<br />

Agra, U.P., India<br />

3 Asst. Pr<strong>of</strong>., Department <strong>of</strong> Mechanical Engineering, Graphic Era <strong>University</strong>, Dehradun, Uttrakhand, India<br />

Email: 1 dilipjohari@gmail.com, 2 ashokyadavaca@gmail.com, 3 raviverma<strong>20</strong><strong>20</strong>@gmail.com<br />

Abstract<br />

Energy application from the sun to heat water is well known. Solar water heater is a device which is used for<br />

heating the water for domestic and industrial purposes by utilizing the solar energy. Solar energy is the energy<br />

which is coming from sun in the form <strong>of</strong> solar radiations in infinite amount, when these solar radiations falls on<br />

absorbing surface, then they gets converted into the heat, this heat is used for heating the water.This paper presents<br />

the study based on three procedure theory. Exergy analysis is conducted with the aim <strong>of</strong> providing some methods to<br />

save cost and keep the efficiency <strong>of</strong> solar water heater to desired extent and at the same time figuring out related<br />

exergy losses. In the Exergy analysis <strong>of</strong> solar water heater systems, the conversion <strong>of</strong> solar radiation is typically<br />

included within the analysis. Exergy analysis has been widely used for the optimisation and allocation <strong>of</strong> losses in<br />

energy systems. Exergy is the expression for loss <strong>of</strong> available energy due to the creation <strong>of</strong> entropy in irreversible<br />

systems or processes. The exergy loss in a system or component is determined by multiplying the absolute<br />

temperature <strong>of</strong> the surroundings by the entropy increase. Exergy is also a measure <strong>of</strong> the maximum useful work that<br />

can be done by a system interacting with an environment. It has been widely used in the design, simulation and<br />

performance evaluation <strong>of</strong> energy systems.<br />

Keywords: Solar water heater, Laws <strong>of</strong> Thermodynamics, Exergy Analysis, Three procedure theory<br />

1. Introduction<br />

The solar energy is the most capable <strong>of</strong> the alternative energy sources. Despite the characteristic <strong>of</strong> low density and<br />

unsteady in nature, the research <strong>of</strong> solar energy has received significant attention in recent years. Due to increasing<br />

demand for energy and rising cost <strong>of</strong> fossil type fuels (i.e., gas or oil) solar energy is considered an attractive source<br />

<strong>of</strong> renewable energy that can be used for water hearing in both homes and industry. Heating water consumes nearly<br />

<strong>20</strong>% <strong>of</strong> total energy consumption for an average family. Solar water heating systems are the cheapest and most<br />

easily affordable clean energy available to homeowners that may provide most <strong>of</strong> hot water required by a family.<br />

Solar heater is a device which is used for heating the water, for producing the steam for domestic and industrial<br />

purposes by utilizing the solar energy. Solar energy is the energy which is coming from sun in the form <strong>of</strong> solar<br />

radiations in infinite amount, when these solar radiations falls on absorbing surface, then they gets converted into the<br />

heat, this heat is used for heating the water. This type <strong>of</strong> thermal collector suffers from heat losses due to radiation<br />

and convection. Such losses increase rapidly as the temperature <strong>of</strong> the working fluid increases.<br />

Exergy is a measure <strong>of</strong> the maximum useful work that can be done by a system interacting with an environment<br />

which is at a constant pressure and temperature. Exergy is the expression for loss <strong>of</strong> available energy due to the<br />

creation <strong>of</strong> entropy in irreversible processes. The analysis is based on the three procedure theory given by Pr<strong>of</strong>essor<br />

Hua Ben. The three different procedures <strong>of</strong> this theory are: Conversion procedure, utilization procedure, and<br />

recycling procedure.<br />

2. Problem Statement<br />

In today’s modern world, where new technologies are introduced every day, the use <strong>of</strong> non renewable energy is<br />

increasing quickly particularly petroleum fuel. Quickly depleting reserve <strong>of</strong> petroleum and decreasing air quality<br />

raise question about the future. The fact that non renewable energy resources will be available at the present usage<br />

level only for a limited period has been accepted worldwide. As a consequence, the need for renewable energy<br />

resources becomes very urgent. As an absolutely clean energy, solar energy is <strong>of</strong> most importance and has been<br />

most emphasized on so far.<br />

1


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Solar water heater technology is a method <strong>of</strong> solar energy utilization. It has been well developed and can be easily<br />

implemented at a low cost. But, the use <strong>of</strong> solar water heating system not familiar in India and the people in India<br />

still not realize about the practical <strong>of</strong> using solar water heating systems.<br />

Earlier studies on solar water heaters were based on the First law <strong>of</strong> Thermodynamics which tells us that energy is a<br />

conserved quantity; “Energy can neither be created nor destroyed, only transformed from one form to another”.<br />

Perhaps then we should stop worrying about “energy saving” and “energy conservation” and instead focus on<br />

recycling all this energy which will always be here Unfortunately, Thermodynamics has a Second law which states<br />

that processes occur in a certain direction, and that energy has quality as well as quantity. So, it is necessary to<br />

evaluate solar water heaters from the point <strong>of</strong> view <strong>of</strong> the Second law <strong>of</strong> thermodynamics because, as we know, it is<br />

the quality <strong>of</strong> energy that is important not the quantity <strong>of</strong> energy.<br />

3. Solar Water Heating System<br />

SWH systems are generally very simple using only sunlight to heat water. A working fluid is brought into contact<br />

with a dark surface exposed to sunlight which causes the temperature <strong>of</strong> the fluid to rise. This fluid may be the water<br />

being heated directly, also called a direct system, or it may be a heat transfer fluid such as a glycol/water mixture<br />

that is passed through some form <strong>of</strong> heat exchanger called an indirect system. These systems can be classified into<br />

three main categories:<br />

(a) Active systems<br />

(b) Passive systems<br />

(c) Batch systems<br />

3.1 Active Systems<br />

Active systems use electric pumps, valves, and controllers to circulate water or other heat-transfer fluids through the<br />

collectors. So, the Active systems are also called forced circulation systems and can be direct or indirect. The active<br />

system is further divided into two categories:<br />

(a) Open-loop (Direct) Active System<br />

(b) Closed-loop (Indirect) Active System<br />

3.1.1 Open-Loop Active Systems<br />

Open-loop active systems use pumps to circulate water through the collectors. This design is efficient and lowers<br />

operating costs but is not appropriate if the water is hard or acidic because scale and corrosion quickly disable the<br />

system. These open-loop systems are popular in nonfreezing climates.<br />

Fig1. Open-Loop Active Systems<br />

3.1.2 Closed-Loop Active Systems<br />

These systems pump heat-transfer fluids (usually a glycol-water antifreeze mixture) through collectors. Heat<br />

exchangers transfer the heat from the fluid to the household water stored in the tanks. Closed-loop glycol systems<br />

are popular in areas subject to extended freezing temperatures because they <strong>of</strong>fer good freeze protection.<br />

2


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig2. Closed loop Active System<br />

3.2 Passive Systems<br />

Passive systems simply circulate water or a heat transfer fluid by natural convection between a collector and an<br />

elevated storage tank (above the collector). The principle is simple, as the fluid heats up its density decreases. The<br />

fluid becomes lighter and rises to the top <strong>of</strong> the collector where it is drawn to the storage tank. The fluid which has<br />

cooled down at the foot <strong>of</strong> the storage tank then flows back to the collector. Passive systems can be less expensive<br />

than active systems, but they can also be less efficient. Thermosiphon system is the best example <strong>of</strong> passive systems.<br />

3.2.1 Thermosiphon Systems<br />

In the thermosyphon system, water comes from the over head tank to bottom <strong>of</strong> solar collector by natural circulation<br />

and water circulates from the collector to storage tank as long as the absorber keeps absorbing heat from the sun and<br />

water gets heated in the collector. The cold water at the bottom <strong>of</strong> storage tank run into the collector and replaces the<br />

hot water, which is then forced inside the insulated hot water storage tank. The process <strong>of</strong> the circulation stops when<br />

there is no solar radiation on the collector. Thermosiphon system is simple and requires less maintenance due to<br />

absence <strong>of</strong> controls and instrumentation. Efficiency <strong>of</strong> a collector depends on the difference between collector<br />

temperature and ambient temperature and inversely proportional to the intensity <strong>of</strong> solar radiation.<br />

Fig3. Thermosiphon System<br />

3.3 Batch systems<br />

Batch System (also known as integral collector storage systems) are simple passive systems consisting <strong>of</strong> one or<br />

more storage tanks placed in an insulated box that has a glazed side facing the sun. Batch systems have combined<br />

collection and storage functions. Depending on the system, there is no requirement for pumps or moving parts, so<br />

they are inexpensive and have few components in other words, less maintenance and fewer failures.<br />

3


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig4. Batch System<br />

4. Components <strong>of</strong> Solar Water Heater<br />

SWH generally consists <strong>of</strong> a solar radiation collector panel, a storage tank, a pump, a heat exchanger, piping units,<br />

and auxiliary heating unit. Some <strong>of</strong> important components are described in the next sections.<br />

4.1 Solar Collectors<br />

The choice <strong>of</strong> collector is determined by the heating requirements and the environmental conditions in which it is<br />

employed. There are mainly three types <strong>of</strong> solar collectors like flat plate solar collector, evacuated tube solar<br />

collector, concentrated solar collector.<br />

4.1.1 Flat Plate Collectors<br />

Flat-plate collectors are used extensively for domestic water heating applications. It is simple in design and has no<br />

moving parts so requires little maintenance. It is an insulated, weatherpro<strong>of</strong>ed box containing a dark absorber plate<br />

under one or more transparent covers. They collect both direct and diffuse radiation. Their simplicity in construction<br />

reduces initial cost and maintenance <strong>of</strong> the system. A more detailed picture <strong>of</strong> these systems is <strong>of</strong> interest and is<br />

presented in the following section.<br />

.<br />

Fig5. Flat plate collector along with heat loss mechanism.<br />

4.1.2 Evacuated-Tube Collectors<br />

Evacuated-Tube Collectors are made up <strong>of</strong> rows <strong>of</strong> parallel, transparent glass tubes. Each tube consists <strong>of</strong> a glass<br />

outer tube and an inner tube, or absorber, covered with a selective coating that absorbs solar energy well but inhibits<br />

radiative heat loss. The air is withdrawn (“evacuated”) from the space between the tubes to form a vacuum, which<br />

4


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

eliminates conductive and convective heat loss. They are most suited to extremely cold ambient temperatures or in<br />

situations <strong>of</strong> consistently low-light. They are also used in industrial applications, where high water temperatures or<br />

steam need to be generated where they become more cost effective.<br />

Fig6. Evacuated-Tube Collectors<br />

4.1.3 Concentrating Collectors<br />

Concentrating collectors use mirrored surfaces to concentrate the sun's energy on an absorber called a receiver. A<br />

heat-transfer fluid flows through the receiver and absorbs heat. These collectors reach much higher temperatures<br />

than flat-plate collectors and evacuated-tube collectors, but they can do so only when direct sunlight is available.<br />

However, concentrators can only focus direct solar radiation, with the result being that their performance is poor on<br />

hazy or cloudy days.<br />

Fig7. Concentrating Collectors<br />

4.2 Storage Tank<br />

Most commercially available solar water heaters require a well-insulated storage tank. Thermal storage tank is made<br />

<strong>of</strong> high pressure resisted stainless steel covered with the insulated fiber and aluminum foil. Some solar water heaters<br />

use pumps to recirculate warm water from storage tanks through collectors and exposed piping. This is generally to<br />

protect the pipes from freezing when outside temperatures drop to freezing or below.<br />

4.3 Heat Transfer Fluid<br />

A heat transfer fluid is used to collect the heat from collector and transfer to the storage tank either directly or with<br />

the help <strong>of</strong> heat exchanger. In order to have an efficient SHW configuration, the fluid should have high specific heat<br />

capacity, high thermal conductivity, low viscosity, and low thermal expansion coefficient, anti-corrosive property<br />

5


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

and above all low cost. Among the common heat transfer fluids such as water, glycol, silicon oils and hydrocarbon<br />

oils, the water turns out to be the best among the fluids. Water is the cheapest, most readily available and thermally<br />

efficient fluid but does freeze and can cause corrosion.<br />

5. Exergy Analysis<br />

To provide an efficient and effective use <strong>of</strong> fuels, it is essential to consider the quality and quantity <strong>of</strong> the energy<br />

used to achieve a given objective. In this regard, the first law <strong>of</strong> thermodynamics deals with the quantity <strong>of</strong> energy<br />

which states that energy cannot be created or destroyed, whereas the second law <strong>of</strong> thermodynamics deals with the<br />

quality <strong>of</strong> energy, i.e., it is concerned with the quality <strong>of</strong> energy to cause change, degradation <strong>of</strong> energy during a<br />

process. First and second law efficiencies are <strong>of</strong>ten called energy and exergy efficiencies, respectively. It is expected<br />

that exergy efficiencies are usually lower than the energy efficiencies, because the irreversibilities <strong>of</strong> the process<br />

destroy some <strong>of</strong> the input exergy.<br />

Exergy analysis method is employed to detect and evaluate quantitatively the causes <strong>of</strong> the thermodynamic<br />

imperfection <strong>of</strong> the process. Exergy is also a measure <strong>of</strong> the maximum useful work that can be done by a system<br />

interacting with an environment which is at a constant pressure and temperature. Exergy is the expression for loss <strong>of</strong><br />

available energy due to the creation <strong>of</strong> entropy in irreversible processes. The exergy loss in a system or component<br />

is determined by multiplying the absolute temperature <strong>of</strong> the surroundings by the entropy increase. The concepts <strong>of</strong><br />

exergy, available energy, and availability are essentially similar. The concepts <strong>of</strong> exergy destruction, exergy<br />

consumption, irreversibility, and lost work are also essentially similar.<br />

5.1 Three Procedure Theory<br />

An energy analysis entitled ‘Three Procedure Theory’ can be conveniently conducted as presented by Pr<strong>of</strong>essor Hua<br />

Ben. Compared with other theories <strong>of</strong> energy analysis, three procedure theory furnishes us a good platform to<br />

perform energy analysis. The three different procedures <strong>of</strong> this theory are: Conversion procedure, utilization<br />

procedure, and recycling procedure. A schematic diagram <strong>of</strong> three procedure theory for the solar water heater is<br />

shown in Fig 8. In Three procedure theory energy conversion procedure takes places at the sun. The nuclear reaction<br />

in the sun makes it possible for the sun to emit a great quantity <strong>of</strong> power, which is transmitted in the form <strong>of</strong><br />

electromagnetic waves. Energy utilization is carried out in the collector. Solar radiation penetrates the cover and is<br />

incident on the black-color plate where it heats water flowing through the pipe. Energy recycling procedure takes<br />

places between the collector and the storage tank which corresponds to the storage tank keep hot water is pumped to<br />

users and cold water fills the storage tank from the bottom pipe simultaneously.<br />

Fig8. Three procedure theory for the solar water heater<br />

6


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Energy balance equations:<br />

At Collector:<br />

(1)<br />

Where,<br />

= Energy from Sun (input Energy) (W)<br />

= Energy from storage tank to collector associated with water recycle (W)<br />

= Energy losses due to imperfectly thermal insulation in collector (W)<br />

= Energy from collector to storage tank (W)<br />

At Storage Tank:<br />

(2)<br />

Where,<br />

= Energy losses due to imperfectly thermal insulation in storage tank (W)<br />

= Energy from storage tank to user (output Energy) (W)<br />

Exergy balance equations:<br />

At Collector:<br />

(3)<br />

Where,<br />

= Exergy from sun (input power) (W)<br />

= Exergy from storage tank to collector associated with water recycle (W)<br />

= Exergy losses due to imperfectly thermal insulation in collector (W)<br />

= Exergy from collector to storage tank (W)<br />

At Storage Tank:<br />

(4)<br />

Where,<br />

= Exergy losses due to imperfectly thermal insulation in storage tank (W)<br />

= Exergy from storage tank to user (output exergy) (W)<br />

= Exergy losses due to irreversibility in storage tank<br />

In utilization procedure, we assume the change in kinetic energy are very small since the solar water heater is driven<br />

by the difference <strong>of</strong> density <strong>of</strong> water, namely no great decrease in pressure is involved, so we can calculate exergy<br />

from collector to storage tank ( ) by use the following equation. [23]<br />

(5)<br />

Where,<br />

= Mass flow rate <strong>of</strong> water (kg/s)<br />

= Outlet temperature <strong>of</strong> water from collector to storage tank (K)<br />

= Ambient temperature (K)<br />

= Specific heat <strong>of</strong> water {J/(kg.K)}<br />

7


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Assuming the temperature distribution in the storage tank is linear (∆T α ∆L), where L is the height <strong>of</strong> the storage<br />

tank), we get;<br />

Where T x , T L and T 0 are the temperature <strong>of</strong> water at position X, L and O from the bottom <strong>of</strong> the storage tank. Then<br />

we obtain the exergy from storage tank to users ( ) by use the following equation:<br />

(6)<br />

6. Conclusion<br />

The study <strong>of</strong> solar water heater based on exergy analysis is done in this paper. the conversion <strong>of</strong> solar radiation in<br />

the evaluation <strong>of</strong> direct-solar systems leads to extremely high exergy losses in the direct solar systems.<br />

Subsequently, the optimisation <strong>of</strong> these systems should be oriented so as to reduce the magnitude <strong>of</strong> exergy losses in<br />

the conversion device. Exergy efficiency <strong>of</strong> solar systems is highly dependent on the daily solar radiation and<br />

radiation intensity. To improve the exergy efficiency, we must select the material and design the number layer <strong>of</strong><br />

transparent cover and a judicious choice <strong>of</strong> the length <strong>of</strong> pipe is necessary. It is a good way to find out to design a<br />

new style <strong>of</strong> storage tank, because large exergy losses in the storage tank.<br />

7. Suggestions for Future work<br />

• In this study, the flat plate collector is considered for analysis and it would be a good initiative to explore the<br />

impact <strong>of</strong> other types <strong>of</strong> solar collector such as an evacuated tube or a concentrated collector.<br />

• In this paper, only two components <strong>of</strong> the solar water heater are analyzed. Other components such as pump and<br />

piping system could also be considered. Analysis <strong>of</strong> other components would help in calculation <strong>of</strong> pressure<br />

drop across the system in order to select the pump and optimize the piping size.<br />

References<br />

1. Xiaowu, W. and Ben, H., “Exergy analysis <strong>of</strong> domestic-scale solar water heaters”, Renewable and Sustainable<br />

Energy Reviews 9(<strong>20</strong>05), 638 – 645.<br />

2. Koroneos,C., Spachos, T.and Moussiopoulos,N., “Exegy analysis <strong>of</strong> renewable energy sources”, Renewable<br />

Energy, <strong>20</strong>03 ; 28 ; 295 - 310.<br />

3. R. Saidur, G. Boroumand Jazi, S. Mekhlif, M. Jameel, “Exergy analysis <strong>of</strong> solar energy applications”,<br />

Renewable and Sustainable Energy Reviews 16 (<strong>20</strong>12) 350– 356<br />

4. Arif Hepbasli, “A key review on exergetic analysis and assessment <strong>of</strong> renewable energy resources for a<br />

sustainable future”, Renewable and Sustainable Energy Reviews 12 (<strong>20</strong>08) 593–661<br />

5. Onder Ozgener, Arif Hepbasli, “A review on the energy and exergy analysis <strong>of</strong> solar assisted heat pump<br />

systems”, Renewable and Sustainable Energy Reviews 11 (<strong>20</strong>07) 482–496<br />

6. Saidur R, Masjuki HH, Jamaluddin MY. “An application <strong>of</strong> energy and exergy analysis in residential sector <strong>of</strong><br />

Malaysia”. Energy Policy <strong>20</strong>07; 35(2):1050–63.<br />

7. M. Sheffer, “Solar Water Heating: A Viable <strong>Technology</strong> Alternative”, Energy User News, (<strong>19</strong>:9), p. 44,<br />

September <strong>19</strong>94.<br />

8. B. Keisling, “The Homeowner’s Handbook <strong>of</strong> Solar Water Heating Systems”, Rodale Press, <strong>19</strong>83.<br />

9. Ahmad asyraf bin ramli, “Theoretical analysis <strong>of</strong> solar water heating system”. A project report, December,<br />

<strong>20</strong>10<br />

10. Sambo, A.S. and Bello, M.B. “An Experimental Evaluation <strong>of</strong> Collector Units for Thermosyphon Solar Water<br />

Heater”. Nig. J. <strong>of</strong> Solar Energy. (<strong>19</strong>90) 9:223-238.<br />

11. Braun, J.E., Klein, S.A., Pearson, K.A., “An improved design method for solar water heating systems”. Solar<br />

Energy 31 (<strong>19</strong>83), 597–604.<br />

12. Buckles, W.E., Klein, S.A., “Analysis <strong>of</strong> solar domestic hot water heaters”. Solar Energy 25 (<strong>19</strong>80), 417–424.<br />

(7)<br />

8


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

GREEN VEHICLE: POLLUTION CONTROL THROUGH CATALYTIC<br />

CONVERTER AND PERFORMANCE ANALYSIS OF THE SAME<br />

Pankaj Agarwal 1 , Manish Jain 2<br />

1 M.Tech (Pur.), Jagannath <strong>University</strong>, Jaipur, Email:mr.pankajagarwal@gmail.com<br />

2 PhD Scholar, JECRC <strong>University</strong>, Jaipur, Email: manish_jecrc@yahoo.com<br />

Abstract<br />

Regardless <strong>of</strong> how perfect engine is operating, there will always be some harmful byproducts <strong>of</strong> combustion.<br />

When the combustion <strong>of</strong> fuel takes place in an engine <strong>of</strong> an automobile in the presence <strong>of</strong> air, following<br />

reaction takes place:<br />

Hydrocarbons<br />

xCO 2 +yH 2 O+Heat<br />

Fumes <strong>of</strong> un-burnt hydrocarbons produce a number <strong>of</strong> petrochemical oxidants & photochemical smog with<br />

O 2 & N2 which causes adverse effects on physiological activities <strong>of</strong> living beings. Emissions from gasoline<br />

powered vehicles are generally the hydrocarbons like CO, NOx, SO 2 , etc.<br />

Catalytic converter is a device which treats the exhaust emission and converts them into the less harmful<br />

substances. This device is located in-line with the exhaust system and is used to cause a desirable chemical<br />

reaction to take place in the exhaust flow. In this paper the various aspects <strong>of</strong> design, construction, and working<br />

and performance analysis <strong>of</strong> a catalytic converter are discussed. The converter performance is simulated by<br />

considering chemical reactions and heat transfer phenomena as the exhaust gases flow through the catalyst.<br />

Keywords: Green Vehicle, Pollution control<br />

1. Introduction<br />

The three main types <strong>of</strong> automotive vehicles being used in our country are:<br />

1. Motorcars, scooters powered by gasoline engine.<br />

2. Passenger cars powered by four stroke gasoline engines.<br />

3. Large buses & trucks powered by four stroke diesel engines.<br />

Fig 1: Catalytic Converter<br />

A serious issue that is always been debated among the environmentalists over the decades and recent years is air<br />

pollution. As the technology keep on evolving and emerging, it carries along undesirable effects apart from its<br />

broad application and use. One <strong>of</strong> the main contributors is said to be the emission <strong>of</strong> harmful gases produced by<br />

vehicle exhaust lines. The number <strong>of</strong> vehicles miles travels per year continues to increase as a result <strong>of</strong> higher<br />

demand and needs.<br />

9


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Consequently, an increase in the number led to the increase <strong>of</strong> the content <strong>of</strong> pollutants in air. The need to<br />

control engine emissions was recognized as early as <strong>19</strong>09. Due to the more stringent rules and emission<br />

standards, automotive manufacturers begun to develop a treatment device for exhaust gases known as catalytic<br />

converter for their vehicle models. General Motors (GM) was the pioneer in the early <strong>19</strong>70s followed by Ford<br />

and Chrysler. Catalytic converters came in many concepts, structures and even the materials; nevertheless, it<br />

continued to evolve depending on different vehicle requirements.<br />

Emissions from gasoline powered vehicles are generally classified as:<br />

1. Exhaust emission<br />

2. Crank-case emission<br />

3. Evaporative emission<br />

4. Fuel tank emission<br />

The conversion process is performed by means <strong>of</strong> catalyst which accelerates the chemical reactions. It remains<br />

unchanged through the process and able to sustain high temperatures caused by incoming exhaust stream. Most<br />

frequently, precious metals such as Platinum (Pt), Palladium (Pd), Rhodium (Rh) and Vanadium (V) are being<br />

used as catalysts and because <strong>of</strong> their rareness and outstanding ability, catalytic converters become among the<br />

most expensive devices in a vehicle. Though the researchers begin to replace them with oxides <strong>of</strong> base metals,<br />

which are much cheaper, such as Zinc (Zn), Aluminum (Al) and Magnesium (Mg), however, due to their lower<br />

performance compared to the precious ones, they do not have any other choice rather than to keep on<br />

implementing those expensive metals for automotive catalysts and other industrial applications. The experiment<br />

is carried out to analyze the performance characteristics and behavior <strong>of</strong> the three-way ceramic monolith<br />

catalytic converter (TWCC) especially its efficiency in reducing the amount <strong>of</strong> pollutants. Experiment is<br />

conducted to compare the performance <strong>of</strong> two ceramic converters <strong>of</strong> different hydraulic diameter, channel length<br />

and cell density on conversion efficiencies and pressure drop. By observing the results, suggestions on the<br />

considerable design geometries for catalytic converter properties are made.<br />

Emission test on engine test bed with converter installed and how engine operating conditions would influence<br />

the performance <strong>of</strong> catalytic converter is investigated. The test is done at various engine speeds and at different<br />

air-to-fuel ratio. The content <strong>of</strong> carbon dioxide (CO2), carbon monoxide (CO), hydrocarbon (HC), oxides <strong>of</strong><br />

nitrogen (NOx) and oxygen (O2) are measured before and after the converters using the MRU Delta 1600-L<br />

multi-gas analyzer which is used during the emission test. After completing the test, the converters were cut to<br />

extract the substrate or ‘honeycomb’ inside the housing and being analyzed for microstructure and materials<br />

composition using Scanning Electron Microscopy (SEM) and Energy Dispersive Analysis (EDX).<br />

The main objective <strong>of</strong> the paper is to compare and analysis the performance characteristics <strong>of</strong> converters from<br />

PROTON Wira 1.3L and another one from FIAT Punto Selecta 1.2L. Both converters had same substrate<br />

material.<br />

2. Specific Pollutants from IC Engines<br />

Motor vehicles produce many different pollutants. The principal pollutants <strong>of</strong> concern- those that have been<br />

demonstrated to have significant effects on human, animal, plants and environmental health and welfare-include:<br />

Hydrocarbons (65%) – This class is made up <strong>of</strong> burned or partially burned fuel, and is a major contributor to<br />

urban smog, as well as being toxic. Prolonged exposure to hydrocarbons contributes to asthma, liver disease,<br />

lung disease, and cancer.<br />

Carbon monoxide (CO) - A product <strong>of</strong> incomplete combustion, carbon monoxide reduces the blood's ability to<br />

carry oxygen; overexposure (carbon monoxide poisoning) may be fatal. Carbon Monoxide poisoning is a major<br />

killer.<br />

Nitrogen oxides (NO x )- Generated when nitrogen in the air reacts with oxygen at the high temperature. NO x is a<br />

precursor to smog and acid rain. NO x is a mixture <strong>of</strong> NO, N 2 O, and NO 2 . NO 2 is extremely reactive. It destroys<br />

resistance to respiratory infection Particulate matter Soot or smoke made up <strong>of</strong> particles in the micrometer size<br />

range: Particulate matter causes negative health effects, including but not limited to respiratory disease and<br />

cancer.<br />

Sulfur oxide (SO x ) -It is the oxides <strong>of</strong> sulfur, which are emitted from motor vehicles burning fuel containing<br />

sulfur.<br />

Volatile organic compounds (VOCs)- Organic compounds which typically have a boiling point less than or equal<br />

to 250 °C; for example chlor<strong>of</strong>luorocarbons (CFCs) and formaldehyde. Volatile organic compounds are a<br />

subsection <strong>of</strong> Hydrocarbons that are mentioned separately because <strong>of</strong> their dangers to public health.<br />

10


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3. Methods <strong>of</strong> Controlling Emission<br />

Air injection: The mechanism by which exhaust emissions are controlled depends on the method <strong>of</strong> injection and<br />

the point at which air enters the exhaust system, and has varied during the course <strong>of</strong> the development <strong>of</strong> the<br />

technology. Exhaust gas recirculation: In internal combustion engines, exhaust gas recirculation (EGR) is a<br />

nitrogen oxide (NO x ) emissions reduction technique used in petrol/gasoline and diesel engines.<br />

Catalytic Converter: A catalytic converter (colloquially, "cat" or "catcon") is a device used to convert toxic<br />

exhaust emissions from an internal combustion engine into non-toxic substances. The first widespread<br />

introduction <strong>of</strong> catalytic converters was in the United States market, where <strong>19</strong>75 model year automobiles were so<br />

equipped to comply with tightening U.S. Environmental Protection Agency regulations on automobile exhaust<br />

emissions. Catalytic converters are also used on generator sets, forklifts, mining equipment, trucks, buses,<br />

locomotives, airplanes and other engine fitted devices. Inside a catalytic converter, a catalyst stimulates a<br />

chemical reaction in which noxious byproducts <strong>of</strong> combustion are converted to less toxic substances.<br />

Fig 2: Catalytic converter<br />

4. Catalytic Converter<br />

Catalytic converter has gone through many processes and remarkable evolution for the past 30 years. It is said to<br />

be one <strong>of</strong> the most effective tool to fight against the overwhelming pollutant contents in our environment, as it<br />

reduces almost 80% <strong>of</strong> the harmful gases resulting from the incomplete combustion <strong>of</strong> the engine. Catalytic<br />

converter is a stainless steel container mounted somewhere along the exhaust pipe <strong>of</strong> the engine and inside the<br />

container is a porous ceramic structure through which the exhaust gas flows (Ganesan, <strong>20</strong>04). In most converters,<br />

the ceramic is a single honeycomb structure with many flow passages. The passages comprise <strong>of</strong> many shapes,<br />

including square, triangular, hexagonal and sinusoidal. Early converters used loose granular ceramic with the gas<br />

passing between the packed spheres. Since it is difficult to keep the spheres in place, many converter developers<br />

opted for ceramic monolith which <strong>of</strong>fers various advantages. Among these advantages are smaller volumes,<br />

lower mass and greater ease <strong>of</strong> packaging (Heck & Farrauto, <strong>19</strong>95).<br />

The catalytic converter consists <strong>of</strong> several components:<br />

1. Catalyst Core or Substrate: For automotive catalytic converters, the core is usually a ceramic monolith with a<br />

honeycomb structure. Metallic foil monoliths made <strong>of</strong> FeCrAl are used in some applications. This is partially<br />

a cost issue. Ceramic cores are inexpensive when manufactured in large quantities. Metallic cores are less<br />

expensive to build in small production runs. Either material is designed to provide a high surface area to<br />

support the catalyst washcoat, and therefore is <strong>of</strong>ten called a "catalyst support". The cordierite ceramic<br />

substrate used in most catalytic converters was invented by Rodney Bagley, Irwin Lachman and Ronald<br />

Lewis at Corning Glass, for which they were inducted into the National Inventors Hall <strong>of</strong> Fame in <strong>20</strong>02.<br />

Fig 3: metal core converter<br />

2. The washcoat: A washcoat is a carrier for the catalytic materials and is used to disperse the materials over a<br />

high surface area. Aluminum oxide, Titanium dioxide, Silicon dioxide, or a mixture <strong>of</strong> silica and alumina can<br />

be used. The catalytic materials are suspended in the washcoat prior to applying to the core. Washcoat<br />

11


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

materials are selected to form a rough, irregular surface, which greatly increases the surface area compared to<br />

the smooth surface <strong>of</strong> the bare substrate. This maximizes the catalytically active surface available to react<br />

with the engine exhaust.<br />

3. The catalyst itself is most <strong>of</strong>ten a precious metal: Platinum is the most active catalyst and is widely used, but is<br />

not suitable for all applications because <strong>of</strong> unwanted additional reactions and high cost. Palladium and<br />

rhodium are two other precious metals used. Rhodium is used as a reduction catalyst, palladium as oxidation<br />

catalysts, and platinum is used both for reduction and oxidation. Cerium, iron, manganese and nickel are also<br />

used, although each has its own limitations. Nickel is not legal for use in the European Union (because <strong>of</strong> its<br />

reaction with carbon monoxide into nickel tetra carbonyl). Copper can be used everywhere except North<br />

America, where its use is illegal because <strong>of</strong> the formation <strong>of</strong> dioxin.<br />

4.1 Catalytic converter for petrol engines<br />

Two-way: A two-way (or "oxidation") catalytic converter has two simultaneous tasks: Oxidation <strong>of</strong> carbon<br />

monoxide to carbon dioxide: 2CO + O 2 → 2CO 2. Oxidation <strong>of</strong> hydrocarbons (unburnt and partially-burnt fuel) to<br />

carbon dioxide and water: C x +2H 2x + [(3x+1)/2] O 2 → xCO 2 + (x+1) H 2 O (a combustion reaction).<br />

This type <strong>of</strong> catalytic converter is widely used on diesel engines to reduce hydrocarbon and carbon monoxide<br />

emissions. They were also used on gasoline engines in American- and Canadian-market automobiles until <strong>19</strong>81.<br />

Because <strong>of</strong> their inability to control oxides <strong>of</strong> nitrogen, they were superseded by three-way converters.<br />

Three-way: Since <strong>19</strong>81, "three-way" (oxidation-reduction) catalytic converters have been used in vehicle<br />

emission control systems in the United States and Canada; many other countries have also adopted stringent<br />

vehicle emission regulations that in effect require three-way converters on gasoline-powered vehicles [8]. The<br />

reduction and oxidation catalysts are typically contained in a common housing, however in some instances they<br />

may be housed separately. A three-way catalytic converter has three simultaneous tasks:<br />

Reduction <strong>of</strong> nitrogen oxides to nitrogen and oxygen:<br />

2NO x → xO 2 + N 2<br />

Oxidation <strong>of</strong> carbon monoxide to carbon dioxide:<br />

2CO + O 2 → 2CO 2<br />

Oxidation <strong>of</strong> unburn hydrocarbons (HC) to carbon dioxide and water:<br />

Cx+2H 2 x + [(3x+1)/2]O 2 → xCO 2 + (x+1)H 2 O<br />

These three reactions occur most efficiently when the catalytic converter receives exhaust from an engine<br />

running slightly above the stoichiometric point. This point is between 14.6 and 14.8 parts air to 1 part fuel, by<br />

weight, for gasoline. The ratio for Auto gas (or liquefied petroleum gas (LPG)), natural gas and ethanol fuels is<br />

each slightly different, requiring modified fuel system settings when using those fuels. In general, engines fitted<br />

with 3-way catalytic converters are equipped with a computerized closed-loop feedback fuel injection system<br />

using one or more oxygen sensors, though early in the deployment <strong>of</strong> three-way converters, carburetors equipped<br />

for feedback mixture control were used.<br />

Three-way catalysts are effective when the engine is operated within a narrow band <strong>of</strong> air-fuel ratios near<br />

stoichiometry, such that the exhaust gas oscillates between rich (excess fuel) and lean (excess oxygen)<br />

conditions. However, conversion efficiency falls very rapidly when the engine is operated outside <strong>of</strong> that band <strong>of</strong><br />

air-fuel ratios. Under lean engine operation, there is excess oxygen and the reduction <strong>of</strong> NO x is not favored.<br />

Under rich conditions, the excess fuel consumes all <strong>of</strong> the available oxygen prior to the catalyst, thus only stored<br />

oxygen is available for the oxidation function. Closed-loop control systems are necessary because <strong>of</strong> the<br />

conflicting requirements for effective NO x reduction and HC oxidation. The control system must prevent the<br />

NO x reduction catalyst from becoming fully oxidized, yet replenish the oxygen storage material to maintain its<br />

function as an oxidation catalyst.<br />

Three-way catalytic converters (TWC) have done a tremendous job in reducing the engine emissions by more<br />

than 90%. There are various approaches for the design improvements. Some <strong>of</strong> them, such as electrically or<br />

chemically heated catalysts, are focused mainly on reducing the cold start emissions by minimizing the catalyst<br />

warm up period during the cold engine starts. Due to cost-effectiveness, mathematical modeling is better suited<br />

for optimization studies. In this study, the effect <strong>of</strong> geometry (length, cross-sectional area, cell wall thickness and<br />

cell density) on the converter performance during the US Federal Test Procedure (FTP) is assessed [2].<br />

12


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4.2 Catalytic converter for diesel engines<br />

For compression-ignition (i.e., diesel engines), the most-commonly-used catalytic converter is the Diesel<br />

Oxidation Catalyst (DOC). This catalyst uses O 2 (oxygen) in the exhaust gas stream to convert CO (carbon<br />

monoxide) to CO 2 (carbon dioxide) and HC (hydrocarbons) to H 2 O (water) and CO 2 . These converters <strong>of</strong>ten<br />

operate at 90 percent efficiency, virtually eliminating diesel odor and helping to reduce visible particulates<br />

(soot). These catalysts are not active for NO x reduction because any reductant present would react first with the<br />

high concentration <strong>of</strong> O 2 in diesel exhaust gas.<br />

Reduction in NO x emissions from compression-ignition engine has previously been addressed by the addition <strong>of</strong><br />

exhaust gas to incoming air charge, known as exhaust gas recirculation (EGR). In <strong>20</strong>10, most light-duty diesel<br />

manufactures in the U.S. added catalytic systems to their vehicles to meet new federal emissions requirements.<br />

There are two techniques that have been developed for the catalytic reduction <strong>of</strong> NO x emissions under lean<br />

exhaust condition - selective catalytic reduction (SCR) and the lean NO x trap or NO x adsorber. Instead <strong>of</strong><br />

precious metal-containing NO x adsorbers, most manufacturers selected base-metal SCR systems that use a<br />

reagent such as ammonia to reduce the NO x into nitrogen. Ammonia is supplied to the catalyst system by the<br />

injection <strong>of</strong> urea into the exhaust, which then undergoes thermal decomposition and hydrolysis into ammonia.<br />

One trademark product <strong>of</strong> urea solution, also referred to as Diesel Emission Fluid (DEF), is AdBlue.<br />

Diesel exhaust contains relatively high levels <strong>of</strong> particulate matter (soot), consisting in large part <strong>of</strong> elemental<br />

carbon. Catalytic converters cannot clean up elemental carbon, though they do remove up to 90 percent <strong>of</strong> the<br />

soluble organic fraction, Diesel exhaust contains relatively high levels <strong>of</strong> particulate matter (soot), consisting in<br />

large part <strong>of</strong> elemental carbon. Catalytic converters cannot clean up elemental carbon, though they do remove up<br />

to 90 percent <strong>of</strong> the soluble organic fraction.<br />

5. Performance Analysis <strong>of</strong> Catalytic Converter<br />

The experimental methodology consists <strong>of</strong> two different parts. The first one is the emission test and the other one<br />

is microstructure and materials composition analysis. The emission test was conducted by multi-gas analyzer for<br />

emission measurements. After completing the test, the converters were cut to extract the substrate or<br />

‘honeycomb’ inside the housing and being analyzed for microstructure and materials composition using<br />

Scanning Electron Microscopy (SEM) and Energy Dispersive Analysis (EDX) [7].<br />

Fig 4: Experimental Setup [7]<br />

Two ceramic catalytic converters (underbody type) <strong>of</strong> different vehicle models were evaluated. The first one is<br />

extracted from PROTON Wira 1.3L and another one from FIAT Punto Selecta 1.2L. Both converters had same<br />

substrate material, synthetic cordierite ceramic and substrate shape, square cell except they differ in size,<br />

chemical properties and geometrical attributes. Double substrate systems are as thermal mass, geometric surface<br />

area, and washcoat distribution (Presti et. al <strong>20</strong>02). Per Marsh et. al (<strong>20</strong>01) have shown that less favorable mass<br />

transfer and higher flow velocity can be found as a results <strong>of</strong> the reduction <strong>of</strong> diameter, however, compensated<br />

with the cases <strong>of</strong> lower cell densities implemented on both converters for separate reduction and oxidation<br />

purposes.<br />

13


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Single heat shield is applied to Fiat converter while double heat shields that cover both the upper and bottom part<br />

are used in Proton converter. Also, for each converter, the inlet and outlet cones were fabricated identically. The<br />

engine used in the test is a spark-ignition (inline 4 cylinder) Proton engine coupled with eddy-current type<br />

dynamometer. It is controlled by AUTOTEST VI main controller located outside <strong>of</strong> the engine room with the aid<br />

<strong>of</strong> AUTOTEST VI computer s<strong>of</strong>tware via numerous sensors. The gas analyzer employed in the setup was the<br />

upgraded version (MRU Delta 1600-L) which is capable to measure simultaneous reactions <strong>of</strong> carbon monoxide,<br />

carbon dioxide, hydrocarbon, oxygen and also nitrogen oxides. It also incorporates a probe, suitable to measure<br />

the gases at the inlet and outlet region, along with the thermocouple, to attain temperature values for ambient and<br />

the exhaust gas itself. Figure shows the complete experimental setup.<br />

The substrate materials, type <strong>of</strong> catalysts and their corresponding percentage loading for both converters were<br />

determined using the EDX machine that is coupled with the scanning electron microscopy (SEM) system.<br />

5.1 Results and discussion<br />

The objective <strong>of</strong> the experiment was to observe the behavior <strong>of</strong> the catalytic converters from cold condition.<br />

Usually, this happens about 2 minutes after engine starts and based on this, a transient analysis can be built up to<br />

show the variation <strong>of</strong> main pollutants content over a period <strong>of</strong> time. However, for this analysis (mainly at idling<br />

condition), this range <strong>of</strong> temperature cannot be reached. As a result, the pollutants reduction or gas conversions<br />

were absent. For that reason, a set <strong>of</strong> recommended transient analysis for the experiment was then transferred to<br />

steady-state analysis, where the temperature was risen up to 250ºC by increasing the speed and then set back to<br />

idling mode to ensure efficient converter operation. However, for uniformity, the cold start consideration was<br />

eliminated for both experiment and analysis. The tabulated data were plotted into graphs to clearly indicate the<br />

composition <strong>of</strong> pollutants before and after passing through the catalytic converter over half n hour duration.<br />

FIG 9 CO contents in PROTON converter[7]<br />

FIG 10 CO contents in FIAT converter[7]<br />

14


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

FIG 11 HC contents in PROTON converter[7]<br />

FIG 12 HC contents in FIAT converter[7]<br />

Meanwhile, the amount <strong>of</strong> CO after the converter at the same speed maintains the highest level among all speeds<br />

with a range between 2.0 to 2.5% by volume.<br />

Fiat converter performed much better in oxidizing the CO with a lower range <strong>of</strong> overall percentage, i.e., around<br />

0.5 to 2.0% before converter and 0.0 to 1.25% after the converter.<br />

Experimental data show that the Fiat converter has higher air-fuel ratio (leaner mixture) compared to Proton<br />

converter which results the lower concentration <strong>of</strong> CO because <strong>of</strong> greater presence <strong>of</strong> oxygen.<br />

Unburned hydrocarbon contents at idling speed <strong>of</strong> 1000 rpm is much higher in Proton converter than in Fiat<br />

converter, though the exhaust temperatures for both are similar.<br />

The hydrocarbon oxidation is still weak even kept for 30 minutes while Fiat converter has performed a HC<br />

decrease from the very beginning. It has maintained the HC level below 500 ppm for the three different speeds<br />

after passing through the substrates and again, the air-fuel ratio is one <strong>of</strong> the factors contributing to those results.<br />

For NOx reduction, both converters perform in similar way by putting the residual NO as low as 5 to 15 ppm.<br />

Experimental studies suggest that by implementing a catalytic converter significant amount <strong>of</strong> reduction in<br />

exhaust emissions are observed:<br />

• Presence <strong>of</strong> CO in exhaust emission is reduced from 4-4-5% to 2-2-5% by volume.<br />

• Presence <strong>of</strong> hydrocarbons is reduced from 3000ppm to 1100ppm.<br />

• Presence <strong>of</strong> NO in exhaust emission came down to 50ppm from 400-450ppm.<br />

15


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

6. Conclusions<br />

Based upon the experimentation and simulation, it is concluded that:<br />

1. Fiat converter is better than Proton converter in terms <strong>of</strong> conversion efficiencies <strong>of</strong> three main pollutants CO,<br />

NO and HC at three different engine speeds. Factors affecting the performance include the geometric design<br />

<strong>of</strong> monolithic channel such as hydraulic diameter, channel length, cell density and wall thickness. Fiat<br />

converter with higher cell densities, longer channel, thinner wall and smaller hydraulic diameter produced<br />

lower emission than Proton converter.<br />

2. Fiat converter with higher cell density and slightly thinner wall thickness allows more precious metal<br />

catalysts to be loaded hence increasing reaction surface areas for better conversion efficiency.<br />

3. Longer channel in Fiat converter <strong>of</strong>fers an advantage <strong>of</strong> better mass transfer because more exhaust gases can<br />

be attracted to the channel wall for a longer time, but at the same time produces higher pressure drop. HC and<br />

CO emission decreases as channel length increases, however, not much effect on NOx emission.<br />

4. Smaller hydraulic diameter in Fiat converter channel exhibits more favorable mass transfer as a result <strong>of</strong><br />

higher flow velocity. Fresh exhaust gases are easily attracted to the channel wall with small diameter to<br />

undergo chemical reactions with catalysts compared to the channel with large diameter.<br />

5. The simulation and experimental results exhibited small differences in reducing main three pollutants HC,<br />

CO and NO [1].It may be caused by many factors and among them is the model itself. In actual converter,<br />

double substrates were used while in simulation, only single substrate was used. Also, the precious metals<br />

cannot be arranged together in ratios in the simulation which also lead to the difference in end results.<br />

Catalytic converter can help to reduce the presence <strong>of</strong> toxic and harmful contents in exhaust emission without<br />

affecting the performance <strong>of</strong> the engine. This could be the one <strong>of</strong> the measures to save our environment and<br />

achieving a green revolution.<br />

References<br />

1. Presti, M., Pace, L., et al., <strong>20</strong>02, “A Computational and Experimental Analysis for Optimization <strong>of</strong> Cell<br />

Shape in High Performance <strong>of</strong> Catalytic Converters”, SAE Paper <strong>20</strong>02-01-0355.<br />

2. Marsh, P., Acke, F., et al., <strong>20</strong>01, “Application Guideline to Define Catalyst Layout for Maximum Catalytic<br />

Efficiency”, SAE Paper <strong>20</strong>01-01-0929.<br />

3. Rosen, Erwin M., <strong>19</strong>75. The Peterson automotive troubleshooting & repair manual. Grosset & Dunlap, Inc..<br />

ISBN 978-04481<strong>19</strong>465.<br />

4. Exhaust Emissions and Driveability — Chrysler Corporation.<br />

5. Heywood, John B., "Internal Combustion Engine Fundamentals," McGraw Hill.<br />

6. Van Basshuysen, Richard, and Schäfer, Fred, <strong>20</strong>04. Internal Combustion Engine Handbook. SAE<br />

International.<br />

7. A.K.M. Mohiuddin and Muhammad Nurhafez,<strong>20</strong>07., Experimental analysis and comparison <strong>of</strong> performance<br />

characteristics <strong>of</strong> catalytic converters including simulation, International Journal <strong>of</strong> Mechanical and Materials<br />

Engineering (IJMME), Vol. 2, No. 1, 1-7.<br />

8. Sameh M. Metwalley, Shawki A. et al., <strong>20</strong>11, Determination <strong>of</strong> the catalytic converter performance <strong>of</strong> bi-fuel<br />

vehicle, Journal <strong>of</strong> Petroleum <strong>Technology</strong> and Alternative Fuels Vol. 2(7), pp. 111-131.<br />

9. Steven D. Burch, Matthew A. Keyser, Chris P. Colucci, Thomas F. Potter, David K. Benson. <strong>19</strong>96,<br />

Applications and Benefits <strong>of</strong> Catalytic Converter Thermal Management, Presented at SAE Fuels &<br />

Lubricants Spring Meeting (Dearborn, MI).<br />

10. Wojciech Marek ,Władyslaw Mitianiec, <strong>20</strong>02, modeling and research analysis <strong>of</strong> catalytic converter in a<br />

small SI two-stroke engine, Journal <strong>of</strong> kones Internal Combustion Engines No. 3‐4.<br />

16


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

PERFORMANCE INVESTIGATION OF A COMPACT TRI-GENERATION<br />

SYSTEM BASED ON RENEWABLE ENERGY POWER PLANT EXHAUST GAS<br />

WASTE HEAT UTILIZATION<br />

Dr. Raj Kumar 1 , Anil Kumar 2<br />

1 Pr<strong>of</strong>essor (Mechanical Engineering Department)<br />

2 Ph.D. scholar, mech_annu@rediffmail.com<br />

1,2 <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad<br />

Abstract<br />

This paper presents a compact tri-generation system in order to cover the electric and thermal power demand <strong>of</strong><br />

small rural areas using the renewable energy. The gasifier generator coupled power plants are being widely<br />

used in rural communities where electric network doesn’t exist. The recovery <strong>of</strong> the exhaust gases makes the<br />

system very attractive. Apart from it, there is the performance study <strong>of</strong> a compact power plant and a trigeneration<br />

plant. The stack gases from internal combustion engine are directed to a 25 kW ammonia-water<br />

absorption refrigeration chiller. In the power plant,31.25% is the electric power generation <strong>of</strong> the total fuel gas<br />

input and same amount <strong>of</strong> stack gases at temperature 400 0 C just at out let <strong>of</strong> engine is used to operate<br />

absorption chiller machine which is having COP <strong>of</strong> 0.517. The temperature <strong>of</strong> cold storage was between 0 0 C-5 C<br />

at 15kW cooling capacity. The engine water jacket was used for heating purpose and the temperature gain was<br />

between 60 0 C -63.5 0 C.<br />

Keywords: Tri-generation, renewable energy, exhaust gas waste.<br />

1. INTRODUCTION<br />

Though producer gas as a fuel has been known since 1785, gasifier use with engines for power<br />

generation came into existence only around <strong>19</strong><strong>20</strong>. Maximum Gasification development activities were carried<br />

out during the II nd world war due to the shortage <strong>of</strong> fossil fuels. The possibilities <strong>of</strong> using this gas for heating and<br />

power generation was first realized by Europe, therefore this gas emerged in Europe producer gas system. With<br />

recent price rise and scarcity <strong>of</strong> fossil fuel there has been a trend towards use <strong>of</strong> alternative energy sources like<br />

solar, wind, biomass etc . Biomass derived gaseous fuel can be proved better in running Internal Combustion<br />

Engine to produce electricity for agro enterprises, processing <strong>of</strong> agricultural products, lighting and other end uses<br />

(Arteconi et al. <strong>20</strong>09). But there is huge wastage <strong>of</strong> heat energy as the stack gas so it may boost to develop new<br />

technologies for efficient use <strong>of</strong> this type <strong>of</strong> energy. One such technology is downdraft gasifier integrated with SI<br />

Engine running an electric generator and simultaneously the stack gases from engine can be used in operating the<br />

vapor absorption machine as well as heating (Rathore et al. <strong>20</strong>09). The MNRE New Delhi has developed and<br />

installed such system.<br />

2. SYSTEMS DESCRIPTION<br />

2.1 POWER PLANT<br />

The biomass-based power plant installed at MNRE New Delhi is <strong>of</strong> 50kW rated capacity. The system consists <strong>of</strong><br />

a gasifier, water scrubber filters and gas engine coupled with AC Generator. The details <strong>of</strong> the system are given<br />

in Fig. 1.<br />

(i) Gasifier: The gasifier is <strong>of</strong> down draft type with vibrator. The ash is removed through it. The gasifier outlet is<br />

connected with ventury water scrubber. In a ventury negative pressure is created through which producer gas is<br />

supplied to burner for starting <strong>of</strong> gasifier (Sridhar et al. <strong>20</strong>01). It is having possible different zones which can be<br />

distinguished four separate zones in the gasifier: Drying zone, Pyrolysis zone, Oxidation (combustion) zone &<br />

Reduction zone (Sridhar et al. <strong>20</strong>04).<br />

(ii) Cooling and cleaning system: The gas produced from gasifier is passed through a cooling & cleaning<br />

system consisting <strong>of</strong> a ventury, one course filter, two fine filters and one security filter. The gas coming out from<br />

the gasifier is cooled in a ventury scrubber. The cooled gases received after ventury scrubber was further cleaned<br />

in the course filter. The coarse filter is filled with small wood chips. In which tar & solid particulates present in<br />

gases gets cleaned. The gases are further passed through two units <strong>of</strong> fine filters. The fine filters are filled with<br />

sawdust in which the tar is further cleaned and sent to security filter. The security filter is fitted with fabric cloth.<br />

The gases are passed through fabric cloth to arrest the remaining dust particles present in the producer gas. The<br />

cleaned gases are supplied to SI Engine coupled with AC Generator.<br />

17


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Gasifie<br />

r<br />

Ventury<br />

Scrubber<br />

Course filter<br />

Fine filter<br />

Safety fabric<br />

Control Panel<br />

filter<br />

Producer gas engine coupled<br />

with AC generator<br />

Fig. 1. Schematic diagram <strong>of</strong> gasifier coupled to producer gas engine system<br />

(iii) Engine: The producer gas engine coupled with gasifier is spark ignition water-cooled engine having six<br />

cylinders. The carburetor has been fitted to regulate mixing <strong>of</strong> producer gas and air for smooth running <strong>of</strong> the<br />

engine at different load (Sridhar et al. <strong>20</strong>05).<br />

(iv) AC Generator: The AC Generator is <strong>of</strong> three phase operating at 1500 rated rpm. The generator is connected<br />

with loading device, fitted with heaters. The generator has self-regulated exciter including battery charger DC<br />

output at 24V (Sharma et al. <strong>20</strong>09).<br />

2.2 TRI-GENERATION PLANT<br />

Solar<br />

HRU<br />

To environment (or to heat)<br />

Exhaust gases<br />

Biomass<br />

Gasifier<br />

GEN<br />

Engine gen-set<br />

Producer gas<br />

VAM<br />

Smart Grid<br />

To consumer<br />

Fig. 2. Schematic diagram <strong>of</strong> tri-generation system<br />

This waste heat based tri-generation system consists as follows:<br />

(i) Cold Storage System: In the cold storage system, the compressor is replaced by an absorber, a pump, a<br />

generator and pressure reducing valve. These components in this system perform the same function as that <strong>of</strong> a<br />

compressor in the vapor compression system. The pump increases the pressure <strong>of</strong> the strong solution up to 10<br />

bar. It consists <strong>of</strong> an analyser, a rectifier and two heat exchangers.<br />

(ii) Gas Engine-Generator coupled with VAM: The gas outlet <strong>of</strong> gasifier is connected with the various<br />

downstream systems Gas produced in Gasifier is scrubbed and cooled. Cool, Clean Gas and Air is then sucked<br />

into the Engine through a mixer butterfly consisting <strong>of</strong> piping and valves arrangement (Sridhar et al. <strong>20</strong>04). The<br />

shaft <strong>of</strong> the gas engine is coupled with the generator which produces the electricity (Rocha et al. <strong>20</strong>11). Some<br />

18


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

portion <strong>of</strong> the electricity is used in the pump <strong>of</strong> the cold storage system and rest <strong>of</strong> the electricity is given to the<br />

Smart Grid. From the smart grid, the electricity can be used for other ends purposes or by the consumers.<br />

(iii) Waste heat recovery unit: Waste heat recovery unit is nothing but counter flow or shell and tube heat<br />

exchanger, in which during the solar hours, solar energy and engine exhaust are used as hot fluid. While during<br />

the non-solar hours, engine exhaust and auxiliary firing <strong>of</strong> producer gas can be used as hot fluid in the heat<br />

recovery unit (Arteconi et al. <strong>20</strong>09). The hot fluid always flows towards the generator <strong>of</strong> the cold storage system,<br />

where it imparts the heat and ammonia is separated from strong aqua-solution. Apart from this, the thrice sources<br />

<strong>of</strong> energy can be used simultaneously but the system will not be economical viable.<br />

(iv) Scheffler’s Collectors: A concentrating primary reflector (or scheffler’s collector) tracks the sun, focusing<br />

sunlight on a fixed receiver. The primary reflector produces a converging beam <strong>of</strong> sunlight aligned with an axis<br />

<strong>of</strong> rotation. The axis <strong>of</strong> rotation is parallel to the axis <strong>of</strong> the earth, and it passes through the centers <strong>of</strong> both the<br />

reflectors (Hua et al. <strong>20</strong>10). The clock mechanism rotates the primary reflector around its axis <strong>of</strong> rotation at a<br />

rate <strong>of</strong> one revolution per day.<br />

3. RESULT AND ANALYSIS<br />

Biomass<br />

100%<br />

(100kW)<br />

Gasification 80%<br />

(80 kW)<br />

Losses <strong>20</strong>% (<strong>20</strong>kW)<br />

Fig.3. Energy flux diagram for gasifier<br />

The above figures show the experimental data. During all the tests, the ammonia- water absorption chiller was<br />

set up and these data are taken at full load operational mode. Fig.3 shows the energy flux diagram for the<br />

gasification <strong>of</strong> biomass in the gasifier. If the 100kW biomass is fed into gasifier then 80kW <strong>of</strong> producer gas can<br />

be produced for the end uses. Where <strong>20</strong> kW will be the losses in gasification. Biomass as the power and<br />

producer gas thermal power are defined as follows:<br />

Electric Energy 31.25%<br />

(25kW)<br />

Producer<br />

gas<br />

100%<br />

(80kW)<br />

Exhaust gases 31.25%<br />

(25kW)<br />

Heat losses in Jacket 31.25%<br />

(25kW)<br />

Losses 6.25%<br />

(5kW)<br />

Fig.4. Energy flux diagram for Engine gen-set<br />

<strong>19</strong>


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Q biomass = m biomass X CV biomass<br />

And Q producer gas = m producer gas X C P producer gas X ∆T<br />

Where, m biomass is biomass consumption rate in kg/h, C P producer gas is average specific heat is in kJ/kgK and ∆T<br />

is temperature difference between producer gas and environmental air. When the gasifier ran at the full load then<br />

the following parameters were found: m biomass =56kg/h, m producer gas = 170 m 3 /h, ∆T= 9 0 C and C P producer gas =<br />

1.232 kJ/kg 0 C.<br />

Fig.4 shows the energy flux diagram for engine gen-set in which the producer gas from gasifier was used in the<br />

internal combustion engine. At the full load operational condition; the electric load produced is <strong>of</strong> 25kW<br />

capacity, that measured by using <strong>of</strong> loading device fitted with heaters 3kW each ,the total stack gases thermal<br />

power was 25kW at 400 0 C.Initally this power was totally wastage but after some combination <strong>of</strong> cycles, this<br />

could be utilized. Such like this, the heat losses were in the engine jacket <strong>of</strong> about 25kW at 92 0 C. By considering<br />

the cooling water energy <strong>of</strong> internal combustion engine in the jacket is a potential for using this thermal energy<br />

for the heating purposes. At least 5kW was the accounted loss and it is compulsory to overcome frictional losses<br />

so these are the unaccounted losses or can’t be recovered and the following models were used in the above<br />

calculations:<br />

P = √3 VI for star connection<br />

Q exhaust gas = (m a + m pg ) X Cp exhaust gas X ∆T<br />

Q Jacket = m Jacket X C P water X ∆T<br />

Q unaccounted = Q producer gas – (P + Q exhaust gas + Q Jacket )<br />

Where (m a + m pg ) is the mass flow rate <strong>of</strong> exhaust gases in kg/h, m Jacket is the mass flow rate <strong>of</strong> water in kg/h,<br />

Cp exhaust gas is the specific heat <strong>of</strong> the exhaust in kJ/kg K, C P water is specific heat <strong>of</strong> water in kJ/kg K, V is voltage,<br />

I is current in ampere and ∆T is temperature difference while Q unaccounted is showing the frictional losses in genset.<br />

At the full load, electric power is 35 kW, mass flow rate <strong>of</strong> exhaust is 300kg/h and specific heat <strong>of</strong> exhaust<br />

gases is 1.008kJ/kg K. This system may be an advance system and ornamented with some modern technology.<br />

Now a days, the combined cycle’s plants are being generated for utilization <strong>of</strong> waste or stack or exhaust gases. In<br />

this technology exhaust gases give the heat to generator through heat recovery unit at 400 0 C apart from the<br />

heating by engine jacket , these gases can be used for this purpose after all.<br />

Cooling 51.7% (cooling<br />

capacity 15kW, COP<br />

0.517)<br />

Exhaust<br />

gases<br />

100%<br />

(25kW<br />

&4kWe)<br />

Pump 13.79%<br />

(4kWe)<br />

Losses 34.48%<br />

(10kW)<br />

Fig.5. Energy flux diagram for VAM<br />

Fig.5 shows the utilization <strong>of</strong> thermal power <strong>of</strong> stack gases which are at 400 0 C. About 15kW was effectively<br />

transformed into cooling load by absorption chiller (C.O.P =0.517 in this case) at temperature <strong>of</strong> the cold storage<br />

between 0 0 C – 5 0 C. About 40% losses <strong>of</strong> stack gases heat was due to design consideration <strong>of</strong> absorption<br />

chiller machine .13.79% <strong>of</strong> energy was utilized in running <strong>of</strong> the pump <strong>of</strong> VAM. In a gasifier gen-set power<br />

plant, there were the 62.5% losses. 31.25% losses <strong>of</strong> which were totally wastage. This wastage could be used in<br />

<strong>20</strong>


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

producing the cooling load <strong>of</strong> 60% <strong>of</strong> above losses in the combination <strong>of</strong> vapour absorption machine. This is the<br />

unique and advanced techniques in itself and it can be said that this system is the self sufficient system.<br />

4. CONCLUSION<br />

Experimental results were obtained from power plant and tri-generation systems. In the power plant, there were<br />

the losses <strong>of</strong> 31.25% as the stack gases but in the tri-generation system 51.7% <strong>of</strong> stack gases was utilized in<br />

operating the vapor absorption machine through a heat recovery unit. The COP <strong>of</strong> the system was 0.52 and room<br />

temperature was between 0 0 C-5 0 C.The thermal power from the engine water cooling jacket (31.25%) was<br />

utilized for heating purposes and the temperature <strong>of</strong> heating medium was noted 60 0 C - 63.5 0 C, while 72% heat<br />

can be recovered through the exhaust gases after heat recovery unit. The total losses in power plant were 68.75%,<br />

in which 62.5% was the recoverable losses. These recoverable losses were reflected in the form <strong>of</strong> cooling and<br />

heating in combined form for tri-generation system. Therefore, results show that power plant combined with<br />

absorption chiller (gases driven into generator through heat recovery unit) gives the better utilization <strong>of</strong> thermal<br />

losses which were in the form <strong>of</strong> stack gases and engine water cooling jacket. This was understood till now that<br />

there is no meaning <strong>of</strong> wastage in the world but this paper has presented useful meaning <strong>of</strong> wastage. It is nothing<br />

but the theme <strong>of</strong> this paper.<br />

NOMENCLATURE<br />

HRU<br />

GEN<br />

VAM<br />

m a<br />

m pg<br />

COP<br />

Heat Recovery Unit<br />

Generator <strong>of</strong> absorption machine<br />

Vapor Absorption Machine<br />

Mass Flow Rate <strong>of</strong> air<br />

Mass Flow Rate <strong>of</strong> Producer gas<br />

Coefficient <strong>of</strong> Performance<br />

REFERENCES<br />

[i] Arteconi A, Brandoni C and Polonara F, Distributed generation and trigeneration; energy saving<br />

opportunities in Italian supermarket sector, Applied Thermal Engineering 29 (<strong>20</strong>09), 1735-1743.<br />

[ii] Rocha MS, Andreos R and Moreira JR “Performance tests <strong>of</strong> small tri-generation pilot plants” Applied<br />

thermal engineering xxx, December <strong>20</strong>11, pp1-8.<br />

[iii] Sharma D.and Panwar N.L.,”Performance Evaluation <strong>of</strong> Biomass based Natural Draft Gasifier System for<br />

Thermal Application”, IE(I) Journal-AG, Vol.90, June <strong>20</strong>09 pp 34-38.<br />

[iv] Rathore N.S., Panwar N.L. and Vijay Chiplunkar Y.,” Design and Techno-Economic Evaluation <strong>of</strong> Biomass<br />

Gasifier for Industrial Thermal Applications” African Journal <strong>of</strong> Environmental <strong>Science</strong> and <strong>Technology</strong>,<br />

vol.3 (1), pp. 006-012, January <strong>20</strong>09.<br />

[v] Sridhar G, Sridhar H. V., Dasappa S, Paul P.J., Subbukrishna D. N. and Rajan N K S., “Biomass gasification<br />

technology- a route to meet energy needs”, Current <strong>Science</strong>, Vol. 87, no. 7, pp. 908-916, <strong>20</strong>04.<br />

[vi] Sridhar G, Paul P. J., Mukunda H.S., “Biomass Derived Producer Gas as a reciprocating Engine fuel – An<br />

Experimental Analysis”, Biomass and Bioenergy, vol. 21, no. 1, pp. 61-72, July <strong>20</strong>01.<br />

[vii] Sridhar G, Sridhar H. V., Dasappa S, Paul P.J., Rajan N K S. Mukunda H.S., “Development <strong>of</strong> Producer Gas<br />

Engine”, Journal <strong>of</strong> automobile engineering, Part D, Proc. Instrn. Mech Engrs, Vol. 2<strong>19</strong>, pp. 423-438, <strong>20</strong>05.<br />

[viii]Hua E, Yang YP, Nishimura A, Yilmaz F, Kouzani A. Solar thermal aided power generation. Applied<br />

Energy <strong>20</strong>10; 87(9):2881–5.<br />

21


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

DECOMPOSITION OF ENERGY CONSUMPTION IN INDIA: A DISCUSSION IN<br />

THE CONTEXT OF INDEX DECOMPOSITION ANALYSIS (IDA)<br />

Ponnala Vimal Mosahari 1* , D. Ganeshwar Rao 2 , Rajeev Satsangi 3<br />

1,3<br />

Department <strong>of</strong> Mechanical Engineering, Technical College, Dayalbagh Educational Institute, Dayalbagh, Agra<br />

2<br />

Department <strong>of</strong> Mechanical Engineering, Faculty <strong>of</strong> Engineering, Dayalbagh Educational Institute, Dayalbagh,<br />

Agra<br />

1*<br />

pvimalmosahari@gmail.com<br />

Abstract<br />

India is a developing country with enormous growth in the Industrial sector. A major concern however lies in the<br />

limited energy resources which are the driving force <strong>of</strong> any industry or country as a whole. Hence, it becomes<br />

important to focus on the energy consumption pattern <strong>of</strong> the country and to identify where optimization is<br />

needed. Energy consumption is also related to the environment i.e. CHG emissions and therefore CHG<br />

monitoring is also important to check the emissions. Index Decomposition Analysis (IDA) is an analytical tool<br />

based on the Index Number Theory used in Economics and Statistics. It is at present a much sought after<br />

research area to analyse the energy consumption pattern or to decompose energy indicators. IDA is widely used<br />

to disentangle and separate changes in energy consumption, energy intensity and CHG emissions in energy and<br />

environmental field. In the present work an attempt has been made to review the energy consumption in India<br />

and discuss IDA.<br />

Keywords: IDA, CHG<br />

1. Introduction<br />

India is not a resource rich country in terms <strong>of</strong> energy; it relies mostly on oil imports from Middle East. India is a<br />

developing country which needs to use its capital wisely, so it becomes necessary to monitor the energy<br />

consumption pattern and try to optimise it economically. The industrial sector in India consumes about 37% <strong>of</strong><br />

the energy (<strong>20</strong>04-05) [Sahu & Narayanan] and is an energy intensive sector. This work is concerned with the<br />

study and discussion on the use <strong>of</strong> Index Decomposition Analysis (IDA) to compute the energy consumption. An<br />

attempt has been made to study IDA, its attributes, its methods and how it can be used to calculate energy<br />

consumption. A simple discussion on energy consumption and energy intensity in India follows after the<br />

description <strong>of</strong> IDA that shows why aggregate indicators are important.<br />

Indian Energy Scenario: India is an oil importing country, depending on the Gulf countries for most <strong>of</strong> its energy<br />

needs. India faced the oil shock <strong>of</strong> rising prices, and then it faced with rising inflation and a balance <strong>of</strong> payment<br />

crisis in mid <strong>19</strong>91. The Government <strong>of</strong> India introduced comprehensive policy reform package comprising<br />

currency devaluation, deregulation, de-licensing, and privatization <strong>of</strong> the public sector [Sahu & Narayanan]. The<br />

rising oil prices has always been a serious concern for India since long due to its limited energy resources.<br />

Commercial sources <strong>of</strong> Energy (sources that cost i.e. Coal, Petroleum and Electricity) are only 50% <strong>of</strong> total<br />

energy consumption in India. It means non-commercial sources like wood, agricultural waste & animal dung<br />

constitute half <strong>of</strong> the total energy consumption in India. More than 60% <strong>of</strong> Indian households depend on<br />

traditional sources <strong>of</strong> Energy for cooking & heating needs. At the present rate <strong>of</strong> production &<br />

consumption, Coal reserves in India would last for about 130 years, Oil for only about 30 years. The commercial<br />

energy consumption in India is also diversified; Coal constitutes 29%, Oil & Gas 54% & Electricity 17%. At<br />

present only 15% <strong>of</strong> total hydro-power potential has been used, more Hydro Power Projects are in construction<br />

although the estimated annual energy potential from hydro-electric sources is around 90000 MW. Out <strong>of</strong> the total<br />

electricity production, 65.8% comes from Thermal power plants (which basically rely on<br />

Coal), 26.3% from hydro electricity & only 3.1% from nuclear power. Non-conventional, renewable energy<br />

sources like solar, wind energy constitute nearly 4.9%. (Source: Ministry <strong>of</strong> Power). The share <strong>of</strong> Public<br />

sector producing electricity is 558 billion kWh while private sector produces 58 billion kWh. Uranium reserves<br />

in country amounting to 70,000 tonnes (equivalent to 1<strong>20</strong> billion tonnes <strong>of</strong> coal) and Thorium reserves<br />

amounting to 3,60,000 tonnes (equivalent to 600 billion tonnes <strong>of</strong> coal) is about 5 times the coal reserves in<br />

country. 65% <strong>of</strong> total rural energy consumption is met from fuel woods (180 million tonnes for households + 43<br />

million tonnes for cottage industry, hotels etc). From <strong>19</strong>51 to <strong>20</strong>04, the coal production has increased 12<br />

times, crude oil 110 times & electricity 65 times. In <strong>19</strong>73, price for petroleum crude oil in global market was<br />

only $2 per barrel ($2.09 exactly). Only 0.3% <strong>of</strong> world’s known oil reserves are in India. Transport sector<br />

accounts for 56% <strong>of</strong> total oil consumption in India. Demand for coal rises @ 4 to 5% per year, for petroleum<br />

products 6 to 7% per year & for electricity 9 to 10% per year. India is second largest exploiter <strong>of</strong> Wind Energy –<br />

1000 MW (70% by private sector). There are 33 lakh bio-gas plants, 2 lakh solar cookers & 10000 street lighting<br />

22


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

systems using solar photo-voltaic technology. Out <strong>of</strong> total electricity consumption in India, 37% goes to<br />

Industry, 24% to agriculture, 21 % to domestic use, 14% to public lighting & 4% to railway traction. These<br />

figures do not include captive (i.e. private sector) power generation.<br />

2. Background and Objective<br />

The Oil shocks <strong>of</strong> <strong>19</strong>70s, the volatile economic conditions, the depleting energy resources, the population growth<br />

and various other factors compel the global economy to consider their energy consumption pattern and focus on<br />

conservation. The energy crisis made the energy economists realise the need to identify the energy consumption<br />

pattern and also the factors that are responsible for the changes in consumption. The idea was to identify the<br />

consumption areas, the factors that results in increased energy demands and also to predict the future energy<br />

requirement. IDA methodology was first used in late <strong>19</strong>70s and since then many changes and modifications have<br />

come up. The IDA methodology was designed on the basis <strong>of</strong> the Index Number Theory used in Economics and<br />

Statistical Studies. With rising energy consumption, Green House Gas (CHG) generation also increased that tend<br />

to destroy the equilibrium <strong>of</strong> the planet. Hence, there was need to monitor these CHG emissions too so as to<br />

reduce it wherever possible without affecting the economic activities. Since, energy consumption is directly<br />

responsible for the emission <strong>of</strong> CHG, so there is a need to understand how energy consumption effects CHG<br />

emissions.<br />

Index Decomposition Analysis (IDA) has been developed and a large number <strong>of</strong> IDA studies have been reported<br />

in the last 25 years [Ang and Zhang, <strong>20</strong>00]. IDA is now broadly acknowledged as an analytical tool for<br />

policymaking to deal with energy and environmental issues [Granel <strong>20</strong>03]. India to become a global economic<br />

power hence needs to use the scarce energy resources it has carefully, without compromising on the growth it<br />

tends to achieve. It becomes important to monitor the energy consumption and its related growth in the Indian<br />

Economy as a whole. The idea <strong>of</strong> the present work is to identify the need to use IDA technique to analyse the<br />

energy sector in India to make policies. This is due to the fact that energy consumption is increasing<br />

exponentially but the GDP growth rate is not in line with the national energy consumption. The question arises<br />

where is the energy going Industries in India consume about 37% <strong>of</strong> the total energy consumption <strong>of</strong> the Nation,<br />

and also tends to be one <strong>of</strong> the largest revenue earner. Hence, the energy consumed in the industry needs to be<br />

monitored and also the CHG it emits has to be kept in check. This work shows how the use <strong>of</strong> IDA technique<br />

will help to monitor the energy sector in India.<br />

3. Index Decomposition Analysis (IDA)<br />

Decomposing and separating the elements <strong>of</strong> a system is a useful technique to study any changes in the system.<br />

IDA is a technique that has been developed to decompose indicator changes at the sector level [Granel, <strong>20</strong>03].<br />

IDA traces its roots to the index number theory used in Economics and Statistical Analysis. However it is now<br />

widely used in environmental field to analyse the changes in indicators such as energy use, energy intensity or<br />

energy related CHG emissions [Granel, <strong>20</strong>03]. IDA was first used in the energy sector after the energy crisis in<br />

the <strong>19</strong>70s, and now it is widely used in this sector. Pr<strong>of</strong>. Ang B. Wah [<strong>20</strong>04] identified 5 main application areas:<br />

(i) Energy demand and supply,<br />

(ii) Energy related CHG emissions,<br />

(iii) Materials flow and dematerialization,<br />

(iv) National energy efficiency trend monitoring, and<br />

(v) Cross counties comparison.<br />

3.1 Aggregate indicators<br />

Aggregate Indicators can be defined as the statistical combination <strong>of</strong> a number <strong>of</strong> indicators taken from a variety<br />

<strong>of</strong> sources into a single indicator. It provides more accurate results as in a broader data set which covers a larger<br />

number <strong>of</strong> variables and sources. They are able to highlight how the concerned quantities change and therefore<br />

make comparison studies practical [Zhang, <strong>19</strong>99]. Theoretically it should always be the lowest indicator that has<br />

to be selected but generally in a practical approach aggregate <strong>of</strong> the indicators are used. The advantage <strong>of</strong><br />

aggregate indicators is such that the data is limited and easy to handle.<br />

Mathematical expression for an aggregate indicator V can be expressed as<br />

Where are the causal factors, the aggregate depends on this. The summation is taken over ‘p’ sectors.<br />

The equation helps us to see the changes in the aggregate indicator V, with respect to change in the causal<br />

factors. The causal factors in case <strong>of</strong> energy related analysis are energy consumed ‘E’, energy consumed per unit<br />

production ‘I’ and CHG emissions.<br />

23


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

There are two ways to decompose aggregate indicator i.e. multiplicative and additive. Suppose that from year 0<br />

to T, the aggregate V varies from V 0 to V T . There are two different ways to express such a change: the<br />

multiplicative one and the additive one . Any decomposition can therefore be done<br />

either multiplicatively or additively [Granel et al.]. An aggregate given as a ratio should be decomposed through<br />

a multiplicative approach whereas an absolute change <strong>of</strong> an aggregate, usually given in the original unit <strong>of</strong><br />

measurement, should be run through an additive approach [Ang et al. <strong>20</strong>03]. There are three ways to handle the<br />

decomposition in time domain i.e. fixed base year manner, rolling base year and multilateral indices. Following<br />

are the mathematical representation <strong>of</strong> aggregate indicators used in the energy analysis.<br />

The aggregate energy consumption indicator [Park <strong>19</strong>92, Sun <strong>19</strong>98]<br />

Where, E = Total industrial energy input (energy unit), Q = Total industrial production (monetary unit),<br />

; represents the energy intensity and represents the share <strong>of</strong> industrial production.<br />

The aggregate energy intensity indicator [Gozalez and Suarez <strong>20</strong>03, Choi and Ang <strong>20</strong>02]<br />

The aggregate CHG emissions indicator [Sun and Ang <strong>20</strong>00, Ang and Liu <strong>20</strong>01]<br />

Where C is the total CHG emissions and the CHG emissions are due to fuel type j.<br />

There are various methods available to perform an IDA such as Laspeyres index, Divisia Index, mean-rate-<strong>of</strong>change<br />

index method and many more. The sequence to be followed while performing an IDA is<br />

1. Choose the aggregate indicator you want to decompose<br />

2. Decide whether to go through an additive or multiplicative approach on the basis <strong>of</strong> the problem.<br />

3. Choose the IDA method you want to use, do it wisely on the basis <strong>of</strong> the problem.<br />

4. Decide whether to use a fixed or a rolling base year.<br />

Table 1 Trends in Energy Consumption and Energy Intensity in India<br />

(Energy Statistics <strong>20</strong>12, Ministry <strong>of</strong> Statistics and Program Implementation, GOI)<br />

Year Energy Consumption GDP (Rs. Crores ) Energy Intensity<br />

in Billion kWh<br />

<strong>19</strong>70-71 663.99 517148 0.1284<br />

<strong>19</strong>75-76 840.53 596428 0.1409<br />

<strong>19</strong>80-81 1012.58 6883<strong>20</strong> 0.1456<br />

<strong>19</strong>85-86 1477.50 766135 0.1653<br />

<strong>19</strong>90-91 <strong>19</strong>02.75 852297 0.1594<br />

<strong>19</strong>95-96 2436.77 939540 0.1593<br />

<strong>20</strong>00-01 3154.28 1034931 0.1553<br />

<strong>20</strong>05-06 3909.37 1117734 0.1374<br />

<strong>20</strong>06-07 4226.78 1134023 0.1355<br />

<strong>20</strong>07-08 4508.26 1147677 0.1325<br />

<strong>20</strong>08-09 4845.25 1161495 0.1166<br />

<strong>20</strong>09-10 5462.31 1175480 0.1224<br />

<strong>20</strong>10-11 5693.54 1182105 0.1167<br />

3.2 Trends in energy consumption and energy intensity in India<br />

Energy intensity is the amount <strong>of</strong> energy consumed for generating one unit <strong>of</strong> Gross Domestic Product (GDP) (at<br />

constant prices). Energy Intensity is the most used policy indicator. In a developing country like India, where the<br />

data on consumption <strong>of</strong> non-conventional energy from various sources, particularly in rural areas are not<br />

available, Energy Intensity is generally computed on the basis <strong>of</strong> the basis <strong>of</strong> the consumption <strong>of</strong> conventional<br />

energy [Energy Statistics <strong>20</strong>12, Ministry <strong>of</strong> Statistics and Program Implementation, GOI].<br />

24


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The table below shows the energy intensity from the period <strong>19</strong>70-71 to <strong>20</strong>10-11 as per the Energy Statistics <strong>20</strong>12<br />

published by Ministry <strong>of</strong> Statistics and Program Implementation, GOI. The table given below shows that the<br />

energy intensity (at <strong>19</strong>99-<strong>20</strong>00 prices) increased from 0.128 kWh in <strong>19</strong>70-71 to 0.165 kWh in <strong>19</strong>85-86, but it<br />

again came down to 0.117 kWh (at <strong>20</strong>04-05 prices) in <strong>20</strong>10-11. Figure 1 shows how the energy consumption is<br />

growing linearly over the mentioned period, but the GDP growth shown in figure 2 goes almost flat in the period<br />

between <strong>20</strong>05-06 to <strong>20</strong>10-11. The growth in GDP exists but not in line with the energy consumption. The third<br />

figure shows the energy intensity between the period <strong>of</strong> <strong>19</strong>70-71 and <strong>20</strong>10-11. The decline in energy intensity<br />

shows the efficiency <strong>of</strong> the national energy consumption. The period between <strong>20</strong>08-09 and <strong>20</strong>10-11 do not show<br />

much change in the energy intensity.<br />

Figure 1<br />

Figure 2<br />

Figure 3<br />

25


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4. Conclusion<br />

The major concern that arises after looking at the data is whether the country is using the energy optimally. To<br />

address such concerns we need to decompose the energy consumption unit into its constituent sectors and then<br />

analyze the decomposed energy sector for its energy consumption, energy intensity or CHG emissions. The<br />

Index Decomposition Analysis is a simple but apt technique to address this problem and will help the<br />

government to plan policy in a better way so as to achieve the planed targets.<br />

The present work was just a discussion on IDA, its methodologies and its attributes based on the comparison<br />

done by Frederic Granel in <strong>20</strong>03 on various IDA methods. In view <strong>of</strong> the tool i.e. available to us, we can in<br />

future decompose the energy consumption <strong>of</strong> India, where wastage <strong>of</strong> energy is a key problem. We may able to<br />

identify the aggregate energy indicators and then help plan the policy to conserve energy and waste less.<br />

End Note<br />

The IDA in its present form is the work <strong>of</strong> distinguished Pr<strong>of</strong>. Ang Beng Wah <strong>of</strong> NUS, Singapore. He has<br />

authored many papers and technical notes in international journals on the subject and also guided many PG and<br />

doctoral students. Today the Industrial and System Engineers owe most <strong>of</strong> the findings related to new techniques<br />

<strong>of</strong> IDA to him. The equations and text related to IDA, used in this paper has mostly been referred from Frederic<br />

Granel’s doctoral thesis submitted in <strong>20</strong>03.<br />

References<br />

1. Granel, F., <strong>20</strong>03, A Comparative Analysis <strong>of</strong> Index decomposition Methods, M. Eng. Thesis (National<br />

<strong>University</strong> <strong>of</strong> Singapore).<br />

2. Ang, B.W., <strong>20</strong>04, Decomposition analysis for policymaking in energy: which is the preferred method’,<br />

Energy Policy 32, pp. 1131-1139.<br />

3. Ang, B.W., Liu, F.L., Chew, E.P., <strong>20</strong>03, Perfect decomposition techniques in energy and environmental<br />

analysis, Energy Policy 31, pp. 1561-1566.<br />

4. Ang, B.W., Lee, S.Y., <strong>19</strong>94, Decomposition <strong>of</strong> Industrial Energy Consumption: Some methodological and<br />

application issues, Energy Economics, Vol 16, No. 2, pp 83-92.<br />

5. Sahu, S.K., Narayanan, K., ‘Decomposition <strong>of</strong> Industrial Energy Consumption in Indian Manufacturing: The<br />

Energy Intensity Approach’.<br />

6. Na, L., <strong>20</strong>06, Energy Efficiency Monitoring and Index Decomposition Analysis, Doctoral Thesis (National<br />

<strong>University</strong> <strong>of</strong> Singapore).<br />

7. Energy Statistics <strong>20</strong>12, Ministry <strong>of</strong> Statistics and Program Implementation, GOI.<br />

8. Energy Statistics <strong>20</strong>11, Ministry <strong>of</strong> Statistics and Program Implementation, GOI.<br />

26


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

THERMO-ECONOMIC OPTIMIZATION OF WORK CONSUMING<br />

DEVICES<br />

Rajesh Arora<br />

Associate Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering,<br />

Dronacharya College <strong>of</strong> Engineering, Khentawas (FarrukhNagar), Gurgaon<br />

Email: rajesharora12<strong>19</strong>@rediffmail.com<br />

Abstract<br />

The finite-time and finite size are considered to be the major constraints in the optimization <strong>of</strong> the real systems.<br />

In classical thermodynamic analysis, these constraints are not considered because <strong>of</strong> the inherent assumption <strong>of</strong><br />

reversibility. Finite Time Thermodynamics provide a fundamental starting point for the optimization <strong>of</strong> real<br />

systems. The optimization studies <strong>of</strong> refrigeration and heat pump systems that consider various objective<br />

functions based on Finite Time Thermodynamics and thermo-economics are reviewed here.<br />

Keywords: FTT, Endo-reversible, Refrigerator, Heat Pump, Heat Reservoir<br />

1. INTRODUCTION:<br />

In 1824, Carnot [1] proposed a cycle operating on reversibility principles and the efficiency <strong>of</strong> this reversible<br />

Carnot cycle became the upper bound <strong>of</strong> thermal efficiency for heat engines that work between the same<br />

temperature limits in classical thermodynamics. This equally applies to the COP <strong>of</strong> refrigerator and heat pumps<br />

that execute a reversed Carnot cycle. When T H and T L denote the temperatures <strong>of</strong> hot and cold thermal<br />

reservoirs, thermal efficiency <strong>of</strong> Carnot heat engines and COP for refrigerators and heat pumps are expressed as<br />

η c = 1 – T L/ T H , COP ref = T L / (T H - T L ) and COP hp = T L / (T H - T L ), respectively.<br />

Since all processes are reversible and executed in quasi-static fashion in a Carnot cycle so efficiency and COP<br />

mentioned above can only be approached by infinitely slow processes. Therefore, duration <strong>of</strong> the processes will<br />

be infinitely long hence it is not possible to obtain a certain amount <strong>of</strong> power from a heat engine or <strong>of</strong> heating<br />

load / cooling load from a heat pump / refrigerator with heat exchangers having finite heat transfer areas, i.e.<br />

W = 0, Q H = 0 and Q L = 0 for 0 < A < ∞.<br />

If we require certain amount <strong>of</strong> power output in a heat engine, heating load / cooling load in a refrigerator<br />

executing an ideal Carnot cycle, the necessary heat exchanger area would be infinitely large, i.e. A = ∞ for W ><br />

0, Q H > 0 and Q L > 0<br />

Thus the Carnot thermal efficiency and COP do not have great significance and are poor guides to the<br />

performances <strong>of</strong> real heat engines, heat pumps and refrigerators. In practice, all processes take place in finite size<br />

devices in finite time, therefore, it is impossible to meet thermodynamic equilibrium and hence irreversibility<br />

conditions between the system and the surroundings. For this reason, the reversible Carnot cycle cannot be<br />

considered as a comparison standard for real thermal systems on size perspective, although it gives an upper<br />

bound <strong>of</strong> performance limits.<br />

In order to obtain a certain amount <strong>of</strong> power with finite size devices, Chambadal [2,3], Novikov [4,5]. Novikov’s<br />

analysis was reprinted in some engineering textbooks [6, 7] and Curzon – Ahlborn [8] extended the reversible<br />

Carnot cycle to an endoreversible Carnot cycle by taking the irreversibility <strong>of</strong> finite-time heat transfer into<br />

account and investigated the maximum power conditions. During the last decade, many optimization studies for<br />

heat engines based on endoreversible and irreversible mode have been performed, using FTT approach [9-11] by<br />

number <strong>of</strong> researchers. Usually in these studies, the performance parameters chosen were power output, thermal<br />

efficiency, specific power, entropy generation, power density, exergy and ecological benefit for performance<br />

analysis <strong>of</strong> heating engines. Thus, FTT provides a tool for such analysis as it is characterized by finite time, finite<br />

size and finite rate constraints.<br />

In the recent years the optimization studies using FTT have been further extended to the performance <strong>of</strong><br />

endoreversible and irreversible refrigerator and heat pump systems. The maximum COP is not necessarily the<br />

primary concern in the design <strong>of</strong> real refrigerators and heat pumps, cooling/ heating power, cost, size, weight and<br />

other considerations are also important. Sahin and Kodal [12] introduced a new finite time thermo-economic<br />

performance criterion based on objective function defined as the cooling load <strong>of</strong> refrigeration and heating load <strong>of</strong><br />

heat pumps per unit total cost. They investigated the economic design conditions for optimizing thermo<br />

economic performance for endoreversible single stage vapor compression refrigeration and heat pump systems<br />

27


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

by considering a reservoir <strong>of</strong> infinite thermal capacity. However, in real engineering systems the reservoirs are<br />

generally <strong>of</strong> finite size and finite thermal capacity. Consequently, the temperature distributions in the heat source<br />

and heat sink are not constant throughout the heat exchangers. Therefore, the system performance depends also<br />

on the magnitude <strong>of</strong> the thermal capacitance rates and temperature variations <strong>of</strong> the reservoirs.<br />

This paper presents the thermo economic optimization <strong>of</strong> endoreversible refrigerator and heat pumps with<br />

variable temperature heat reservoir. The thermo economic function, defined as the cooling or heating load per<br />

unit total cost is taken as the objective for the performance analysis <strong>of</strong> systems under consideration. The<br />

objective function is optimized with respect to the working fluid temperature and the expressions for various<br />

parameters at the optimal operating conditions are obtained. The obtained results are compared with those<br />

obtained by using fixed temperature heat reservoir. It is observed that when a variable temperature heat reservoir<br />

is coupled with refrigerator and heat pump, the optimal operating conditions appear at lower values <strong>of</strong> objective<br />

function. This indicates a reduced performance with respect to those obtained by systems coupled to fixed<br />

temperature heat reservoir. It is also studied that to maintain the same value <strong>of</strong> optimal specific heating or<br />

cooling load as that <strong>of</strong> values predicted for systems with fixed temperature heat reservoir, more cost is required.<br />

The results since obtained under realistic conditions <strong>of</strong> variable temperature heat reservoir, provide a practical<br />

prediction for the performance and design <strong>of</strong> actual refrigerator and heat pump systems.<br />

Nomenclature<br />

a<br />

investment cost parameter for heat exchangers<br />

A heat transfer area <strong>of</strong> heat exchanger (m 2 )<br />

b 1<br />

investment cost parameter for compressor and its driver<br />

b 2<br />

energy consumption cost parameter<br />

b p<br />

equivalent annual operation hours per unit power input.<br />

b<br />

b 1 + b 2 + b p<br />

c<br />

cost<br />

C<br />

heat capacitance rate (KW/K)<br />

C p<br />

specific heat <strong>of</strong> external fluid (KJ/kg-K)<br />

COP<br />

coefficient <strong>of</strong> performance<br />

F<br />

objective function<br />

k<br />

a/b; economic parameter<br />

LMTD log mean temperature difference<br />

m<br />

mass flow rate <strong>of</strong> external fluid (kg/s)<br />

Q<br />

heat transfer rate (cooling or heating power) (W)<br />

q Q/A; specific heating or cooling load (W/m 2 )<br />

T<br />

temperature (K)<br />

U overall heat transfer coefficient (W/m 2 K)<br />

W<br />

power input (W)<br />

Greek letters<br />

ε<br />

effectiveness<br />

Subscripts<br />

e<br />

energy consumption<br />

H<br />

high temperature condenser side (sink side)<br />

H 1<br />

inlet heat <strong>of</strong> reservoir<br />

H 2<br />

outlet heat <strong>of</strong> reservoir<br />

hp<br />

heat pump<br />

i<br />

investment<br />

L<br />

low temperature evaporator side (source side)<br />

L 1<br />

inlet heat <strong>of</strong> reservoir<br />

L 2<br />

outlet heat <strong>of</strong> reservoir<br />

max<br />

maximum<br />

opt<br />

optimum<br />

ref<br />

refrigerator<br />

x<br />

warm working fluid (sink side)<br />

y<br />

cold working fluid (source side)<br />

Superscripts<br />

* optimum condition<br />

28


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2.OPTIMIZATION ANALYSIS :<br />

2.1 Optimization for Endoreversible Heat Pump system<br />

Taking the finite thermal capacity <strong>of</strong> reservoir makes the cycle realistic, conceptual heat pump cycle. The<br />

schematic model and T-S diagram <strong>of</strong> an endoreversible heat pump system, coupled to a variable temperature heat<br />

reservoir are shown in Fig 1. The system operates steadily between two variable reservoirs, i.e. between heat<br />

source <strong>of</strong> temperature range (T L1 -T L2 ) and heat sink <strong>of</strong> temperature range (T H2 -T H1 ). The working fluid in the<br />

heat pump, exchanges heat with the reservoirs, has two constant temperature limits T y and T x . Assuming that the<br />

heat exchangers are counter flow, and the heat conductance (heat transfer co-efficient and area product) <strong>of</strong> hot<br />

and cold side heat exchangers are U H A H and U L A L , respectively.<br />

From the heat transfer theory, the steady rate <strong>of</strong> heat flow (Q L ) from heat source to the working fluid <strong>of</strong> heat<br />

pump and the rate (Q H ) at which the heat is rejected from the working fluid <strong>of</strong> heat pump to the heat sink in the<br />

heat exchangers, during the two isothermal processes are, respectively, given by:<br />

Q H<br />

T H<br />

1/U H A H<br />

T X<br />

T H2<br />

T H1<br />

3<br />

2<br />

T X<br />

Q H<br />

Heat Pump<br />

Q L<br />

Q L<br />

T Y<br />

T L<br />

W<br />

T X<br />

T L1<br />

TL2<br />

T Y 4<br />

1/U L A L<br />

1<br />

Fig 1 Endo-reversible Carnot heat pump model and its T-S diagram<br />

Q L = U L A L (LMTD) L = m L C pL (T L1 – T L2 ) (1)<br />

Q H = U H A H (LMTD) H = m H C pH (T H2 – T H1 ) (2)<br />

Where U L and U H are the overall heat transfer coefficients on evaporator and condenser side; and A L , A H are the<br />

heat transfer area <strong>of</strong> the heat exchangers on evaporator and condenser side, respectively.<br />

LMTD is the logarithmic mean temperature difference and is defined as<br />

(LMTD) L = {(T L1 - T Y ) – (T L2 - T Y )} / ln {(T L1 - T Y ) / (T L2 - T Y )} (3)<br />

(LMTD) H = {(T X – T H1 ) – (T X – T H2 )} / ln {(T X – T H1 ) / (T X – T H2 )} (4)<br />

Using above equations, the following expressions are obtained<br />

T L2 = T Y + (T L1 - T Y ) exp (-U L A L / m L C pL ) (5)<br />

T H2 = T X - (T X – T H1 ) exp (-U H A H / m H C pH ) (6)<br />

Further, Eq. (1) - (6) gives<br />

Q L = C L ε L (T L1 - T Y ) (7)<br />

Q H = C H ε H (T X – T H1 ) (8)<br />

On rearranging,<br />

C L = Q L / ε L (T L1 - T Y ) (9)<br />

Where,<br />

C L = m L C pL (10)<br />

ε L = 1 - exp (-U L A L / m L C pL ) (11)<br />

and,<br />

C H = Q H / ε H (T X – T H1 ) (12)<br />

Where,<br />

C H = m H C pH (13)<br />

ε H = 1 - exp (-U H A H / m H C pH ) (14)<br />

29


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

are the thermal capacitance rates and effectiveness <strong>of</strong> heat exchangers on evaporator side (cold) and condenser<br />

side (hot) respectively.<br />

Let<br />

y = (T L1 - T Y ) (15)<br />

So T Y = (T L1 – y)<br />

x = (T X – T H1 ) (16)<br />

so T X = T H1 + x<br />

expressing A L and A H in terms <strong>of</strong> ε L & ε H<br />

A L = -C L ln(1 - ε L ) / U L (17)<br />

A L = -Q L ln(1 - ε L ) / (U L ε L y) (18)<br />

Let k L = -ln(1 - ε L ) / (U L ε L ) (<strong>19</strong>)<br />

So A L = Q L k L / y (<strong>20</strong>)<br />

Similarly,<br />

A H = -C H ln(1 – ε H ) / U H (21)<br />

A H = -Q H ln(1 – ε H ) / (U H ε H y) (22)<br />

Let k H = -ln(1 – ε H ) / (U H ε H ) (23)<br />

So A H = Q H k H / y (24)<br />

From the first law <strong>of</strong> thermodynamics, the power input to the heat pump is<br />

W = Q H - Q L (25)<br />

From the second law <strong>of</strong> thermodynamics, for an endoreversible cycle, the changes in entropies <strong>of</strong> the working<br />

fluid for heat addition and heat removing isothermal process yields:<br />

Q L / T Y = Q H / T X<br />

So Q L = T Y Q H / T X<br />

Or Q L = Q H (T L1 – y) / (T H1 + x) (26)<br />

The coefficient <strong>of</strong> performance for endoreversible heat pump, as defined earlier is<br />

COP hp = Q H / W = (T H1 + x) / [(T H1 + x) - (T L1 - y )] (27)<br />

The objective function <strong>of</strong> thermoeconomic optimization as proposed by earlier researchers [9, 12-13] is given by<br />

F hp = Q H / (C i + C e + C m ) (28)<br />

Where C i , C e and C m are the annual investment, energy consumption cost and maintenance costs, respectively.<br />

The investment cost includes the investment cost <strong>of</strong> the main system components which are the heat exchangers<br />

and the compressor together with its prime movers, where the investment cost <strong>of</strong> the heat exchangers is assumed<br />

to be proportional to the total heat transfer area, while the investment cost <strong>of</strong> the compressor and its driver is<br />

assumed to be proportional to its compression capacity or required power input. Thus the annual investment cost<br />

<strong>of</strong> the system can be given as:<br />

C i = a(A H + A L ) + b 1 W (29)<br />

Where a is the proportionality coefficient <strong>of</strong> the heat exchangers and is equal to the capital recovery factor times<br />

investment cost per unit heat transfer are and its dimension is ncu/year-m 2 . The proportionality coefficient <strong>of</strong> the<br />

compressor and its driver, b 1 is equal to the capital recovery factor times investment cost per unit power and its<br />

dimension is ncu/year-kW. The unit ncu stands for the national currency unit. The initial investment cost is<br />

converted to equivalent yearly payment using the capital recovery factor. The annual energy consumption cost is<br />

proportional to the power input i.e.<br />

c e = b 2 W = b 2 (Q H - Q L ) (30)<br />

Where the coefficient, b 2 is equal to the annual operation hours times price per unit energy and its dimension is<br />

ncu/year-m 2 .<br />

And C m = b p (Q H - Q L ) (31)<br />

Here b p is equal to equivalent annual operation hours per unit power input.<br />

Substituting Eqs. (29), (30) and (31) into Eq. (28), gives<br />

F hp = Q H / {a (A H + A L ) + b (Q H - Q L )} (32)<br />

Where b = b 1 + b 2 + b p<br />

Using Eqs. (<strong>20</strong>), (24), and (26) gives<br />

F hp = Q H / Q H [a{(k H / x) + (k L (T L1 - y) / y(T H1 + x))}+ b {1 – ((T L1 - y) / (T L1 + x))}]<br />

Or bF hp = 1 / [k{(k H / x) + (k L (T L1 - y) / y(T H1 + x))}+ b {1 – ((T L1 - y) / (T L1 + x))}] (33)<br />

Where k = a/b; Economical parameter<br />

30


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The objective function given in Eq. (32) can be plotted with respect to the coefficient <strong>of</strong> performance <strong>of</strong> the heat<br />

pump given in Eq. (27) for various k values, as shown in Fig-2. It is apparent from the Fig 2 that there exists a<br />

certain value <strong>of</strong> COP hp at which the objective function bF hp is maximum for a given k value. Thus Eq. (32) can<br />

be maximized with respect to y and x.<br />

Therefore, ∂bF hp / ∂y = 0 and ∂bF hp / ∂x = 0 gives:<br />

y * = √(kk L T L1 ) and (34)<br />

x * = T H1 / [√{(T L1 – y) / (kk H )(1-((kk L )/y))} - 1] (35)<br />

The optimal values <strong>of</strong> x * and y * can be submitted in Eq. (32) to obtain the value <strong>of</strong> bF max<br />

bF hp = 1 / [k{(k H / x * ) + (k L (T L1 – y * ) / y * (T H1 + x * ))}+ b {1 – ((T L1 – y * ) / (T L1 + x * ))}]<br />

(36)<br />

and the optimum coefficient <strong>of</strong> performance is<br />

COP * hp = Q H / W = (T H1 + x * ) / [(T H1 + x * ) - (T L1 – y * )] (37)<br />

2.2 Optimization for Endoreversible Refrigerator system<br />

The model and T-S diagram as given in Fig 1 for an endoreversible heat pump hold schematically for<br />

endoreversible refrigerator also. However, in this case (T H2 – T H1 ) is the ambient temperature and (T L1 – T L2 ) is<br />

the temperature <strong>of</strong> the cooled space. Therefore, Eqs. (1) – (26) can be used for endoreversible refrigerator. The<br />

coefficient <strong>of</strong> performance (COP) for endoreversible refrigerator is:<br />

COP ref = Q L / W = (T L1 - y) / [(T H1 + x) - (T L1 - y)] (38)<br />

The objective function <strong>of</strong> thermoeconomic optimization as proposed by earlier researchers [9, 12-13] is given by<br />

F ref = Q L / (C i + C e + C m ) (39)<br />

C i = a(A H + A L ) + b 1 W<br />

C e = b 2 W = b 2 (Q H - Q L )<br />

And C m = b p (Q H - Q L )<br />

Here b p is equal to equivalent annual operation hours per unit power input.<br />

Substituting the value <strong>of</strong> C i , C e and C m into Eq. (39), gives<br />

F ref = Q L / {a (A H + A L ) + b (Q H - Q L )} (40)<br />

Where b = b 1 + b 2 + b p<br />

Using Eqs. (<strong>20</strong>), (24), and (26) gives<br />

F ref = Q L / Q L [a{(k H / x)((T H1 + x) / (T L1 - y)) + (k L / y) }+ b {((T H1 + x) / (T L1 - y)) - 1}]<br />

Or b F ref = 1 / [k{(k H / x)((T H1 + x) / (T L1 - y)) + (k L / y) }+ {((T H1 + x) / (T L1 - y)) - 1}]<br />

(41)<br />

Where k = a/b; Economical parameter<br />

The objective function given in Eq. (41) can be plotted with respect to the coefficient <strong>of</strong> performance <strong>of</strong> the heat<br />

pump given in Eq. (38) for various k values, as shown in Fig-3. It is apparent from the Fig 3 that there exists a<br />

certain value <strong>of</strong> COP hp at which the objective function bF hp is maximum for a given k value. Thus Eq. (41) can<br />

be maximized with respect to y and x.<br />

Therefore, ∂bF hp / ∂y = 0 and ∂bF hp / ∂x = 0 gives:<br />

x * = √(kk H T H1 ) and` (42)<br />

y * = T L1 / [√{(T H1 + x) / (kk L )(1+ ((kk H )/x))} + 1] (43)<br />

The optimal values <strong>of</strong> x * and y * can be submitted in Eq. (32) to obtain the value <strong>of</strong> bF max<br />

b F ref = 1 / [k{(k H / x * )((T H1 + x * ) / (T L1 – y * )) + (k L / y * ) }+ {((T H1 + x * ) / (T L1 – y * )) - 1}]<br />

(44)<br />

and the optimum coefficient <strong>of</strong> performance is<br />

COP ref = Q L / W = (T L1 – y * ) / [(T H1 + x * ) - (T L1 – y * )] (45)<br />

3.PERFORMANCE ANALYSIS<br />

The variation <strong>of</strong> objective function for refrigerators and heat pumps with respect to the coefficient <strong>of</strong><br />

performance (COP) for various values <strong>of</strong> economic parameter (k), corresponding to both fixed and variable<br />

temperature heat reservoir are shown in Fig 2 and Fig 3, respectively. In each figure, the dotted line represents<br />

curves for a system with fixed temperature heat reservoir, while the curves with solid line show the variation, for<br />

the same system but with variable temperature heat reservoir. In both the cases, for each system, a similar pattern<br />

<strong>of</strong> variation is observed; however, the value <strong>of</strong> COP that maximizes the objective function for the given value <strong>of</strong><br />

31


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

k appears at lower a value for the system with finite temperature heat reservoir. The reduced global and optimal<br />

performance with respect to systems with fixed temperature reservoir will correspondingly affect the<br />

performance and design criterion.<br />

3.5<br />

3<br />

2.5<br />

bFref<br />

2<br />

1.5<br />

1<br />

0.5<br />

0<br />

2.0 2.5 3.0 3.5 4.0 4.5 5.0<br />

COPref<br />

kv = 0.4 kf = 0.4 kv = 0.1 kf = 0.1<br />

Fig 2 Variation <strong>of</strong> objective function for the endoreversible refrigerator wrt COP for various values <strong>of</strong> k<br />

Fig 3 Variation <strong>of</strong> objective function for the endoreversible heat pump wrt COP for various values <strong>of</strong> k<br />

The variation <strong>of</strong> the optimum COP for the refrigerators and heat pumps with respect to economic parameter (k),<br />

corresponding to both variable and fixed temperature heat reservoir, respectively, are shown in Fig 4 and Fig 5. It<br />

displays, in all cases, an increase in optimal performance coefficients as k decreases. At k = 0, COP =<br />

(COP)carnot, but in real applications, k is always greater than zero and its value is determined by the economic<br />

conditions <strong>of</strong> a country.<br />

32


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig 4 Variations <strong>of</strong> optimum COP <strong>of</strong> refrigerator wrt k<br />

Fig 5 Variations <strong>of</strong> optimum COP <strong>of</strong> heat pump w.r.t k<br />

4. CONCLUSION<br />

The thermo economic performance analysis <strong>of</strong> work consuming devices coupled to variable temperature heat<br />

reservoir has been presented for more realistic optimization and design considerations. The objective functions,<br />

taken as the heating power per unit total cost for the heat pumps and cooling power per unit total cost for the<br />

refrigerators is optimized with respect to the working fluid temperatures and the values <strong>of</strong> various parameters at<br />

optimal operating conditions are calculated. The maximum objective function and the corresponding optimum<br />

COP have been determined in terms <strong>of</strong> economic parameters. The results are compared with those obtained for a<br />

system with fixed temperature heat reservoirs. The optimal value <strong>of</strong> COP for a typical set <strong>of</strong> operating conditions<br />

at which the objective function attains its maximum value has been found to appear at lower value when<br />

compared with systems coupled with infinite capacity heat reservoir. It is concluded that the optimized results for<br />

systems with finite capacity heat reservoir will provide more realistic standard for the performance and economic<br />

design conditions.<br />

33


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

REFERENCES<br />

[1] Carnot S. Reflections sur la puissance motrice du feu. Paris: Bachelier; 1824.<br />

[2] Chambadal P. Les Centrales Nuclea ires. Paris: Armand Colin; <strong>19</strong>57. P. 41-58<br />

[3] Chambadal P. Le choix du cycle thermique dans une usine generatrice nucleaire. Rev Gen Elect <strong>19</strong>58; 67:<br />

332-345<br />

[4] Novikov II. Atomnaya Energiya <strong>19</strong>57; 409-412. [in Russian]<br />

[5] Novikov II. The efficiency <strong>of</strong> atomic power station (a review). J Nucl Energy <strong>19</strong>58; 125-128.<br />

[6] El-Wakil MM. Nuclear power engineering. New York: McGraw- Hill; <strong>19</strong>62. P. 162-165.<br />

[7] EI-Wakil MM. Nuclear energy conversion. International Textbook Company; <strong>19</strong>71. p. 31-35.<br />

[8] Curzon FL, Ahlborn B. Efficiency <strong>of</strong> a carnot engine at maximum power output. Am J Phys <strong>19</strong>75;<br />

43(1):22-24.<br />

[9] Salamon P and Nitzan A, Finite time optimization <strong>of</strong> a Newton’s law Carnot cycle, J Chem Phys, 74 (<strong>19</strong>81)<br />

3446.<br />

[10] Sahin B., Kodal A., Yavuz H., Maximum power density for an endoreversible carnot heat engine, Energy 2<br />

(<strong>19</strong>96) 12<strong>19</strong>-1225.<br />

[11] Sahin B., Kodal A., Ekmiekc I., Yilmaz T., Exergy optimization for an endoreversible cogeneration cycle,<br />

J. Inst. Energy 22 (<strong>19</strong>97) 551-557<br />

[12] Sahin B., Kodal A., Finite time thermoeconomic optimization for endoreversible refrigerators and heat<br />

pumps, Energy Conversion and Management 4 (<strong>19</strong>99) 951-960<br />

[13] Kodal A, Sahin B and Yilmaz T, Effect <strong>of</strong> internal irreversibility and heat leakage on the finite time<br />

thermoeconomic performance <strong>of</strong> refrigerators and heat pumps, Energy Convers Mgmt, 41 (<strong>20</strong>00) 607<br />

[14] Kaushik S.C., Kumar P., Jain S., Performance evaluation <strong>of</strong> irreversible cascaded refrigeration and heat<br />

pump cycles, Energy Coversion & Mgmt. 43 (<strong>20</strong>02) 2405-2424<br />

[15] Kodal A. etal., Thermoeconomic optimization for irreversible absorption refrigerators and heat pumps.<br />

Energy Conv. & Mgmt.,44 (<strong>20</strong>03) 109-123<br />

34


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

CLEAN COAL TECHNOLOGIES FOR POWER GENERATION IN<br />

INDIA: A NEAR ZERO EMISSION PLANT APPROACH<br />

Siddhartha 1* , Navdeep Malhotra 2<br />

1 M.Tech. (Mechanical) <strong>YMCA</strong>UST, Faridabad<br />

Mobile : 0918527243948, E-Mail : mailsiddhartha08@gmail.com<br />

2 Pr<strong>of</strong>essor <strong>YMCA</strong>UST, Sec.-6, Zakir Nagar, Faridabad<br />

Mobile :09<strong>19</strong>466175277, E-Mail: navdeep_malhotra<strong>20</strong>01@yahoo.com<br />

Abstract<br />

Coal is chemically and physically a complex and heterogeneous material, consisting <strong>of</strong> organic and<br />

inorganic constituents from its origin .Concerted efforts are needed to reduce “ash-forming” inorganic<br />

elements and to develop clean methods <strong>of</strong> using coal. A combined-cycle gas turbine power plant consists <strong>of</strong> one<br />

or more gas turbine generators equipped with heat recovery steam generators to capture heat from the gas<br />

turbine exhaust. Steam produced in the heat recovery steam generators powers a steam turbine generator to<br />

produce additional electric power. Gas-fired combined-cycle plants produce less carbon dioxide per unit energy<br />

output than other fossil fuel technologies because <strong>of</strong> the relatively high thermal efficiency <strong>of</strong> the technology<br />

.Grate firing was the first combustion system used for solid fuels followed by pulverized and fluidized bed<br />

firing. The concept <strong>of</strong> burning coal that has been pulverized into a fine powder stems from the belief that if the<br />

coal is made fine enough ,it will burn almost as easily and efficiently as gas. Various scrubbing processes<br />

have been proposed to remove carbon dioxide from air or flue gases. In contrast to wet scrubbers which<br />

apply energy directly to the flowing fluid medium, an ESP applies energy only to the particulate matter being<br />

collected and therefore is very efficient in its consumption <strong>of</strong> energy (in the form <strong>of</strong> electricity). Most FGD<br />

systems employ two stages: one for fly ash removal and the other for SO2 removal. However, these systems<br />

experienced severe maintenance problems and low removal efficiency. In wet scrubbing systems, the flue gases<br />

normally passes first through a fly ash removal device, either an electrostatic precipitator or a wet scrubber, and<br />

then into the SO2-absorber. However, in dry injection or spray drying operations, the SO2 is first reacted with<br />

the sorbent, and then the flue gas passes through a particulate control device. Another important design<br />

consideration associated with wet FGD systems is that the flue gas exiting the absorber is saturated with water<br />

and still contains some SO2. These gases are highly corrosive to any downstream equipment such as fans, ducts,<br />

and stacks. Usage <strong>of</strong> supercritical and ultrasupercritical pulverised coal technologies along with<br />

Circulating Fluidised Bed Combustion besides IGCC has been discussed as Clean Coal Technologies for<br />

power generation. Hence the paper Clean Coal Technologies for Power Generation in India : A Near Zero<br />

Emission Plant Approach is limited to the study <strong>of</strong> various technologies to reduce emissions/greenhouse gases<br />

by coal combustion.<br />

Keywords: Coal Beneficiation, Coal Gasification, Fluidised Bed Combustion, Integrated Gasification Combined<br />

Cycle, Flue Gas Desulphurisation, Electrostatic Precipitator, Carbon Capture and Storage.<br />

1. INTRODUCTION<br />

Coal currently supplies around 30% <strong>of</strong> primary energy and 41% <strong>of</strong> global electricity generation. The total<br />

global coal resource is estimated to be 11000 billion tonnes and the extraction reserve is at 909 billion<br />

tonnes. Hence,evidently , coal is a key fuel option to overcome energy shortages in the foreseeable future.<br />

The installed capacity in India has crossed <strong>20</strong>0 GW with the thermal power surmounting to 132GW.Clean<br />

coal technology is a collection <strong>of</strong> technologies being developed to reduce the environmental impact <strong>of</strong> coal<br />

energy generation. When coal is used as a fuel source, the gaseous emissions generated by the thermal<br />

decomposition <strong>of</strong> the coal, include sulphur dioxide, nitrogen dioxide, carbon dioxide, and other chemical by<br />

products that vary depending <strong>of</strong> the type <strong>of</strong> the coal being used. These emissions have been established to have a<br />

negative impact on the environment, contributing to acid rain or climate change. As a result, clean coal<br />

technologies are being developed to remove or reduce pollutant emissions to the atmosphere. Some <strong>of</strong> the<br />

techniques that would be used to accomplish this include chemically washing minerals and impurities from the<br />

coal gasification, treating the flue gases with steam to remove sulfur dioxide, carbon capture and storage<br />

technologies to capture the carbon dioxide from the flue gas and dewatering lower rank coals (brown coals) to<br />

improve the calorific value, and thus increases the efficiency <strong>of</strong> the conversion into electricity. A key strategy in<br />

the mitigation <strong>of</strong> coal’s environmental impact is to improve the energy efficiency <strong>of</strong> the power plants.<br />

Efficient power plants burn less coal per unit <strong>of</strong> energy produced and consequently have lower associated<br />

environmental impacts.<br />

35


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Clean coal technology usually addresses atmospheric problems resulting from burning coal. The primary focus<br />

was on sulfur dioxide and particulates, since it is the most important gas in the causation <strong>of</strong> acid rain. More<br />

recent focus has been on carbon dioxide (due to its impact on global warming) as well as other pollutants.<br />

Concerns exist regarding the economic viability <strong>of</strong> these technologies and the time frame <strong>of</strong> delivery, potentially<br />

high hidden economic costs in terms <strong>of</strong> social and environmental damage, and the costs and viability <strong>of</strong><br />

disposing <strong>of</strong> removed carbon and other toxic matter.<br />

Coal, which is primarily used for the generation <strong>of</strong> electricity, is the largest domestic contributor to carbon<br />

dioxide emissions . The public has become more concerned about global warming through Intergovernmental<br />

Panel On Climate Change(IPCC). The facility captures Carbon dioxide(CO 2) and acid rain producing sulfides,<br />

separates them, and compresses the CO 2 into liquid. Plans are to inject the CO 2 into depleted natural gas fields<br />

or other geological formations[1]. This technology is considered not to be a final solution for CO 2 reduction in<br />

the atmosphere, but provides as an achievable solution in the near term with more desirable alternative<br />

solutions to power generation which can be made economically practical.<br />

Proposed Clean Coal <strong>Technology</strong>(CCT) Roadmap by DST in 11 th ,12 th<br />

and 13 th Five Year Plans are as follows:<br />

Near Term( up to <strong>20</strong>12): Improved coal recovery , Coal Beneficiation , Reduction in Cost .<br />

More emphasis on fluidised bed combustion (FBC), super critical power plant boilers, Integrated Gasification<br />

Combined Cycle(IGCC) Demonstration.<br />

Enhanced energy recovery from coal: CoalBedMethane(CBM),CoalMineMethane(CMM) etc. Pilot scale studies<br />

on coal liquefaction.<br />

Medium Term ( <strong>20</strong>12 – <strong>20</strong>17) : IGCC, PFBC, Ultra super critical power plants(USCP) , enhanced energy<br />

recovery from coal, CBM , Commercial scale coal liquefaction , Zero Emission technologies(ZET)(pilot scale),<br />

Carbon sequestration(pilot scale).<br />

Long Term ( <strong>20</strong>17 and beyond) : Zero Emission Technologies(Commercialisation),Carbon Sequestration<br />

(demonstration plant) , IGFC and production <strong>of</strong> Hydrogen fuels from Coal.<br />

Coal Power<br />

The clean coal technology is <strong>of</strong> the utmost importance because: (i) coal is abundant and will remain a major<br />

source <strong>of</strong> energy for future years, (ii) emission from coal based generation is a matter <strong>of</strong> serious concern.<br />

Thus, clean coal research has begun to:<br />

•Improve the quality <strong>of</strong> non-coking coal at the pre-combustion stage for use in power generation by value<br />

addition,<br />

•Adopt new coal combustion and conversion technologies for improving efficiency <strong>of</strong> coal utilization, and<br />

•Reduce carbon dioxide and other pollutant emissions in the environment through Renovation and<br />

Modernization(R&M).<br />

Coal usually occurs as large-size shales <strong>of</strong> <strong>20</strong>0 mm, found at up to 500 m depth and has mineral or inorganic<br />

matter as extraneous and inherent impurities, which needs to be removed. For commercial applications, high<br />

grade coal is a preferred option, but it is generally low grade coals that are available in large quantities. Hence,<br />

technology advancements are taking place in the use <strong>of</strong> low grade coals.<br />

Clean coal technologies are categorized into: (i) Coal beneficiation, (ii) Coal conversion<br />

(iii)Coal combustion , and (iv) Post-combustion.<br />

2(a) Coal Beneficiation <strong>Technology</strong><br />

Coal beneficiation enables value addition in coal, mainly by reducing the percentage <strong>of</strong> ash generated on<br />

combustion. Each type <strong>of</strong> coal has its own ‘washability’ criteria, depending on the chemical composition <strong>of</strong> coal.<br />

Extraneous impurities are easier to remove by mechanical means as the specific gravity <strong>of</strong> coal is lower than the<br />

impurities, so that upon washing, these impurities sink while the coal floats on the water surface. However, a part<br />

<strong>of</strong> extraneous impurities is intimately inter-meshed with ROM coal and is difficult to remove only by mechanical<br />

means. It requires chemical and biological methods <strong>of</strong> cleaning. Therefore, both dry and wet coal beneficiation<br />

technologies have evolved. Coal is broken down into specified sizes according to the washing technology<br />

applicable. Coarse coal is handled by dry separation in air jigs or hydraulic jigs, while cyclones and<br />

36


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

concentrators are used for medium-size coal, and coal fines are separated by flotation or agglomeration. Byproducts<br />

<strong>of</strong> the beneficiation process are clean coal, middling, and rejects. In a dry cleaning process, water and<br />

energy use is conserved. In the case <strong>of</strong> coal containing heavy metal as intermeshed impurities, only 7 to 8 per<br />

cent reduction in ash is possible through conventional methods <strong>of</strong> beneficiation. Advanced techniques <strong>of</strong> coal<br />

cleaning such as heavy media cyclone, barrel-cum-cyclone, and vortex separator are customized to suit such<br />

types <strong>of</strong> indigenous coal[3]. In a wet process, water or a dense medium like oil is used for preparing finely<br />

meshed coal . Higher efficiency can be achieved by washing as compared to dry cleaning. For difficult-to-wash<br />

coals, advanced coal beneficiation technologies under development include enhanced gravity separators, multi –<br />

stage density separators and microbial leaching.<br />

2(b) Coal Conversion <strong>Technology</strong><br />

The next category <strong>of</strong> clean coal infrastructure comprises the technology <strong>of</strong> converting coal into gas through<br />

gasification and into oil through liquefaction. Coal conversion processes reduce pollution and increase<br />

efficiency, but adds to infrastructure needs for coal suppliers/users.<br />

2b(i) Coal Gasification: Producer gas obtained from the partial combustion <strong>of</strong> coal , coke, or wood with<br />

added water vapour has a heating value <strong>of</strong> only 100 to 180 Btu / scf. The reactions with air or oxygen<br />

are partial combustion because a rich mixture is used , i.e. , one having a fuel to air ratio greater than<br />

chemically correct , or stoichiometric , which also means that the oxygen in either case is not sufficient to<br />

convert all the carbon to carbon dioxide.<br />

Low - Btu Gas : The feedstock is reacted with a mixture <strong>of</strong> air and steam. The air may be enriched in<br />

oxygen , but will be less than stoichiometric. The reactions taking place are :<br />

In air , C + O2 + 3.76 N2 = CO2 + 3.76 N2<br />

CO2 from this reaction reacts further with additional C in the rich mixture to give<br />

C + CO2 + 3.76 N2 = 2CO + 3.76 N2<br />

In Steam C + H2O = CO + H2<br />

The result is a gas composed principally <strong>of</strong> CO , H2 , N2 and some CO2 . The N2 may be less than<br />

shown if the air is oxygen – enriched. The CO2 appears if the air is increased beyond that shown or<br />

because <strong>of</strong> stratification in the gasifier. It may also contain small amounts <strong>of</strong> H2O , CH4 and C2H6 . The<br />

gas has a heating value range <strong>of</strong> 180 to 350 Btu / scf , depending upon the composition <strong>of</strong> reactants and<br />

resulting composition <strong>of</strong> products .<br />

Medium - Btu gas : The feedstock is burned with a mixture <strong>of</strong> oxygen and steam in the same<br />

reactions as shown in above Low – Btu Gas reactions but with the nitrogen removed. The result is a<br />

gas, composed principally <strong>of</strong> Coal and H2, that has a heating value range <strong>of</strong> 250 to 500 Btu / scf , again<br />

depending upon the composition <strong>of</strong> reactants and resulting products. The increase in heating value is a<br />

result <strong>of</strong> the absence <strong>of</strong> the diluting effect <strong>of</strong> nitrogen.<br />

The next step in processing low and medium Btu gases is quenching to condense the tars and heavy<br />

oils that come with the feedstock and did not burn. This is followed by a purification process in which<br />

the hydrogen sulfide in the gas , formed by the combination <strong>of</strong> the sulphur in the coal with hydrogen gas,<br />

is converted to elemental sulphur by an absorption process and simultaneously , a cleaning process in which<br />

char , dust and ash are removed. These processes occur at low temperature with aqueous solutions at 100<br />

to 2<strong>20</strong> degree F so that energy in the form <strong>of</strong> sensible heat <strong>of</strong> the product gases is lost to the<br />

environment.<br />

High - Btu gas : Purified medium – Btu gas may be converted to a high - Btu gas by two additional<br />

steps. The first is the shift conversion , in which CO from the CO – rich gas is saturated with steam and<br />

passed through a catalytic reactor thus producing more hydrogen and carbon dioxide.<br />

CO + H2O = H2 + CO2 .<br />

The ratio <strong>of</strong> H2 to CO2 in the products can be changed by changing the composition <strong>of</strong> the reactants.<br />

CO2 is removed in a wash plant. The next step is that <strong>of</strong> methanation , which is the production <strong>of</strong><br />

methane , CH4, from the available mixture <strong>of</strong> CO and H2 in a catalytic reactor<br />

3H2 + CO = CH4 + H2O<br />

37


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

and the H2O is removed . High – Btu gas is thus largely methane , with a heating value <strong>of</strong> 950 to 1000 Btu<br />

/ scf , approaching that <strong>of</strong> natural gas , which is 950 – 1100 Btu / scf .It has all the characteristics <strong>of</strong> natural<br />

gas but without the sulfur and other pollutants .Various methods under development for the production <strong>of</strong><br />

high Btu gas , is more complex and expensive than low – Btu gas . Purified low – Btu gas can be fired<br />

directly in a conventional steam generator. It has the advantages <strong>of</strong> being sulphur and ash – free, thus<br />

eliminating the need for precipitators and scrubbers. The lack <strong>of</strong> SO2 in the flue gases also permits lower<br />

stack temperatures, which results in improved efficiency .<br />

An attractive utilization <strong>of</strong> low – Btu gas for electric generation is a fuel for Combined – cycle power plant<br />

.A combined cycle is one which uses a gas turbine at the high temperature end and a steam turbine at the<br />

low temperature end .Low – Btu gasifiers operate at different pressures and temperatures , depending<br />

upon the process used . They operate at exit temperatures between 1000degree F and <strong>20</strong>00degree F . The<br />

exit gas must be cooled for purification and cleaning .Normally this cooling represents a large loss <strong>of</strong><br />

energy to the environment . A combined cycle takes advantage <strong>of</strong> the high gasifier and recovers much <strong>of</strong><br />

that heat loss by a gas to gas heat exchanger .The gas turbine drives one <strong>of</strong> two electric generators and<br />

the compressor. Superheated steam is generated in HRSG , expands through a steam turbine that drives the<br />

second electric generator and exhausts to a condenser.<br />

Gasification reactors are designed to suit coal characteristics. Three well-known configurations are the fixed bed,<br />

fluidized bed, and entrained bed systems.<br />

• Fixed Bed Gasifier reactor has different zones for each operation such as drying, devolatilizing, gasification,<br />

and combustion. Coal <strong>of</strong> 10–50mm size is fed from the top and air or oxygen is blown through the fuel bed. The<br />

crude gas leaves the gasifier from above. This type <strong>of</strong> gasifier obviates the need for a heat exchanger, has lower<br />

oxygen consumption, and has the lowest energy requirement <strong>of</strong> all gasification processes. This technology has<br />

been commercialized and about <strong>20</strong>0 fixed bed gasifiers are operating around the world[4].<br />

• Fluidized Bed Gasifier works on the counter-current principle and allows coal particles to move vigorously.<br />

It consists <strong>of</strong> a vertical cylindrical refractory lined vessel with recycle cyclone. The temperature in the reactor<br />

goes up to 850–1,050°C. It is a non-slagging gasifier and has been tested with all types <strong>of</strong> coal and lignite, and is<br />

found attractive for high ash coals as well as high reactive coals. The chemical reaction in this gasifier is<br />

accelerated by turbulent mixing and close contact. There are no separate de-gasification and gasification zones.<br />

Dust-laden gas leaves the reactor at the top, and is cooled and purified before use[14].<br />

• Entrained Bed Process is the third configuration. Finely ground coal <strong>of</strong> 0.1 mm is entrained at high<br />

temperatures <strong>of</strong> the order <strong>of</strong> 1,400 to 1,600°C. Coal gasifies instantly and volatile matter in coal also contributes<br />

to the gas at the reaction temperatures. The product gas has almost 80 per cent <strong>of</strong> the energy <strong>of</strong> the feed coal.<br />

The ash in the coal melts and runs down the refractory-lined walls.<br />

2b(ii) Coal Liquefaction : It is the conversion <strong>of</strong> coal into a liquid fuel for direct energy production or a<br />

liquid substitute for refinery feedstock from which other liquid fuels may be obtained. In coal<br />

liquefaction, the long molecules are shortened by adding hydrogen. The needed hydrogen is generated , and<br />

desulfurization is accomplished , in the same manner as for coal gasification. The Fischer – Tropsch process<br />

first produces a mixture <strong>of</strong> CO and H2 from coal and steam.This is followed by catalytic reactions at<br />

about 300 degree F and 150 bar , which yield a range <strong>of</strong> hydrocarbons from gaseous methane to higher<br />

liquid hydrocarbons. These are then separated with methane going as pipeline gas and the rest going to<br />

different liquid fuels.<br />

2(c) Coal Firing / Combustion <strong>Technology</strong><br />

38


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

All such stokers are designed to continuously feed coal into the furnace by moving it on a grate within<br />

the furnace and also to remove ash from the furnace. Pulverised coal firing represented a major increase<br />

in combustion rates over mechanical stokers. To prepare the coal for use in pulverised firing , it is crushed<br />

and then ground to such a fine powder that approximately 70 percent <strong>of</strong> it will pass a <strong>20</strong>0 mesh sieve. It is<br />

suitable for a wide variety <strong>of</strong> coal , particularly the higher grade ones. Advantages <strong>of</strong> pulverised coal firing<br />

are the ability to use any size coal ; good variable load response ; lower requirement for excess air for<br />

combustion , resulting in lower fan power consumption ;lower carbon loss ; higher combustion temperatures<br />

and improved thermal efficiency ; lower operation and maintenance costs ; and the possibility <strong>of</strong> design<br />

for multiple – fuel combustion.<br />

Early, cyclone firing was introduced and became the major advance in coal firing. It is now widely used<br />

though for a lesser variety <strong>of</strong> uses than is pulverised coal. These are the obvious savings in pulverising<br />

equipment because coal need only be crushed , reduction in furnace size , and reduction in fly ash content <strong>of</strong><br />

the flue gases.Coal – size for cyclone – furnace firing is accomplished in a simple crusher and covers a<br />

wide band , with approx. 95% <strong>of</strong> it passing a 4 – mesh sieve. In this type <strong>of</strong> firing , crushed particles <strong>of</strong><br />

coal are injected into the fluidised bed so that they spread across an air distribution grid.The combustion<br />

air , blown through the grid , has an upward velocity sufficient to cause the coal particles to become fluidised ,<br />

i.e. held in suspension as they burn. Unburned carbon leaving the bed is collected in a cyclone separator<br />

and returned back to the bed for another go at combustion. The main advantage <strong>of</strong> fluidised bed<br />

combustion is the ability to desulfurise the fuel during combustion in order to meet air quality standards<br />

for sulphur dioxide emissions. Desulfurisation is accomplished by the addition <strong>of</strong> limestone directly to the<br />

bed[5].<br />

An integrated gasification combined cycle (IGCC) is a technology that uses a gasifier to turn coal and other<br />

carbon based fuels into gas—synthesis gas (syngas). It then removes impurities from the syngas before it is<br />

combusted. Some <strong>of</strong> these pollutants, such as sulfur, can be turned into re-usable byproducts. This results in<br />

lower emissions <strong>of</strong> sulfur dioxide, particulates, and mercury. With additional process equipment, the carbon in<br />

the syngas can be shifted to hydrogen via the water-gas shift reaction, resulting in nearly carbon free fuel. The<br />

resulting carbon dioxide from the shift reaction can be compressed and permanently sequestered. Excess heat<br />

from the primary combustion and syngas fired generation is then passed to a steam cycle, similar to a combined<br />

cycle gas turbine. This results in improved efficiency compared to conventional pulverized coal.<br />

Figure – 1 : Cost analysis for different power plants and its operations.<br />

39


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Source : EPRI presentation from www.gasification.org<br />

Technological developments which are expected to be achieved by the next generation <strong>of</strong> IGCC projects and<br />

contribute to cost reductions include:<br />

• Utilization <strong>of</strong> dry coal feed system instead <strong>of</strong> slurry;<br />

• Improvement <strong>of</strong> gasifier refractory properties, resulting in longer life cycle;<br />

• Ion transport membranes for air separation;<br />

• Gas turbine inlet chilling where appropriate and effective;<br />

• Advanced syngas turbines to increase efficiency and reduce NOx emissions;<br />

• Improved reliability <strong>of</strong> key components and the overall system in general; and Reduced use <strong>of</strong> water.<br />

Pulverized Coal (PC) fi ring is the oldest method <strong>of</strong> thermal power generation. Hot flue gases are used to heat<br />

water in a boiler. The steam produced is used to drive the steam turbine. The waste heat from the turbine is<br />

allowed to condense. It can use any type <strong>of</strong> coal and is relatively insensitive to the quality <strong>of</strong> coal burnt. Efforts<br />

have been made to render coal combustion more efficient and less polluting. Fluidized Bed Combustion (FBC)<br />

uses a fluidized bed <strong>of</strong> fine coal particles suspended in air. At high pressures solid coal behaves like a fluid and<br />

allows rapid transfer <strong>of</strong> heat. The efficiency <strong>of</strong> the burning process gets enhanced because the motion <strong>of</strong> coal<br />

brings a constant supply <strong>of</strong> hot particles to the surface. The heat is extracted and utilized in a conventional power<br />

generation cycle. It works at lower temperatures than the Pulverized Fuel (PF) process, and hence, reduces NOx<br />

emissions in the atmosphere.<br />

Two operating versions <strong>of</strong> FBC are Circulating Fluidized Bed Combustion (CFBC) and Pressurized Fluidized<br />

Bed Combustion (PFBC). In Circulating Fluidized Bed Combustion coal particle size is reduced to 0.07–0.3 mm<br />

and the fluidization velocity is kept at 5–10 m/sec, so that the particles are ablated in the steam gas. Since the<br />

gasifier is compact, higher heat release rate per unit area can be achieved. The CFBC can utilize low grade coal<br />

with high ash, or even lignite, and has been adopted in India. Pressurized Fluidized Bed Combustion uses<br />

crushed coal with a limestone suspension as a sorbent (to absorb the sulphur content in the coal). As air pressure<br />

inside the boiler is increased to 16 to <strong>20</strong> bars at a temperature around 850°C, the limestone sorbent captures the<br />

sulphur in the coal and forms a dry paste, which gets collected at the bottom <strong>of</strong> the boiler and can be removed.<br />

This technique is particularly suitable for high sulphur coals.<br />

Pulverized coal power plants are broken down into three categories; subcritical pulverized coal (SubCPC) plants,<br />

supercritical pulverized coal (SCPC) plants, and ultra-supercritical pulverized coal (USCPC) plants. The primary<br />

difference between the three types <strong>of</strong> pulverized coal boilers are the operating temperatures and pressures.<br />

Subcritical plants operate below the critical point <strong>of</strong> water (647.096 K and 22.064 MPa). Supercritical and ultrasupercritical<br />

plants operate above the critical point. As the pressures and temperatures increase, so does the<br />

operating efficiency. Subcritical plants are at about 37%, supercriticals at about 40% and ultra-supercriticals in<br />

the 42-45% range.<br />

Subcritical pulverized coal plant has steam outlet pressure below 22.1 MPa. Typical steam outlet temperatures<br />

(superheat and reheat, respectively) are:538oC/538oC and net plant efficiency (HighHeatingValue(HHV)-basis)<br />

<strong>of</strong> 35-38 percent for most coals and countries. As an example, a reference plant in the US (subcritical burning<br />

Bituminous coal in standard US ambient and design conditions) is estimated to have plant efficiency <strong>of</strong> to be<br />

37.7 percent (HHVnet)[6].<br />

• Supercritical pulverized coal plants have steam outlet pressure above 22.1 MPa.Typically, the pressure is 24.7<br />

MPa and the steam outlet temperatures 538- 565oC/565oC resulting in net plant efficiency <strong>of</strong> 38-40 percent. The<br />

same study estimates that reference supercritical plant in the US would have an efficiency <strong>of</strong> 39.1 percent<br />

(HHVnet), or 1.4 percentage points higher that the subcritical.<br />

• Ultra-supercritical pulverized coal (USCPC) plants have steam outlet pressure above 22.1 MPa, typically<br />

around 27 MPa, and the steam outlet temperatures in the 565oC to 625oC range. Net plant efficiency in the 42.0-<br />

45 percent range.<br />

• Advanced USCPC plants have steam outlet pressure above 22.1 MPa and steam outlet temperatures above<br />

625-650oC. Typical net plant efficiency: 42.5-46.0 percent.<br />

Capture – ready pulverised coal plant requires :<br />

(a) Design <strong>of</strong> the steam cycle to better accommodate CO2 compression intercooling.<br />

40


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

(b)Increased FGD size assuming that Mono Ethanol Amine ( MEA) is used for CO2 capture.<br />

2(d) Post Combustion <strong>Technology</strong><br />

Post-combustion technology is the fourth stage alternative in which end-<strong>of</strong>-pipe pollutants such as SOx, NOx,<br />

and CO2 are captured and removed from the atmosphere. Desulphurization and de-NOx operations have been<br />

tested in conventional power generation plants. Advanced clean coal technologies (CCTs) are also perspective<br />

greenhouse gas mitigation technologies.<br />

The CO2 capture technologies are also discussed as follows:<br />

Perspective Clean Coal <strong>Technology</strong><br />

Advanced CCTs for substantive improvement in coal combustion efficiencies, underground coal gasification,<br />

methane extraction from coal bed and mines, and CO2 sequestration are to be pursued in mission mode.<br />

These advanced CCTs are:<br />

• Combined Cycle Technologies<br />

• Underground Coal Gasifi cation<br />

• Coal Bed Methane<br />

• Carbon Capture and Storage<br />

Combined Cycle Technologies<br />

Co-generation in the power sector has been suggested as means <strong>of</strong> reducing emissions <strong>of</strong> pollutants and<br />

achieving<br />

better energy output. Co-generation technologies could be:<br />

• A topping cycle, in which electricity is generated first and waste heat utilized later.<br />

• A bottoming cycle, in which heat utilization is followed by electricity generation.<br />

• A combined cycle, which uses both topping and bottoming cycles for achieving maximum efficiency.<br />

Examples <strong>of</strong> combined cycle power generation techniques are IGCC, etc.<br />

Underground Coal Gasifi cation<br />

Underground coal gasifi cation (UCG) is in-situ gasifi cation <strong>of</strong> coal/lignite deposits to produce clean energy in<br />

the<br />

form <strong>of</strong> gaseous fuel from unmineable, deep coal seams. The UCG research began in Russia in <strong>19</strong>31 based on<br />

the<br />

principle <strong>of</strong> creation <strong>of</strong> a sustained burn-zone inside the coal bed and recovery <strong>of</strong> gas through injection <strong>of</strong> fluid to<br />

create an artificial fracture. It requires creation <strong>of</strong> enough permeability in the coal seams so that a stream <strong>of</strong> air<br />

could flow from one point to another, allowing combustion to take place. The coal is then ignited at either end to<br />

allow for burn-zone growth in the upstream direction. Desirable drilling depths for UCG are in the range 100 to<br />

600 m deep to extract energy from coal seams that are too thick or too thin. The gas can be burned as fuel<br />

directly. The process <strong>of</strong> gas recovery is similar to oil or gas recovery from the interior <strong>of</strong> the earth. Four major<br />

technical steps involved in UCG recovery are:<br />

• Drilling a pair <strong>of</strong> vertical holes or breaking the ground with explosives<br />

• Linking boreholes by reverse combustion, horizontal drilling, or high power lasers<br />

• Igniting coal seam using Controlled Refractory Injection Point (CRIP) technology<br />

• Injecting gasifying fluids such as air, oxygen, or steam for the recovery <strong>of</strong> coal gas.<br />

Through technology- and cost-intensive, UCG has tremendous economic significance; it does not require coal<br />

beneficiation and there is no problem <strong>of</strong> ash disposal. Through this method huge quantities <strong>of</strong> coal deposits<br />

located at great depths, which cannot possibly be extracted by conventional coal mining methods, can be<br />

utilized[8].<br />

Coal Bed Methane : Diff erent methods are adopted for extracting methane. If a source is detected in an<br />

operational mine, conventional techniques such as open hole, vertical jet slot, hydraulic fracturing, and<br />

perforation type <strong>of</strong> drilling at the coal seam depths, can be used for draining the gas before the mining starts. In<br />

41


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

an abandoned mine, carbon dioxide sequestration by pumping flue gas from a power plant (containing CO2) into<br />

the coal seam under pressure is being considered a possibility. The carbon dioxide molecules get attached to coal<br />

and the trapped methane molecule is released. Those mines graded as saturated CBM reservoirs require better<br />

understanding <strong>of</strong> the<br />

reservoir mechanism for a controlled drainage <strong>of</strong> gas, as they may contain five times the amount <strong>of</strong> gas available<br />

in an ordinary coal mine. With the advancement in the technology <strong>of</strong> gas recovery from underground, CBM<br />

mining is becoming feasible. Several coal basins are currently being developed for CBM around the world.<br />

Carbon Capture and Storage <strong>Technology</strong><br />

CO2 Sequestration—Carbon Capture and Storage (CCS) technology is one <strong>of</strong> the emerging clean coal<br />

technologies<br />

to meet the global emission stabilization targets while meeting the national energy needs. It involves capture<br />

<strong>of</strong>CO2 in the atmosphere and its permanent fi xation away from the atmosphere. If the power plant and the<br />

storage sites are not near each other, it will involve transport <strong>of</strong> CO2 in liquid form over longer distances.<br />

Essentially, the CCS has three main components, starting with capture <strong>of</strong> CO2 in the atmosphere emitted from<br />

large point sources; fixing it or transporting it to a possible location where it can be safely stored; and finally<br />

process <strong>of</strong> fixation[9].<br />

Carbon Capture<br />

CO2 capture technology as an end-<strong>of</strong>-pipe solution to power generation is based on chemical absorption,<br />

membrane separation, physical adsorption, and cryogenic separation methods. Chemical absorption process<br />

requires the use <strong>of</strong> chemical solvents. Mono-ethanolamine (MEA), diethanolamine (DEA), mixed amines, and<br />

tertiary amines have been investigated. Notwithstanding the regenerative capability <strong>of</strong> the solvent, the energy<br />

penalty and additional equipment requirements for circulating large volumes <strong>of</strong> liquid absorbents add<br />

significantly to the cost, thus limiting applications <strong>of</strong> the process.<br />

Flue Gas Desulfurization (FGD), which is one <strong>of</strong> the largest markets for scrubbing systems can be categorized as<br />

dry or wet. It deals about dry scrubbing systems that control SO2 and other acid gases from utility and industrial<br />

boilers and incinerators.<br />

In wet FGD scrubbing systems, the scrubbing liquid contains an alkali reagent to enhance the absorption <strong>of</strong> SO2<br />

and other acid gases. More than a dozen different reagents have been used, with lime and limestone being the<br />

most popular. Sodium-based solutions (sometimes referred to as clear solutions) provide better SO2 solubility<br />

and less scaling problems than lime or limestone. However, sodium reagents are much more expensive.<br />

Wet FGD scrubbers can further be classified as nonregenerable or regenerable.<br />

Nonregenerable processes, also called throwaway processes, produce a sludge waste that must be disposed <strong>of</strong><br />

properly. It should be noted that in throwaway or nonregenerable processes the scrubbing liquid can still be<br />

recycled or regenerated; however, no useful product is obtained from the eventual sludge. Regenerable processes<br />

produce a product from the sludge that may be sold to partially <strong>of</strong>fset the cost <strong>of</strong> operating the FGD system.<br />

Regenerated products include elemental sulfur, sulfuric acid and gypsum. Another important design<br />

consideration associated with wet FGD systems is that the flue gases exiting the absorber is saturated<br />

with water and contains some SO2.Therefore these gases are highly corrosive to any downstream<br />

equipment fans , ducts and stacks. Two methods that minimize corrosion are :<br />

(1.) Reheating the gases to above their dew point and<br />

(2.) Choosing construction materials and design conditions that allow equipment to withstand the<br />

corrosive conditions. The selection <strong>of</strong> a reheating method or the decision not to reheat are very<br />

controversial topics connected with FGD design . 4 methods used to reheat stack gases are :<br />

(1.) Indirect in – line reheating : The flue gas passes through a H.E. that uses steam or hot water .<br />

(2.) Indirect – direct reheating : Steam is used to heat air and then the hot air is mixed with the<br />

scrubbed gases.<br />

(3.) Direct combustion reheating : Oil or gas is burned either in the duct or in an external chamber and<br />

the resulting hot gases are mixed with the scrubbed gases.<br />

(4.) By pass reheating : A portion <strong>of</strong> the untreated hot flue gas bypasses the scrubber and is mixed with<br />

scrubbed gases.<br />

42


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

A wet scrubber is used to clean air, flue gas or other gases <strong>of</strong> various pollutants and dust particles. Wet<br />

scrubbing works via the contact <strong>of</strong> target compounds or particulate matter with the scrubbing solution. Solutions<br />

may simply be water (for dust) or solutions <strong>of</strong> reagents that specifically target certain compounds.<br />

Process exhaust gas can also contain water soluble toxic and/or corrosive gases like hydrochloric acid (HCl) or<br />

ammonia (NH 3 ). These can be removed very well by a wet scrubber.<br />

Removal efficiency <strong>of</strong> pollutants is improved by increasing residence time in the scrubber or by the increase <strong>of</strong><br />

surface area <strong>of</strong> the scrubber solution by the use <strong>of</strong> a spray nozzle, packed towers or an aspirator. Wet scrubbers<br />

may increase the proportion <strong>of</strong> water in the gas, resulting in a visible stack plume, if the gas is sent to a stack.<br />

A dry or semi-dry scrubbing system, unlike the wet scrubber, does not saturate the flue gas stream that is being<br />

treated with moisture. In some cases no moisture is added, while in others only the amount <strong>of</strong> moisture that can<br />

be evaporated in the flue gas without condensing is added. Therefore, dry scrubbers do generally not have a stack<br />

steam plume or wastewater handling/disposal requirements. Dry scrubbing systems are used to remove acid<br />

gases (such as SO 2 and HCl) primarily from combustion sources.<br />

There are a number <strong>of</strong> dry type scrubbing system designs. However, all consist <strong>of</strong> two main sections or devices:<br />

a device to introduce the acid gas sorbent material into the gas stream and a particulate matter control device to<br />

remove reaction products, excess sorbent material as well as any particulate matter already in the flue gas.<br />

Dry scrubbing systems can be categorized as dry sorbent injectors (DSIs) or as spray dryer absorbers (SDAs).<br />

Spray dryer absorbers are also called semi-dry scrubbers or spray dryers.<br />

Dry scrubbing systems are <strong>of</strong>ten used for the removal <strong>of</strong> odorous and corrosive gases from wastewater treatment<br />

plant operations. The medium used is typically an activated alumina compound impregnated with materials to<br />

handle specific gases such as hydrogen sulfide. Media used can be mixed together to <strong>of</strong>fer a wide range <strong>of</strong><br />

removal for other odorous compounds such as methyl mercaptans, aldehydes, volatile organic compounds,<br />

dimethyl sulfide, and dimethyl disulfide[13].<br />

Dry sorbent injection involves the addition <strong>of</strong> an alkaline material (usually hydrated lime or soda ash) into the<br />

gas stream to react with the acid gases. The sorbent can be injected directly into several different locations: the<br />

combustion process, the flue gas duct (ahead <strong>of</strong> the particulate control device), or an open reaction chamber (if<br />

one exists). The acid gases react with the alkaline sorbents to form solid salts which are removed in the<br />

particulate control device. These simple systems can achieve only limited acid gas (SO 2 and HCl) removal<br />

efficiencies. Higher collection efficiencies can be achieved by increasing the flue gas humidity (i.e., cooling<br />

using water spray). These devices have been used on medical waste incinerators and a few municipal waste<br />

combustors.<br />

In spray dryer absorbers, the flue gases are introduced into an absorbing tower (dryer) where the gases are<br />

contacted with a finely atomized alkaline slurry. Acid gases are absorbed by the slurry mixture and react to form<br />

solid salts which are removed by the particulate control device. The heat <strong>of</strong> the flue gas is used to evaporate all<br />

the water droplets, leaving a non-saturated flue gas to exit the absorber tower. Spray dryers are capable <strong>of</strong><br />

achieving high (80+%) acid gas removal efficiencies. These devices have been used on industrial and utility<br />

boilers and municipal waste incinerators.<br />

An electrostatic precipitator (ESP), or electrostatic air cleaner is a particulate collection device that removes<br />

particles from a flowing gas (such as air) using the force <strong>of</strong> an induced electrostatic charge. Electrostatic<br />

precipitators are highly efficient filtration devices that minimally impede the flow <strong>of</strong> gases through the device,<br />

and can easily remove fine particulate matter such as dust and smoke from the air stream. ESPs continue to be<br />

excellent devices for control <strong>of</strong> many industrial particulate emissions, including smoke from electricitygenerating<br />

utilities (coal and oil fired), salt cake collection from black liquor boilers in pulp mills, and catalyst<br />

collection from fluidized bed catalytic cracker units in oil refineries to name a few. These devices treat gas<br />

volumes from several hundred thousand ACFM to 2.5 million ACFM (1,180 m³/s) in the largest coal-fired boiler<br />

applications. For a coal-fired boiler the collection is usually performed downstream <strong>of</strong> the air preheater at about<br />

160 °C (3<strong>20</strong> deg.F) which provides optimal resistivity <strong>of</strong> the coal-ash particles. For some difficult applications<br />

with low-sulfur fuel hot-end units have been built operating above 371 °C (700 deg.F).<br />

43


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The original parallel plate–weighted wire design (described above) has evolved as more efficient (and robust)<br />

discharge electrode designs were developed, today focusing on rigid (pipe-frame) discharge electrodes to which<br />

many sharpened spikes are attached (barbed wire), maximizing corona production. Transformer-rectifier systems<br />

apply voltages <strong>of</strong> 50 – 100 kV at relatively high current densities. Modern controls, such as an automatic voltage<br />

control, minimize electric sparking and prevent arcing (sparks are quenched within 1/2 cycle <strong>of</strong> the TR set),<br />

avoiding damage to the components. Automatic plate-rapping systems and hopper-evacuation systems remove<br />

the collected particulate matter while on line, theoretically allowing ESPs to stay in operation for years at a time.<br />

Carbon capture and storage (CCS), (carbon capture and sequestration), refers to technology attempting to<br />

prevent the release <strong>of</strong> large quantities <strong>of</strong> CO 2 into the atmosphere from fossil fuel use in power generation and<br />

other industries by capturing CO 2 , transporting it and ultimately, pumping it into underground geologic<br />

formations to securely store it away from the atmosphere. It is a potential means <strong>of</strong> mitigating the contribution <strong>of</strong><br />

fossil fuel emissions to global warming. The process is based on capturing carbon dioxide (CO 2 ) from large point<br />

sources, such as fossil fuel power plants, and storing it where it will not enter the atmosphere. It can also be used<br />

to describe the scrubbing <strong>of</strong> CO 2 from ambient air as a geoengineering technique. Although CO 2 has been<br />

injected into geological formations for various purposes, the long term storage <strong>of</strong> CO 2 is a relatively new<br />

concept. Table 1 provides the details for the selection <strong>of</strong> various technological response from various associated<br />

environmental impacts due to coal combustion.<br />

TABLE -1 : SELECTION OF TECHNOLOGICAL RESPONSE FROM ASSOCIATED ENVIRONMENTAL<br />

IMPACTS BASED ON COAL USAGE AS FUEL[7] :<br />

Sl.No. ENVIRONMENTAL CHALLENGES /<br />

IMPACT<br />

1 Particulates<br />

Impact : Human health,dust,visibility<br />

2 SO2<br />

Impact : Acid deposition ,Human health<br />

3 NO2<br />

Impact : Acid deposition, GHG gas,smog<br />

4 Mercury<br />

Impact :Bioaccumulates in<br />

environment,toxic<br />

5 Fly – Ash<br />

Impact : Increased waste for disposal<br />

TECHNOLOGICAL<br />

RESPONSE<br />

Hot gas filtrationiltration<br />

Wet particulate scrubbers<br />

ESP<br />

Fabric filters<br />

Sorbet injection process<br />

Dry Scrubbers<br />

Wet scrubbers<br />

Flue gas recirculation<br />

Burner optimisation<br />

Air staging<br />

Fuel staging<br />

Selective Catalytic<br />

Reduction<br />

ESP<br />

Coal washing<br />

Baghouses<br />

Modified<br />

ESP,DryScrubbers<br />

Wet Scrubbers<br />

Utilisation as construction<br />

and Civil Engg.materials<br />

MAXIMUM<br />

REDUCTION<br />

ACHIEVABLE<br />

98%<br />

99.9%<br />

99.99%<br />

>99.9999%<br />

90%<br />

97%<br />

99%<br />


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

the emissions would not only be zero, but negative, so that not only the emissions, but the absolute amount <strong>of</strong><br />

CO 2 in the atmosphere would be reduced.<br />

3. Energy Fuels by CO2 Sequestration<br />

The process <strong>of</strong> underground storage <strong>of</strong> CO2 and consequent changes in the viscosity <strong>of</strong> fluids in depleting oil<br />

reservoirs can provide additional fuel for energy. The CO2 will mix with the crude and by changing the oil<br />

properties will help flush out remaining reserves making it flow easily. At the surface the gas mixture containing<br />

both CO2 and natural petroleum gas will have to be separated from the oil before it is sent for refining. The<br />

stripped CO2 can be recycled back into the oil fields to extract more oil. CO2 management through this approach<br />

will be a highly challenging task. It will have to be adopted when all the conventional methods <strong>of</strong> enhanced oil<br />

recovery have failed. A CO2-EOR (CO2-Enhanced Oil Recovery) project designed to minimize CO2 emissions<br />

back to the atmosphere with appropriate incentives would have an important role in assuring energy security.<br />

Like oilfields, unmineable coal seams can also prove to be potential reservoirs for CO2 storage. On average three<br />

molecules <strong>of</strong> CO2 are absorbed for displacing one molecule <strong>of</strong> methane (CH4). By injecting CO2 in coal seams,<br />

coal bed methane recovery can be enhanced. Three main CO2 capture processes under development for power<br />

generation are as follows[7][10]:<br />

3(a) Pre combustion Capture Systems<br />

It takes the syngas produced from coal gasification and convert it via – a – steam based chemical reaction into<br />

separate streams <strong>of</strong> CO2 and H2. It facilitates the collection and compression <strong>of</strong> CO2 into a supercritical fluid<br />

like form suitable for transportation and geological storage.H2 is being separated from CO2 to be able to be<br />

used for combustion in gas turbines which is primarily done by Pressure Awing Adsorption(PSA) , amine<br />

scrubbing and membrane reactors.<br />

3(b) Post combustion Cycle<br />

It separate CO2 from the flue gases produced by the combustion <strong>of</strong> coal in air.Post combustion CO2 capture<br />

technology based on chemical absorption processes is large scale technology to be deployed for power<br />

generation purpose.<br />

3(c), Oxy – fuel combustion<br />

It involves combustion <strong>of</strong> coal in pur O2 rather than air, to fuel a steam generator.By avoiding N2 into the<br />

combustion cycle , the amount <strong>of</strong> CO2 in the power station exhaust stream is greatly concentrated making it<br />

easier to capture and compress.<br />

Globally, research in CCS has grown by almost 100 per cent in the last five years as compared to previous five<br />

years block in USA. In India, research is still in its infancy. Under the National Programme on CO2<br />

Sequestration (NPCS), research started in DST in <strong>20</strong>06; the following thrust areas are identified as :<br />

• CO2 Sequestration through Micro-algae Bio-fixation<br />

• Carbon Capture Process Development<br />

• Terrestrial Agro-forestry Sequestration Modeling Network<br />

• Policy Development Studies.<br />

Further studies for Cost <strong>of</strong> Electricity(COE)comparisons for different power plants with CCS are stated in<br />

Table-2.<br />

TABLE – 2 : EXPECTED COST OF ELECTRICITY (COE) FOR DIFFERENT POWER PLANTS WITH<br />

CCS in USA[7]<br />

Sl.No. Power Plant Pulverised Coal Natural Gas<br />

Combined Cycle<br />

Integrated Gasification<br />

Combined Cycle<br />

1 COE without CCS ( 43- 52) (31 – 50) ( 41 – 61)<br />

(US $ / MWh)<br />

2 COE with CCS<br />

( US $ / MWh)<br />

(63 – 99) ( 43 – 77) (55 – 91)<br />

45


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3 CCS mitigation cost<br />

(US $/ t CO2 avoided)<br />

4 COE with CCS and<br />

EOR(US $/MWh)<br />

5 CCS and EOR<br />

Mitigation Cost ( US $<br />

/ t CO2 avoided)<br />

( 30 – 71 ) ( 38 – 91) (14 – 53)<br />

( 49 – 81) (37 – 70) (40 – 75)<br />

( 09- 44) ( <strong>19</strong> – 68) ((-7) – 31)<br />

4. Barriers to CCT Implementation<br />

On a world-wide basis, prospects <strong>of</strong> CCT are good in view <strong>of</strong> the advantages such as higher efficiency <strong>of</strong> power<br />

generation and lower GHG emissions per kW <strong>of</strong> installed capacity. The clean coal technology has been<br />

advancing rapidly to achieve goals <strong>of</strong> zero emission technology. In India efforts towards clean coal technology<br />

development began more than two decades ago, but have not kept pace with the global developments. Research<br />

eff orts carried out in the country for the past several years have shown that as compared to IGCC, the quality <strong>of</strong><br />

coal requirement in CFBC is less demanding. Yet IGCC has been given highest attention. There have been other<br />

barriers and constraints in the advancement <strong>of</strong> CCT, such as :<br />

(i)High cost involved to support development <strong>of</strong> Clean Coal<strong>Technology</strong> to proving stage,<br />

(ii)Amenability <strong>of</strong> advanced technologies to available coal with high ash content<br />

(iii)Inadequate R&D infrastructure in academic institutions and national laboratories,<br />

(iv)Lack <strong>of</strong> academic–industry interaction for new coal-based technology,<br />

(v)Constraints in development <strong>of</strong> coal blocks in the absence <strong>of</strong> adequate equipment infrastructure and<br />

(vi)Lack <strong>of</strong> sufficient coal evacuation facilities, among others.<br />

5. CONCLUSION<br />

Coal is an important source <strong>of</strong> primary energy for the world and demand is growing rapidly in many developing<br />

countries as they enjoy a period <strong>of</strong> long-overdue economic growth. Over the 50 years from <strong>20</strong>00 to <strong>20</strong>50,<br />

demand might double to exceed 7 000 million tonnes <strong>of</strong> coal equivalent and so account for 32% <strong>of</strong> the world’s<br />

primary energy supply, up from today’s 30%. Strong environmental policies could see substantially lower coal<br />

use – it is, after all, the most carbon-intensive fuel. However, given coal’s abundance, there will be pressure to<br />

exploit this resource for energy security and economic reasons. Improving coal’s environmental performance is<br />

key to coal’s future role in the energy mix[2]. In particular, a group <strong>of</strong> technologies, known as carbon dioxide<br />

capture and storage (CCS), <strong>of</strong>fers the potential to balance the sometimes competing goals <strong>of</strong> energy security,<br />

economic development and environmental sustainability.<br />

Clean coal technologies (CCTs) have been developed and deployed to reduce the environmental impact <strong>of</strong> coal<br />

utilisation over the past 30 to 40 years. Initially, the focus was upon reducing emissions <strong>of</strong> particulates, SO2,<br />

NOX and mercury. The coal sector – producers, consumers and equipment suppliers – as well as governments<br />

and agencies in countries where coal is essential, have a long experience <strong>of</strong> stimulating clean coal technology<br />

deployment. Experience continues to grow as the technologies are introduced and spread in developing<br />

countries. The clean coal technology focus in developed countries has moved to the development and operation<br />

<strong>of</strong> low and near-zero GHG emission technologies like carbon dioxide capture and storage (CCS).<br />

Deployment <strong>of</strong> CCS, as part <strong>of</strong> an effort to reduce GHG emissions, has been endorsed by G8 leaders, The Stern<br />

Review and the IPCC. The International Energy Agency has identified four groups <strong>of</strong> CCTs (coal upgrading,<br />

efficiency improvements at existing power plants, advanced technologies and near-zero emission technologies)<br />

which can dramatically reduce GHG emissions[12].<br />

With supercritical and ultra critical plants introduction, it is realistic to expect that lower emissions with<br />

high efficiency and steam <strong>of</strong> 16.9MPa /538/565degree Centigrade. Hence the term Clean Coal Technologies is<br />

used to mean every option capable <strong>of</strong> reducing emissions upstream , downstream , or within the power<br />

generation process. The purpose <strong>of</strong> Clean Coal Technologies is to reduce GHG emissions in power<br />

generation.<br />

For new plants the following options are considered :<br />

(a) Supercritical and Ultrasupercritical pulverised coal technologies.<br />

(b) Circulating Fluidised Bed Combustion .<br />

46


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

(c)<br />

(d)<br />

Integrated Gasification Combined Cycle.<br />

Biomass Co-firing for CO2 reductions.<br />

Hence an integrated coal analysis which includes coal mining , coal transport and energy conversion<br />

(power plants) and addresses the cost effectiveness <strong>of</strong> options such as upstream coal beneficiation<br />

(cleaning) and clean coal conversion technologies in an integrated manner[11].<br />

Way Forward<br />

Nevertheless prospects <strong>of</strong> CCTs are becoming high as aresult <strong>of</strong> global warming concerns. Actually both local as<br />

well as global environmental concerns can be addressed better through the use <strong>of</strong> CCT. The costs are coming<br />

down, although it may take long to establish their economic competitiveness. A long-term clean coal policy to<br />

address the issues <strong>of</strong> installation <strong>of</strong> thermal power plants based on CCTs, R&D, and transfer <strong>of</strong> technology are<br />

imperatives for growth. Most CCTs are research intensive and are still evolving, therefore, joint research<br />

ventures should be considered for technology transfer. In super-critical and ultra-super-critical coal fired plants,<br />

much higher efficiency can be achieved. The super-critical technology is already under development in our<br />

country. These efforts need to be augmented for ultra-super-critical combustion capabilities and Underground<br />

coal gasification processing[15] .<br />

REFERENCES<br />

1. IEA ,Coal Industry Advisory Board (<strong>20</strong>08) , Clean Coal Technologies : Accelerating Commercial and<br />

Policy Drivers for Deployment.<br />

2. Clean Coal Power Generation <strong>Technology</strong> Review : World wide experience and implications for India<br />

. Background Paper India : Strategy for Low Carbon Growth (June <strong>20</strong>08), The World Bank .<br />

3. Chapter 4 , http://web.mit.edu/coal .<br />

4. CEA , (<strong>20</strong>03) “ Report <strong>of</strong> the Committee to recommend next higher size <strong>of</strong> coal fired thermal power<br />

stations ,” .<br />

5. Mott Mac Donald , (<strong>20</strong>06) ” India’ Ultra Mega Power Projects / Exploring the use <strong>of</strong> Carbon Financing<br />

,” .<br />

6. Electric Power Development Corporation <strong>of</strong> Japan ,(<strong>19</strong>99)” Adoption <strong>of</strong> supercritical technology for<br />

Sipat Super Thermal Power Plant ,” .<br />

7. World Coal Institute,”Coal meeting the Climate Change – <strong>Technology</strong> to reduce GHG emissions”.<br />

8. Goel Malti, (<strong>20</strong>07) “Barriers to Deployment <strong>of</strong> Clean Coal <strong>Technology</strong>: Key Issues and Perspectives”,6 th<br />

Annual Conference on Carbon Sequestration , 7-11 May,Pittsburg, USA.<br />

9. Simon Shackley and Preeti Verma,(<strong>20</strong>08) “Tackling CO2 reduction in India through use <strong>of</strong> CO2 Capture<br />

and Storage : Prospects and Challenges”.<br />

10. MIT,(<strong>20</strong>07) ”The Future <strong>of</strong> Coal : Options for a carbon restrained world”.<br />

11. Ananth P.Chikkatur and Ambuj D. Sagar,(<strong>20</strong>07) “Towards better technology policies for the Indian<br />

coal – power sector” .<br />

12. Ritu Mathur , Sharat Chand and Tetsuo Tezuka, (<strong>20</strong>03)”Optimal use <strong>of</strong> coal for power generation in<br />

India”.<br />

13. Zievers J.F. , et.al. ,(<strong>19</strong>96) “Use <strong>of</strong> waste metal oxides for dry scrubbing with barrier filters”.<br />

14. Krishnan,G.N. et. al.,(<strong>19</strong>96) “Vaporisation <strong>of</strong> alkali and trace metal impurities in coal gasification and<br />

combustion systems”.<br />

15. Rudra V. Kapila, (<strong>20</strong>10) “Carbon Capture and Storage prospects in India : Results from an expert<br />

stakeholder survey”.<br />

47


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

LIMITATIONS OF ENERGY UTILIZATION OF SOLID WASTE DUE<br />

TO IT’S POOR QUALITY<br />

Desh Deepak Johri 1 Manish Gaur 2 Sachin Rathod 3<br />

1<br />

Associate Pr<strong>of</strong>essor, Deptt. Of Mech. Engg., ABESIT, Ghaziabad<br />

2<br />

Associate Pr<strong>of</strong>essor, Deptt. Of Mech. Engg., KIET, Ghaziabad<br />

3<br />

Assistant Pr<strong>of</strong>essor, Deptt. Of Mech. Engg., KIET, Ghaziabad<br />

E mail: ddjohri@gmail.com<br />

Abstract<br />

The increasing problem <strong>of</strong> continuous population growth in the metro cities and subsequent increase in solid<br />

waste disposal has created a severe problem as well as its hazardous effects may not be overlooked. The major<br />

utilization <strong>of</strong> this solid waste in India is limited to composting only. The amount <strong>of</strong> solid waste in Delhi alone is<br />

nearly 9000 MT / day. The quality <strong>of</strong> compost is not appropriate because <strong>of</strong> mixed solid waste and its poor<br />

quality. The compost thus produced is not salable in the market. In domestic solid waste if the organic content is<br />

collected separately the food stuff waste content can be utilized for compost which shall be <strong>of</strong> good quality.<br />

Again the content in the form <strong>of</strong> Plastic and paper is suitable for the purpose <strong>of</strong> energy extraction as these<br />

contents have high value <strong>of</strong> energy. This work has been carried out by in order to calculate the amount <strong>of</strong> high<br />

energy ingredients in domestic solid waste. The domestic solid waste samples from the residents <strong>of</strong> two different<br />

societies were collected and estimation was carried out for the energy content per capita. This approach <strong>of</strong><br />

collection and studying the sample on micro basis was done with an intention to estimate the exact amount <strong>of</strong><br />

high energy content, as there is a vast deviation <strong>of</strong> the sample disposed from the houses to that reaches to the<br />

dumpsites due to ragpikking.<br />

Key Words: Sanitary Land Fills (SLF), Waste to Energy Generation (WTE), Municipal Solid Waste (MSW)<br />

1. Introduction<br />

In urban areas a lot <strong>of</strong> solid waste being dumped everyday, the amount is very high on account <strong>of</strong> life style as<br />

well as the increasing population density. In Delhi it is nearly 9,000MT per day [10]. So it is important to<br />

manage it properly in order to avoid its impact on environment and to make effective utilization <strong>of</strong> this.<br />

The continuous shortage <strong>of</strong> electricity in big cities as well as the paucity <strong>of</strong> land has diverted the attention <strong>of</strong><br />

engineers and local governing bodies for energy production from the solid waste. Urban solid waste includes<br />

household garbage and rubbish, street sweeping, construction and demolition debris, sanitation residues and<br />

industrial refuse and bio-medical waste (CPCB, <strong>20</strong>00). Solid waste management (SWM) has three basic<br />

components:- collection, transportation and disposal [5]. The efforts are being made to utilize the solid waste by<br />

composting it as well as establishing the project for producing energy from it. Still it is not being done at its full<br />

potential. The economic viability <strong>of</strong> these projects is questionable, but active participation <strong>of</strong> financial<br />

institutions, NGOs and the financial support <strong>of</strong> State and Central Govt. can solve the problem [9].<br />

The potential energy contained per kg <strong>of</strong> plastics, wood, paper, cardboard and food waste are nearly 32500 kJ,<br />

18300kJ, 16750kJ, 16300kJ and 4600kJ respectively. As electricity is the most convenient form <strong>of</strong> energy and<br />

for Delhi alone the electricity generation potential from solid waste is more than 1<strong>20</strong>MW approximately. For<br />

NCR it is nearly 180MW [10].<br />

This paper is an attempt to bring the facts about the quality and quantity <strong>of</strong> solid waste to the bodies involved in<br />

managing the solid waste and for its utilization for energy generation. For estimating the content <strong>of</strong> energy in the<br />

domestic solid waste the option was to adopt a micro or macro approach. It was not possible to get the real<br />

sample disposed by residents at dump sites as the recyclable constituents are picked up by rag pickers, so the<br />

micro approach was adopted [1].<br />

2. Methodology Adopted<br />

The micro approach was adopted for the estimation <strong>of</strong> energy content per capita <strong>of</strong> domestic solid waste. The<br />

societies at Rajendra Nagar Sahibabad were requested for providing the solid waste, the individuals were<br />

approached for. At Sahara II, all the 5 occupants agreed for, where as at Rajmahal II, 10 out <strong>of</strong> 11 occupants<br />

agreed for. Following is the details <strong>of</strong> collected samples.<br />

48


3. MATHEMATICAL FORMULATION<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

ESTIMATION OF PER CAPITA ENERGY CONTENT<br />

The samples collected at two residential building comprising <strong>of</strong> food, fruit, vegetable and plastics (polythene<br />

only being organic compound) & paper products waste was found to have Paper to Plastic ratio as 7:1.<br />

The energy potential / kg <strong>of</strong> different ingredients are normally as mentioned below.<br />

1 – Plastics 27900kJ/kg<br />

2 – Paper Products 11600kJ/kg<br />

3 – Food Waste 3500kJ/kg<br />

For collected sample energy potential /kg content shall be as calculated ahead:-<br />

Av.Energy/kg from paper & plastic waste = (27900*1+11600*7)/8 = 13637.5 kJ<br />

Which can approximately be taken as 13635kj/kg<br />

Energy content <strong>of</strong> the solid waste sample containing paper & plastic and vegetable waste<br />

e = (46*13635 + 107*3500)/1000 = 1001.71 kJ/capita, take it as 1000 kJ per capita.<br />

The present population <strong>of</strong> Delhi is 1,70,00,000.<br />

Table 1 SAHARA – II (Family members)<br />

Flat<br />

No.<br />

Family<br />

Members<br />

Agreed Type <strong>of</strong><br />

flat<br />

G - 1 4 Yes MIG<br />

G - 2 2 Yes MIG<br />

F - 1 4 Yes MIG<br />

F - 2 4 Yes MIG<br />

S - 1 3 Yes MIG<br />

S - 2 Nil Vacant MIG<br />

Total Members - 17<br />

Table 2 RAJ MAHAL – II (Family members)<br />

Flat<br />

No.<br />

Family<br />

Members<br />

Agreed Type<br />

<strong>of</strong> flat<br />

M - 1 4 No MIG<br />

M - 2 Nil Vacant MIG<br />

M– 5 4 Yes MIG<br />

M - 6 5 Yes MIG<br />

M– 9 3 Yes MIG<br />

M- 10 2 Yes MIG<br />

L – 3 3 Yes LIG<br />

L – 4 3 Yes LIG<br />

L - 7 4 Yes LIG<br />

L - 8 3 Yes LIG<br />

L - 11 4 Yes LIG<br />

L - 12 4 Yes LIG<br />

Total Members – 35<br />

Table 3 Solid Waste Sample, SAMPLE No. 1 at SAHARA – II<br />

Date Gross Wt. (grams) Paper/plastic wt.(grams) Veg. Waste wt.(gram)<br />

12/2/08 2593 840 1753<br />

13/2/08 24<strong>19</strong> 850 1569<br />

14/2/08 2178 806 1372<br />

15/2/08 2521 870 1651<br />

16/2/08 <strong>20</strong>82 740 1342<br />

17/2/08 1585 502 1083<br />

18/2/08 2141 780 1361<br />

Wt./capita/day 130 45 85<br />

49


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 4 Solid Waste Sample, SAMPLE No. 2 at SAHARA – II<br />

Date Gross Wt. (grams) Paper/plastic wt.(grams) Veg. Waste wt.(gram)<br />

10/3/08 2834 886 <strong>19</strong>48<br />

11/3/08 2585 796 1789<br />

12/3/08 2622 634 <strong>19</strong>88<br />

13/3/08 2989 854 2135<br />

14/3/08 <strong>20</strong>87 694 1393<br />

15/3/08 2876 867 <strong>20</strong>09<br />

16/3/08 2500 816 1684<br />

Wt./capita/day 155 47 109<br />

Table 5 Solid Waste Sample, SAMPLE No. 3 at SAHARA – II<br />

Date Gross Wt. (grams) Paper/plastic wt.(grams) Veg. Waste wt.(gram)<br />

18/4/08 2811 836 <strong>19</strong>75<br />

<strong>19</strong>/4/08 2169 649 1515<br />

<strong>20</strong>/4/08 2231 730 1501<br />

21/4/08 2857 855 <strong>20</strong>02<br />

22/4/08 3161 982 2179<br />

23/4/08 2690 856 1834<br />

24/4/08 2854 730 2124<br />

Wt./capita/day 158 47 111<br />

Table 6 Averages<br />

Average Gross Wt. Per capita/day(gram) 148<br />

Average Wt. <strong>of</strong> plastic/paper Per capita/day (gram) 47<br />

Average Wt. <strong>of</strong> Veg. Waste Per capita/day(gram) 101<br />

Sample 1 at Sahara - II<br />

3000<br />

Wt. (grams)<br />

2500<br />

<strong>20</strong>00<br />

1500<br />

1000<br />

500<br />

Gross Wt. (grams)<br />

Plastic/Paper Wt.<br />

(grams)<br />

Veg. Wt. (grams)<br />

0<br />

12-Feb<br />

13-Feb<br />

14-Feb<br />

15-Feb<br />

16-Feb<br />

17-Feb<br />

18-Feb<br />

Dates<br />

50


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Sample 2 at Sahara II<br />

3500<br />

Wt. (grams)<br />

3000<br />

2500<br />

<strong>20</strong>00<br />

1500<br />

1000<br />

Gross Wt. (grams)<br />

Plastic/Paper Wt.<br />

(grams)<br />

Veg. Wt. (grams)<br />

500<br />

0<br />

10-Mar<br />

11-Mar<br />

12-Mar<br />

13-Mar<br />

14-Mar<br />

15-Mar<br />

16-Mar<br />

Dates<br />

Sample 3 at Sahara II<br />

3500<br />

Wt. (grams)<br />

3000<br />

2500<br />

<strong>20</strong>00<br />

1500<br />

1000<br />

Gross Wt. (grams)<br />

Plastic/Paper Wt.<br />

(grams)<br />

Veg. Wt. (grams)<br />

500<br />

0<br />

18-Apr<br />

<strong>19</strong>-Apr<br />

<strong>20</strong>-Apr<br />

21-Apr<br />

22-Apr<br />

23-Apr<br />

24-Apr<br />

Dates<br />

Table 7 Solid Waste Sample SAMPLE No. 1 at RAJMAHAL – II<br />

Date Gross Wt. (grams) Paper/plastic wt.(grams) Veg. Waste wt.(gram)<br />

<strong>20</strong>/2/08 5804 1636 4168<br />

21/2/08 5305 14<strong>20</strong> 3885<br />

22/2/08 5769 1625 4144<br />

23/2/08 5229 1562 3667<br />

24/2/08 5532 1583 3949<br />

25/2/08 5000 1509 3491<br />

26/2/08 5399 1447 3952<br />

Wt./capita/day 155 44 111<br />

Table 8 Solid Waste Sample SAMPLE No. 2 at RAJMAHAL – II<br />

Date Gross Wt. (grams) Paper/plastic wt.(grams) Veg. Waste wt.(gram)<br />

31/3/08 5961 1805 4156<br />

1/4/08 5850 1876 3974<br />

2/4/08 5187 14<strong>20</strong> 3767<br />

3/4/08 5073 1359 3714<br />

4/4/08 5215 1536 3679<br />

5/4/08 5439 1685 3754<br />

6/4/08 5676 1736 3940<br />

Wt./capita/day 157 47 110<br />

51


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 9 Solid Waste Sample, SAMPLE No. 3 at RAJMAHAL – II<br />

Date Gross Wt. (grams) Paper/plastic wt.(grams) Veg. Waste wt.(gram)<br />

26/4/08 5681 1870 3811<br />

27/4/08 5467 1680 3787<br />

28/4/08 5609 1780 3829<br />

29/4/08 5553 1695 3858<br />

30/4/08 5093 14<strong>20</strong> 3673<br />

1/5/08 5749 1834 3915<br />

2/5/08 5269 1569 3700<br />

Wt./capita/day 157 48 108<br />

Table 10 Averages<br />

Average Gross Wt. Per capita/day(gram) 153<br />

Average Gross Wt. Per capita/day(gram) 46<br />

Average Gross Wt. Per capita/day(gram) 107<br />

Samlpe 1 at Rajmahal II<br />

3000<br />

2500<br />

Gross Wt.<br />

(grams)<br />

Wt. (grams)<br />

<strong>20</strong>00<br />

1500<br />

1000<br />

Plastic/Paper<br />

Wt. (grams)<br />

500<br />

0<br />

<strong>20</strong>-Feb<br />

21-Feb<br />

22-Feb<br />

23-Feb<br />

24-Feb<br />

25-Feb<br />

26-Feb<br />

Veg. Wt.<br />

(grams)<br />

Dates<br />

Sample 2 at Rajmahal II<br />

Wt. (grams)<br />

3500<br />

3000<br />

2500<br />

<strong>20</strong>00<br />

1500<br />

1000<br />

500<br />

Y<br />

Gross Wt.<br />

(grams)<br />

Plastic/Paper<br />

Wt. (grams)<br />

0<br />

31-Mar<br />

1-Apr<br />

2-Apr<br />

3-Apr<br />

4-Apr<br />

Dates<br />

5-Apr<br />

6-Apr<br />

Veg. Wt.<br />

(grams)<br />

52


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Sample 3 at Rajmahal II<br />

3500<br />

3000<br />

Gross Wt.<br />

(grams)<br />

Wt. (grams)<br />

2500<br />

<strong>20</strong>00<br />

1500<br />

1000<br />

Y<br />

Plastic/Paper<br />

Wt. (grams)<br />

500<br />

0<br />

26-Apr<br />

27-Apr<br />

28-Apr<br />

29-Apr<br />

30-Apr<br />

1-May<br />

2-May<br />

Veg. Wt.<br />

(grams)<br />

Dates<br />

Table 11 Overall Average<br />

Average Gross Wt. Per Capita/day (gram) 148<br />

Average Wt. <strong>of</strong> plastic Per Capita/day (gram) 47<br />

Average Wt. <strong>of</strong> Veg. waste Per Capita/day (gram) 101<br />

Overall contents <strong>of</strong> domestic SW<br />

Average Wt. <strong>of</strong> Veg. waste Per<br />

Capita/day (gram)<br />

Contents<br />

Average Wt. <strong>of</strong> plastic Per<br />

Capita/day (gram)<br />

Average Gross Wt. Per<br />

Capita/day (gram)<br />

0 50 100 150 <strong>20</strong>0<br />

Wt. (grams)<br />

4. RESULT<br />

ENERGY POTENTIAL OF WASTE AT DELHI<br />

E = P*e/1000<br />

Where E is the estimated potential <strong>of</strong> total energy /day in MJ<br />

P is the population <strong>of</strong> Delhi<br />

e is the energy potential per capita in kJ<br />

With the samples collected it would be as :-<br />

E= 1,70,00,000*1000/1000 = 1,70,00,000MJ/day<br />

Three samples were taken as we see from these samples that the collection <strong>of</strong> different components <strong>of</strong> the waste<br />

varies on daily basis from same apartment as well as from different apartments. We may conclude that the waste<br />

content is neither fixed for individual house nor for entire collection <strong>of</strong> society on per day basis.<br />

5. CONCLUSIONS<br />

A good amount <strong>of</strong> energy contained in the biodegradable content <strong>of</strong> waste <strong>of</strong> Delhi can be utilized for heat<br />

energy recovery or for power generation purpose by utilizing different method <strong>of</strong> WTE application. The major<br />

bottle neck is the poor quality <strong>of</strong> solid waste reaching to the dumping sites. Out <strong>of</strong> various methods, incineration<br />

53


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

and biomethanization are found to be more suitable. Although the pollution problems are associated with<br />

incineration but it can be made viable for handling small amount <strong>of</strong> waste, If due care is given to the treatment <strong>of</strong><br />

flue gases [2]. Similarly biomethanization is recommended for small quantities. The gas obtained from<br />

biomethanization can be used for power generation purpose [4]. As the amount <strong>of</strong> entire waste generation for<br />

Delhi is as high as 9000 MT per day it can alone not be dealt by using any one method only. But incineration and<br />

biomethanization are method which reduces the load on Sanitary Land Fills [4]. The proper segregation <strong>of</strong> solid<br />

waste at the source itself will enable us to extract higher amount <strong>of</strong> energy at a considerable low cost as well as it<br />

helps us in producing a high quality compost. During the survey at Balswa compost plant wecame to know that<br />

the composting plant is underutilized due to the poor quality <strong>of</strong> waste reaching to dump site (Plant capacity is<br />

500 MTPD and it operates at 300 MTPD).The need is to make the public aware <strong>of</strong> the fact and to operate on an<br />

efficient waste collection and utilization mechanism [6]. In order to exploit the solid waste as a source <strong>of</strong> energy<br />

the steps are to be taken by ULBs and the participation <strong>of</strong> private sector as well as that <strong>of</strong> the RWAs and NGOs<br />

is must for the success <strong>of</strong> WTE application [3]. If we do not take the necessary steps on time we shall be facing<br />

the problem <strong>of</strong> public hygiene as well as the deterioration <strong>of</strong> environment [8]. There is a considerable amount <strong>of</strong><br />

energy content which can be extracted from the domestic solid waste, but we are deprived <strong>of</strong> this because <strong>of</strong> the<br />

fact that we are not able put the ban on rag picking. Also there is no accountability <strong>of</strong> govt. <strong>of</strong>ficials deployed for<br />

the solid waste management [7].<br />

The complete elimination <strong>of</strong> SW is not possible at all, so the emphasis should be on its proper management.<br />

Certain suggestions to improve the situation are as mentioned below:-<br />

• Commercial establishments and road side vendors must ensure for safe disposal <strong>of</strong> SW.<br />

• Participation <strong>of</strong> NGOs and RWAs is to be encouraged.<br />

• Government should have a strict supervision on recycling plants.<br />

• Public Awareness through hygiene camps.<br />

• Encouraging separate use <strong>of</strong> separate containers for biodegradable and non biodegradable waste<br />

segregation at source. Garbage should be transported in covered vehicles.<br />

• Open disposal <strong>of</strong> waste is to be banned and ensuring the segregation at the source.<br />

• Introduction <strong>of</strong> sanitation course at school level.<br />

• Developing nodal energy centers for institutional MSW to handle and WTE generation.<br />

• Funding and subsidizing the loans for implementation <strong>of</strong> such projects.<br />

Acknowledgement<br />

We acknowledge our sincere thanks to the residents <strong>of</strong> SAHARA II, and RAJMAHAL -- II, for their support in<br />

conducting the experiment and providing us their domestic solid waste on regular basis. We are also thankful to<br />

the staff deployed at composting plant at Bhalswa for providing us the valuable informations.<br />

References<br />

1. Al-Momani, A. H. (<strong>19</strong>94). Solid waste management: Sampling, analysis and assessment <strong>of</strong> household waste<br />

in the city <strong>of</strong> Amman. International Journal <strong>of</strong> Environmental Health Research, 4, <strong>20</strong>8–222.<br />

2. Brunnr, P. H., & Ernst, W. R. (<strong>19</strong>86). Alternative methods for the analysis <strong>of</strong> municipal solid waste. Waste<br />

Management & Research, 4, 147–160.<br />

3. BIO ENERGY NEWS from Ministry <strong>of</strong> Non-Conventional Energy Sources (<strong>20</strong>06)<br />

4. C. Chiemchairi. W. Chiemchairi, Sunil Kumar. J.P.A.Hettiaratchi , (<strong>20</strong>07) “Solid Waste Characteristics and<br />

their relationship to gas production in tropical landfill”, Environ Monit Assess 135:41–48<br />

5. C. Chiemchairi. , J.P.Juanga. , C. Viswanathan, (<strong>20</strong>07) “Municipal Solid Waste management in Thailand and<br />

disposal emission Inventory”, Environ Monit Assess 135:13–<strong>20</strong><br />

6. Desh Deepak Johri and Dr. Emran Khan (<strong>20</strong>08) “Potential <strong>of</strong> Energy Generation from Solid Waste”. National<br />

Conference at KIET, 18, 247-254<br />

7. Desh Deepak Johri, M.K.Lohumi and Deepak Bhalla (<strong>20</strong>08) “Solid Waste Disposal in Metro Cities – A threat<br />

to environment” National Conference at KIET, 21, 247-254<br />

8. Times <strong>of</strong> India, Mumbai, March 7, <strong>20</strong>02<br />

9. Times <strong>of</strong> India, TIMES CITY (Delhi) May <strong>20</strong>, <strong>20</strong>08<br />

10. Renewable Energy Akshay Urja Journel from MNES (<strong>20</strong>05)<br />

54


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

A FEASIBILITY STUDY ON WASTE HEAT RECOVERY IN AN<br />

IC ENGINE USING ELECTRO TURBO GENERATION<br />

S.N.Srinivasa Dhaya Prasad 1 N.Parameshwari 2<br />

1 Assistant Pr<strong>of</strong>essor, Department <strong>of</strong> Automobile Engg., SACS MAVMM Engg. College, Madurai, Tamilnadu.<br />

E-mail: iamdhaya77@gmail.com<br />

2 Asst. Pr<strong>of</strong>. /Research Scholar, Department <strong>of</strong> Automobile Engg, SACS MAVMM Engineering College,<br />

E-mail: paramspraba@gmail.com<br />

Abstract<br />

In a conventional IC engine a considerable heat is carried away by exhaust gases. To recover the waste heat,<br />

various methods are being adopted. One <strong>of</strong> them is turbo charging. In this project an attempt has been made to<br />

explore the various possibilities <strong>of</strong> waste heat / energy recovery methods in conventional commercial two<br />

wheeler and four wheelers. In this context, a new concept <strong>of</strong> hybrid engine has also been discussed. The heat<br />

energy contained in the exhaust gases are recovered in three different methodologies.<br />

Firstly, by introducing an auxiliary combustion chamber and injecting an additional suitable fuel and then<br />

allowing it to expand in a turbine which forms the part <strong>of</strong> turbo charger unit. Thus the waste heat energy is<br />

utilized to burn an additional amount <strong>of</strong> fuel. The second stage contains a thermoelectric generator which<br />

produces electrical energy by utilizing the high heat <strong>of</strong> exhaust gases. The third stage energy recovery is done by<br />

coupling a compressor and an alternator. Both being coupled to the turbine shaft, produces electrical energy<br />

and compressed air which can be accumulated and used effectively for running any auto auxiliaries. Thus the<br />

principle <strong>of</strong> electro turbo generation has been adopted for waste heat recovery In order to use the aforesaid<br />

combination <strong>of</strong> waste energy recovery systems a matrix has also been suggested.<br />

1. Introduction<br />

As the oil resources are depleting day by day with a rapid increase demand for energy, research is in progress to<br />

identify an alternative source. At the same time the present day equipments are being developed to give<br />

maximum output to conserve resources till an alternative is developed.<br />

Reciprocating Internal combustion engines being the most widely preferred prime movers gives a maximum<br />

efficiency range <strong>of</strong> 27% to 29%.Rotary engines, even though having higher efficiencies up to 45% are restricted<br />

to aircrafts due to their very high speeds <strong>of</strong> 45000 rpm to 90000 rpm. Cogeneration is the method <strong>of</strong><br />

simultaneous production <strong>of</strong> heat and other form <strong>of</strong> energy in a process. Many cogeneration techniques have been<br />

employed in IC engines to recover the waste heat. Turbo charging is also a kind <strong>of</strong> waste heat recovery technique<br />

in which the exhaust gases leaving the engine are utilized to run a turbine to produce power.<br />

2. Literature Review<br />

Reciprocating engines remain the dominant power plant for both vehicles and power generation up to a few MW.<br />

Yet, circa 30% <strong>of</strong> the energy in the fuel is lost through the exhaust system. In today's market, it has become<br />

essential to attempt to recover some <strong>of</strong> this “wasted energy” and put it to good use. Exhaust Heat Recovery<br />

(EHR) systems are playing an increasingly important role in the Emissions and Fuel Consumption challenges<br />

facing today's Heavy Commercial Vehicle (HCV), Off-Highway and Power Gen markets globally. Exhaust heat<br />

recovery using electro turbo generators by Patterson, A., Tett, R., and McGuire, J. puts forward an argument in<br />

favor <strong>of</strong> Electro-Turbo compounding as a system that is technically mature enough to benefit the above markets<br />

today.<br />

Only a part <strong>of</strong> the energy released from the fuel during combustion is converted to useful work in an engine. The<br />

remaining energy is wasted and the exhaust stream is a dominant source <strong>of</strong> the overall wasted energy. There is<br />

renewed interest in the conversion <strong>of</strong> this energy to increase the fuel efficiency <strong>of</strong> vehicles. There are several<br />

ways this can be accomplished. This work involves the utilization thermoelectric (TE) materials which have the<br />

capability to convert heat directly into electricity. A model was developed to study the feasibility <strong>of</strong> the concept.<br />

A Design <strong>of</strong> Experiment was performed to improve the design on the basis <strong>of</strong> higher power generation and less<br />

TE mass, backpressure, and response time. Results suggest that it is possible to construct a realistic device that<br />

can convert part <strong>of</strong> the wasted exhaust energy into electricity thereby improving the fuel economy <strong>of</strong> a gaselectric<br />

hybrid vehicle. Thus the Various possible exhaust heat recovery methods have been discussed by Husain,<br />

Q., Brigham, D., and Maranville,C in Thermoelectric Exhaust Heat Recovery for Hybrid Vehicles.<br />

Considering heavy truck engines up to 40% <strong>of</strong> the total fuel energy is lost in the exhaust. Because <strong>of</strong> increasing<br />

petroleum costs there is growing interest in techniques that can utilize this waste heat to improve overall system<br />

55


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

efficiency. Leising, C., Purohit, G., DeGrey, S., and Finegold, J., examines and compares improvement in fuel<br />

economy for a broad spectrum <strong>of</strong> truck engines and waste heat utilization concepts.<br />

The engines considered are the Diesel, spark ignition, gas turbine, and Stirling. Principal emphasis is placed on<br />

the turbocharged four-stroke Diesel engine. Because <strong>of</strong> increased exhaust energy and a large potential<br />

improvement in performance, the still-to-be-developed "adiabatic" Diesel is also examined.<br />

The waste heat utilization concepts include preheating, regeneration, turbo charging, turbo compounding, and<br />

Rankine engine compounding. Predictions are based on fuel-air cycle analyses, computer simulation, and engine<br />

test data. All options are compared on the basis <strong>of</strong> maximum theoretical improvement. The Diesel and adiabatic<br />

Diesel are also evaluated in terms <strong>of</strong> maximum expected improvement and expected improvement over a driving<br />

cycle.<br />

The results indicate that Diesels should be turbocharged and after cooled to the maximum possible level. Based<br />

on current design practices fuel economy improvements <strong>of</strong> up to 6% might be possible. It is also revealed that<br />

Rankine engine compounding can provide about three times as much improvement in fuel economy as turbo<br />

compounding, but perhaps only the same improvement per dollar. By turbo charging, turbo compounding, and<br />

Rankine engine compounding, driving cycle performance could be increased by up to <strong>20</strong>% for a Diesel and by<br />

up to 40% for an adiabatic Diesel. The study also indicates that Rankine engine compounding can provide<br />

significant fuel economy improvement for gas turbine and spark ignition engines and regeneration could<br />

significantly enhance the performance <strong>of</strong> spark ignition engines. Because <strong>of</strong> the low heat content in the exhaust<br />

<strong>of</strong> a Stirling engine it has only a small potential for further waste heat recovery.<br />

3. Electro Turbo Generation<br />

Fig. 1. Energy split in a diesel engine<br />

The above figure illustrates the energy path <strong>of</strong> a diesel engine. Energy is lost in several forms. The largest being<br />

the heat energy dissipated to the environment via exhaust gases. The EHR system is designed to recover heat<br />

energy in the exhaust gases and convert in to useful work for the vehicle. Existing system convert come <strong>of</strong> the<br />

exhaust heat energy in to mechanical energy that is fed back to crank shaft via hydraulic coupling and gear train.<br />

The concept <strong>of</strong> electro turbo generation converts some exhaust heat energy in to electrical energy.<br />

56


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The underlying technology is based on integrating compact high speed electrical machines (alternators) with<br />

high performance turbo machinery in various combinations.<br />

4. Electro Turbocharged hybrid engine with cogeneration<br />

In this project an attempt has been made to explore the possibilities <strong>of</strong> waste heat recovery in conventional IC<br />

Engines. The heat contained in the exhaust gases is recovered in two stages. The exhaust gases coming out <strong>of</strong> the<br />

engine is allowed to pass through an auxiliary combustion chamber. The temperature <strong>of</strong> exhaust gases in a petrol<br />

engine lies between <strong>20</strong>0 deg Celsius to 230 deg Celsius. At this high temperature fuel can be injected at<br />

comparatively low injection pressures and burnt. In this auxiliary combustion chamber, an injector injects a fuel<br />

and the fuel is burnt due to the high heat <strong>of</strong> exhaust gases. This results in a boost <strong>of</strong> pressure and temperature.<br />

This high temperature gas is introduces into a turbine stage where it is expanded. The output <strong>of</strong> this turbine is<br />

given to an alternator to produce electrical energy. The electrical power thus produced is tapped into a battery to<br />

run a dc motor.<br />

Fig.2. Proposed model for waste heat recovery<br />

The test rig is a two wheeler dynamometer used to measure the performance <strong>of</strong> a two wheeler. This essentially<br />

consists <strong>of</strong> a base and a clamp to fix the front wheel <strong>of</strong> the vehicle. The rear wheel will be driving a drum<br />

provided at the base to measure the brake power and speed.<br />

The test rig is connected to a computer and the sensors mounted at various locations will send inputs (engine<br />

running parameters) to the computer.<br />

5. Experimental setup<br />

Fig.3.Power recovered from electro turbo generator<br />

57


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig.4.Fabricated model Turbo charger connected with exhaust pipe<br />

The experimental model used consists <strong>of</strong> a turbo charger (TATA Indica ) attached to the exhaust manifold <strong>of</strong> a<br />

HERO HONDA CD 100 bike. The turbo charger shaft is coupled to a DC Generator <strong>of</strong> voltage rating <strong>of</strong> 6 V.<br />

6. Results and Discussion<br />

In order to find out the feasibility <strong>of</strong> running a DC dynamo by the turbo charger, the engine was allowed<br />

to run at different speeds .the output <strong>of</strong> the generator was also noted.<br />

Table: 1. Experimental Data<br />

Engine Speed in RPM 1<strong>20</strong>0 RPM 1800 RPM 2400 RPM 3500 RPM 4000 RPM<br />

Output voltage <strong>of</strong> the Alternator ------ ---- 9.0V 11 V<br />

Power produced by the electrical machine<br />

Power (P) = Voltage x Current<br />

= 11 V x 0.48 A<br />

= 5.48 Watts<br />

BHP Produced = 5148 Watts<br />

58


Before mounting electro turbo generator:<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table: 2 Energy split data as applied to the test engine<br />

Total power given by<br />

fuel<br />

Useful power at crank<br />

shaft<br />

Frictional<br />

losses<br />

Cooling<br />

losses<br />

Exhaust<br />

gases<br />

100 % 25% 5% 30% 40%<br />

<strong>20</strong>592 Watts 5148 Watts 1029Watts 6178Watts 8237Watts<br />

After mounting electro turbo generator:<br />

From the experiment, the power obtained by connecting the alternator to the turbo charger is 5.48 Watts which is<br />

0.025% <strong>of</strong> the total power supplied by the fuel. Thus it is obvious that, out <strong>of</strong> the 40% exhaust losses 0.06% can<br />

be recovered by electro turbo charging in this engine.<br />

Table: 3 Energy split data after mounting electro turbo generator<br />

Total power<br />

given by fuel<br />

Useful power<br />

at crank shaft<br />

Frictional<br />

losses<br />

Cooling<br />

losses<br />

Exhaust<br />

gases<br />

Recovered power from<br />

electro turbo generation<br />

100 % 25% 5% 30% 39.975% 0.025%<br />

<strong>20</strong>592 Watts 5148 Watts 1029Watts 6178Watts 8237Watts 5.48Watts<br />

59


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

0.025%<br />

recovered<br />

from e-<br />

turbo gen<br />

37.975%<br />

7. Conclusion<br />

In an attempt to explore the possibilities <strong>of</strong> waste heat recovery in an IC engine, the concept <strong>of</strong> Electro Turbo<br />

generator has been proved by running an alternator coupled to a turbocharger. By the introduction <strong>of</strong> electro<br />

turbo generation the useful work obtained from the engine has been increased from 25% to 25.025%.<br />

The above quantity is a very small quantity. As the electro turbo generation system used here is not a specially<br />

designed one for this engine. By designing an alternator for this engine conditions, the quantity <strong>of</strong> useful work<br />

recovered can be improved. In a small engine this quantity may be <strong>of</strong> less advantageous. But thinning in a global<br />

manner the energy conserved will be high.<br />

At present this idea is in initial stage and is to be analyzed by constructing the appropriate physical system. The<br />

following are the constraints which are to be overcome.<br />

1) Designing <strong>of</strong> auxiliary combustion chamber<br />

2) Type <strong>of</strong> fuel to be used / selection <strong>of</strong> fuel for auxiliary CC.<br />

3) Design <strong>of</strong> the alternator ( due to frequency very high)<br />

4) Overall efficiency.<br />

5) Torque and speed performance <strong>of</strong> the turbo charger to be studied<br />

REFERENCES<br />

[1] A., Tett, R., and McGuire, J., "Exhaust Heat Recovery using Electro-Turbo generators," SAE Technical<br />

Paper <strong>20</strong>09-01-1604, <strong>20</strong>09, doi: 10.4271/<strong>20</strong>09-01-1604.<br />

[2] Husain, Q., Brigham, D., and Marienville, C., "Thermoelectric Exhaust Heat Recovery for Hybrid<br />

Vehicles," SAE Int. J. Engines 2(1):1132-1142, <strong>20</strong>09, doi: 10.4271/<strong>20</strong>09-01-1327.<br />

[3] Leising, C., Purohit, G., DeGrey, S., and Feingold, J., "Waste Heat Recovery in Truck Engines," SAE<br />

Technical Paper 780686, <strong>19</strong>78, doi: 10.4271/780686.<br />

[4] Alberto, Boretti Missouri <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong> “Improving the Efficiency <strong>of</strong><br />

Turbocharged Spark Ignition Engines for Passenger Cars through Waste Heat Recovery” Date<br />

Published: <strong>20</strong>12-04-16Paper Number: <strong>20</strong>12-01-0388 DOI: 10.4271/<strong>20</strong>12-01-0388<br />

[5] New developments in turbo charging SAE Technical Paper 540017, <strong>19</strong>54, doi:10.4271/540017.<strong>19</strong>54-01-<br />

01PaperNumber: 540017 DOI: 10.4271/540017<br />

60


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

REDUCING BATTERY DISCHARGING RATE USING<br />

PHOTO-ELECTRIC EFFECT<br />

Jeet Kumar Gaur, Abhinav Mittal, Bikash Chandra Maurya,<br />

B.Tech. 3 rd year students, Mechanical Engineering Department,<br />

KIET, Ghaziabad, India<br />

e-mail: jeetkumargaur@gmail.com, Ph-+91-8909518527<br />

Abstract<br />

To make the battery work longer once charged the electrons can be made to get over the negative terminal <strong>of</strong> the<br />

battery using the photon energy by the use <strong>of</strong> a low wave length ultra violet lamp [1]. In process forms a circuit<br />

that acts as the charging circuit <strong>of</strong> the battery. Thus the rate <strong>of</strong> discharge <strong>of</strong> the battery reduces and battery life<br />

increases. Such an arrangement if used with the battery will tend to recharge the battery when it’s being used.<br />

Thus the net discharging rate <strong>of</strong> the battery is reduced.<br />

Key words: Electrons, photons, photo-electric effect, Work function, Ultra Violet Lamp.<br />

1. Introduction<br />

When charging <strong>of</strong> the battery occurs using an external electricity source, the electrons that are carried to the<br />

positive terminal <strong>of</strong> the battery are carried back to the negative terminal <strong>of</strong> the battery by applying an opposite<br />

and higher electric field.<br />

The photo electric effect is another way <strong>of</strong> charging the battery using solar energy, but this technology is by<br />

using the energy from the sun rays and thus is dependent on the sun.<br />

Here is an attempt to combine the usefulness <strong>of</strong> photo electric effect with the concept <strong>of</strong> charging to enhance the<br />

life <strong>of</strong> a battery. This can be done using source <strong>of</strong> photons with energy higher than the threshold frequency <strong>of</strong> the<br />

circuitry material (here it is taken as copper).<br />

2. Related Works<br />

In <strong>19</strong>05 Albert Einstein in one <strong>of</strong> his papers about the photoelectric effect, made clear that when any metallic<br />

body is illuminated by photons having energy more that the work function <strong>of</strong> that metal, free electrons get<br />

ejected from that body [2].<br />

Work function <strong>of</strong> any material can be defined as the minimum amount <strong>of</strong> the energy required to just free the<br />

electron from the orbit <strong>of</strong> the atom <strong>of</strong> that material. If the energy <strong>of</strong> the photon is higher than the work function<br />

<strong>of</strong> the material then the extra energy provides kinetic energy to the electrons.<br />

Fig 1 Ejection <strong>of</strong> electrons by photo electric effect<br />

Thus came the equation,<br />

hv =φ + K.E [3]<br />

Where,<br />

h=plank’s constant=6.63*10^(-34) joule-second<br />

v=frequency <strong>of</strong> the striking photon.<br />

hv=total energy <strong>of</strong> the striking photon<br />

φ=work function <strong>of</strong> the material<br />

K.E. =Kinetic energy <strong>of</strong> the electron<br />

The main conclusions <strong>of</strong> the photoelectric effect are as follows<br />

61


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

1. There is no effect <strong>of</strong> the photon on the electron it strikes if the value <strong>of</strong> the work function is higher than<br />

the energy <strong>of</strong> the photon.<br />

2. A photon which is a quantum <strong>of</strong> energy <strong>of</strong> light give it’s energy to none or one electron<br />

3. No photon can give its energy to more than one electron. Here comes the particulate nature <strong>of</strong> light.<br />

4. If the value <strong>of</strong> the work function equals the energy <strong>of</strong> the photon then the electron gets freed from the<br />

orbital but has no kinetic energy to leave.<br />

Using this effect solar cell, photo cells or LDRs (Light Detecting Resistors), solar chargeable batteries are<br />

made [4].<br />

3. Reducing the Discharging Rate <strong>of</strong> Battery Using Photo Electric Effect<br />

An arrangement can be attached to the battery via which the external load is connected to the battery. But the<br />

effect <strong>of</strong> reduced discharging rate in battery can be obtained by an arrangement that tends to form a circuitry that<br />

tends to charge the battery when in use without using any external source.This arrangement is connected directly<br />

to the two terminals <strong>of</strong> the battery in a vacuum bulb and then via this arrangement the external load is connected.<br />

The main compenents used in this arrangement are vacuum bulb, low wavelength UV lamp,semi cylindrical<br />

reflecting mirror, copper plates.<br />

3.1 Vacuum bulb<br />

This is a glass bulb with vacuum inside .The main purpose <strong>of</strong> using it is that it prevents the hurdle that would be<br />

created for the electrons emited by photo electric effect due to collision with air molecules.This contains the low<br />

wavelength UV lamp, copper plates,semi cylindrical reflecting mirror connected as shown below.<br />

3.2 Low wavelength UV lamp<br />

This is the source <strong>of</strong> photons causing the photons electric effect in this arrangement.The lamp is connected to the<br />

negative terminal <strong>of</strong> the battery and placed inside the vacuum bulb.The position <strong>of</strong> the lamp with respect to the<br />

copper plate is such that most photons strike the copper plate.<br />

3.3 Semi cylindrical reflecting mirror<br />

This is a miorror which is semi cylindrical in shape.This component <strong>of</strong> the arrangement is to make use <strong>of</strong><br />

maximum number <strong>of</strong> the photon by directing them over the copper plate (a).The position <strong>of</strong> the mirror is such<br />

that most <strong>of</strong> the photons falling on itget reflected on the copper plate (a).<br />

Fig 2 Semi cylindrical reflecting mirror<br />

3.4. Copper plate (a)<br />

This copper plate is connected directly to the negative terminal <strong>of</strong> the battery.This plate is the one from which<br />

electrons are ejected as a result <strong>of</strong> the photo electric effect towards the surface <strong>of</strong> plate (b).<br />

62


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig 3 Copper plate (a)<br />

3.5.Copper plate (b)<br />

This plate is oriented in space such this electrons reflected from plate (a) as a result <strong>of</strong> the photo electric effect<br />

move to it’s surface.<br />

In Figure 4:<br />

(c) is the negative terminal <strong>of</strong> the battery<br />

(g) is the positive terminal <strong>of</strong> the battery<br />

(a),(b) are the two copper plates<br />

(f) is the external load<br />

Fig 4 Arrangement <strong>of</strong> complete system<br />

In this arrangement the battery terminal (c) that is the negative terminal is connected to a low wavelength ultra<br />

violet lamp which is then connected to a copper plate (b).The positive terminal <strong>of</strong> the battery is connected to the<br />

copper plate (a).<br />

A semi cylindrical reflecting mirror is placed around the ultra violet lamp to reflect most <strong>of</strong> the photons on the<br />

copper plate (a), the plate (a) is given some curvature in the direction <strong>of</strong> the lamp. This helps all the electron that<br />

get emitted by the photo electric effect due to photons coming from the low wave length UV lamp to move<br />

almost towards a point, This point lies on the plate (b).This arrangement containing the UV lamp ,semi<br />

cylindrical reflecting mirror and the copper plates (a)&(b) are enclosed in a vacuum bulb. And the load is<br />

connected to terminals (1) and (2).<br />

63


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4. Working<br />

Now ,as the external load is connected the circuit closes and current flows through path (g)(a)(1)(f)(2)(b)(d)(c)<br />

but, as the UV lamp blows , it’s photons tend to illuminate to the plate (a) due to the arrangement.<br />

If the wave length <strong>of</strong> the UV rays is λ<br />

Then, the energy <strong>of</strong> the photons =hc/λ<br />

Let work function <strong>of</strong> the metal=φ<br />

Then, hc/λ=φ + K.E [4]<br />

This is the K.E <strong>of</strong> the ejected electrons.<br />

So,<br />

The voltage with which these electrons are accelerated, V o = (K.E)/e<br />

Where, e=1.6*10 ^ (-<strong>19</strong>) coulomb<br />

This is similar to the motion <strong>of</strong> electrons, when we charge a battery by external voltage <strong>of</strong> higher value. So, here<br />

also if the voltage with which the electrons are accelerated from copper plate (a) to copper plate (b) is higher than<br />

the potential difference between the points <strong>of</strong> connection <strong>of</strong> the two plates then this will allow electron to<br />

become a part <strong>of</strong> the current flowing through copper plate (b) in the direction <strong>of</strong> flow. Thus the current from the<br />

output <strong>of</strong> the battery reduces.<br />

Fig 5 Reduction in discharging rate <strong>of</strong> battery arrangement<br />

Here this can be explained taking actual values.<br />

The UV lamp <strong>of</strong> low wave length (10 nano meters) emit photons <strong>of</strong> energy equal to<br />

[hc/(10*10^(-9))]=6.63*10^ (-34) * (3*10^8)/(10^(-8))<br />

=1.989*10^ (-17) joule<br />

Which is more then the work function <strong>of</strong> copper (4.7ev or 7.52*10^ (-<strong>19</strong>) joule) [5].<br />

So by the photo electric equation<br />

K.E. = hv-φ =1.9138*10^ (-17) joule<br />

With this kinetic energy the electrons emitted from plate (a) have energy=1<strong>19</strong>.6125ev that is as if it’s accelerated<br />

by 1<strong>19</strong>.6125 volt .So even a battery <strong>of</strong> 110 volts will get charged this way. But, since not all photons can be<br />

participating in the photoelectrical electron emission thus there is discharging <strong>of</strong> the battery but at a very low<br />

rate.<br />

Take the potential at point (b) be 12 volts then the charging voltage required is low (18 to <strong>20</strong> volts) so the wave<br />

length <strong>of</strong> UV lamp can be increased accordingly to get desired result.<br />

Thus the electron reach the plate (b) and now tends to flow along path (b)(2)(f)(1)(a)(g) .Whenever the circuit is<br />

completed (that is load is connected )this effect occurs. The discharging rate <strong>of</strong> the battery thus reduces as the<br />

rate <strong>of</strong> electrons reaching the positive terminal <strong>of</strong> battery from the negative terminal reduces and from a circuit<br />

(b)(2)(f)(1)(a)(b).<br />

The life <strong>of</strong> the battery increases thus once charged the battery will work longer due to reduced discharging rate.<br />

64


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5. Conclusions<br />

As the current from the battery remains low as compared to the former case <strong>of</strong> usual batteries the discharging <strong>of</strong><br />

battery occurs at a lower rate with time. If the number <strong>of</strong> photons being directed over the copper plate (a) is made<br />

more by efficient use <strong>of</strong> the reflecting surface <strong>of</strong> the semi cylindrical mirror then the life <strong>of</strong> battery can be<br />

increased remarkably. This can in turn, if used over a large scale save energy widely, also if the battery life is<br />

extendable for much time then this can be used in long journey space vehicles as the energy source also if used in<br />

household widely it will reduce the overall consumption <strong>of</strong> electricity. Although it’s not a new energy resource<br />

but it acts as a method to reduce the present rate <strong>of</strong> resource consumption at the same time maintaining the rate<br />

<strong>of</strong> energy consumption.<br />

Acknowledgement<br />

The Authors would like to thank Mr. Sachin Rathor and Mr. Satish Patel for his support and guidelines in<br />

completing the paper.<br />

References<br />

[1] http://www.kutl.kyushu-u.ac.jp/seminar/MicroWorld1_E/Part3_E/P36_E/photo_electron_E.htm<br />

[2] Pranawa C. Deshmukh and Shyamala Venkataraman,“100 Years <strong>of</strong> Einstein’s Photoelectric Effect,“<br />

Department <strong>of</strong> Physics Indian Institute <strong>of</strong> <strong>Technology</strong> – Madras Chennai – 600 036<br />

[3] http://en.wikipedia.org/wiki/Photoelectric-effect<br />

[4] http://en.wikipedia.org/wiki/Solar_cell<br />

[5] http://hyperphysics.phy-astr.gsu.edu/hbase/tables/photoelec.html<br />

65


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

THERMODYNAMIC MODELLING OF GROUND SOURCE HEAT<br />

PUMP FOR SPACE HEATING<br />

Rajeev Satsangi 1 , Ashok Yadav 2 and Ponnala Vimal Mosahari 1<br />

1 Department <strong>of</strong> Mechanical Engineering, Technical College, Dayalbagh Educational Institute<br />

(Deemed <strong>University</strong>), Dayalbagh, Agra 282110<br />

2 Department <strong>of</strong> Mechanical Engineering, Faculty <strong>of</strong> Engineering, Dayalbagh Educational Institute<br />

(Deemed <strong>University</strong>), Dayalbagh, Agra 282110<br />

Corresponding Author: rajeevsatsangi<strong>20</strong>08@gmail.com<br />

ABSTRACT<br />

Fossil fuels are depleting day by day due to rapid industrialization and urbanization, so there are lot <strong>of</strong> effort<br />

made all over the world to use alternative energy resources. Ground Source Heat Pump is considered as one <strong>of</strong><br />

the renewable energy resources used for heating and cooling purposes. In the present work, conservation<br />

equation for mass and energy are derived for a GSHP system with simple U Tube Ground heat exchanger. The<br />

performance characteristics <strong>of</strong> GSHP are computed in terms <strong>of</strong> COP and energetic aspect. After successful<br />

validation <strong>of</strong> the equation and procedure, the analysis has been performed for the application <strong>of</strong> GSHP for space<br />

heating load <strong>of</strong> 5KW for R 22 and R 134 a (Tetra fluoro ethane) refrigerants. It has been seen that R 134 a have<br />

high COP than R 22. R134 a have no chlorine content and it can be considered as eco-friendly.<br />

Keyword: Ground Source Heat Pump, Energy Analysis, Mass flow rate, Coefficient <strong>of</strong> Performance<br />

1. INTRODUCTION<br />

Non-conventional resources are the need <strong>of</strong> the future and many efforts has been made to consume these<br />

resources for producing electricity and other purpose. Geo thermal energy is used to produce electricity with the<br />

steam generated from underground reservoir. Since these underground steam reservoirs underlie only in<br />

geological energetic areas, consumption <strong>of</strong> geothermal energy for generation <strong>of</strong> electric power has been limited.<br />

In geological energetic areas steam has been used for producing energy, such as space heating, cooling. Lot <strong>of</strong><br />

effort has been made to make the use <strong>of</strong> ground source heat pump for heating and cooling a building for<br />

residential purpose. For GSHP electricity is primarily needed to run heat pump but environment control energy<br />

comes from earth, geo heat pump save tremendous amount <strong>of</strong> heat pump energy.[1]<br />

Ground source heat pumps are installed in various countries, Austria (<strong>19</strong>96) 13000, Germany (<strong>19</strong>95) 14 000-22<br />

000, Netherlands (<strong>19</strong>97) 900, Sweden (<strong>19</strong>98) 60 000, Switzerland (<strong>19</strong>98) <strong>20</strong> 000, France (<strong>19</strong>99) 10 000 - <strong>20</strong> 000,<br />

Europe (extrapolated to end <strong>of</strong> <strong>19</strong>98) 110 000-140 000. [2] And many controlled experiments have been<br />

conducted for residential in Turkey by Arif Hebpasli [3 – 6]. GSHP are “Economically Preferable” [7] renewable<br />

energy resource in term <strong>of</strong> having high net present value. A GSHP simulation model has been devolved for<br />

Canadian climate.[7]<br />

In last many years, many research have conducted on GSHP system regarding design, modeling and<br />

experimental (e.g. Ozgener and Hepbasli, <strong>20</strong>04, <strong>20</strong>05, Sanner et al., <strong>20</strong>03,Kavanaugh, <strong>19</strong>92;Kavanaugh and<br />

Rafferty, <strong>19</strong>97; Healy and Ugursal, <strong>19</strong>97; Hepbasli, <strong>20</strong>02; Hepbasli et al.,<strong>20</strong>03;; Hepbasli and Akdemir, <strong>20</strong>04; Bi<br />

et al., <strong>20</strong>04; Yumrutas and Kaska,<strong>20</strong>04).<br />

In present study rather than setting experimental investigation, this paper deal with thermal analysis <strong>of</strong> GSHP for<br />

a space heating by using Mass balance and energy balance equation. [8] The investigation has done in response<br />

to a case study and then calculation has been done in terms <strong>of</strong> mass balance and energy balance equation.<br />

2. GROUND SOURCE HEAT PUMP TECHNOLOGY<br />

Ground Source Heat Pumps are the new discovery in the field <strong>of</strong> technology for heating and cooling <strong>of</strong> buildings.<br />

They have a dual purpose to serve, along with saving energy, they also helps to save heating and cooling cost.<br />

Ground Source Heat Pumps are the devices which has three main components: the ground side to get heat out <strong>of</strong><br />

or into the ground, the heat pump which helps in the conversion <strong>of</strong> heat to a suitable temperature level, and the<br />

spacing side transferring the heat or cold into the rooms. A good design <strong>of</strong> these pumps is necessary in order to<br />

regulate the whole system in a proper way. [9] GSHPs are eco- friendly as they are helpful in reducing the<br />

consumption <strong>of</strong> fossil fuels, for instance, oil and natural gas, and the potentially harmful by-products associated<br />

with their use. [10] An observation carried out in Paris and it is scientifically proven that there is a steady<br />

66


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

temperature below earth. In 17 th century famous French Chemist Lavoisie kept a thermometer 27 m below earth<br />

surface and found that temperature remain constant throughout the year. In 1799 Humboldt found that the<br />

average temperature below the earth surface is 12° C and only variation <strong>of</strong> temperature is 0.04° C. The Royal<br />

Edinburgh Observatory in Scotland started the exact measurement <strong>of</strong> ground temperature in 1838.<br />

Figure 1 Underground temperature from a borehole south <strong>of</strong> Wetzlar [11]<br />

2.1 GSHP Operation Mode<br />

GSHP are used not only for heating but for cooling too. There are typically three modes for operating these<br />

pumps.<br />

Figure.2 Different GSHP Operation Mode<br />

The feasibility <strong>of</strong> direct cooling is there, when space to be cooled is smaller than heating and the environmental<br />

humidity is less. If the condition opposite then heat pump will act as a chiller and extra additional<br />

dehumidification is required.<br />

The efficiency <strong>of</strong> Heat Pump will be measured in terms <strong>of</strong> COP (Coefficient <strong>of</strong> Performance).<br />

For an electric powered compression heat, COP is expressed as<br />

COP= (Useful Heat / Electric Power Input)<br />

2.2 Various GSHP Systems<br />

GSHP can be classified into open and closed systems, and closed systems may further subdivided into horizontal<br />

and vertical systems, the latter being applicable in a situation when the temperature below a certain depth<br />

remains constant and there is a need to install sufficient heat exchange capacity under a confined surface area. In<br />

GSHP system, many type <strong>of</strong> bore hole heat exchanger configuration have been installed, [11]<br />

Out <strong>of</strong> those two basic concepts are<br />

67


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

• U-Pipes in this two straight pipes are connected by a 180 turn at bottom<br />

• Concentric (coaxial) pipes<br />

3. THERMAL MODELING<br />

Thermodynamic analysis <strong>of</strong> a GSHP system is carried out initially in order to understand the performance <strong>of</strong><br />

individual components <strong>of</strong> the system. For this purpose First law <strong>of</strong> thermodynamic for open system is utilized<br />

to model the individual components. Then the energy flow analysis <strong>of</strong> each component is also studied in detailed<br />

to estimate the overall performance <strong>of</strong> GSHP system. The detail <strong>of</strong> thermodynamic modeling and energy analysis<br />

is discussed in the following section.<br />

For a general steady-state, steady flow process, the four balance equation, namely mass, energy balance<br />

equations are applied to ground source heat pump (GSHP) in order to find the heat input, the rate <strong>of</strong> mass <strong>of</strong> flow<br />

<strong>of</strong> refrigerant flowing into the circuit. Figure 3 show the schematic diagram <strong>of</strong> the GSHP considered for<br />

thermodynamic analysis. The GSHP system consists <strong>of</strong> compressor, condenser, Expansion Valve, Evaporator,<br />

Fan- Coil unit and ground heat exchanger. It is assumed that the flow is steady through every component <strong>of</strong> the<br />

GSHP system and heat loss is ignored. The governing equation for the individual Component <strong>of</strong> the system are<br />

derived as follow<br />

The mass balance equation can be expressed in the rate form as<br />

in= out ( 1 )<br />

Where is the mass flow rate, and the subscript is stand for inlet and outlet.<br />

in= out ( 2 )<br />

Energy balance equation can also be written more explicitly as<br />

Q + inh in = Ẁ + outh out ( 3 )<br />

Where, Q = Q net.in = Q in – Q out is the rate <strong>of</strong> net heat input Ẁ = Ẁ net, out = Ẁ out - Ẁ in is tge rate <strong>of</strong> net work output<br />

and h is the enthalpy per unit mass.<br />

The rate form <strong>of</strong> the entropy balance can be expressed as<br />

S in - S out + S gen =0………………………………………………(4)<br />

3.1 Compressor<br />

Figure 3. The Main Components and Schematic <strong>of</strong> the GSHP<br />

68


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Using the notation used to represent various stage points in GSHP system, the mass balance equation for<br />

compressor can be expressed as<br />

1 = 2 = r (5)<br />

Assuming no heat loss , using the enrgy balance equation the work input to the compressor can be expressed as<br />

Ẁ comp = r (h 2 -h 1 ) (6)<br />

3.2 Condenser<br />

Mass Balance for the refrigerant flow in the condenser can be denoted as<br />

r = 2 = 3 (7)<br />

Similarly the mass balance for air flow in the fan coil unit which is connected to the condenser for heat<br />

extraction, can be expressed as<br />

5 = 6 = w (8)<br />

The energy balance for refrigerant and air side are given by<br />

Q cond = r (h 2 -h 3 ) (9)<br />

Q cond =Q fc = w C pw (T 5 -T 6 ) (10)<br />

3.3 Throttling valve<br />

The Mass Balance for the refrigerant flow in the throttling valve can be denoted as<br />

r = 4 = 3 (11)<br />

In the absence <strong>of</strong> heat loss the energy balance is<br />

h 3 =h 4 (12)<br />

3.4 Evaporator<br />

The Mass Balance for the refrigerant flow in the Evaporator can be denoted as<br />

r = 4 = 1 (13)<br />

Similarly the mass balance equation for brine water flow through the bore heat exchanger which is coupled to the<br />

evaporator for heat transfer, is given as<br />

7 = 8 = bw (14)<br />

The energy balance for Evaporator is given by<br />

Q evap = r (h 1 -h 4 ) (15)<br />

Q evap = Q gh (16)<br />

3.5 Fan coil unit<br />

The Mass Balance for the refrigerant flow in the fan coil unit can be denoted as<br />

air, in = air, out = air (17)<br />

Q fc = Q cond (18)<br />

Q cond = Q gh (<strong>19</strong>)<br />

3.6 Ground – heat exchanger<br />

The Mass Balance for the refrigerant flow in the Ground – heat exchanger can be denoted as<br />

7 = 8 = bw (<strong>20</strong>)<br />

The energy balance for Ground – heat exchanger is given by<br />

Q gh = bw C p.bw (T 8 -T 7 ) (21)<br />

Q evap = Q gh (22)<br />

3.7 Performance Parameter<br />

The Performance parameter <strong>of</strong> a GSHP unit can be estimated using parameter as defined below<br />

COP = ( Q cond / Ẁ comp ) (23)<br />

Where Q cond is the heat transfer rate <strong>of</strong> the condenser, while Ẁ comp is rate <strong>of</strong> work input to the compressor.<br />

The actual power input to the compressor may be computed as follows<br />

69


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Ẁ comp,act = ( Ẁ comp / Isentropic ŋ ) (24)<br />

4. THERMAL ANALYSIS OF GSHP SYSTEM FOR A CASE STUDY<br />

The thermodynamic analysis <strong>of</strong> GSHP system for district heating was investigated in terms <strong>of</strong> both energy<br />

analyses, which aim at better, identifies the COP <strong>of</strong> GSHP System. Expression for this analysis was derived<br />

using mass, energy balance equation discussed earlier in the section.<br />

Referring figure 3, it can be observed that the GSHP mainly consist <strong>of</strong> three separate Circuits<br />

i. The ground coupling circuit ( Brine Circuit ) With a nominal Diameter U- bend ground heat<br />

exchanger,<br />

ii. The refrigerant Circuit<br />

iii. The Fan Coil Circuit ( Water Circuit )<br />

Here we were considering brine water as simple water. The Refrigerant Circuit was built <strong>of</strong> closed – loop copper<br />

tubing. The Working fluid is R- 22.<br />

The energy performance <strong>of</strong> a GSHP system can be influenced by three primary factors<br />

i. The heat Pump Machine<br />

ii. The Circulating pump or ground water heat pump<br />

iii. The ground temperature<br />

For evaluating the performance <strong>of</strong> a GSHP system, the temperature and pressure at the inlet and outlet <strong>of</strong> a<br />

various components <strong>of</strong> a GSHP system have to be given or assumed. We are interested to know the effect <strong>of</strong><br />

Indian condition on the performance <strong>of</strong> GSHP system. For this purpose we have to take average temperature <strong>of</strong><br />

India during winter. Here we are taking ambient temperature 11˚ C. Changing ground inlet and outlet<br />

temperature according to our condition s for various refrigerants such as R-22 and R134 a, for same heating load<br />

<strong>of</strong> 5 KW. We are interested to know the comparison in COP for both. Here we are assuming same pressure and<br />

temperature as input for the entire refrigerant. With the help <strong>of</strong> psychometric Properties chart we get other<br />

required values such as enthalpy and entropy [12]. Now we make table <strong>of</strong> result for refrigerants one by one then<br />

we compare their result by comparing their COP which include in section <strong>of</strong> result and discussion. The Soil<br />

temperature is assumed as <strong>20</strong>˚C according to our condition for the entire refrigerant. The word brine water is<br />

only used here in actual we are taking the properties <strong>of</strong> water for making our calculation. The soil temperature<br />

measured in Agra about <strong>20</strong> meter below is comes out to , T soil =<strong>20</strong>˚C and heat pump Capacity is= 5KW. Overall<br />

efficiency <strong>of</strong> compressor is about 80%<br />

From equation Q sh =Q cond = r (h 2 -h 3 ),Mass flow rate <strong>of</strong> refrigerant is comes out to be, r = 0.0253 kg/sec<br />

From the equation Q fc = w C pw (T 5 -T 6 ),we get mass flow rate <strong>of</strong> water in fan coil unit, w = 0.833 kg/sec where<br />

C pw taken as 4.18 kj/kgk<br />

From the equation Q gh = bw C p.bw (T 8 -T 7 ), Where Q gh = Q evap = r (h 1 -h 4 ), bw = 0.4242 kg/sec<br />

Table 1 Property data for different components <strong>of</strong> GSHP (R22)<br />

S. No Description Fluid Temp T<br />

˚C<br />

Pressure<br />

P (bar)<br />

Specific Enthalpy<br />

h (kj/kg )<br />

Specific Entropy<br />

s (kj/kgk )<br />

1 - Refrigerant 11 1.013 388.609 1.825<br />

2 - Water 11 1.013 46.31 0.1658<br />

3 - Brine Water 11 1.013 46.31 0.1658<br />

4 Compressor Inlet Refrigerant -2 4.6 404.626 1.75475<br />

5 Compressor Outlet Refrigerant 52 <strong>20</strong>.32 447.98 1.68<br />

6 Condenser Outlet Refrigerant 40 15.335 249.686 1.1666<br />

7 Evaporator Inlet Refrigerant -5 4.21 <strong>19</strong>4.176 0.9787<br />

8 Fan Coil Unit Inlet Water 50 2.4 211.39 0.7027<br />

70


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

9 Fan Coil Unit Outlet Water 44 2.4 186.35 0.6245<br />

10 GHE water Pump Inlet Brine Water 1 2.4 4.4<strong>19</strong> 0.01527<br />

11 GHE water Pump Outlet Brine Water 4 3.4 17.151 0.0611<br />

4.1 Energy Analysis (for R22)<br />

1 = 2 = r == 0.0245kg/sec<br />

Table 2 Different energy rate <strong>of</strong> GSHP system<br />

Energy rate<br />

Inlet (KW)<br />

Energy rate<br />

Outlet (KW)<br />

Compressor 10.2 11.30<br />

Condenser 6.314 -<br />

Evaporator 4.91 -<br />

Fan Coil Unit 176.08 155.229<br />

Ground Heat Exchanger 7.27 1.87<br />

Coefficient Of Performance ( COP ) <strong>of</strong> heat pump = 3.73<br />

Table 3 Property data for different components <strong>of</strong> GSHP (R 134 a)<br />

S. No Description Fluid Temp T Pressure Specific Enthalpy<br />

˚C P (bar) h (kj/kg )<br />

Specific Entropy<br />

s (kj/kgk )<br />

1 - Refrigerant 11 1.013 382.9 1.7476<br />

2 - Water 11 1.013 46.31 0.1658<br />

3 - Brine Water 11 1.013 46.31 0.1658<br />

4 Compressor Inlet Refrigerant -2 2.926 398.68 1.7274<br />

5 Compressor Outlet Refrigerant 52 13.85 425.03 1.7061<br />

6 Condenser Outlet Refrigerant 40 10.216 256.35 1.<strong>19</strong>03<br />

7 Evaporator Inlet Refrigerant -5 2.41 <strong>19</strong>3.08 0.9505<br />

8 Fan Coil Unit Inlet Water 50 2.4 211.39 0.7027<br />

9 Fan Coil Unit Outlet Water 44 2.4 186.35 0.6245<br />

10 GHE water Pump Inlet Brine Water 1 2.4 4.4<strong>19</strong> 0.01527<br />

11 GHE water Pump Outlet Brine Water 4 3.4 17.151 0.0611<br />

Solving the equation we get mass flow rate <strong>of</strong> refrigerant, 1 = 2 = r = 0.0296 kg/sec<br />

4.2 Energy Analysis (R 134 a)<br />

Table 4. Different energy rate <strong>of</strong> GSHP system<br />

Energy rate<br />

Inlet (KW)<br />

Energy rate<br />

Outlet (KW)<br />

Compressor 11.80 12.58<br />

Condenser 7.5879 -<br />

Evaporator 5.7151 -<br />

Fan Coil Unit 176.08 155.229<br />

Ground Heat Exchanger 7.27 1.87<br />

Coefficient Of Performance ( COP ) <strong>of</strong> heat pump = 5.128<br />

71


5. RESULT<br />

As we see from figure 4.1 COP <strong>of</strong> R 134 a is more than R22<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 4 Comparisons <strong>of</strong> COP for R22 and R 134 a<br />

6. Conclusion<br />

In present study, the results were evaluated to determine the performance <strong>of</strong> a GSHP unit and the overall system.<br />

Some important conclusions that may be drawn from present study that the value <strong>of</strong> COP <strong>of</strong> heat pump unit was<br />

obtained to be 5.128 for R134 a, which is higher than COP <strong>of</strong> R22 and it is scientifically proven that R 134 a<br />

Refrigerant is Eco friendly because there is no Chlorine content in this so there is less pollution with this<br />

refrigerant while using in an refrigeration cycle. The Present work is first attempt to carry out theoretical works<br />

on a GSHP system for space heating. However, the present work has provided us a good learning on the various<br />

factors that affect the performance <strong>of</strong> a GSHP system.<br />

References<br />

1. U.S. Department <strong>of</strong> Energy, Office <strong>of</strong> Energy Efficiency and Renewable Energy, “Buyer’s Guide to<br />

Geothermal Heat Pumps,”<br />

2. http://www.eere.energy.gov/consumer/your_home/space_heating_cooling/index.cfmmytopic=12640<br />

3. Justus-liebig university, giessen, Germany, “Shallow geothermal energy”, Burkhard sanner.<br />

4. A. Hepbasli, O. Akdemir, and E. Hancioglu, <strong>20</strong>03. “Experimental Study <strong>of</strong> a Closed Loop Vertical Ground<br />

Source Heat Pump System,” Energy Conversion and Management 44:4, pp. 527 – 548.<br />

5. A. Hepbasli and O. Akdemir, <strong>20</strong>04. “Energy and Exergy Analysis <strong>of</strong> a Ground Source Heat Pump,” Energy<br />

Conversion and Management 45:5, pp. 737 – 753.<br />

6. O. Ozgener and A. Hepbasli, <strong>20</strong>04. “Experimental Performance Analysis <strong>of</strong> a Solar-Assisted Ground-Source<br />

Heat Pump Greenhouse Heating System,” Energy and Buildings 37:1, pp. 101 – 110.<br />

7. O. Ozgener and A. Hepbasli, <strong>20</strong>05. “Exergoeconomic Analysis <strong>of</strong> a Solar Assisted Ground-Source Heat<br />

Pump,” Applied Thermal Engineering 25:10, pp. 1459 – 1471.<br />

8. SP. F. Healy and V. I. Ugursal, <strong>19</strong>98. “Performance and Economic Feasibility <strong>of</strong> Ground-Source Heat Pumps<br />

in a Cold Climate,” International Journal <strong>of</strong> Energy Research, 21:10, pp. 857 – 870.<br />

9. Arif Hepbasli <strong>20</strong>05. “Thermodynamic analysis <strong>of</strong> a ground-source heat pump system for district heating,<br />

International journal <strong>of</strong> energy research, 29:671–687.<br />

10. Ground source heat pump : a guide book<br />

11. Fact sheet commonwealth <strong>of</strong> Pennsylvania, Department <strong>of</strong> environmental protection Ground source heat<br />

pump systems.<br />

12. Burkhard sanner et. al, shallow geothermal energy, <strong>University</strong>, giessen, Germany<br />

13. M.L. Mathur and F.S. Mehta,“Refrigerant and Psychrometric properties (Table & Chart)” <strong>20</strong>10.<br />

72


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Alternatives to R134a (CF 3 CH 2 F) Refrigerant- A Review<br />

Gaurav a , Dr. Raj Kumar b<br />

a Assistant Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, Mewat Engineering College, Mewat-122107,<br />

Haryana, India. E-mail: gaurav.citm@gmail.com<br />

b Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad-<br />

121006, Haryana, India<br />

Abstract<br />

R134a (Hydr<strong>of</strong>luorocarbon refrigerant) is used in domestic refrigeration and other vapour compression system.<br />

R134a is having zero ozone depletion potential (ODP) and almost same thermodynamic properties as R12<br />

(Chlor<strong>of</strong>lurocarbon refrigerant), but it has 1300 global warming potential (GWP) per year which is very high.<br />

So, there is a need to find out the alternatives to R134a from toxicity, flammability, thermodynamic,<br />

thermoeconomic and environment point <strong>of</strong> view. This review paper also represents the recent development done<br />

on alternatives to R134a.<br />

Keywords: Global warming, Ozone depletion, Alternative refrigerant, Flammability<br />

1. Introduction<br />

The first mechanically produced cooling system was developed in England in 1834. The process later became<br />

known as vapour compression. After availability <strong>of</strong> electricity automatic refrigeration system was developed in<br />

1897. Basically a refrigeration or air conditioning is nothing more than a heat pump whose job is to remove heat<br />

from a lower temperature source and reject heat to high temperature sink.<br />

Figure 1<br />

The vapour compression uses a circulating liquid refrigerant as the medium which absorbs and removes heat<br />

from the space to be cooled and subsequently rejects that heat elsewhere. Figure 1 depicts a typical, single-stage<br />

vapour-compression system. All such systems have four components: a compressor, a condenser, a thermal<br />

expansion valve (also called a throttle valve or Tx Valve), and an evaporator. Circulating refrigerant enters the<br />

compressor in the thermodynamic state known as a saturated vapour and is compressed to a higher pressure,<br />

resulting in a higher temperature as well. Saturated vapour is then routed through a condenser where it is cooled<br />

and condensed into a liquid by flowing through a coil or tubes with cool water or cool air flowing across the coil<br />

or tubes. This is where the circulating refrigerant rejects heat from the system and the rejected heat is carried<br />

73


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

away by either the water or the air (whichever may be the case). The condensed liquid refrigerant, in the<br />

thermodynamic state known as a saturated liquid, is next routed through an expansion valve where it undergoes<br />

an abrupt reduction in pressure. That pressure reduction results in the adiabatic flash evaporation <strong>of</strong> a part <strong>of</strong> the<br />

liquid refrigerant. The auto-refrigeration effect <strong>of</strong> the adiabatic flash evaporation lowers the temperature <strong>of</strong> the<br />

liquid and vapour refrigerant mixture to where it is colder than the temperature <strong>of</strong> the enclosed space to be<br />

refrigerated. The cold mixture is then routed through the coil or tubes in the evaporator. A fan circulates the<br />

warm air in the enclosed space across the coil or tubes carrying the cold refrigerant liquid and vapour mixture.<br />

That warm air evaporates the liquid part <strong>of</strong> the cold refrigerant mixture. At the same time, the circulating air is<br />

cooled and thus lowers the temperature <strong>of</strong> the enclosed space to the desired temperature. The refrigerant vapour<br />

from the evaporator is again a saturated vapour and is routed back into the compressor, thus cycle repeats.<br />

2. Literature Review:<br />

• R. Cabello et al [1] studied the influence <strong>of</strong> the evaporating pressure, condensing pressure and<br />

superheating degree <strong>of</strong> the vapour on the exergetic performance <strong>of</strong> a refrigeration plant using three<br />

different working fluids R134a, R407c, R22.<br />

• K. Senthil Kumar et al [2] studied the behavior <strong>of</strong> HCFC (Hydrochlor<strong>of</strong>lurocarbon) -123/ HC-290<br />

refrigerant mixture computationally as well as experimentally and found that refrigerant mixture 7/3 as<br />

a promising alternative to R12 system.<br />

• B.O. Bolaji et al [3] investigated experimentally the performances <strong>of</strong> three ozone friendly<br />

Hydr<strong>of</strong>luorocarbon (HFC) refrigerants R12, R152a and R134a. R152a refrigerant found as a drop in<br />

replacement for R134a in vapour compression system.<br />

• B.O. Bolaji [4] discussed the process <strong>of</strong> selecting environmental-friendly refrigerants that have zero<br />

ozone depletion potential and low global warming potential. R23 and R32 from methane derivatives<br />

and R152a, R143a, R134a and R125 from ethane derivatives are the emerging refrigerants that are non<br />

toxic, have low flammability and environmental-friendly. These refrigerants need theoretical and<br />

experimental analysis to investigate their performance in the system.<br />

• A.S. Dalkilic et al [5] studied the performance analysis <strong>of</strong> alternative new refrigerant mixtures as<br />

substitute for R12, R134a and R 22. Refrigerant blend <strong>of</strong> R290/R 600a (40/60 by wt. %) and R<br />

290/R1270 (<strong>20</strong>/80 by wt. %) are found to be the most suitable alternative among refrigerants tested for<br />

R12 and R22.<br />

• S. Wongwises et al [6] found that 6/4 mixture <strong>of</strong> R290 and R600 is the most appropriate refrigerant to<br />

replace HFC134a in a domestic refrigerator.<br />

• K Mani et al [7] found that R290/R600a (68/32 by wt. %) can be considered as a drop in replacement<br />

for R12 and R134a.<br />

• Miguel Padilla et al [8] found that R413A (mixture <strong>of</strong> 88% R134a, 9%R218, 3%R600a) can replace<br />

R12 and R134a in domestic refrigerator.<br />

• Bukola O. Balaji et al [9] investigated the exergetic performance <strong>of</strong> R12 and its substitute (R134a and<br />

R 152a) in the domestic refrigerator. R152a performed better than R134a in terms <strong>of</strong> COP, exergetic<br />

efficiency and efficiency defect as R12 substitute in domestic refrigeration system.<br />

• Alka Bani Agrawal et al (10) worked on eco-friendly refrigerant as a substitute for CFC<br />

(Chlor<strong>of</strong>lurocarbon). The binary mixture in the ration <strong>of</strong> 64% and 36% <strong>of</strong> R290 and R600a found to be<br />

a retr<strong>of</strong>it or drop in substitute <strong>of</strong> R12 for use in the vapour compression refrigeration trainer.<br />

• M.M. EI-Awad [11] performed the validation <strong>of</strong> model against experimental data that compared the<br />

performance <strong>of</strong> liquefied petroleum gas (LPG) to that <strong>of</strong> refrigerant R12 for domestic refrigeration.<br />

• Abhishek Tiwari et al [12] published a review paper on recent development on domestic refrigeration.<br />

74


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3. Need for Alternatives <strong>of</strong> R134a<br />

3.1 Generation <strong>of</strong> Refrigerants:<br />

• The first generation (1830-<strong>19</strong>30) <strong>of</strong> refrigerants was based on the availability. These refrigerants were<br />

<strong>of</strong>ten highly toxic, flammable and some very highly reactive. Example – Ethers, CO 2 , NH 3 , CCl 4 etc.<br />

• The second generation (<strong>19</strong>30-<strong>19</strong>90) <strong>of</strong> refrigerants focused on reducing toxicity and flammability.<br />

Example: CFCs, HCFCs, HFCs, NH 3 , H 2 O etc.<br />

• The third generation (<strong>19</strong>90-<strong>20</strong>10) <strong>of</strong> refrigerants focused on protecting the ozone layer. Example -<br />

HCFCs, HFCs, HCs, NH 3 , H 2 O, CO 2 etc.<br />

• The fourth generation (from <strong>20</strong>10 onwards) focused on refrigerants that do not contribute to global<br />

warming, ozone layer depletion, efficient, non flammable and non toxic with good stability. But the<br />

outlook for discovery or synthesis <strong>of</strong> these ideal refrigerants is extremely unlikely. Therefore, trade -<strong>of</strong>f<br />

among desired objectives are necessary to achieve the balanced solution.<br />

3.2 Montreal Protocol:<br />

• In <strong>19</strong>87 Montreal protocol established the requirements that began the world – wide phase out <strong>of</strong> CFCs.<br />

Production <strong>of</strong> CFCs was phased out by the Montreal Protocol in developed countries in 1 st <strong>of</strong> January,<br />

<strong>19</strong>96. Production in developing countries was phased out in <strong>20</strong>10 [4].<br />

• In <strong>19</strong>92 Montreal protocol established the requirements that began the world – wide phase out <strong>of</strong><br />

HCFCs. Complete production <strong>of</strong> HCFCs will be phased out by Montreal protocol in <strong>20</strong>30.<br />

3.3 Kyoto Protocol:<br />

• Kyoto protocol aims at phasing out <strong>of</strong> substances that will lead to global warming.<br />

• R134a is used in domestic refrigerator and other vapour compression systems as it was identified as a<br />

replacement to CFC-12, keeping in view its zero ozone depleting potential. R134a has 1300 global<br />

warming potential per 100 year, which is very high. The sale <strong>of</strong> R134a reported to AFEAS <strong>19</strong>70-<strong>20</strong>03<br />

[13] is significantly increasing during the past two decades. The increased emission <strong>of</strong> R134a to the<br />

atmosphere are steadily increasing the concentration <strong>of</strong> green house gases via leaks and mostly, in an<br />

indirect way, via energetic performance <strong>of</strong> refrigeration plant. This will lead to adverse climatic<br />

problem. Hence, R134a is one <strong>of</strong> the six chemicals in the “basket” that are to be phased out in the near<br />

future under Kyoto protocol.<br />

4. Environmental Concern<br />

• The first major concern is depletion <strong>of</strong> ozone layer. Ozone layer is a layer which protects the earth from<br />

ultraviolet rays. Ozone depletion potential is evaluated on a scale that uses CFC-11 as a benchmark. All<br />

the other components are based on how damaging to the ozone they are in relation to CFC-11.<br />

• The second major concern is global warming. Global warming is the increase in global earth surface<br />

temperature due to the absorption <strong>of</strong> infrared emission from earth surface. Global warming potential is<br />

evaluated on a scale that uses CO 2 as the bench mark i.e. CO 2 is assigned a value and other components<br />

are compared to CO 2 .<br />

5. Analysis <strong>of</strong> Vapour Compression Refrigeration Cycle<br />

• Thermodynamic analysis is the analysis based on energy. Raising the efficiency <strong>of</strong> an energy system is<br />

within the domain <strong>of</strong> thermodynamics.<br />

• Thermoeconomic analysis is the analysis based on exergy and economic principles to provide system<br />

designer or operator with information not available through conventional energy analysis and economic<br />

evaluations but crucial to the design and operation <strong>of</strong> a cost effective system. Energy cannot be<br />

destroyed-a first-law concept. The idea that something can be destroyed is useful in the design and<br />

75


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

analysis <strong>of</strong> thermal systems. This idea does not apply to energy, however, but to exergy (availability)-a<br />

second law concept. Exergy analysis usually predicts the thermodynamic performance and the<br />

inefficiency <strong>of</strong> an energy system.<br />

6. Alternatives to R134a<br />

Chlorine content present in the CFCs and HCFCs contribute to depletion <strong>of</strong> ozone layer. Hence, Montreal<br />

Protocol established the phase out <strong>of</strong> CFCs and HCFCs. Alternative refrigerant <strong>of</strong> CFCs and HCFCs is HFCs as<br />

there is no chlorine content in it. R134a is HFC (Hydr<strong>of</strong>luorocarbon) refrigerant. Through research it was found<br />

that R134a contribute to Global Warming because <strong>of</strong> Fluorine content in it. R134a has a relatively high global<br />

warming potential (1300 times that <strong>of</strong> CO 2 ). Although Global warming is a good thing in itself and allows life to<br />

exist in all its variety but the concern is that man’s activities are increasing the concentration <strong>of</strong> carbon dioxide<br />

and other green gases in the atmosphere, causing the amount <strong>of</strong> absorbed infrared radiation to increase, and<br />

leading to atmospheric temperatures and consequent long term climate changes. Hence, Kyoto protocol<br />

established the phased out <strong>of</strong> HFCs in the near future. Montreal and Kyoto protocols are interconnected, total<br />

climate change and ozone depletion depends on both the global warming potential and ozone depletion potential<br />

<strong>of</strong> the substances [14]. Alternative to HFC refrigerants can be HC (Hydrocarbon) as there is no fluorine content.<br />

Hydrocarbons (HCs) are the class <strong>of</strong> natural–occurring substances that include propane, pentane and butane.<br />

HCs are excellent refrigerants in many ways - energy efficiency, critical point, solubility, transport, heat transfer<br />

properties and environmentally sound but their major concern is their flammability. Properties <strong>of</strong> alternative<br />

refrigerants <strong>of</strong> R134a are given in Table 1.<br />

Refrigerant<br />

(Category)<br />

Chemical<br />

Formula<br />

Normal<br />

Boiling<br />

Point<br />

(°C)<br />

Table 1<br />

Critical<br />

Temperature<br />

(°C)<br />

ODP<br />

GWP<br />

(per 100<br />

Year)<br />

Safety<br />

Group<br />

R134a CF 3 CH 2 F -26.07 101.06 0 1300 A1<br />

(HFC)<br />

R152a CH 3 CHF 2 -24.02 113.3 0 1<strong>20</strong> A2<br />

(HFC)<br />

R290 (HC) C 3 H 8 -42.1 96.8 0 <strong>20</strong> A3<br />

R600 (HC) C 4 H 10 -0.56 153 0 <strong>20</strong><br />

R600a (HC) (CH 3 ) 3 CH -11.67 135.0 0 <strong>20</strong> A3<br />

R32(HFC) CH 2 F 2 -51.65 78.41 0 550 A2<br />

R143a CH 3 CF 3 -47.24 73.1 0 4300 A2<br />

(HFC)<br />

R125 CHF 2 CF 3 -48.1 66.25 0 3400 A1<br />

(HFC)<br />

R123<br />

(HCFC)<br />

CHCl 2 CF 3 27.82 183.79 0.0<strong>20</strong> 90 B1<br />

Comparing the different values <strong>of</strong> alternative refrigerants as given in above table and from literature review,<br />

some <strong>of</strong> the alternative refrigerants <strong>of</strong> R134a can be R32, R152a, R125, R413A (mixture <strong>of</strong> 88% R134a,<br />

9%R218, 3%R600a), R290/R600a (68/32 by wt. %), R290/R 600a (40/60 by wt. %) and R123/ R290 (mixture<br />

<strong>of</strong> 7/3). These alternative refrigerants must be compare thermodynamically and thermoeconomically (Exergy<br />

+Economic), so that best alternative can be found out.<br />

76


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

7. Conclusions<br />

Following conclusions can be drawn from this review paper<br />

• R134a is a HFC refrigerant and it contributes to global warming because <strong>of</strong> fluorine content in it.<br />

Ozone depletion and total climate change depends on both global warming potential and ozone<br />

depletion potential. So, there is a need to find out alternatives <strong>of</strong> R134a under Kyoto protocol and<br />

Montreal protocol.<br />

• From literature review and properties <strong>of</strong> refrigerant R32, R152a, R125, R413A (mixture <strong>of</strong> 88%<br />

R134a, 9%R218, 3%R600a), R290/R600a (68/32 by wt. %), R290/R 600a (40/60 by wt. %) and R123/<br />

R290 (mixture <strong>of</strong> 7/3) are identified as alternatives <strong>of</strong> R134a.<br />

• There is a need <strong>of</strong> comparing the alternative refrigerants from thermodynamic, thermoeconomical,<br />

environmental, toxicity, stability and flammability point <strong>of</strong> view. So, that best alternative to R134a can<br />

be found out.<br />

• There is a need <strong>of</strong> further research to be done on the different mixtures <strong>of</strong> HFCs and HCs, to find the<br />

alternatives <strong>of</strong> R134a.<br />

References<br />

[1] R. Cabello, E. Torrella, J. Navarro-Esbri, Experimental evaluation <strong>of</strong> a vapour compression plant<br />

performance using R134a, RR407C and R22 as working fluids, Applied Thermal Engineering 24 (<strong>20</strong>04)<br />

<strong>19</strong>05-<strong>19</strong>17.<br />

[2] K. Senthil Kumar, K. Rajagopal, Computational and experimental investigation <strong>of</strong> low ODP and low GWP<br />

HCFC-123 and HC-290 refrigerant mixture alternative to CFC-12, Energy Conversion and Management 48<br />

(<strong>20</strong>07) 3053-3062.<br />

[3] B.O.Bolaji, M.A. Akintunde, T.O. Falade, Comparative analysis <strong>of</strong> performance <strong>of</strong> three ozone-friends HFC<br />

refrigerants in a vapour compression refrigerator, Journal <strong>of</strong> Sustainable Energy and Environment 2 (<strong>20</strong>11)<br />

61-64.<br />

[4] B.O.Bolaji, Selection <strong>of</strong> environment-friendly refrigerants and the current alternatives in vapour<br />

compression refrigeration systems, Journal <strong>of</strong> <strong>Science</strong> and Management, Vol 1, No. 1 (<strong>20</strong>11) 22-26.<br />

[5] A.S. Dalkilic, S. Wongwises, A performance <strong>of</strong> vapour-compression refrigeration system using various<br />

alternative refrigerants, International Communication in Heat and Mass Transfer 37 (<strong>20</strong>10) 1340-1349.<br />

[6] Somchai Wongwises, Nares Chimres, Experimental study <strong>of</strong> hydrocarbon mixtures to replace HFC-134a in a<br />

domestic refrigerator, Energy Conversion and Management 46 (<strong>20</strong>05) 85-100.<br />

[7] K. Mani, V. Selladurai, Experimental analysis <strong>of</strong> a new refrigerant mixture as a drop in replacement for CFC<br />

12 and HFC 134a, International Journal <strong>of</strong> Thermal <strong>Science</strong> 47 (<strong>20</strong>08) 1490-1495.<br />

[8] Miguel Padilla, Remi Revellin, Jocelyn Bonjour, Exergy analysis <strong>of</strong> R413A as a replacement <strong>of</strong> R12 in a<br />

domestic refrigeration system, Energy Conversion and Management 51 (<strong>20</strong>10) 2<strong>19</strong>5-2<strong>20</strong>1.<br />

[9] Bukola o. Bolaji, Exergetic performance <strong>of</strong> a domestic refrigerator using R12 and its alternative refrigerants,<br />

Journal <strong>of</strong> Engineering <strong>Science</strong> and <strong>Technology</strong>, Vol. 5, No. 4 (<strong>20</strong>10) 435-446.<br />

[10] Alka Bani Agrawal and Vipin Shrivastava, Retr<strong>of</strong>itting <strong>of</strong> vapour compression refrigeration trainer by an<br />

ec0-friendly refrigerant, Indian Journal <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Vol. 3, No. 4 (<strong>20</strong>10) 455-458.<br />

[11] M.M. EI-Awad, Validation <strong>of</strong> computerized analytical model for evaluating natural hydrocarbon mixtures<br />

as alternative refrigerants, Journal <strong>of</strong> Sustainable Energy and Environment 2 (<strong>20</strong>11) 175-179.<br />

[12] Abhishek Tiwari, R.C. Gupta, Recent developments on domestic refrigerator-a review, International<br />

Journal <strong>of</strong> Engineering <strong>Science</strong> and <strong>Technology</strong>, Vol. 3, No. 5(<strong>20</strong>11) 4233-4239.<br />

[13] , <strong>20</strong>06.<br />

[14] Report <strong>of</strong> the TEAP HFC and PFC Task Force, The implication to the Montreal protocol <strong>of</strong> the inclusion <strong>of</strong><br />

HFCs and PFCs in the Kyoto Protocol: October <strong>19</strong>99.<br />

[15] C.P.Arora, Refrigeration and Air Conditioning, Tata MeGraw Hill, New Delhi, India, <strong>20</strong>10.<br />

77


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

A REVIEW OF COMBINED CYCLE POWER PLANT<br />

THERMODYNAMIC CYCLES<br />

Nikhil Dev 1* , Samsher 2 , S. S. Kachhwaha 3 , Rajesh Attri 1<br />

1 <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad, Haryana, India.<br />

2 Delhi Technological <strong>University</strong>, Delhi, India<br />

3 Pandit Deendayal Petroleum <strong>University</strong>, Gandhinagar, India<br />

nikhildevgarg@yahoo.com<br />

ABSTRACT<br />

Simple cycle gas turbine engines suffer from limited efficiencies and consequential dominance <strong>of</strong> fuel<br />

prices on generation costs. Combined cycles, however, exploit the waste heat from exhaust gases to boost<br />

power output, resulting in overall efficiencies around 50%, which are significantly above those <strong>of</strong> steam<br />

power plants. This paper reviews various types <strong>of</strong> combined cycles, including repowering, integrated<br />

gasification and other advanced systems.<br />

INTRODUCTION<br />

The interest in the combined cycle operation was aroused through the world in mid <strong>19</strong>70’s. During the last<br />

two decades a number <strong>of</strong> alternative combined cycle concepts have been developed. In this chapter, a<br />

detailed review <strong>of</strong> literature on combined cycle power plant has been undertaken, which evaluates various<br />

gas/steam combined cycle arrangements consisting <strong>of</strong> a gas turbine coupled to an alternative bottoming<br />

cycles. In addition the methods <strong>of</strong> thermodynamic analysis and simulation <strong>of</strong> these power plants available<br />

in the literature have been briefly reviewed.<br />

Figure.1. Schematic flow diagram <strong>of</strong> Combined Cycle Power Plant.<br />

Working <strong>of</strong> a typical combined cycle power plant shown in figure 1 is explained in this section. The air at<br />

the ambient temperature is compressed by the air compressor and directed to the combustion chamber. The<br />

compressed air mixes with the natural gas from the fuel supply system to produce hot combustion gas in<br />

the combustor. The hot combustion gas is delivered to the gas turbine where the power is generated. The<br />

exhaust gas passes through a heat recovery steam generator where water is converted to high pressure<br />

steam. The high pressure steam from the boiler drives the steam turbine. The spent steam from the turbine<br />

flows into the condenser. The steam is separated in the boiler drum and supplied to the super heater section<br />

78


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

and the boiler condenser section. The super heated steam produced in the super heater then enters into the<br />

turbine through the turbine stop valve. After expansion in the turbine the exhaust steam is condensed in the<br />

condenser.<br />

Improving the combined cycle efficiency has always been an important objective <strong>of</strong> any cycle analysis. The<br />

gas turbine power plant despite its low efficiency is a very versatile unit because <strong>of</strong> its simplicity and low<br />

cost. The advantages are even greater if the energy <strong>of</strong> the exhaust gas can be effectively used. Because <strong>of</strong><br />

high air fuel ratio, exhaust gas has a high portion <strong>of</strong> oxygen and further combustion can also be carried out.<br />

One convenient approach is to combine two different cycles to form a new power generating cycle. One <strong>of</strong><br />

the popular schemes is the combination <strong>of</strong> Brayton cycle and Rankine cycle. Such a combination is called<br />

the combined cycle power plant.<br />

During the last two decades a number <strong>of</strong> alternative combined cycle concepts have been evolved. The<br />

simplest <strong>of</strong> course consists <strong>of</strong> simple gas turbine coupled with a single pressure bottoming cycle. However,<br />

in this concept, the waste heat utilization is not very effective both in terms <strong>of</strong> energy and exergy. This can<br />

be substantially held by employing dual pressure or triple pressure bottoming cycle with or without<br />

reheating. In selective cases the combined cycle using supplementary firing in a waste HRSG boiler is also<br />

used with advantage.<br />

Recent Developments in CCPP Thermodynamic Cycles<br />

Ertesvag et al. (<strong>20</strong>05) have shown the exergy analysis <strong>of</strong> a gas-turbine combined-cycle power plant with<br />

precombustion CO 2 capture. A concept for natural-gas (NG) fired power plants with CO 2 capture was<br />

investigated using exergy analysis. NG was reformed in an auto-thermal reformer (ATR), and the CO 2 was<br />

separated before the hydrogen-rich fuel was used in a conventional combined-cycle (CC) process. The<br />

main purpose <strong>of</strong> the study was to investigate the integration <strong>of</strong> the reforming process and the combined<br />

cycle. A corresponding conventional CC power plant with no CO 2 capture was simulated for comparison.<br />

A base case with CO 2 capture was specified with turbine-inlet temperature (TIT) <strong>of</strong> 1250 and an aircompressor<br />

outlet pressure <strong>of</strong> 15.6 bar. In this case, the net electric-power production was 48.9% <strong>of</strong> the<br />

lower heating value (LHV) <strong>of</strong> the NG or 46.9% <strong>of</strong> its chemical exergy. The captured and compressed CO 2<br />

(<strong>20</strong>0 bar) represented 3.1% <strong>of</strong> the NG chemical exergy, while the NG, due to its pressure (50 bar), had a<br />

physical exergy equal to 1.0% <strong>of</strong> its chemical exergy. This research explores the effects <strong>of</strong> the changed NG<br />

composition and environmental temperature.<br />

Sengupta et al. (<strong>20</strong>07) have studied the exergy analysis <strong>of</strong> a coal-based 210 MW thermal power plant. In<br />

the present work, exergy analysis <strong>of</strong> a coal-based thermal power plant is done using the design data from a<br />

210 MW thermal power plant under operation in India. The entire plant cycle is split up into three zones for<br />

the analysis: (1) only the turbo-generator with its inlets and outlets, (2) turbo-generator, condenser, feed<br />

pumps and the regenerative heaters, (3) the entire cycle with boiler, turbo-generator, condenser, feed<br />

pumps, regenerative heaters and the plant auxiliaries. It helps to find out the contributions <strong>of</strong> different parts<br />

<strong>of</strong> the plant towards exergy destruction. The exergy efficiency is calculated using the operating data from<br />

the plant at different conditions, viz. at different loads, different condenser pressures, with and without<br />

regenerative heaters and with different settings <strong>of</strong> the turbine governing.<br />

Khaliq and Choudhary (<strong>20</strong>07) have studied the combined first and second-law analysis <strong>of</strong> gas turbine<br />

cogeneration system with inlet air cooling and evaporative aftercooling <strong>of</strong> the compressor discharge. They<br />

performed Computational analysis to investigate the effects <strong>of</strong> the overall pressure ratio, turbine inlet<br />

temperature, and ambient relative humidity on the exergy destruction in each component, first-law<br />

efficiency, power-to-heat ratio, and second-law efficiency <strong>of</strong> the cycle. They found that the thermodynamic<br />

analysis indicates that exergy destruction in various components <strong>of</strong> the cogeneration cycle is significantly<br />

affected by overall pressure ratio and turbine inlet temperature, and not at all affected by the ambient<br />

relative humidity. It also indicates that the maximum exergy is destroyed during the combustion process,<br />

which represents over 60% <strong>of</strong> the total exergy destruction in the overall system. Results clearly show that<br />

performance evaluation based on first-law analysis alone is not adequate, and hence, more meaningful<br />

evaluation must include second-law analysis.<br />

79


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Sanjay et al. (<strong>20</strong>07) have performed research work on energy and exergy analysis <strong>of</strong> steam cooled reheat<br />

gas steam combined cycle. This research paper deals with parametric energy and exergy analysis <strong>of</strong> reheat<br />

gas–steam combined cycle using closed-loop-steam-cooling. They have compared the blade cooling<br />

techniques and found that closed-loop-steam-cooling to be superior to air-film cooling. The reheat gas–<br />

steam combined cycle plant with closed-loop-steam-cooling exhibits enhanced thermal efficiency (around<br />

62%) and plant specific work as compared to basic steam–gas combined cycle with air-film cooling as well<br />

as closed-loop-steam cooling.<br />

Butcher and Reddy (<strong>20</strong>07) have studied Second law analysis <strong>of</strong> a waste heat recovery based power<br />

generation system. In this paper the performance <strong>of</strong> a waste heat recovery power generation system based<br />

on second law analysis is investigated for various operating conditions. The temperature pr<strong>of</strong>iles across the<br />

heat recovery steam generator (HRSG), network output, second law efficiency and entropy generation<br />

number are simulated for various operating conditions. The variation in specific heat with exhaust gas<br />

composition and temperature are accounted in the analysis and results. The effect <strong>of</strong> pinch point on the<br />

performance <strong>of</strong> HRSG and on entropy generation rate and second law efficiency are also investigated. The<br />

researchers found that the second law efficiency <strong>of</strong> the HRSG and power generation system decreases with<br />

increasing pinch point. The first and second law efficiency <strong>of</strong> the power generation system varies with<br />

exhaust gas composition and with oxygen content in the gas. The results contribute further information on<br />

the role <strong>of</strong> gas composition, specific heat and pinch point influence on the performance <strong>of</strong> a waste heat<br />

recovery based power generation system based on first and second law <strong>of</strong> thermodynamics.<br />

Ameri et al. (<strong>20</strong>08) have studied the exergy analysis <strong>of</strong> a 4<strong>20</strong>MW combined cycle power plant. Their<br />

objective is to evaluate irreversibility <strong>of</strong> each part <strong>of</strong> Neka CCPP using the exergy analysis. The results<br />

show that the combustion chamber, gas turbine, duct burner and heat recovery steam generator (HRSG) are<br />

the main sources <strong>of</strong> irreversibility representing more than 83% <strong>of</strong> the overall exergy losses. The results<br />

show that the greatest exergy loss in the gas turbine occurs in the combustion chamber due to its high<br />

irreversibility. As the second major exergy loss is in HRSG, the optimization <strong>of</strong> HRSG has an important<br />

role in reducing the exergy loss <strong>of</strong> total combined cycle. In this case, LP-SH has the worst heat transfer<br />

process. The first law efficiency and the exergy efficiency <strong>of</strong> CCPP are calculated. Thermal and exergy<br />

efficiencies <strong>of</strong> Neka CCPP are 47 and 45.5% without duct burner, respectively. The results show that if the<br />

duct burner is added to HRSG, these efficiencies are reduced to 46 and 44%. Nevertheless, the results show<br />

that the CCPP output power increases by 7.38% when the duct burner is used.<br />

Som and Datta (<strong>20</strong>08) have shown the thermodynamic irreversibilities and exergy balance in combustion<br />

processes. The present paper makes a comprehensive review pertaining to fundamental studies on<br />

thermodynamic irreversibility and exergy analysis in the processes <strong>of</strong> combustion <strong>of</strong> gaseous, liquid and<br />

solid fuels. The need for such investigations in the context <strong>of</strong> combustion processes in practice is first<br />

stressed upon and then the various approaches <strong>of</strong> exergy analysis and the results arrived at by different<br />

research workers in the field have been discussed. It has been recognized that, in almost all situations, the<br />

major source <strong>of</strong> irreversibilities is the internal thermal energy exchange associated with high temperature<br />

gradients caused by heat release in combustion reactions. They observed that the primary way <strong>of</strong> keeping<br />

the exergy destruction in a combustion process within a reasonable limit is to reduce the irreversibility in<br />

heat conduction through proper control <strong>of</strong> physical processes and chemical reactions resulting in a high<br />

value <strong>of</strong> flame temperature but lower values <strong>of</strong> temperature gradients within the system. The optimum<br />

operating condition in this context can be determined from the parametric studies on combustion<br />

irreversibilities with operating parameters in different types <strong>of</strong> flames.<br />

Borelli and Junior (<strong>20</strong>08) have studied the exergy-based method for analyzing the composition <strong>of</strong> the<br />

electricity cost generated in gas-fired combined cycle plants. They proposed a method to analyze the<br />

composition <strong>of</strong> the cost <strong>of</strong> electricity is based on the energy conversion processes and the destruction <strong>of</strong> the<br />

exergy through the several thermodynamic processes that comprise a combined cycle power plant.<br />

Aljundi (<strong>20</strong>09) has studied energy and exergy analysis <strong>of</strong> a steam power plant in Jordan. In this study, the<br />

energy and exergy analysis <strong>of</strong> Al-Hussein power plant in Jordan is presented. The researcher has observed<br />

that the energy losses mainly occurred in the condenser where 134 MW is lost to the environment while<br />

80


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

only 13 MW was lost from the boiler system. The percentage ratio <strong>of</strong> the exergy destruction to the total<br />

exergy destruction was found to be maximum in the boiler system (77%) followed by the turbine (13%),<br />

and then the forced draft fan condenser (9%). In addition, the calculated thermal efficiency based on the<br />

lower heating value <strong>of</strong> fuel was 26% while the exergy efficiency <strong>of</strong> the power cycle was 25%.<br />

Horlock (<strong>19</strong>95) based on thermodynamic considerations, outlined developments <strong>of</strong> <strong>19</strong>70s, <strong>19</strong>80s and future<br />

prospects <strong>of</strong> combined-cycle power plants. The main focus was on (i) raising the mean temperature <strong>of</strong> heat<br />

supply; (ii) minimizing the irreversibility within the heat recovery steam generator; (iii) keeping the heat<br />

loss between the two plants as low as possible. The optimum pressure ratio for the combined plant (CR=18)<br />

is less than that for the gas turbine alone (CR=30) although it is still greater than the pressure ratio, which<br />

gives maximum specific work in the higher plant (CR=11). However, the efficiency varies little with r<br />

about the optimum point, and design pressure ratios may be set close to compression ratio for maximum<br />

work with little penalty on overall efficiency.<br />

Najjar and Akyurt (<strong>19</strong>94) reviewed various types <strong>of</strong> combined cycles, including repowering, integrated<br />

gasification and other advanced systems. According to this study: 1). Combined cycles boost power output<br />

and efficiency to levels that are considerably above those <strong>of</strong> steam power plants 2). Repowering, when<br />

converting an existing steam plant to combined cycle, <strong>of</strong>fers savings in capital cost as compared to new<br />

construction 3). Combined cycle, when integrated with coal gasification, holds promise in converting coal<br />

into electric power in an efficient, economical and environmentally acceptable manner 4). The airbottoming<br />

cycle (ABC), chemically recuperated gas turbine, compressed air energy storage (CAES) and<br />

compressed air storage humidification (CASH) are among advanced concepts with promise for combined<br />

cycle applications.<br />

Pilavachi (<strong>20</strong>00) gave an overview <strong>of</strong> power generation with gas turbine and combined heat and power<br />

(CHP) systems and discussed various methods to improve the performance <strong>of</strong> the several types <strong>of</strong> gas<br />

turbine cycles. Heppenstall (<strong>19</strong>98), described and compared several power generation cycles which have<br />

been developed to take advantage <strong>of</strong> the gas turbine's thermodynamic characteristics. Emphasis has been<br />

given to systems involving heat recovery from the gas turbine's exhaust and these include the combined,<br />

Kalina, gas/gas recuperation, steam injection, evaporation and chemical recuperation cycles.<br />

Thermodynamic and economic characteristics <strong>of</strong> the various cycles are considered in order to establish<br />

their relative importance to future power generation markets. The present dominance <strong>of</strong> the combined cycle<br />

as the preferred option for a new plant is thought likely to continue.<br />

Cerri and Sciubba (<strong>19</strong>87) analyzed the combined gas–steam plant, without reheat, from the thermodynamic<br />

point <strong>of</strong> view. In his analysis, he discussed the major parameters that most influence efficiency, and further<br />

reported that combined cycles exhibit a good performance if suitably designed, when the highest gasturbine<br />

temperatures are used.<br />

Butcher and Reddy (<strong>20</strong>07) studied performance <strong>of</strong> a waste heat recovery power generation system based on<br />

second law analysis is investigated for various operating conditions. The temperature pr<strong>of</strong>iles across the<br />

heat recovery steam generator (HRSG), network output, second law efficiency and entropy generation<br />

number are simulated for various operating conditions.<br />

Khaliq and Kaushik (<strong>20</strong>04a) carried an improved second-law analysis <strong>of</strong> the combined power-cycle with<br />

reheat and showed the importance <strong>of</strong> the parameters examined. The analysis has included the exergy<br />

destruction in the components <strong>of</strong> the cycle and an assessment <strong>of</strong> the effects <strong>of</strong> pressure ratio; temperature<br />

ratio and number <strong>of</strong> reheat stages on the cycle performance. The exergy balance or second-law approach<br />

presented facilitates the design and optimization <strong>of</strong> complex cycles by pinpointing and quantifying the<br />

losses. By placing reheat in the expansion process, significant increases in specific power output and<br />

efficiency were obtained. The gains are substantial for one and two reheats, but progressively smaller for<br />

subsequent stages.<br />

γ −1<br />

γ<br />

81


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Khaliq and Kaushik (<strong>20</strong>04b) presented a relatively simple and systematic methodology based on first and<br />

second law for the thermodynamic performance evaluation, <strong>of</strong> combustion gas turbine cogeneration system<br />

with reheat. The analysis <strong>of</strong> a certain case <strong>of</strong> combustion gas turbine cogeneration has proven the<br />

usefulness <strong>of</strong> the presented method for analysing the energetic and exergic performance <strong>of</strong> cogeneration<br />

plant. Reheat expansions gives significant improvement in first- and second-law efficiencies. Since the<br />

selection <strong>of</strong> cogeneration system is a complex decision involving technical as well as economic<br />

considerations. For decision-makers this methodology is useful in obtaining important thermodynamic<br />

information for proper trade-<strong>of</strong>fs in comparison and selection <strong>of</strong> cogeneration systems and one can have<br />

better understanding <strong>of</strong> such systems without getting into mechanical details and component efficiencies.<br />

Polyzakis et al. (<strong>20</strong>08) this work contains an optimization analysis <strong>of</strong> four potential GT cycles, namely<br />

single cycle (SC), intercooled cycle (IC), reheated cycle (RH) and intercooled and reheated cycle (IC/RH).<br />

The optimum gas turbine cycle to operate in a combined cycle power plant came out to be the reheated<br />

cycle. This is due to the high EGT = 911.1 K and steam flow =83.54 kg/s, resulting in the steam cycle<br />

efficiency <strong>of</strong> 36.6% and the overall efficiency <strong>of</strong> 53.5%. It is worth mentioning that a fraction <strong>of</strong> wetness <strong>of</strong><br />

8.0% is much lower than the acceptable limit <strong>of</strong> 13%, which simply means longer life for the installation<br />

.<br />

Korakianitis et al. (<strong>20</strong>05) studied design-point performance characteristics <strong>of</strong> a wide variety <strong>of</strong> combinedcogeneration<br />

power plant, with different amounts <strong>of</strong> supplementary firing, different amounts steam<br />

injection (or no steam injection), different amounts <strong>of</strong> exhaust gas condensation, etc. It was concluded that<br />

the performance <strong>of</strong> these plants is optimized by: (a) maximizing turbine rotor inlet temperature in the gas<br />

turbine; (b) optimizing the gas turbine pressure ratio for gas turbine performance; (c) optimizing steam<br />

turbine boiler pressure; and (d) maximizing steam injection in the gas turbine.<br />

Lugand and Parietti (<strong>19</strong>91)studied combined cycle using combinations <strong>of</strong> a new model GEC Altsthom<br />

MS9001F <strong>20</strong>0MW gas turbine with a single shaft VEGA <strong>20</strong>9E and VEGA<strong>20</strong>9F steam turbine. Following<br />

table shows typical characteristics and performance <strong>of</strong> these cycles.<br />

Table 1: Performance Characteristics <strong>of</strong> 9001E, 9001F Gas turbines<br />

Gas Firing Exhaust gas Exhaust gas Compressor Gross Net efficiency<br />

turbine temperature flow (Kg/s) temperature ratio output (LHV)%<br />

mode (°C)<br />

(°C)<br />

(MW)<br />

9001E 1104 408.6 529 12.1 116.9 33.1<br />

9001F 1260 612.2 583 13.5 212.2 34.1<br />

It is observed that net efficiency <strong>of</strong> VEGA <strong>20</strong>9E plant with 9E gas turbine is 50%. This value is increased<br />

by 2% for a VEGA <strong>20</strong>9F combined with 9F gas turbine.<br />

Table 2: 9F and 9E VEGA Performance Characteristics<br />

<strong>20</strong>9E Two<br />

pressure<br />

<strong>20</strong>9F Two<br />

pressure<br />

Steam turbine inlet Gross output (MW) Net Net<br />

Pressure<br />

(bar)<br />

Temperature(°C) Gas<br />

turbine<br />

Steam<br />

turbine<br />

Total output<br />

(MW)<br />

efficiency<br />

(%)<br />

70/6 510/210 2x115.3 127.1 357.7 352.4 50<br />

100/6 540/<strong>19</strong>0 2x210.1 237.1 657.3 646.4 52<br />

Also, the performance <strong>of</strong> combined cycle coupling 9F gas turbine to VEGA 109F steam turbine with<br />

alternative WHRB arrangements have been evaluated and summarized in the following table.<br />

82


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Simple cycle<br />

one-pressure<br />

Two<br />

pressure<br />

cycle<br />

Enhanced<br />

cycle Twopressure<br />

reheat<br />

Enhanced<br />

cycle Threepressure<br />

reheat<br />

Table 3: VEGA 109F Steam Cycle Option<br />

Steam turbine inlet Gross output (MW) Net Net<br />

Pressure Temp Gas Steam Increase Total output efficiency<br />

(bar) ( °C) Turbine Turbine in Steam<br />

(MW) %<br />

Turbine<br />

Output %<br />

65 540 210.7 106.4 _ 317.1 312.3 50.3<br />

100/6 540/<br />

<strong>19</strong>0<br />

110/30/7 540/<br />

540/<br />

240<br />

110/30/6 540/<br />

540/<br />

235<br />

210.1 117.1 9.94% 327.2 321.7 51.8<br />

210 121 13.72% 331 325.7 52.4<br />

<strong>20</strong>9.7 124 16.54% 333.7 328.3 52.8<br />

Bolland (<strong>19</strong>91) studied alternative measures to improve the efficiency <strong>of</strong> combined gas and steam cycles. A<br />

typical modern dual pressure cycle was chosen as reference and alternative arrangements such as dual<br />

pressure with reheat, triple-pressure cycle, triple pressure with reheat, and dual/triple pressure supercritical<br />

reheat cycles were considered. It is observed that with new V94.3 gas turbine, the combined cycle net<br />

efficiency reaches 55% for triple pressure reheat cycle. Also, based on the combination <strong>of</strong> first law energy<br />

analysis and second law exergy analysis, the thermodynamic performance <strong>of</strong> various cycle arrangements<br />

has been analyzed and summarized in the following table.<br />

Table 4: Cycle performance for V94.3 Gas Turbine<br />

Type <strong>of</strong> cycle V94.3 η cc V94.3 W cc V94.3<br />

V94.3<br />

(%)<br />

(MW)<br />

A HRSG T STACK ( °C)<br />

Dual pressure 53.61 577.3 21.59 88.4<br />

Dual pressure reheat 54.06 582.2 22.70 93.4<br />

Dual pressure with<br />

54.60 588.0 29.79 88.1<br />

supercritical reheat<br />

Triple pressure 54.12 582.8 27.36 75.3<br />

Triple pressure reheat 54.57 587.6 26.88 80.0<br />

Triple pressure with<br />

supercritical reheat<br />

55.03 592.7 33.90 81.3<br />

It is observed that reheat improves the cycle efficiency by 0.2-0.4% compared to non-reheat cycles. The<br />

difference between the dual and triple- pressure cycle is about 0.5-0.6%. From the above table it is<br />

observed that the triple pressure supercritical steam cycle gives the largest efficiency. On the other hand,<br />

the increase in heat transfer area is large compared to the gain in efficiency. There is therefore a need to<br />

study the triple-pressure in great detail.<br />

Bruckner and Emsperger (<strong>19</strong>89) studied the retr<strong>of</strong>itting <strong>of</strong> a conventional steam power plant by adding the<br />

gas turbine, where good fuel efficiency, low power generation cost and reduction in pollutants emissions<br />

are major factors. It has also been expressed that the advantages <strong>of</strong> converting a plant into a combined cycle<br />

unit by adding a topping cycle are:<br />

1. Increase in total plant output, upto 25%<br />

2. Increase in efficiency, by 5%<br />

83


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3. Fuel saving (15-<strong>20</strong>%)<br />

4. Low investment cost for generating power compared to conventional units<br />

5. Low NO x emission<br />

Moreover they also pointed out that conversion <strong>of</strong> conventional plant into combined cycle unit is not just<br />

limited to installation <strong>of</strong> a gas turbine with connecting ducts. Other major alteration and modifications<br />

which are necessary for the combined cycle plant are: Gas turbine bypass, Air ducts, Burner, Fans, Control<br />

system, Boiler design etc.<br />

STIG in to gas turbine for power augmentation represents a combined Brayton and Rankine cycle in which<br />

the exhaust generated steam is introduced ahead <strong>of</strong> the turbine section <strong>of</strong> the gas turbine. Conceptually it is<br />

equivalent to the combined cycle except that the steam is expanded together with the gas in the same<br />

turbine instead <strong>of</strong> in a separate steam turbine. Its advantages can be summarized as below:<br />

1. Better part load efficiency<br />

2. Flexibility <strong>of</strong> operation<br />

3. Reduction <strong>of</strong> flame temperature, which in turn, reduces NO x emission<br />

4. Reduction <strong>of</strong> condenser size<br />

Tuzson (<strong>19</strong>92) has reviewed in detail the historical perspective and advantages <strong>of</strong> STIG plant. Cheng at<br />

international power technology patented a unique cycle combining Rankine and Brayton cycle using steam<br />

injection.<br />

In <strong>19</strong>78 the Japanese government started a national project for energy conservation called the Moonlight<br />

project based on the concept <strong>of</strong> steam injection. The cycle is also termed as integrated gas and steam cycle<br />

(IGSC). Takeya and Yasui (<strong>19</strong>88) have presented the development and performance <strong>of</strong> integration <strong>of</strong><br />

AGTJ-100A twin spool reheat gas turbine with an intercooler and water spray type heat exchanger, coupled<br />

to dual pressure and triple pressure reheat waste heat recovery boiler. It is found that the plant efficiency <strong>of</strong><br />

IGSC is increased upto 54% for reheat system.<br />

Moran (<strong>19</strong>96) has established a design methodology for the Gas turbine cogeneration system. This simple<br />

system is integrated with Regenerator and a HRSG is attached to utilize the waste heat. A 30 MW Gas<br />

turbine is designed on the basis <strong>of</strong> analysis <strong>of</strong> enthalpy and entropy <strong>of</strong> air and gas. Methane has been used<br />

as fuel. Simultaneously, the exergy and energy destruction at different points are also tabulated. The waste<br />

heat from turbine (exhaust gases) has been used to produce steam for other processes. Steam is formed at<br />

<strong>20</strong> bar and 14 kg/s, which is a assumption to design heat recovery steam generator.<br />

Ali (<strong>19</strong>97) has studied simple Gas turbine system with inlet air refrigeration by vapor compression cycle.<br />

Mass flow rate term has been replaced by volumetric flow rate, thus reducing the inlet air temperature<br />

increases the volumetric flow rate. The result shows improvement in terms <strong>of</strong> cycle efficiency and specific<br />

power output.<br />

Kumar and Krishna (<strong>20</strong>06a) studied the characteristics <strong>of</strong> Gas turbine power plant adopting the air-cooling<br />

at intake with alternative regenerative configuration. In this study the performance are examined for the<br />

restricted set <strong>of</strong> operational and design conditions. The study shows that plant efficiency with above<br />

configuration has been improved by 10% as compared to simple cycle. Kumar and Krishna (<strong>20</strong>06b)<br />

performed the second law analysis <strong>of</strong> Gas turbine power plant with Alternative regeneration. This work<br />

deals with thermodynamic analysis <strong>of</strong> a Gas turbine Alternative regeneration system and compares it with<br />

conventional regeneration configuration. The analysis deals with comparison <strong>of</strong> efficiency, work done and<br />

exergy loss. The results shows that, the Alternative regeneration proved to be efficient than the<br />

conventional configuration.<br />

Dock (<strong>19</strong>96) worked out the exergy analysis <strong>of</strong> Gas turbine cogeneration system. The paper examined<br />

performance <strong>of</strong> Gas turbine cogeneration systems well as the exergy destruction in each component in the<br />

system when it is operated at part and full load conditions. In addition, the effect <strong>of</strong> inlet air temperature,<br />

humidity <strong>of</strong> the inlet air, water and steam injection on the performance <strong>of</strong> the system is analyzed.<br />

84


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Yadav (<strong>20</strong>05) analyzed simple gas/steam combined cycle power plant for different type <strong>of</strong> coolants for gas<br />

turbine stage cooling. Steam coolant is bled from heat recovery steam generator. Influence <strong>of</strong> different type<br />

<strong>of</strong> coolant upon the performance <strong>of</strong> topping, bottoming, combined cycle and HRSG as been presented and<br />

analyzed. Specific heats are taken in terms <strong>of</strong> temperature.<br />

Facchini (<strong>20</strong>00) performed the detailed study <strong>of</strong> reheat gas turbine/combined cycle and close loop steam<br />

gas cooled gas turbine. The detailed exergy balance is used in this study to compare the performance <strong>of</strong><br />

plant sections and to understand the margin for potential improvement.<br />

Felster et al. (<strong>20</strong>01) performed study <strong>of</strong> combined cycle with advanced options viz. Compressor air<br />

intercooling, water injection and reheating. Environmental and economic analysis has also been<br />

simultaneously studied. The work shows the validity <strong>of</strong> methods for the development <strong>of</strong> energy system.<br />

Finally, the system has been optimized for economic and better operation.<br />

Sancho-Bastos et al. (<strong>20</strong>05) worked out the simulation <strong>of</strong> cogeneration system. A dynamic model <strong>of</strong> midcapacity<br />

system is developed, including gas turbine and HRSG. The simulations for different demand cases<br />

are performed. In this work, a solution is presented to how a cogeneration system can be controlled to<br />

satisfy transient power, heating and cooling demands. Temporal simulation <strong>of</strong> the cogeneration system<br />

shows that it is possible to meet all the demand with conventional equipments and controls.<br />

Korakianitis (<strong>20</strong>05) performed analysis <strong>of</strong> combined cogeneration power plant with various power and<br />

efficiency enhancement. This work has elaborated the exergy and exergy destruction at different points <strong>of</strong><br />

combined cogeneration plant. General trends <strong>of</strong> parametrically varying the performance enhancing schemes<br />

on efficiency; power output, plant effectiveness and exergy rate has been shown.<br />

Shang et al. (<strong>20</strong>06) studied effect <strong>of</strong> manufacturing tolerances on regenerative exchanger number <strong>of</strong> unit<br />

and entropy generation. This work uses analytical methods to show that the standard deviation in channel<br />

sizes reduce the effective numbers <strong>of</strong> transfer units. Depends on operating condition, entropy generation<br />

number either increases or decreases, which may cause energy destruction at different flow channels. This<br />

work shows that both temperature and pressure affect the entropy generation. In a regenerative exchanger<br />

entropy analysis has been done.<br />

Dellenback (<strong>20</strong>06) studied a reassessment <strong>of</strong> a alternative regenerative cycle. The revised modeling shows<br />

that the alternative regenerative cycle can produce efficiency higher than conventional only for limited set<br />

<strong>of</strong> conditions. This paper optimized the pressure ratio at all points for maximum possible efficiency. The<br />

turbine inlet temperature (TIT) is taken rather higher for current design value to examine the both current<br />

and future feasibility <strong>of</strong> cycle.<br />

Methods <strong>of</strong> Improving Combined-Cycle Performance<br />

The main categories <strong>of</strong> combined-cycles may be classified by (a) the rate <strong>of</strong> excess air utilized, (b) the<br />

number <strong>of</strong> steam pressure levels used in heat recovery, (c) the availability <strong>of</strong> supplemental firing and (d)<br />

the use <strong>of</strong> steam reheat.<br />

Bolland (<strong>19</strong>91) studied alternative arrangements for improving the efficiency <strong>of</strong> the combined-cycle.<br />

These were the dual pressure reheat cycle, the triple-pressure cycle, the triple-pressure reheat cycle, the<br />

dual pressure supercritical reheat cycle and the triple pressure supercritical reheat cycle.<br />

Allen and Triassi (<strong>19</strong>89) investigated the performance <strong>of</strong> heavy-duty and aircraft-derivative gas turbines for<br />

utility and industrial applications, comparing single and two-shaft arrangements as combined cycles. Gerri<br />

and Colage (<strong>19</strong>85) scrutinized the influence <strong>of</strong> steam cycle regeneration on combined plant performance<br />

and demonstrated a positive influence on combined-cycle efficiency for small degrees <strong>of</strong> regeneration.<br />

Rice (<strong>19</strong>80) carried out a critical analysis <strong>of</strong> the reheat gas turbine cycle combined with the steam turbine<br />

Rankine cycle, which arrangement promises to increase power plant thermal efficiency appreciably. He<br />

established the cycle pressure ratio, firing temperature, and output. The results <strong>of</strong> this analysis were applied<br />

85


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

to the reheat LM5000 and the reheat steam cycle. Rice (<strong>19</strong>86) also suggested a method for choosing<br />

optimal values <strong>of</strong> combined-cycle parameters such as pinch point, gas pressure drop, single or dual pressure<br />

and reheat, based on the economical internal rate <strong>of</strong> return.<br />

Figure 2. Integrated gasification combined cycle.<br />

Lugand and Parietti (<strong>19</strong>91) showed that a three-pressure level steam reheat cycle, featuring a <strong>20</strong>0 MW gas<br />

turbine engine with a firing temperature <strong>of</strong> 1260°C, yields plant efficiencies in excess <strong>of</strong> 53%. A parametric<br />

analysis was conducted by Cerri and Sciubba (<strong>19</strong>87) for a plant equipped with a gas generator and with<br />

steam injection into an after-burner placed upstream <strong>of</strong> the power turbine. The steam was to be produced by<br />

a waste-heat recovery section made up <strong>of</strong> a boiler and distillation plant fed by the gas turbine exhaust. The<br />

results showed a 13% improvement in plant efficiency and a doubling <strong>of</strong> the specific work output when<br />

compared with a standard gas turbine cycle with full reheat and optimal steam injection.<br />

A novel heat-recovery process for improving the thermal efficiency <strong>of</strong> a gas turbine in electric power<br />

generation was suggested by Higdon et al. (<strong>19</strong>90). The process uses an air saturation unit to evaporate<br />

heated water (below its boiling point) into the combustion air. The resultant mass flow <strong>of</strong> water vapor<br />

through the rest <strong>of</strong> the system reduces the power required to compress air and permits better utilization <strong>of</strong><br />

the otherwise wasted heat. The authors calculated the efficiency <strong>of</strong> the system to be 54.8%, as compared to<br />

47.9% for an inter-cooled, steam-injected system.<br />

Compressed air energy storage (CAES) emerged as an innovative method <strong>of</strong> meeting peak demand<br />

requirements <strong>of</strong> electric utilities. Excess power produced during low-load periods is utilized to compress air<br />

and store it; the stored energy is then returned to the system during peak-load periods (Lee <strong>19</strong>91).<br />

Gyarmathy (<strong>19</strong>89) studied the relative merits <strong>of</strong> various load control methods involving fixed and variablegeometry<br />

gas turbine compressors. The results implied exceptional merits for compressor guide vane<br />

adjustment, serving to maintain gas turbine exhaust temperature at high levels during part-load operation.<br />

Conclusions<br />

The combined-cycle generation system features high thermal efficiency, low installed cost, fuel flexibility<br />

with a wide range <strong>of</strong> gas and liquid fuels, low operation and maintenance costs, operating flexibility at<br />

base, mid-range and daily start, high reliability and availability, short installation times and high efficiency<br />

in small capacity increments. In particular:<br />

86


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

1. Combined cycles boost power output and efficiency to levels that are considerably above those <strong>of</strong> steam<br />

power plants.<br />

2. Repowering, when converting an existing steam plant to combined cycle, <strong>of</strong>fers savings in capital cost as<br />

compared to new construction.<br />

3. Combined cycle, when integrated with coal gasification, holds promise in converting coal into electric<br />

power in an efficient, economical and environmentally acceptable manner.<br />

4. The air-bottoming cycle (ABC), chemically recuperated gas turbine, compressed air energy storage<br />

(CAES) and compressed air storage humidification (CASH) are among advanced concepts with promise for<br />

combined cycle applications.<br />

Reference:<br />

1. Ali A., <strong>19</strong>97, Optimum power boosting <strong>of</strong> gas turbine cycle with compressor inlet air refrigeration,<br />

Engineering for Gas Turbine and Power, Transaction <strong>of</strong> the ASME, 1<strong>19</strong>, 124-133.<br />

2. Aljundi I. H., <strong>20</strong>09, “Energy and Exergy Analysis <strong>of</strong> a Steam Power Plant in Jordan,” Applied<br />

Thermal Engineering, 29, pp. 324-328.<br />

3. Allen R. P., and Triassi R. P.,<strong>19</strong>89, GE gas turbine performance characteristics, 33rd GE Turbine<br />

State-<strong>of</strong>-the-Art Seminar, Paper No GER 3567.<br />

4. Ameri M., Ahmadi P., and Khanmohammadi S., <strong>20</strong>08, “Exergy Analysis <strong>of</strong> a 4<strong>20</strong> MW Combined<br />

Cycle Power Plant,” International Journal <strong>of</strong> Energy Research, 32, pp. 175-183.<br />

5. Anonymous, <strong>19</strong>91, Low-cost air bottoming cycle for gas turbines, Gas Turbine World, 61.<br />

6. Bolland O., <strong>19</strong>91, A comparative evaluation <strong>of</strong> advanced combined cycle alternatives, Journal <strong>of</strong><br />

Engineering for Gas Turbines and Power, 113, <strong>19</strong>0-<strong>19</strong>7.<br />

7. Borelli S. J. S., and Junior S. D. O., <strong>20</strong>08, “Exergy-Based Method for Analyzing the Composition <strong>of</strong><br />

the Electricity Cost Generated in Gas-Fired Combined Cycle Plants,” Energy, 33, pp. 153-162.<br />

8. Bruckner H., Emsperger W., <strong>19</strong>89, Retr<strong>of</strong>itting fossil fired power plant with gas turbines as a means<br />

<strong>of</strong> increasing output and efficiency, international forum on Mathematical modeling <strong>of</strong> process in<br />

energy systems, Sarajevo, Yugoslavia.<br />

9. Bruno F., Fiaschi D., Manfrida G., <strong>20</strong>00, Exergy analysis <strong>of</strong> combined cycles using latest generation<br />

gas turbines, Engineering for gas turbine and Power, Transaction <strong>of</strong> the ASME, 122, 233-237.<br />

10. Butcher C.J. and Reddy B.V., <strong>20</strong>07, Second law analysis <strong>of</strong> a waste heat recovery based power<br />

generation system, International Journal <strong>of</strong> Heat and Mass Transfer, 50, 2355–2363.<br />

11. Butcher C.J., and Reddy B.V., <strong>20</strong>07, “Second Law Analysis <strong>of</strong> a Waste Heat Recovery Based Power<br />

Generation System,” International Journal <strong>of</strong> Heat and Mass Transfer, 50, PP. 2355-2363.<br />

12. Cerri G. and Sciubba E., <strong>19</strong>87, Aero-derived reheat gas turbines steam injection into the afterburner,<br />

ASME, Advanced Energy Systems Division Publication, AES, 3(3), 7946.<br />

13. Chase D. L., Tomlinson L. O. and Bjorge R. W., <strong>19</strong>89, GE combined cycle product line and<br />

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Engineering for gas turbine and Power, Transaction <strong>of</strong> the ASME 123, 717-726.<br />

21. Gerri G. and Colage A., <strong>19</strong>85, Steam cycle regeneration influence on combined gas-steam power plant<br />

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87


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

23. Gyarmathy G., <strong>19</strong>89, On load control methods for combined cycle plants, ASME Cogen Turbo, 39-50.<br />

24. Harmel L., <strong>19</strong>89, The combined cycle--an economical system for production <strong>of</strong> electricity, ASME<br />

Cogen-Turbo, 357-370.<br />

25. Heppenstall T., <strong>19</strong>98, Advanced gas turbine cycles for power generation: a critical review, Applied<br />

Thermal Engineering, 18, 837-846.<br />

26. Higdon C. R., Loules B. M. and Lynn S., <strong>19</strong>90, A novel heat-recovery process for improving the<br />

thermal efficiency <strong>of</strong> gas turbines in electric power generation, Proc. American Power Conf. 52, 216-.<br />

27. H<strong>of</strong>feins H., Romeyke N. and Hebel D., <strong>19</strong>80, Commissioning the first air-storage gas turbine set,<br />

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28. Horlock J.H., <strong>19</strong>95, Combined power plants present, and future, Joumal <strong>of</strong> Engineering for Gas<br />

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30. Karalis A. J., Sonsnowvics E. J. and Haselbacher H., <strong>19</strong>87, Optimizing the design conditions <strong>of</strong> a<br />

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31. Khaliq A. and Kaushik S.C., <strong>20</strong>04a, Thermodynamic performance evaluation <strong>of</strong> combustion gas<br />

turbine cogeneration system with reheat, Applied Thermal Engineering, 24, 1785–1795.<br />

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Cogeneration System with Inlet Air Cooling and Evaporative Aftercooling <strong>of</strong> the Compressor<br />

Discharge,” ASME Journal <strong>of</strong> Engineering for Gas Turbine and Power, 129, pp. 1004-1011.<br />

34. Korakianitis T., Grantstrom J., Wassingho P. and Massardo A. F., <strong>20</strong>05, Parametric performance <strong>of</strong><br />

combined- cogeneration power plants with various power and efficiency enhancement, Journal <strong>of</strong><br />

Engineering for Gas Turbine and Power, 127, 65-72.<br />

35. Kumar R.N., Krishna R.K., <strong>20</strong>06a, Second law analysis <strong>of</strong> gas turbine power plant with alternative<br />

regeneration, ISHMT.Heat and mass transfer conference, IIT, Guwahati, India, 1813-1818.<br />

36. Kumar R.N., Krishna R.K., <strong>20</strong>06b, Improved gas turbine efficiency using spray coolers and through<br />

Alternative regeneration configuration, ISHMT ASME, Heat and mass transfer conference, 18<strong>19</strong>-1824.<br />

37. Lee D., <strong>19</strong>91, Power to spare: compressed air energy storage, Mechanical Engineering, 67-71.<br />

38. Lugand P. and Parietti C., <strong>19</strong>90, Combined cycle plants with frame 9F gas turbines, Journal <strong>of</strong><br />

Engineering for Gas Turbines and Power, 113, 475-481.<br />

39. Macchi E. and Lozza G., <strong>19</strong>87, A study <strong>of</strong> thermodynamic performance <strong>of</strong> CAES plants, including<br />

unsteady effects, ASME paper no 87-GT-23.<br />

40. Moran M.J., <strong>19</strong>96, Thermal System design and optimization, John Wiley and Sons.<br />

41. Najjar Y.S.H. and Akyurt M., <strong>19</strong>94, Combined cycle with gas turbine engine, Heat Recovery Systems<br />

and CHP, 14, 93-103.<br />

42. Nakhamkin M., Patel M. and Louks B. M., <strong>19</strong>89, Integrated compressed-air energy storage concepts<br />

with utilization <strong>of</strong> coal gasification, ASME, Cogen-Turbo, 379-384.<br />

43. Nakhamkin M., Swensen E. C. and Hanck J. A., <strong>19</strong>89, Site analysis and turbomachinery<br />

characteristics for compressed air energy storage plants for the Pacific Gas and Electric Co, Cogen-<br />

Turbo, 371-377.<br />

44. Nasser A. E. and E1-Kalay M. A., <strong>19</strong>91, A heat recovery cooling system to conserve energy in gasturbine<br />

power stations in the Arabian Gulf, Applied Energy, 38, 133-142.<br />

45. Pilavachi P.A., <strong>20</strong>00, Power generation with gas turbine systems and combined heat and power,<br />

Applied Thermal Engineering, <strong>20</strong>, 1421-1429.<br />

46. Piolenc M. D., <strong>19</strong>91, AEC commissions the nation's first air-energy storage plant, Gas Turbine World,<br />

15-<strong>19</strong>.<br />

47. Piolenc M., Piolenc LES, <strong>19</strong>92, 'iced' inlet nets utility another 14 MW <strong>of</strong> peaking at zero fuel cost, Gas<br />

Turbine World, <strong>20</strong>-25.<br />

48. Polyzakis A.L., Koroneos C. and Xydis G., <strong>20</strong>08, Optimum gas turbine cycle power plant, Energy<br />

Conversion and Management, 49, 551-563.<br />

49. Rice I. G., <strong>19</strong>86, Thermodynamic evaluation <strong>of</strong> gas turbine cogeneration cycles: Part 2---Complex<br />

cycles analysis, ASME Paper No 86-GT-7.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

50. Rice I. G., The combined reheat gas turbine/steam turbine cycle. Part I--A critical analysis <strong>of</strong> the<br />

combined reheat gas turbine/steam turbine cycle, Journal <strong>of</strong> Engineering for Gas Turbines and Power,<br />

102, 35-41.<br />

51. Rufli P., <strong>19</strong>87, A systematic analysis <strong>of</strong> the combined gas-steam cycle, ASME Cogen-Turbo, 135-146.<br />

52. Sancho-Bastos, Perez-Blanco H., <strong>20</strong>05, Cogeneration System Simulation and Control to Meet<br />

Simultaneous Power, Heating, and Cooling Demands, Engineering for gas turbine and Power,<br />

Transaction <strong>of</strong> the ASME, 127, 404-409.<br />

53. Sanjay Y., Singh O., and Prasad B.N., <strong>20</strong>07, “Energy and Exergy Analysis <strong>of</strong> Steam Cooled Reheat<br />

Gas Steam Combined Cycle,” Applied Thermal Engineering, 27, pp. 2779-2790.<br />

54. Sengupta S., Datta A., and Duttagupta S., <strong>20</strong>07, “Exergy Analysis <strong>of</strong> a Coal-Based 210 MW Thermal<br />

Power Plant,” International Journal <strong>of</strong> Energy Research, 31, pp. 14-28.<br />

55. Shang W., Robert W., <strong>20</strong>06, Effect <strong>of</strong> manufacturing tolerances on Regenerative Exchanger Number<br />

<strong>of</strong> Transfer unit and Entropy generation, Engineering for gas turbine and Power, Transaction <strong>of</strong> the<br />

ASME, 128, 585-598.<br />

56. Shoko I., Hiroshi S. and Asako I., <strong>20</strong>05, Conceptual design and cooling blade development <strong>of</strong> 1700 0 C<br />

class high – temperature gas turbine, Journal <strong>of</strong> Engineering for gas turbines and power, 127, 358 –<br />

368.<br />

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Processes,” Progress in Energy and Combustion <strong>Science</strong>s, 34, pp. 351-376.<br />

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cycle with dual pressure HRSG, International Journal <strong>of</strong> Thermal <strong>Science</strong>s, 47 (9), 1226-1234.<br />

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60. Stambler I., <strong>19</strong>92, CEC prods OEMs to get on with new gas turbine cycle designs, Gas Turbine World.<br />

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in aquifer, ASME Paper no 86-GT-73.<br />

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combined cycle gas turbines, Institution <strong>of</strong> engineers Journal-MC, 28-32.<br />

66. Zaugg P., <strong>19</strong>80, Air-storage power plants with special consideration <strong>of</strong> USA conditions, Brown Boceri<br />

Review, 12, 723-733.<br />

89


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

A REVIEW ON PARABOLIC TROUGH TYPE SOLAR COLLECTORS:<br />

INNOVATION, APPLICATIONS AND THERMAL ENERGY STORAGE<br />

Devander Kumar Lamba<br />

Mechanical Engineering Department, TITS Bhiwani, Haryana<br />

e-mail:- lambadev1@rediffmail.com<br />

Abstract<br />

The global demand for energy is growing and conventional energy sources like coal and petroleum are<br />

depleting, and renewable resources will play a crucial role in the future. This paper presents an overview about<br />

the parabolic trough solar collector which is one <strong>of</strong> the renewable source. Parabolic trough collector can supply<br />

the thermal energy up to 400 0 C, mainly in steam power plant for electricity generation. Many applications <strong>of</strong><br />

Parabolic Trough Collector, it’s innovations and thermal energy storage materials has been discussed keeping<br />

in mind the environmental benefits. In India, the states <strong>of</strong> Rajasthan and Gujarat have the potential for<br />

widespread application <strong>of</strong> PTC to harness the solar energy. The launch <strong>of</strong> The Jawaharlal Nehru National Solar<br />

Mission (JNNSM) in <strong>20</strong>08 by the Indian Government and its initiatives, complemented by state solar policy<br />

passed by the states <strong>of</strong> Rajasthan and Gujarat, will go a long way based on deployment <strong>of</strong> both solar PV projects<br />

and solar thermal projects in a ratio <strong>of</strong> 50:50, in MW terms to fulfilling India’s upcoming energy needs.<br />

Keywords: Parabolic Trough Collector (PTC), concentrated solar power (CSP), heat transfer fluid (HTF),<br />

Thermal energy storage<br />

1. Introduction<br />

The global demand for energy is growing and conventional energy sources like coal and petroleum are depleting,<br />

and renewable resources will play a crucial role in the future. A worthy investment option is concentrating solar<br />

power (CSP) technology which has the capacity to provide for about 7% <strong>of</strong> the total electricity needs projected<br />

for the world by <strong>20</strong>30 and 25% by <strong>20</strong>50 (considering a high-energy saving, high-energy-efficiency scenario) [1].<br />

As the world’s supply <strong>of</strong> fossil fuels shrinks, there is a great need for clean and affordable renewable energy<br />

sources in order to meet growing energy demands. Achieving sufficient supplies <strong>of</strong> clean energy for the future is<br />

a great societal challenge. Sunlight, the largest available carbon neutral energy source, provides the Earth with<br />

more energy in1h than is consumed on the plane tin an entire year. Despite <strong>of</strong> this, solar electricity currently<br />

provides only a fraction <strong>of</strong> a percent <strong>of</strong> the world’s power consumption. In any country the energy can be<br />

obtained mainly two resources i.e.Non-renewable and renewable resources. The renewable energy resources<br />

comprise <strong>of</strong> solar, hydro, wind, tidal, geothermal, ocean thermal. Solar energy can be used both directly and<br />

indirectly. Solar radiation is a high-temperature, high-exergy energy source at its origin, the Sun, where its<br />

irradiance is about 63 MW/ m2. However, Sun–Earth geometry dramatically decreases the solar energy flow<br />

down to around 1 kW/m2 on the Earth’s surface [2]. It can be used directly by solar collectors and solar cells.<br />

Solar collectors fall into two general categories: non-concentrating and concentrating. Trough type collector is a<br />

concentrating type collector. In concentrating type, solar energy firstly falls on concentrator, then concentrated<br />

on a receiver, and transferred to the fluid flowing through the receiver. The collector area is different as the<br />

absorber area. Though more costly, concentrating collectors have numerous advantages over stationary<br />

collectors, and are generally associated with higher operation temperatures and greater efficiencies. The addition<br />

<strong>of</strong> an optical device to the conventional solar collector (receiver) has proved useful in several regards; various<br />

concentration schemes can achieve a wide range <strong>of</strong> concentration ratios, from unity to over 10,000 sun [2]. This<br />

increases the operation temperature as well as the amount <strong>of</strong> heat collected in a given area, and yields higher<br />

thermodynamic efficiencies. Radiation focusing allows the usage <strong>of</strong> receivers with very small relative surface<br />

areas, which leads to significant reductions in heat loss by convection. There are many type <strong>of</strong> concentrating<br />

collectors in which PTC is one <strong>of</strong> type.<br />

2. Parabolic Trough Collector (PTC)<br />

The first practical experience with PTCs goes back to 1870, when a successful engineer, John Ericsson, a<br />

Swedish immigrant to the United States, designed and built a 3.25-m2-aperture collector which drove a small<br />

373-W engine. Steam was produced directly inside the solar collector (today called Direct Steam Generation or<br />

DSG).<br />

Parabolic trough technology is the most mature concentrated solar power design. It is currently utilized by<br />

multiple operational large-scale CSP farms around the world. Solar Electric Generating Systems (SEGS) is a<br />

collection <strong>of</strong> fully operational PTC systems located in the California desert with a total capacity <strong>of</strong> 354 MW.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

SEGS is at present the largest PTC power plant in the world. PTC plant with a 280MW capacity is being built in<br />

Arizona and is scheduled to become operational in <strong>20</strong>11. PTCs effectively produce heat at temperatures ranging<br />

from50 to 400 0 C. These temperatures are generally high enough for most industrial heating processes and<br />

applications, the great majority <strong>of</strong> which run below300 0 C. There is a series <strong>of</strong> curved mirrors in each parabolic<br />

trough which are used to concentrate sunlight on to thermally efficient receiver tubes placed in the trough’s focal<br />

line through which synthetic oil, heated to approximately 400 ◦C by the concentrated sun’s rays, is used as a heat<br />

transfer medium ( Fig. 1) [28]. Many parallel rows <strong>of</strong> these solar collectors usually aligned north to south, span<br />

across the solar field. The oil transfers heat from collector pipes to heat exchangers, where water is preheated,<br />

evaporated and then superheated. The superheated steam runs a turbine, which drives a generator to produce<br />

electricity and the water returns to the heat exchangers after being cooled and condensed [3]. With the sunlight<br />

concentrated by about 70–100 times, the operating temperatures achieved are in the range <strong>of</strong> 350–550 ◦C. The<br />

annual solar to electric efficiency is estimated to be 15% [4]. An alternative for the integration <strong>of</strong> a parabolic<br />

trough solar field in a steam turbine power plant is generating steam in the solar field called the direct steam<br />

generation technology[5]. Characteristics <strong>of</strong> the electricity production by stationary parabolic, cylindrical solar<br />

concentrator have been discussed in detail by Boji´c et al. [6]. The first parabolic trough systems were installed<br />

in <strong>19</strong>12 near Cairo (Egypt) [4]. The feasibility analysis <strong>of</strong> constructing parabolic trough solar thermal power<br />

plant in Inner Mongolia <strong>of</strong> China in carried out in a study by Zhao et al. [7] and the result was that the power<br />

plant can indeed be operated with its maximum commercial volume and generate power to grid under the support<br />

<strong>of</strong> the state policy. A more recent study by Yang et al. [8] presents the possibility that Tibet, with enough DNI<br />

resources and large amount <strong>of</strong> wasteland, will be a promising candidate site for the construction <strong>of</strong> Parabolic<br />

Trough Solar Thermal Power Plants in China. Nevada Solar One at Boulder City, NV, USA with a capacity <strong>of</strong><br />

64 MW, developed by Acciona and operated by Solar genix Energy is an addition to the parabolic trough plants<br />

in the year <strong>20</strong>07[9].<br />

Fig.1 Parabolic trough [3]<br />

The parabolic trough collector design features light structures and relatively high efficiency. A PTC system is<br />

composed <strong>of</strong> a sheet <strong>of</strong> reflective material, usually silvered acrylic, which is bent into a parabolic shape. Many<br />

such sheets are put together in series to form long troughs. These modules are supported from the ground by<br />

simple pedestals at both ends. The long, parabolic shaped modules have a linear focus (focal line) along which a<br />

receiver is mounted. The receiver is generally a black metal pipe, encased in a glass pipe to limit heat loss by<br />

convection. The metal tube’s surface is <strong>of</strong>ten covered with a selective coating that features high solar absorbance<br />

and low thermal emittance. The glass tube itself is typically coated with antireflective coating to enhance<br />

transmissivity. A vacuum can be applied in the space between the glass and the metal pipes to further minimize<br />

heat loss and thus boost the system’s efficiency.<br />

The heat transfer fluid (HTF) flows through the receiver, collecting and transporting thermal energy to electricity<br />

generation systems (usually boiler and turbine generator) or to storage facilities. The HTF in PTC systems is<br />

usually water or oil, where oil is generally preferred due to its higher boiling point and relatively low volatility.<br />

The Jawaharlal Nehru National Solar Mission in Rajasthan(India) is partially solar thermal project which means<br />

that it uses sunlight through concentrated solar power technology (based on either line focus or point focus<br />

principle) for conversion into heat/steam which can be used for producing electricity.<br />

The DISS (Direct Solar Steam) project PTC plant in Tabernas, Spain, is a leading DSG test facility, where two<br />

successful DSG operational modes and control systems were developed and tested[10]. Both methods utilize<br />

pressure control in addition to temperature control <strong>of</strong> circulating water. This approach is done to achieve a<br />

constant output <strong>of</strong> steam at a monitored temperature throughout most hours <strong>of</strong> the day (9am–6pm). A pressure<br />

91


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

level <strong>of</strong> 100bar and temperatures <strong>of</strong> up to 400 0 C have been demonstrated. The Once Through mode features a<br />

preheated water feed into the inlet. As water circulates through the collectors, it is evaporated and converted into<br />

superheated steam that is used to power a turbine. In the more water-conservative Recirculation mode, a water–<br />

steam separator is placed at the end <strong>of</strong> the collector loop. More water is fed to the evaporator than can be<br />

evaporated in one circulation cycle. Excess water is re-circulated through the intermediate separator to the<br />

collector loop inlet, where it is mixed with preheated water. This process guarantees good wetting <strong>of</strong> absorber<br />

tubes and prevents stratification. Steam is separated from water and fed into the inlet <strong>of</strong> a superheating section.<br />

The Recirculation regime is more easily controlled than the Once-through regime, but has an increased parasitic<br />

load due to the additional process steps. Usage <strong>of</strong> water as a HTF inflicts more stress on the absorber tubes than<br />

other heat transfer media, due to water’s relatively high volatility.<br />

In contrast with the DSG scheme, which employs water as the HTF, recent innovation also promotes the use <strong>of</strong><br />

ionic liquids (molten salts) for heat transfer media[11], as they are more heat-resilient than oil, and thus corrode<br />

the receiver pipes less. Ionic liquids are, however, very costly, and such an investment would have to be weighed<br />

against the incurring costs <strong>of</strong> receiver maintenance and replacement to determine their cost-effectiveness.<br />

PTCs are mounted on a single-axis sun-tracking system that keeps incident light rays parallel to their reflective<br />

surface and focused on the receiver throughout the day. Both east–west and north–south tracking orientations<br />

have been implemented, with the former collecting more thermal energy annually, and the latter collecting more<br />

energy in the summer months when energy consumption is generally the highest[12]. The east–west orientation<br />

has been reported to be generally superior [13].<br />

In order to make the PTC structure more resilient to external forces, it is possible to reinforce collector surfaces<br />

with a thin fiberglass layer. A smooth, 90 0 rim angle reinforced trough was built by a hand lay-up method [14].<br />

The fiber glass layer is added underneath the reflective coating (on the inner surface) <strong>of</strong> the parabolic trough. The<br />

reflector’s total thickness is 7mm, and can with stand a force applied by a 34m/s wind with minimal deviation;<br />

deflection at the center <strong>of</strong> the parabola vertex was only 0.95mm, well within acceptable limits.<br />

3. Applications<br />

PTC applications can be divided into two main groups. The first and most important is Concentrated Solar Power<br />

(CSP) plants. Typical aperture widths are about 6 m, total lengths are from 100 to 150 m and geometrical<br />

concentrating ratios are between <strong>20</strong> and 30. Temperatures are from 300 to 400 0 C [15]. CSP plants with PTCs are<br />

connected to steam power cycles both directly and indirectly. Although the most famous example <strong>of</strong> CSP plants<br />

is the SEGS plants in the United States, a number <strong>of</strong> projects are currently under development or construction<br />

worldwide. The other group <strong>of</strong> applications requires temperatures between 100 and 250 0 C. These applications<br />

are mainly industrial process heat (IPH), low-temperature heat demand with high consumption rates (domestic<br />

hot water, DHW, space heating and swimming pool heating) and heat-driven refrigeration and cooling. Typical<br />

aperture widths are between 1 and 3 m, total lengths vary between 2 and 10 m and geometrical concentrating<br />

ratios are between 15 and <strong>20</strong>. Most <strong>of</strong> the facilities are located in the United States, although some have recently<br />

been built in other countries. There are also some projects and facilities for other applications such as pumping<br />

irrigation water, desalination and detoxification.<br />

3.1. CSP plants<br />

Appropriate site locations for CSP plants in the world include the North African Desert, the Arabian Peninsula,<br />

major portions <strong>of</strong> India, central and western Australia, the high plateaus <strong>of</strong> the Andean states, northeastern<br />

Brazil, northern Mexico and, <strong>of</strong> course, the United States Southwest. Promising site locations in Europe are<br />

found in southern Spain and several Mediterranean islands [16]. All commercial CSP plants are north–south<br />

oriented, because this maximizes the amount <strong>of</strong> power produced along the year. The higher the latitude, the more<br />

necessary this becomes.<br />

There are two ways to integrate a PTC solar field in a steam turbine power plant, directly, that is, generating<br />

steam in the solar field (DSG technology), or indirectly, by heating thermal oil in the solar field and using it to<br />

generate steam in a heat exchanger (HTF technology). In both cases, solar fields can drive all types <strong>of</strong> steam<br />

turbine power plant cycles. Another interesting option is incorporation <strong>of</strong> a solar system in a combined cycle<br />

(CC), called Integrated Solar Combined-Cycle System (ISCCS), in which two different thermodynamic cycles, a<br />

steam-turbine Rankine cycle and gas-turbine Brayton cycle, are combined in a single system through a Heat<br />

Recovery Steam Generator (HRSG). The general concept is an oversized steam turbine, using solar heat for<br />

steam generation and gas turbine waste heat for preheating and superheating steam [17]. Fig.2 shows SSPS<br />

(small solar power system) based on PTC in spain.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig.2. SSPS (small solar power system)/DCS<br />

(distributed collector system) plant at the PSA(Spain) [18,<strong>19</strong>].<br />

3.2 Industrial process heat (IHP)<br />

The key sectors are food and beverages including wine, textile, transport equipment, metal and plastic treatment,<br />

and chemicals. And the most suitable processes are cleaning, drying, evaporation and distillation, blanching,<br />

pasteurisation, sterilisation, cooking, melting, painting, and surface treatment [<strong>20</strong>]. Of the total energy used by<br />

industry, a major portion, approx.45–65%, is used for direct application <strong>of</strong> industrial process heat in the<br />

preparation and treatment <strong>of</strong> goods. The thermal energy demand for IPH is below 300 8C, and 37.2% <strong>of</strong> the total<br />

IPH demand is in the range <strong>of</strong> 92–<strong>20</strong>4 8C [21]. According to the ECOHEATCOOL study done in 32 countries, 3<br />

27% <strong>of</strong> the thermal energy demand for IPH is between 100–400 0 C [22]. For that reason, one <strong>of</strong> the most<br />

important applications <strong>of</strong> a small-sized PTC is IPH.<br />

3.3 Domestic hot water and space heating<br />

One <strong>of</strong> the most widespread applications <strong>of</strong> solar thermal energy is hot water production. According to an IEA<br />

report for <strong>20</strong>06, solar thermal collector capacity in operation worldwide was about 127.8 GWth (182.5 million<br />

m2), most <strong>of</strong> it domestic, both for DHW (kitchen, shower, laundry and sanitation facilities) and space heating<br />

[23]. The temperatures at which energy is required by these applications are below 100 0 C. Therefore,<br />

conventional solar collectors with suitable efficiencies (FPC, CPC or evacuated tube collectors) could be<br />

employed. However, when a large amount <strong>of</strong> hot water is demanded, a large collection area, which sometimes<br />

becomes excessive, must be installed. In this case, PTCs might be <strong>of</strong> interest, because they supply thermal<br />

energy at higher temperatures than those required by the load and, therefore, higher demands can be covered by<br />

mixing the hot solar fluid with another cooler. Examples <strong>of</strong> applications with high hot water consumption rates<br />

are large swimming-pool heating systems, and DHW and space heating for large buildings, such as industrial<br />

buildings, factories, hospitals, educational centres, sport facilities, government buildings, prisons, airports, bus<br />

and train stations, etc. In most situations, a minimum hot water consumption <strong>of</strong> about <strong>19</strong>00 l/day would be<br />

needed to make a PTC system, which is more effective for large, 7-day-a-week hot water users, to be feasible<br />

[24].<br />

The advantages <strong>of</strong> PTCs over the solar collectors traditionally used in water heating facilities are their lower<br />

thermal losses and, therefore, higher efficiency at the higher working temperatures reached, smaller collecting<br />

surface for a given power requirement, and no risk <strong>of</strong> reaching dangerous stagnation temperatures, since in that<br />

case, a control system sends the collectors into <strong>of</strong>f-focus position. The disadvantages <strong>of</strong> PTCs are that its solartracking<br />

system increases installation and maintenance costs, and the need to clean their components also<br />

increases maintenance costs.<br />

3.4 Air-conditioning and refrigeration<br />

PTC facilities connected to high-consumption water-heating systems The Coefficient <strong>of</strong> Performance (COP) is<br />

higher for a LiBr–H 2 O double-effect than for a single-effect absorption chiller, but it requires thermal energy at<br />

temperatures <strong>of</strong> 140–160 0 C [25], at which performance <strong>of</strong> conventional collectors is not good enough. As PTCs<br />

are highly efficient at these temperatures, the combination <strong>of</strong> these two systems is <strong>of</strong> great interest. Connection<br />

<strong>of</strong> NH3– H 2 O absorption chillers to a solar system requires solar collectors able to work efficiently at<br />

temperatures above 95 0 C, such as the PTCs or high-efficiency stationary collectors. Air-conditioning and<br />

refrigeration facilities driven by a PTC solar field are still infrequent. However, several test facilities using this<br />

technology have appeared in the literature during the last 50 years.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3.5 Pumping irrigation water<br />

To make use <strong>of</strong> PTCs for pumping irrigation water, the thermal energy Although pumping irrigation water is not<br />

the most frequent application <strong>of</strong> PTCs, there are several examples <strong>of</strong> this kind <strong>of</strong> facility produced by the solar<br />

field must be converted into mechanical energy for driving the water pump. This application is <strong>of</strong> special interest<br />

in isolated zones and rural areas, where the grid is far away and fuel transport is economically restrictive.<br />

On an experimental level, a 1-kW water pump was installed and assessed at the UNAM in <strong>19</strong>76. The pump was<br />

driven by a 12-m2 PTC field with DSG in the absorber tube. Unfortunately, solar system global efficiency was<br />

found to be only 2%. This poor result led to a new project, without satisfactory improvement. A feasibility study<br />

conducted by the <strong>University</strong> <strong>of</strong> Arizona(United States) in <strong>19</strong>75–<strong>19</strong>76 found that lower cost, improved solar<br />

devices, improved energy use management and availability <strong>of</strong> modestly priced capital were the key engineering<br />

and economic factors preventing successful marketing and use <strong>of</strong> solar-powered pumping plants.<br />

3.6 Desalination<br />

The problem <strong>of</strong> an adequate potable water supply may well become one <strong>of</strong> the most serious challenges facing the<br />

world in this century. Solar desalination is one <strong>of</strong> the most promising technologies for confronting this problem.<br />

The PTC’s suitability for solar desalination has been studied in several different types <strong>of</strong> desalination, such as<br />

Reverse Osmosis (RO), Multi-Effect Distillation (MED) and Multi-Stage Flash (MSF). A few commercial or<br />

pilot plants were implemented.<br />

3.7 Solar chemistry<br />

The widespread presence <strong>of</strong> hazardous organic chemical compounds, mainly in water but also in air, has<br />

motivated interest in finding alternative environmentally friendly solutions for the treatment and/or removal <strong>of</strong><br />

these compounds. Concentrated solar energy augments the detoxification process, because more high-energy<br />

photons are projected directly into the stream <strong>of</strong> water or air. Consequently, there are several examples <strong>of</strong> solar<br />

detoxification using a solar concentrating system. When the solar concentrating system selected is a PTC, a<br />

transparent tube (usually glass) is placed in the focal line <strong>of</strong> the reflector instead <strong>of</strong> the metal absorber tube, as<br />

photo-reactor.<br />

4. Innovations<br />

The new receiver design features porous inclusions inside the tube, which increase the total heat transfer area <strong>of</strong><br />

the receiver, along with its thermal conductivity and the turbulence <strong>of</strong> the circulating HTF (synthetic oil). Heat<br />

transfer for this scheme was enhanced by 17.5% compared with regular (no inclusions) design, but the system<br />

suffered a pressure decrease <strong>of</strong> about 2 kPa.<br />

The integration <strong>of</strong> a parabolic trough collector field with geothermal sources has been suggested by Lentz and<br />

Almanza [25,26]. Hot water and steam from geothermal wells can be directly fed into an absorber pipe going<br />

through a PTC field. The combination <strong>of</strong> both thermal energy sources increases the volume and the quality <strong>of</strong><br />

(directly) generated steam for power production. Several hybrid designs have been suggested by the authors.<br />

PTCs can also be integrated with solar cells in concentrated photovoltaics (CPV) modules. Heat-resistant, highefficiency<br />

photovoltaic cells can be mounted along the bottom <strong>of</strong> the receiver tube to absorb the concentrated<br />

solar flux. The performance <strong>of</strong> a CPV parabolic trough system with a 37 sun concentration ratio was<br />

characterized by Coventry [27] at Australian National <strong>University</strong> in <strong>20</strong>03. Monocrystalline silicon solar cells<br />

were used, along with the thermal PTC apparatus. Measured electrical and thermal efficiencies were 11% and<br />

58%, respectively, producing a total efficiency <strong>of</strong> 69%. It is important to note that uneven illumination <strong>of</strong> the<br />

solar cell modules causes a direct decrease in the cells’ performance, and thus optical considerations must be<br />

weighed carefully.<br />

5. Thermal Energy Storage<br />

A significant complication with the utilization <strong>of</strong> solar thermal power as a primary source <strong>of</strong> energy is the<br />

variable supply <strong>of</strong> solar flux throughout the day, as well as throughout the year. The cyclical availability <strong>of</strong> solar<br />

energy determines two types <strong>of</strong> thermal storage are necessary for maintaining a constant supply <strong>of</strong> solar thermal<br />

power driven electricity. The first is short-term storage, where excess energy harvested daily is stored for<br />

nighttime usage. The second is long-term storage in which excess energy is stored during spring and summer<br />

months in order to complement the smaller energy flux available in winter.<br />

Thermal energy storage can be divided into three main categories: sensible heat storage, latent heat storage and<br />

chemical storage. Sensible heat storage involves heating a solid or liquid and insulating it form the environment<br />

until the stored thermal energy is ready to be used. Latent heat storage involves the phase change (generally<br />

94


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

solid–liquid) <strong>of</strong> the storage material. The heat- induced phase change stores a great deal <strong>of</strong> thermal energy while<br />

maintaining a constant temperature, and can be easily utilized for nighttime energy storage if kept under proper<br />

isolation. Chemical storage is implemented using harvested thermal energy in reversible synthesis/de-synthesis<br />

endothermic reactions. The heat ‘invested’ in producing/dissociating a certain material (ammonia, methane, etc.)<br />

can be easily stored indefinitely. The reverse, exothermic reaction will release the heat with minimal losses for<br />

electricity generation at a later time. Chemical storage is thus most suitable for long-term or seasonal storage.<br />

Sensible heat storage can employ a large variety <strong>of</strong> solid and liquid materials. It can be put into practice in a<br />

direct or indirect manner. For storage in solids such as reinforced concrete, solid NaCl and silica fire bricks, an<br />

indirect storage method must be implemented. This type <strong>of</strong> system uses a heat transfer fluid to circulate through<br />

absorbers, collect heat and transport it to the storage tank. The HTF is then put in thermal contact with the<br />

storage solids, allowing them to absorb the heat convectively. Sensible heat storage in liquids can be achieved in<br />

a direct fashion, i.e. the heat storage liquids themselves are used as heat transfer fluids, and are transported to an<br />

insulating storage tank after circulating through the solar absorbers. Mineral oil, synthetic oil, silicone oil, nitrate,<br />

nitrite and carbonate salts, as well as liquid sodium, can all be used for sensible heat storage. Desired<br />

characteristics <strong>of</strong> ‘sensible-heat-storage-friendly’ molten salts include high density, low vapor pressure, moderate<br />

specific heat, low chemical reactivity and low cost. One big disadvantage <strong>of</strong> molten salts is that they are usually<br />

quite pricey. Detailed characteristics <strong>of</strong> storage materials (Table5 a-d) are given by Gil et al.[26].<br />

Table 5 a–d. Various thermal storage materials and their properties. Data compiled from [26].<br />

(a) Sensible heat storage liquid materials and their properties<br />

Storage<br />

medium<br />

HIETC<br />

HIETC<br />

solar<br />

salt<br />

Mineral<br />

oil<br />

Synthetic<br />

oil<br />

Silicone<br />

oil<br />

Temp.<br />

(cold)(1C)<br />

Temp.<br />

(hot)(1C)<br />

Avg.<br />

density(kg/m3)<br />

Avg. thermal<br />

conductivity<br />

(W/m K)<br />

Avg. heat<br />

capacity (kJ/kg<br />

K)<br />

Volume<br />

specific heat<br />

capacity<br />

(kWh/m3)<br />

Cost per kWh<br />

(US$/kWh)<br />

Nitrite<br />

salts<br />

Nitrate<br />

salts<br />

Carbonate<br />

salts<br />

Liquid<br />

sodium<br />

1<strong>20</strong> <strong>20</strong>0 250 300 250 265 450 270<br />

133 300 350 400 450 565 850 530<br />

n/a 770 900 900 1825 1870 2100 850<br />

n/a 0.12 0.11 0.10 0.57 0.52 2.0 71.0<br />

n/a 2.6 2.3 2.1 1.5 1.6 1.8 1.3<br />

n/a 55 57 52 152 250 430 80<br />

n/a 4.2 43.0 80 12.0 3.7 11.0 21.0<br />

(b) Sensible heat storage solid materials and their properties<br />

Storage<br />

HIETC<br />

medium<br />

Sandrock<br />

Mineral<br />

Oil<br />

Reinforced<br />

Concrete<br />

NaCl<br />

(Solid)<br />

Cast<br />

Iron<br />

Cast<br />

Steel<br />

Silica<br />

Fire<br />

Bricks<br />

Temp. (cold)(1C) <strong>20</strong>0 <strong>20</strong>0 <strong>20</strong>0 <strong>20</strong>0 <strong>20</strong>0 <strong>20</strong>0 <strong>20</strong>0<br />

Temp. (hot)(1C) 300 400 500 400 700 700 1<strong>20</strong>0<br />

Avg.<br />

1700 2<strong>20</strong>0 2160 7<strong>20</strong>0 7800 18<strong>20</strong> 3000<br />

density(kg/m3)<br />

Avg. thermal 1.0 1.5 7.0 37.0 40.0 1.5 5.0<br />

conductivity<br />

(W/m K)<br />

Magnesia<br />

Fire Bricks<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Avg. heat<br />

capacity (kJ/kg<br />

K)<br />

Volume specific<br />

heat capacity<br />

(kWh/m3)<br />

Cost per kWh<br />

(US$/kWh)<br />

1.30 0.85 0.85 0.56 0.60 1.00 1.15<br />

60 100 150 160 450 150 600<br />

4.2 1.0 1.5 60.0 60.0 7.0 6.0<br />

(c)Commercial phase change materials (PCMs) and their properties<br />

Name Type Phasechange<br />

temp. (C)<br />

Density<br />

(kg/m3)<br />

Specific<br />

heat (kJ/kg<br />

K)<br />

Thermal<br />

conductivity<br />

(W/m K)<br />

RT110 Paraffin 112 n/a n/a n/a 213<br />

E117 Inorganic 117 1450 2.61 0.70 169<br />

A164 Organic 164 1500 n/a n/a 306<br />

(c)Inorganic substances with potential use as phase change materials<br />

Latent heat<br />

(kJ/kg)<br />

Compound<br />

Phasechange<br />

temp. (C)<br />

Density<br />

(kg/m3)<br />

MgCl2-6H2O 115-117 1450(liquid,<br />

1<strong>20</strong> 0 C)<br />

1570(solid,<strong>20</strong> 0<br />

C)<br />

Specific<br />

heat<br />

(kJ/kg<br />

K)<br />

Thermal<br />

conductivity (W/m<br />

K)<br />

n/a 0.570(liquid,1<strong>20</strong> 0<br />

C) 0.598(liquid,<br />

140 0 C)<br />

0.694(solid,90 0<br />

C)0.707(solid,110 0<br />

C)<br />

Latent<br />

(kJ/kg)<br />

Hitec: KNO3– 1<strong>20</strong> n/a n/a n/a n/a<br />

NaNO2–NaNO3<br />

Hitec<br />

130 n/a n/a n/a n/a<br />

XL:48%Ca(NO3)2–<br />

45%KNO3–<br />

7%NaNO3<br />

Mg(NO3)–2H2O 130 n/a n/a n/a n/a<br />

KNO3–NaNO2– 132 n/a n/a n/a 275<br />

NaNO3<br />

68% KNO3–32% 133 n/a n/a n/a n/a<br />

LiNO3<br />

KNO3–NaNO2– 141 n/a n/a n/a 75<br />

NaNO3<br />

Isomalt 147 n/a n/a n/a 275<br />

LiNO3–NaNO3 <strong>19</strong>5 n/a n/a n/a 252<br />

40%KNO3– 2<strong>20</strong> n/a n/a n/a n/a<br />

60%NaNO3<br />

54%KNO3– 2<strong>20</strong> n/a n/a n/a n/a<br />

46%NaNO3<br />

NaNO3 307 2260 n/a 0.5 174<br />

KNO3/KCl 3<strong>20</strong> 2100 1.21 0.5 74<br />

KNO3 333-336 2.11 n/a 0.5 266<br />

KOH 380 2.044 n/a 0.5 149.7<br />

MgCl2/KCl/NaCl 380 1800 0.96 n/a 400<br />

AlSi12 576 2700 1.038 160 560<br />

AlSi<strong>20</strong> 585 n/a n/a n/a 460<br />

MgCl2 714 2140 n/a n/a 452<br />

80.5% LiF–<br />

<strong>19</strong>.5%CaF2 eutetic<br />

165<br />

767 2100 1.97 1.7 790<br />

heat<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

NaCl 800-802 2160 n/a 5.0 492<br />

NaCO3–<br />

500-850 2600 n/a 5.0 n/a<br />

BaCO3/MgO<br />

LiF 850 n/a n/a n/a 1800(MJ/m 3 )<br />

Na2CO3 854 2533 n/a 2.0 275.7<br />

KF 857 2370 n/a n/a 452<br />

K2CO3 897 2290 n/a 2.0 235.8<br />

KNO3/NaNO3<br />

eutetic<br />

n/a n/a n/a 0.8 94.25<br />

(d)Organic substances with potential use as phase change materials<br />

Compound Phasechange temp. ( 0 C) Latent heat (kJ/kg) Latent heat (kJ/L)<br />

Isomalt: ((C 12 H 24 O 11 –2H 2 147 275 n/a<br />

O)+( C 12 H 24 O 11 ))<br />

Adipic acid 152 247 n/a<br />

Dimethylol propionic acid 153 275 n/a<br />

Pentaerythritol 187 255 n/a<br />

AMPL<br />

112 28.5 2991.4<br />

((NH2)(CH3)C(CH2OH)2)<br />

TRIS ((NH2)C(CH2OH)3) 172 27.6 3340(KJ/kmol)<br />

NPG<br />

126 44.3 4602.4(KJ/kmol)<br />

((CH3)2C(CH2OH)2)<br />

PE (C(CH2OH)4) 260 36.9 50<strong>20</strong>(KJ/kmol)<br />

Latent heat storage in the solid–liquid phase transition <strong>of</strong> materials is considered a good alternative for sensible<br />

heat storage. From an energy perspective, storage using phase change materials (PCM) can operate in relatively<br />

narrow temperature ranges between charging and discharging thermal energy. Additionally, PCM materials<br />

generally feature higher densities than sensible heat storage materials. The interest in PCM latent heat storage<br />

systems is increasing, mainly due to potential improvements in energy efficiency and nearly isothermal energy<br />

storage and release. In addition to the few commercially available PCMs today, many organic and inorganic<br />

compounds are being investigated for latent heat storage purposes. A disadvantage <strong>of</strong> PCMs is their low thermal<br />

conductivity, which results in slow charge–discharge rates. One suggested initiative for all aviating this problem<br />

involves the fabrication <strong>of</strong> PCM composite materials; mixing pure PCMs with graphite, for example, can boost<br />

thermal conductivity and promote faster energy storing and releasing. Since sensible and latent thermal energy<br />

storage schemes can only retain their energy efficiently for so long, the need for long- term, cross-seasonal<br />

storage is made possible by thermo-chemical storage processes. Thermal energy storage in heat intensive<br />

endothermic reactions has the possibility to realize higher energy efficient processes the thermal storage regimes.<br />

Potentially high energy densities can be stored using chemical storage. Reformation <strong>of</strong> methane and CO2 ,<br />

metal–oxide/metal conversions and ammonia synthesis/dissociation are just a few examples <strong>of</strong> heat-assisted<br />

chemical reactions that can store solar thermal energy in their endothermic reaction products and release it at a<br />

later time/place by the reverse process. Every storage method mentioned can play an important role in several<br />

concentrated solar power designs [27].<br />

6. Conclusion<br />

In light <strong>of</strong> the necessity to tackle climate change, energy produced from renewable sources is gaining<br />

importance. Solar thermal technologies with promising low carbon emissions will play an important role in<br />

global energy supply in the future. A number <strong>of</strong> projects being developed in countries including USA, Spain,<br />

India, Egypt, Morocco, and Mexico are expected to total 15 GW. Numerous countries including India have taken<br />

up the opportunity to harvest the solar resource. Projects based on PTC have the potential for power generation<br />

sources in the near future. World governments are actively announcing incentives for development <strong>of</strong> solar<br />

thermal power plants and establishing policy frameworks. The launch <strong>of</strong> The JNNSM by MNRE, Government <strong>of</strong><br />

India is the first step in the promotion and establishment <strong>of</strong> solar energy as a viable alternative to conventional<br />

sources.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

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Energy 78 (2), 301–311.<br />

[11] M.E. VAN VALKENBURG, et al., <strong>20</strong>05, Thermochemistry <strong>of</strong> ionic liquid heat-transfer fluids,<br />

Thermochimica Acta, 425 (1–2) 181–188.<br />

[12] S.A. KALOGIROU, <strong>20</strong>04, Solar thermal collectors and applications, Progress in Energy and Combustion<br />

<strong>Science</strong> 30 (3) 231–295.<br />

[13] S.A. KALOGIROU, <strong>20</strong>02, Parabolic trough collectors for industrial process heat in Cyprus, Energy 27 (9)<br />

813–830.<br />

[14] A.V. ARASU, T. SORNAKUMAR, <strong>20</strong>07, Design, manufacture and testing <strong>of</strong> fiberglass reinforced<br />

parabola trough for parabolic trough solar collectors, Solar Energy 81 (10): 1273–1279.<br />

[15]A. FERNA´ NDEZ-GARCI´A A, E. ZARZA A, L. VALENZUELA A, M. PE´ REZ, <strong>20</strong>10, Parabolic-trough<br />

solar collectors and their applications” Renewable and Sustainable Energy Reviews 14, 1695–1721<br />

[16] NAVA P, ARINGHOFF R, SVOBODA P, KEARNEY D., <strong>19</strong>96, Status rep on solar trough power plants.<br />

Tech. Rep. Cologne: Pilkington.<br />

[17] PRICE H, KEARNEY D., <strong>20</strong>03, Reducing the cost <strong>of</strong> energy from parabolic trough solar power plants.<br />

Tech. Rep. No. NREL/CP-550-33<strong>20</strong>8. Golden: NREL.<br />

[18] SCHRAUB FA, DEHNE H., <strong>19</strong>83, Electric generation system design: management, startup, and operation<br />

<strong>of</strong> IEA Distributed Collector Solar system in Almerı´a, Spain. Sol Energy, 3(4):351–5.<br />

[<strong>19</strong>] Solar Thermal <strong>Technology</strong>. Annual technical Progress Rep FY <strong>19</strong>81. Volume II: Technical. Tech. Rep. No.<br />

DOE/JPL-1060-53. Pasadena: Jet Propulsion Laboratory for the DOE.<br />

[<strong>20</strong>] VANNONI C, BATTISTI R, DRIGO S. Potential for solar heat in industrial processes, <strong>20</strong>08, Technical<br />

Rep. No. IEA SHC-Task 33 and SolarPACES-Task IV. Madrid: IEACIEMAT.<br />

[21] THOMAS A. <strong>19</strong>92, Operation and performance <strong>of</strong> the solar steam generation system installed at the<br />

government silk factory, Mysore. Energy Convers Manag, 33(3):<strong>19</strong>1–6.<br />

[22] WERNER S, CONSTANTINESKU N. <strong>20</strong>06, ECOHEATCOOL, The European heat market, work package<br />

1. Final Rep. Brussels: Euroheat & Power.<br />

[23] WEISS W, BERGMANN I, FANINGER G. <strong>20</strong>08, Solar heat worldwide—markets and contribution to the<br />

energy supply <strong>20</strong>06. In: IEA. Gleisdorf: AEE INTEC.<br />

[24] COLLINS T, PARKER SA. <strong>20</strong>00, Parabolic-trough solar water heating, renewable technology for<br />

reducingwater-heating costs. Federal <strong>Technology</strong> Alert. Tech. Rep. No. DOE/GO-10<strong>20</strong>00-0973. Washington:<br />

DOE.<br />

[25] HENNING HM. <strong>20</strong>07, Solar assisted air conditioning <strong>of</strong> buildings—an overview. Appl Therm Engg.,<br />

27:1734–816.<br />

[26]GIL. A.,et. al., <strong>20</strong>10, State<strong>of</strong>theartonhightemperaturethermalenergystoragefor power generation. Part1—<br />

concepts, materials and modellization, Renew able and Sustainable Energy Reviews 14(1) 31–55.<br />

98


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[27] DAVID BARLEV A,C, RuxandraVidu b,c, PieterStroeve, <strong>20</strong>11, Innovation in concentrated solar power,<br />

Solar Energy Materials & Solar Cells, 95, 2703–2725<br />

[28]AMITA UMMADISINGUA, M.S. SONIB, <strong>20</strong>11, Concentrating solar power – <strong>Technology</strong>, potential and<br />

policy in India, Renewable and Sustainable Energy Reviews, 15, 5169– 5175.<br />

99


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

STUDY OF FLOW & HEAT TRANSFER IN PLATE FIN HEAT<br />

EXCHANGER AT VARYING REYNOLD’S NO<br />

Pardeep Yadav 1 , Pawan Kumar 1 , Bhupender Singh 2<br />

1<br />

DAV College <strong>of</strong> Engg.& <strong>Technology</strong>,Kanina,(M.Garh) HR<br />

2 <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, HR<br />

Abstract<br />

Heat transfer characteristics and flow structure in laminar and turbulent flows through a rectangular channel<br />

containing built in vortex generators have been analyzed by means <strong>of</strong> solutions <strong>of</strong> the full Navier-Stokes and<br />

energy equations The effects <strong>of</strong> two different shaped LVGs, rectangular winglet pair (RWP) and delta winglet<br />

pair (DWP) with two different configurations, common-flow-down (CFD) and common-flow-up (CFU), are<br />

studied. The numerical results indicate that the application <strong>of</strong> LVGs effectively enhances heat transfer <strong>of</strong> the<br />

channel. According to the performance evaluation parameter, (Nu/Nu 0 )/(f/f 0 ), the channel with DWP has<br />

better overall performance than RWP; the CFD and CFU configurations <strong>of</strong> DWP have almost the same overall<br />

performance; the CFD configuration has a better overall performance than the CFU configuration for<br />

RWP. The basic mechanism <strong>of</strong> heat transfer enhancement by LVGs can be well described by the field synergy<br />

principle. The main purpose <strong>of</strong> this study is to show the performance <strong>of</strong> delta winglet type vortex generators in<br />

improving heat transfer.<br />

Keywords: Vortex generator; Common flow up; Heat transfer enhancement; Plate-fin& tube heat exchanger<br />

1. Introduction<br />

The thermal performance <strong>of</strong> refrigerant-to-air heat exchangers is <strong>of</strong>ten described in terms <strong>of</strong> thermal resistances<br />

and a reduced thermal resistance implies improved heat exchanger performance. The total thermal resistance <strong>of</strong><br />

a refrigerant to air heat exchanger is the sum <strong>of</strong> three resistances: the air-side convective resistance, the<br />

wall conductive resistance, and refrigerant side convective resistance. However, these three resistances do<br />

not contribute equally to the total thermal resistance <strong>of</strong> the heat exchanger. The air side resistance is<br />

generally much higher than the other contributions. The air-side thermal resistance accounts for 76 percent <strong>of</strong> the<br />

total evaporator resistance and 95 percent <strong>of</strong> the total condenser resistance in the two-phase regions <strong>of</strong> residential<br />

refrigerator heat exchangers. Efforts to improve refrigerant to air heat exchanger performance should focus on<br />

reducing the dominant thermal resistance on the air side <strong>of</strong> the heat exchanger generators usually are<br />

incorporated into a surface by means <strong>of</strong> embossing, stamping, punching, or attachment process. They generate<br />

longitudinal vortices which swirl the primary flow and increase the mixing <strong>of</strong> downstream regions. In<br />

addition, the vortex generator determines the secondary flow pattern. Thus, heat transfer enhancement is<br />

associated with the secondary flow with relatively low penalty <strong>of</strong> pressure drop A modified rectangular<br />

longitudinal vortex generator obtained by cutting <strong>of</strong>f the four corners <strong>of</strong> a rectangular wing is presented. Fluid<br />

flow and heat transfer characteristics <strong>of</strong> longitudinal vortex generator mounted in rectangular channel are<br />

experimentally investigated and compared with those <strong>of</strong> original rectangular longitudinal vortex generator.<br />

Results show that the modified rectangular wing pairs have better flow and heat transfer characteristics than<br />

those <strong>of</strong> rectangular wing pair. The literature reporting the enhancement <strong>of</strong> heat transfer <strong>of</strong> using surface<br />

protrusion vortex generators. They noted a maximum in-crease in the local Nusselt number <strong>of</strong> 40%.conducted<br />

heat transfer measurement for a single longitudinal vortex embedded in a turbulent boundary layer. They<br />

interpreted their data in terms <strong>of</strong> vortex circulation and boundary layer thickness extended this work to consider<br />

vortex pairs. Co-rotating pairs were observed to move together and coalesce into a single vortex as they were<br />

adverted downstream In recent years, the use <strong>of</strong> vortex generators in channel flow applications has received<br />

considerable attention. delta wing, rectangular wing, delta winglet, and rectangular winglet as vortex generators<br />

and utilized liquid crystal thermograph to measure the local heat transfer coefficient. Their results identified<br />

an increase in the local heat transfer coefficient in the order <strong>of</strong> several hundred percent and a mean heat transfer<br />

enhancement <strong>of</strong> more than 50%. studied the flow structure <strong>of</strong> an air stream over winglet pair type vortex<br />

generators. They found that the winglet pair produced a main vortex, a corner vortex, and an induced vortex.<br />

The main vortex was formed by flow separation at the leading edge <strong>of</strong> the winglet, while the corner vortex was<br />

generated by the deformation <strong>of</strong> the near wall vortex lines at the pressure side <strong>of</strong> the winglet. studied the<br />

interactions <strong>of</strong> delta-wing type vortex generators with the boundary layer on a flat plate. Their results identified a<br />

50–60% enhancement <strong>of</strong> the average heat transfer analyzed three-dimensional unsteady laminar flow and heat<br />

transfer in a channel with a pair <strong>of</strong> inclined block shape vortex generators. They found unsteady flow occurred at<br />

100


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

ReH> 1000. When the thickness and span angle is increased, stronger and bigger stream wise vortices are formed<br />

downstream <strong>of</strong> the vortex generators. considered the application <strong>of</strong> delta, rectangular, delta winglet, and<br />

rectangular winglet type vortex generators in fin-tube heat exchangers. These studies investigated various<br />

geometric parameters, including aspect ratio and angle <strong>of</strong> attack. It is shown that the ratio <strong>of</strong> heat transfer to flow<br />

loss was highest when a delta winglet vortex generator was used with an angle <strong>of</strong> attack <strong>of</strong> 30° and with an<br />

aspect ratio <strong>of</strong> 2.<br />

Vortex generators and the associated geometrical definitions<br />

For the inline tube arrangement, the vortex generator increases the heat transfer coefficient by 55–65%, resulting<br />

in a corresponding increase <strong>of</strong> <strong>20</strong> - 45% in the apparent friction factor. This is proposed a novel strategy that can<br />

augment heat transfer but nevertheless can reduce pressure-loss in fin-tube heat exchanger in a relative low<br />

Reynolds number flow, by deploying delta winglet-type vortex generators. In case <strong>of</strong> staggered tube banks,<br />

the heat transfer was increased by 10–30%, and yet the pressure loss was reduced by 34–55%. In the case <strong>of</strong> inline<br />

tube banks, the heat transfer was augmented by 10–210% together with the pressure loss reduction <strong>of</strong> 8–<br />

15%. utilized a dye-injection technique to visualize the flow structure for annular and delta winglet vortex<br />

generators. For the same winglet height, the delta winglet vortex generator shows more intensively vertical<br />

motion than that <strong>of</strong> annular vortex generator; while, the corresponding pressure drops <strong>of</strong> the delta winglet<br />

vortex generator are lower than those <strong>of</strong> annular vortex generator. Numerically and experimentally studied the<br />

wave-type vortex generator in plate-fin and tube heat exchangers. Their study identifies a maximum<br />

improvement <strong>of</strong> 1<strong>20</strong>% in the local heat transfer coefficient and an improvement <strong>of</strong> 18.5% in the<br />

average heat transfer coefficient. Reference to the journal <strong>of</strong> Jin-Sheng Leu [15] above details been concluded.<br />

Jin-Sheng Leu [15] indicated that the proposed heat transfer enhancement technique is able to generate<br />

longitudinal vortices and to improve the heat transfer performance in the wake regions. The case <strong>of</strong> α = 45°<br />

provides the best heat transfer augmentation. the delta winglet with common flow up configuration<br />

will also provide best heat augmentation. The foregoing literature review shows that no related comparison study<br />

<strong>of</strong> 3D numerical analysis for a different shaped vortex generator for a plate-fin and tube heat exchanger has<br />

been published. This has motivated the present investigation.<br />

2. Numerical Simulation<br />

Numerical Simulation is to perform by a computational fluid dynamics for the heat transfer and fluid flow for the<br />

temperature distribution and local flow structure. The comparisons <strong>of</strong> heat transfer enhancement with flat tubefin<br />

element with and without vortex generator enhancement under different shaped vortex generators carried out<br />

and optimized shape for heat transfer is been verified. The major parameters influencing the performance for<br />

vortex generator are the position, size and span angles. The present investigation mainly aims to evaluate the<br />

effects <strong>of</strong> span angle a on the thermal hydraulic characteristics. Three different span angles α = 300, 450and<br />

600are investigated in detail for the Reynolds number ranging from 500 to 2500. Turbulent numerical<br />

simulations for the fluid flow and heat transfer over a 3-row tube is to be performed, and the effect <strong>of</strong> turbulence<br />

is simulated using computational fluid dynamics The conjugated convective heat transfers in the flow field and<br />

heat conduction in the fins are also considered.<br />

101


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig.1. Physical model and relevant geometrical dimensions <strong>of</strong> the vortex generators.<br />

(a) Physical model top view, (b) side view, & (c) three different span angles.<br />

The fluid is considered incompressible with constant properties and the flow is assumed to be turbulent, steady<br />

and no viscous dissipation. The conjugated convective heat transfers in the flow field and heat conduction in the<br />

fins are also considered. At this boundary, the flow velocity is assumed to be uniform, and the temperature inlet<br />

is taken to be <strong>20</strong>0C. The intensity <strong>of</strong> the turbulence at the inlet is set to 3%.At the downstream end <strong>of</strong> the<br />

computational domain, located seven times the tube diameter from the last downstream row tube, stream wise<br />

gradient (Neumann boundary conditions) for all the variables are set to zero. At the solid surfaces, no-slip<br />

conditions and constant tube wall temperature Tw (700C) are specified. The delta winglet pair with common<br />

flow up configuration on the fin surface, as shown in 3.With this configuration, the winglet pair can create<br />

constricted passages in aft region <strong>of</strong> the tube which brings about separation delay . The fluid is accelerated in the<br />

constricted passages and as a consequence the point <strong>of</strong> separation travels downstream. Narrowing <strong>of</strong> the wake<br />

and suppression <strong>of</strong> vortex shedding are the obvious outcome <strong>of</strong> such a configuration which reduce form drag.<br />

Since the fluid is accelerated in this passage, the zone <strong>of</strong> poor heat transfer on the fin surface is also removed<br />

from the near wake <strong>of</strong> the tube In case <strong>of</strong> a low Reynolds number flow in absence <strong>of</strong> any vortex<br />

generators, the poor heat transfer zone is created widely on the fin surface in the near-wake <strong>of</strong> the tube and may<br />

extend far downstream even to the next row <strong>of</strong> the tube bank. Hence it is expected that the present strategy may<br />

be more effective for a lower Reynolds number flow.<br />

3. Calculation to Find Heat Transfer (h)<br />

Calculation to Find Heat Transfer (h) The dimensionless time averaged equations for continuity, momentum<br />

(Reynolds-averaged Navier–Stokes equations) and energy maybe ex-pressed in tensor form<br />

:<br />

102


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The Reynolds number represents the ratio <strong>of</strong> the importance <strong>of</strong> inertial effects in the flow, to viscous effects in<br />

the flow.<br />

Reynolds number, Where U, is the flow velocity, R is the radius <strong>of</strong> the cylinder, and ρ and µ are the fluid<br />

properties<br />

Re = 1.109 x 0.025 x 1.71.941x10 -5<br />

Where hydraulic diameter (h d) is 0.025<br />

Velocity = 1.7<br />

Re = 2428<br />

Nusselt number correlation for cross flow over tube banks for N>16 and 0.7 < Pr > 500 and Reynolds number<br />

greater than 1000<br />

Nusselt number is given by NuD = 0.27 ReD0.63 Pr0.36 (Pr/Prs) 0.25<br />

NuD = 0.27 (2428)0.63 0.72410.36 (0.7241/0.7177) 0.25<br />

NuD = 32.701<br />

hence NuD = 32.701x 0.86<br />

NuD = 28.12<br />

To find Heat transfer<br />

NuD = h D/ K<br />

28.12 = h x 0.024<br />

0.02699<br />

h = 31.66 or 32<br />

Heat transfer is been validated with the result which is obtained from the Computational Fluid Dynamics. It is<br />

found that the values are approximately equal as the value <strong>of</strong> h is 32.67466 in Computational Fluid Dynamic.<br />

4. Results and Discussion<br />

Heat transfer: Delta winglets with common flow up configuration in a fin-tube bank in an in-line tube<br />

arrangement successfully Increase the average heat transfer by10%to<strong>20</strong>%, the result indicates triangle<br />

winglet <strong>of</strong> span angle <strong>of</strong> 450 provides the best heat transfer augmentation which are seen in different tables.<br />

Table 1<br />

Re BASE REC 45 TRI 45<br />

500 3.59<strong>20</strong>97 5.059579 5.275462<br />

1000 5.397021 6.595592 7.283932<br />

1500 7.246089 8.0804<strong>19</strong> 8.986521<br />

<strong>20</strong>00 8.23836 8.981102 10.1776<br />

2500 9.226018 9.763312 12.47091<br />

103


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 2<br />

Re BASE REC 45 TRI 45<br />

500 0.634107 0.634107 0.690487<br />

1000 1.516281 1.815082 1.63876<br />

1500 3.480423 4.26515 4.060486<br />

<strong>20</strong>00 5.530667 6.813886 6.<strong>20</strong>9521<br />

2500 8.538239 10.14105 9.253577<br />

Pressure drop: Delta winglets with common flow up configuration in fin-tube bank in an in-line tube<br />

arrangement indicates span angle <strong>of</strong> 450 provides less pressure drop<br />

Table-3<br />

FIN TYPES 30deg 45deg 60deg<br />

BASE 32.67466 --- ---<br />

RECTANGLE 34.83991 39.090824 38.855183<br />

RECTANGLE 37.731<strong>19</strong> 38.348999 38.647732<br />

5. Conclusion<br />

Delta winglets with common flow up configuration in a fin-tube bank in an in-line tube arrangement successfully<br />

Increase the average heat transfer by10%to<strong>20</strong>%, the result indicates triangle winglet <strong>of</strong> span angle <strong>of</strong> 450<br />

provides the best heat transfer augmentation comparatively with all other fin geometries.<br />

References<br />

[1] Chunhua Min , Chengying Qi, Xiangfei Kong, Jiangfeng Dong (<strong>20</strong>10)“Experimental study <strong>of</strong> rectangular<br />

channel with modified rectangular longitudinal vortex generators” International Journal <strong>of</strong> Heat and Mass<br />

Transfer 53 ,pp .3023–3029<br />

[2] F.J. Edwards, G.J.R. Alker, The improvement <strong>of</strong> forces convection surface heat transfer using surfaces<br />

protrusions in the form <strong>of</strong> (A) cubes and (B) vortex generators, in Proceedings <strong>of</strong> the 5th International<br />

Conference on Heat Transfer, Tokyo, vol. 2, <strong>19</strong>74, pp.244–248.<br />

[3] P.A. Eibeck, J.K. Eaton, Heat transfer effects <strong>of</strong> a longitudinal vortex embedded in a turbulent boundary<br />

layer, ASME J. Heat Transfer 109 (<strong>19</strong>87) 37–57.<br />

[4] W.R. Pauley, J.K. Eaton, Experimental study <strong>of</strong> the development <strong>of</strong> longitudinal vortex pairs embedded in a<br />

turbulent boundary layer, AIAA J. 26 (<strong>19</strong>88) 816–823.<br />

[5] S.T. Tiggelbeck, N.K. Mitra, M. Fiebig, Experimental investigations <strong>of</strong> heat transfer enhancement and flow<br />

losses in a channel with double rows <strong>of</strong> longitudinal vortex generators, Int. J. Heat Mass Transfer 36 (<strong>19</strong>93)<br />

2327- 2337.<br />

[6] M. Fiebig, H. Guntermann, N.K. Mitra, Numerical analysis <strong>of</strong> heat transfer and flow loss in a parallel plate<br />

heat exchanger element with longitudinal vortex generators as fins, ASME J. Heat Transfer 117<br />

(<strong>19</strong>95)1064–1067.<br />

104


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[7] G. Biswas, K. Torii, D. Fujii, K. Nishino, Numerical and experimental determination <strong>of</strong> flow structure and<br />

heat transfer effects <strong>of</strong> longitudinal vortices in channel flow, Int. J. Heat Mass Transfer 39 (<strong>19</strong>96)<br />

3441–3451.<br />

[8] M.C. Gentry, A.M. Jacobi, Heat transfer enhancement by delta-wing-generated tip vortices in<br />

flat-plate and developing channel flows, ASME J. Heat Transfer 124 (<strong>20</strong>02) 1158–1168.<br />

[9] A. Sohankar, L. Davidson, Effect <strong>of</strong> inclined vortex generators on heat transfer enhancement in a three<br />

dimensional channel, Number. HeatTransfer, Part A 39 (<strong>20</strong>01) 433–448.<br />

[10] M. Fiebig, A. Valencia, N.K. Mitra, Wing-type vortex generators for fin-and-tube heat exchangers, Exp.<br />

Therm. Fluid Sci. 7 (<strong>19</strong>93) 287–295.<br />

[11] A. Valencia, M. Fiebig, N.K. Mitra, Heat transfer enhancement by longitudinal vortices in a fin-and-tube<br />

heat exchangers element with flattubes, ASME J. Heat Transfer 118 (<strong>19</strong>96) <strong>20</strong>9–211.<br />

[12] K. Torii, K.M. Kwak, K. Nishino, Heat transfer enhancement accompanying pressure-loss reduction with<br />

winglet type vortex generators for fin-tube heat exchangers, Int. J. Heat Mass Transfer 45 (<strong>20</strong>02) 3795–<br />

3801.<br />

[13] C.C. Wang, J. Lo, Y.T. Lin, C.S. Wei, Flow visualization <strong>of</strong> annular and delta winglet vortex generators<br />

in fin-and tube heat exchanger application, Int. J. Heat Mass Transfer 45 (<strong>20</strong>02) 3803–3815.<br />

[14] C.N. Lin, J.Y. Jang, Conjugate heat transfer and fluid flow analysis in fin-tube heat exchangers with wavetype<br />

vortex generators, J. Enhanc. Heat Transfer 9 (<strong>20</strong>02) 123–136. Experiments, ASME, Mech. Eng.<br />

75 (<strong>19</strong>53) 3–8.<br />

[15] Jin-Sheng Leu , Ying-Hao Wu , Jiin-Yuh Jang , (<strong>20</strong>04) ,“Heat transfer and fluid flow analysis in plate-fin<br />

and tube heat exchangers with a pair <strong>of</strong> block shape vortex generators” International Journal <strong>of</strong> Heat and<br />

Mass Transfer 47, pp.4327–4338<br />

105


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

PERFORMANCE IMPROVEMENT OF A CONTROL VALVE USING<br />

COMPUTATIONAL FLUID DYNAMICS<br />

K Thanigavelmurugan # , N.V. Mahalakshmi # , S. Mohan Das*, D. Venkatesh*<br />

# Department <strong>of</strong> Mechanical Engineering, Anna <strong>University</strong>, Chennai – 600 025<br />

*Circor Flow Technologies,Coimbatore,India<br />

thanigavel_murugan@yahoo.co.in<br />

Abstract<br />

This article describes the design and performance improvements <strong>of</strong> a high pressure turbine bypass valve Zick<br />

Twist trim (multi stage, multi path). For effective control <strong>of</strong> velocity, pressure and temperature, a trim designed<br />

to have a tortuous path was designed. Computational fluid dynamics and FEM analyses were used in the design<br />

process. The valve, which was installed with the designed trim, was tested. To evaluate its performance in the<br />

field, the valve was installed at a 225MW combined power plant system for two months. The results showed that<br />

the pressure letdown was successfully controlled by the designed trim, and the noise level was reduced below<br />

85dB. The main objective <strong>of</strong> the work is to find the pressure drop, velocity variation, temperature distribution in<br />

the different stages <strong>of</strong> the turbine bypass valve using computational fluid dynamics. This is done to increase the<br />

performance <strong>of</strong> the valve.<br />

Keywords: Zick Twist trim (multi stage, multi path, tortuous path trim), turbine bypass valve, pressure<br />

control, velocity control, temperature control, disc stacks, computational fluid dynamics<br />

1. Introduction<br />

Power plant system facilities are experiencing increasingly higher temperature and pressure conditions aimed at<br />

improving energy efficiency. Various valves are used to control flow in the power plant system. Valves used at a<br />

power plant are under high temperature, high pressure, and high differential pressure conditions. Therefore,<br />

erosion, hammering, vibration,noise, and damage may arise due to cavitation, flushing, and seat leakage. Turbine<br />

bypass valves plays a very major roll in power plant applications. A high-pressure turbine bypass valve is one <strong>of</strong><br />

these valves to bypass the steam during the starting and stopping mode <strong>of</strong> a turbine and reduction period <strong>of</strong><br />

electric or heating load required at a power plant and to control the pressure <strong>of</strong> the steam for the turbine<br />

expansion process. A trim is an internal component <strong>of</strong> the valve that controls pressure and velocity <strong>of</strong> the steam<br />

by energy loss caused by the flow resistance <strong>of</strong> the flow path. Control valves for power plant systems have been<br />

previously studied [1–6]. Amano and Draxler [1] presented a study <strong>of</strong> steam flow behaviour througha highpressure<br />

turbine bypass valve when it suffered a high-pressure reduction in an electric power plantcogenerator<br />

system. Logaret al. [2] developed the advanced steam turbine bypass valve to integrate thecontrol function and<br />

the trip function with a singlestem design. The flow field in a steam turbine mainstop valve bypass valve was<br />

investigated by means <strong>of</strong> computational fluid dynamic (CFD) simulation, and design recommendations for some<br />

<strong>of</strong> the most important geometric parameters were presented [3]. Excessive high velocity at the valve trim causes<br />

many problems, such as vibration, noise, and reduced valve life. To prevent this situation, a tortuous path trim<br />

was developed to simultaneously control pressure and flow velocity effectively [4–6].<br />

To consider aspects <strong>of</strong> fluid dynamics and confirm structural safety in design processes, CFD and FEM<br />

techniques are used to predict flow fields and to check stress and strain information on the valve [7, 8]. However,<br />

little has been reported about the design processor performance tests in the field for valves used at power plants.<br />

In this article, the design and performance testing <strong>of</strong> a 10˝ turbine bypass valve trim for a 230MWcombined<br />

power plant system are described. The previous valve, which needed to be replaced, had a trim only and used for<br />

reducing the pressure and velocity alone. A high pressure drop occurred simultaneous to a high velocity increase,<br />

after the steam was passed through the tortuous path trim. Owing to the high pressure drop and the velocity<br />

increase, many problems, such as plug damage, vibration, and noise, could be caused by cavitation and flushing.<br />

In light <strong>of</strong> the previous valve problems, a tortuous path disc trim was designed for a new turbine bypass valve to<br />

control pressure, velocity and temperature by using Laval jet nozzle. In order to design a valve trim, CFD and<br />

FEM analyses were used to consider fluid dynamics and structural safety. Seat leakage, pressure rating, and mass<br />

flow rate tests were carried out in a laboratory experimental steam flow line. Finally, to evaluate its performance<br />

in the field, the valve was installed in a 230MW combined power plant system for two months. The valve<br />

location in the power plant for the field test and the schematics <strong>of</strong> the valve and tortuous path trim are illustrated<br />

in Fig. 1.<br />

106


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig.1. The Schematics Of The Valve And Tortuous Path Trim<br />

2. Design <strong>of</strong> a Tortuous Path Trim<br />

A tortuous path trim consists <strong>of</strong> multiple stages so that the pressure between a stage and the next stage is<br />

reduced. Velocity does not significantly increase between stages compared with that <strong>of</strong> a multi-hole cage trim.<br />

Therefore, a tortuous path trim can solve many problems, such as cavitation, erosion, noise, and vibration, due to<br />

high-pressure letdown by one stage. The design parameters <strong>of</strong> the tortuous path used to determine the shape <strong>of</strong><br />

the disc stack have a number <strong>of</strong> conditions, such as the number <strong>of</strong> right- angle turns, the cross-section <strong>of</strong> the path,<br />

and the roughnesses <strong>of</strong> the surfaces. Smaller cross-sectional paths increase the pressure drop at each turn.<br />

Therefore, if possible, it is more advantageous to design smaller cross-sectional sizes. Additionally, particle size<br />

should be considered when determining the cross-sectional area. If the area <strong>of</strong> a path is too small, it can be<br />

frequently clogged, and the plug can be damaged by over-sized particles if the size <strong>of</strong> the path is too large.<br />

Therefore, the path area should be designed within the proper range. The number <strong>of</strong> turns and paths should be<br />

determined by taking into account the pressure drop and flow rate. In this article, the inner and outer diameters <strong>of</strong><br />

the tortuous path disc, according to the size <strong>of</strong> the valve plug, were 140 and 289.6mm, respectively. Considering<br />

the sizes <strong>of</strong> particles in the system, the width and height <strong>of</strong> the path were determined to be 4.5mmand 5mm,<br />

respectively. The thickness <strong>of</strong> the disc was determined to be 5mm based on the cross-section <strong>of</strong> the path and the<br />

structural safety factors. The number <strong>of</strong> right-angle turns, paths, and discs to be stacked was determined to be 8,<br />

48, and <strong>19</strong>, respectively, by considering the pressure drop and flow rate.<br />

107


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig. 2 Single tortuous path pressure field Valve operation<br />

3. ValveOperation<br />

A valve is operated by using an actuator that is connected to the stem to control the position <strong>of</strong> the plug as shown<br />

in Fig. 1. This controlled position <strong>of</strong> the plug determines the opening level <strong>of</strong> the tortuous path disc stack-type<br />

trim. The percentage stroke is 0 when the plug is contacted at the plug seat, which means a completely closed<br />

flow path <strong>of</strong> the trim, and 100 when the plug is located at the fully opening position <strong>of</strong> the flow path <strong>of</strong> the trim<br />

4. Flow Analysis<br />

Flow analysis <strong>of</strong> a single path with a right angle was performed to design the corner edge turns using a<br />

commercial CFD code, Fluent. Figure 2 shows the pressure field <strong>of</strong> a corner path .Flow analyses for eight paths<br />

were performed to determine the relationship between velocity and pressure drop. Steam, which was at 534 ◦C<br />

and 96 bar,was used as the working fluid and a standard k–ε turbulence model was chosen for the analysis <strong>of</strong><br />

both single-path.<br />

To calculate the valve flow field, the trim, which had 912 (48 × <strong>19</strong>) possible paths, was modeled as input<br />

parameter for the steam and the turbulence models to CFD. Using the mass flow rate(115 000 kg/h) as the inlet<br />

condition at the valve inlet, the pressure drop across the valve was calculated when the percentage stroke was 50<br />

per cent the pressure drop from the valve inlet to the outlet was 91 bar, which was the valve’s working condition,<br />

with a 115 000 kg/h mass flow rate.<br />

Meshing details<br />

Surface Mesh Generation:<br />

The surface mesh is generated inANSA,Tri elements are used in surface meshing as the model is<br />

complex.Maximum surface mesh quality is 0.6 skewness, states all the Triesare 60% mapped to best triangle<br />

(Equilateral triangle).<br />

Fig.3.Surface Mesh Generation<br />

108


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Volume Mesh Generation<br />

Volume mesh is done after the surface mesh are developed. It is done to find the characteristics <strong>of</strong> the fluid flow<br />

inside the created model. And this is done by using s<strong>of</strong>tware called T-Grid.Once these above steps are done<br />

without any errors, the model will be transferred to solver s<strong>of</strong>tware.Volume Mesh is generated using T-Grid with<br />

the cell quality <strong>of</strong> 0.8 skewness<br />

Fig. 4 Volume Mesh Generartion<br />

Fig. 5Contours <strong>of</strong> Total Pressure<br />

Fig. 6 Contours <strong>of</strong> Static Temperature<br />

5. Structural Analysis<br />

The structural analysis was performed for the designed tortuous path disc using a commercial FEM<br />

code,ANSYS. Inconel 718 was selected as the material for the disc. The number <strong>of</strong> elements was 163 661 and<br />

ten-node tetrahedral structural solid elements were used .A pressure <strong>of</strong> 96 bar, which was the inlet pressure<br />

condition <strong>of</strong> steam, was applied to the inside <strong>of</strong> the disc and walls and the bottom and top surfaces <strong>of</strong> the flow<br />

path <strong>of</strong> the disc. The top and bottom surfaces, except for the flow path <strong>of</strong> the disc, were fixed in the z-direction.<br />

Bolting parts were fixed in all directions. The maximum stress on the disc was 289.67MPa; Figure 7 shows the<br />

FEM model and the result <strong>of</strong> the maximum stress. The maximum stress was significantly lower than the yield<br />

stress(1035 MPa), and the stress were stable as well.<br />

109


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig. 7meshing <strong>of</strong> disc model<br />

Fig. 8Total Deformation<br />

Fig. 9Maximum Principal stress<br />

6. Determining the Flow Co-efficient (C v )<br />

Two important control valve parameters are the overall flow coefficient C v andthe relative valve capacity factor<br />

Cd. In general the calculation methods for C v area function <strong>of</strong> the valve Reynolds number, Rev. The flow<br />

coefficient C v is a measure <strong>of</strong> the valve capacity. It is given by the ISA standard - ANSI-ISA-S75.02. The flow<br />

co-efficient is the designing factor which relates the pressure drop (∆p) with the flow rate (Q).It is the Water<br />

average flow coefficient in US Gallons per minute (GPM) crossing the valve with a pressure loss ∆p <strong>of</strong> 1 PSI at<br />

60° F. The C v is a dimensional quantity that has evolved through industry usage. In the English Engineering<br />

System <strong>of</strong> units the C v issimply the number <strong>of</strong> gallons per minute <strong>of</strong> water that can flow through the valve with<br />

a pressure drop <strong>of</strong> one pound per square inch. [12] However, in System International units this definition would<br />

not apply. Despite the somewhat ambiguous meaning <strong>of</strong> C v , it has proven to be an acceptable indication <strong>of</strong> valve<br />

capacity. In the SI system the units <strong>of</strong> C v are(m³/hr)/(Kpa) 0.5<br />

7. Performance Test<br />

Performance tests were performed with the valve installed inside the designed trim to check performance under<br />

the operating conditions. Experimental set-up and methods were performed by standards ISA-75.<strong>19</strong>.01, FCI 70-<br />

2, and IEC 60534-2-3 as listed in Table 1.<br />

The pressure transducer used for the test was a bourdon gauge type. A capacitance sensor-type manometer was<br />

used for the measurement <strong>of</strong> the differential pressure. A thermocouple and temperature transmitter was used as a<br />

thermometer. An orifice flow meter was used to measure steam flow rate. Temperature compensation was<br />

carried out to measure exact flow rate <strong>of</strong> the steam. The test results are shown in Table 1.<br />

110


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 1 Performance Test Results For The Operating Condition<br />

Referred Test items<br />

Results<br />

Standards<br />

Mass flow rate<br />

Inlet/outlet pressure<br />

Differential pressure<br />

115 000 kg/h ISA-75.<strong>19</strong>.01, IEC 60534-2-3<br />

96/5 bar ISA-75.<strong>19</strong>.01<br />

91 bar ISA-75.<strong>19</strong>.01<br />

Inlet temperature 534 C ISA-75.<strong>19</strong>.01<br />

Required capacity 127.09 Cv ISA-75.<strong>19</strong>.01, IEC 60534-2-3<br />

Opening travel (% stroke) 50 ISA-75.<strong>19</strong>. IEC 60534-2-3<br />

Seat leakage<br />

Pressure rating<br />

0 l/min ANSI/FCI 70-2 , Class V<br />

226 bar, 5 min ISA-75.<strong>19</strong>.01<br />

The mass flow rate reached 115 000 kg/h with operating conditions <strong>of</strong> 96 bar inlet pressure and 5 bar outlet<br />

pressure, when the percentage stroke position was 50 per cent. The coefficient <strong>of</strong> the valve (C v ) was 127.09 at<br />

this time. This percentage stroke position was about 5 per cent lower than that <strong>of</strong> the CFD results. Considering<br />

the extra mass flow rate during an emergency situation, this result is very acceptable. The field test was<br />

performed at a 225MWcombined cycle power plant over the course <strong>of</strong> two months. A high-pressure steam<br />

turbine, which was installed at the power plant where the field test was performed,works from173 to 534 ◦ C for<br />

the temperature range and from 5bar<br />

to 96 bar for the pressure range. Pressure taps for the differential pressure<br />

measurement in the field were at 2D (D is the valve size) upstream location and 6D downstream location <strong>of</strong> the<br />

valve. The differential pressure was measured using the capacitance sensor-type manometer. Noise level was<br />

measured using a microphone. Figure 5 shows the pressure control performance. Differential pressure was<br />

controlled near 91 bar during the bypass mode. A significant pressure drop during transition between the bypass<br />

mode is not a dangerous situation. The result in Fig. 5 shows a general trend <strong>of</strong> the pressure control <strong>of</strong> the valve<br />

that was installed inside the designed trim. Noise level in the field was maintained well under 85 dB and was 8.1<br />

per cent less than the level <strong>of</strong> the previous valve. This means that application <strong>of</strong> the designed trim was quite<br />

effective in controlling velocity.<br />

8. Results and Discussion<br />

Fig. 10 Contours <strong>of</strong> Total Pressure<br />

Fig. 11Contours <strong>of</strong> Static Pressure<br />

111


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig. 12Contours <strong>of</strong> Static Pressure-disc area<br />

Fig. 13Contours <strong>of</strong> Static Pressure-nozzle area<br />

Fig. 14Contours <strong>of</strong> static temperature-laval plate area<br />

9. Conclusions<br />

A tortuous path trim for a high-pressure turbine bypass valve was designed and installed to controlpressure and<br />

velocity. CFD analysis was used to design the tortuous path and to study the flow field and performance <strong>of</strong> the<br />

valve installed inside the tortuous path trim. Using FEM, structural analysis was performed to check the<br />

structural stability <strong>of</strong> the trim disc .The valve performance was satisfactory with a maximum flow rate <strong>of</strong> 115<br />

000 kg/h at the given operating conditions, which were a steam temperature <strong>of</strong> 534 ◦ C, an inlet pressure <strong>of</strong> 96 bar,<br />

and an outlet pressure <strong>of</strong> 5 bar. ANSI class V leakage performance criteria were met .From the field test results,<br />

pressure letdown was acceptable up to 91 bar with the designed trim. The noise level was less than 85 dB<br />

References<br />

1 Amano, R. S. and Draxler, G. R. High-pressure steam flow in turbine bypass valve system. Part 1: valve<br />

flow.J. Propuls. Power, <strong>20</strong>02, 18(3), 555–560.<br />

2 Logar, A., Depolt, T., and Gobrecht, E. Advanced steam turbine bypass design for flexible power plants. In<br />

Proceedings <strong>of</strong> the <strong>20</strong>02 International Joint Power GenerationConference (IJPG<strong>20</strong>02), Scottsdale, Arizona,<br />

USA,<strong>20</strong>02, pp. 43–49, 49, IJPGC<strong>20</strong>02-26071. <strong>20</strong>02, pp. 43–49, IJPGC<strong>20</strong>02-26071.<br />

3 Mazur, Z., Urquiza, G., Campos, R., and McMahon, B.Improvement <strong>of</strong> the turbine main stop valves with<br />

flow simulation in erosion by solid particle impact CFD.Int. J.Rotat.Mach., <strong>20</strong>04, 10, 65–73.<br />

4 Miller, H. L. and Sterud, C. G.A high-pressure pump recirculation valve. In Proceedings <strong>of</strong> the Electric<br />

Power Research Institute’s Power Plant Symposium, Kansas City, MO, <strong>19</strong>87.<br />

112


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5 Miller, H. L. and Stratton, L. R.Recent advances in noise prediction for control valves, special lecture.In<br />

Proceedings <strong>of</strong> the International SymposiumonFluid controlandmeasurement, Tokyo, <strong>19</strong>85.<br />

6 Rahmeyer,W. J., Miller, H. L., and Sherikar, S. V. Cavitationtesting results for tortuous path control valve.<br />

In Cavitation and multi-phase flow, vol. 210, <strong>19</strong>95, pp. 63–67 (ASME FED, South Carolina), ASME/JSME<br />

Fluid Engineering and Laser Anemometry Conference and Exhibition, Hilton Head, South Carolina, 13–18<br />

August <strong>19</strong>95.<br />

7 Yi, S. I., Shin, M. K., Shin, M. S., Yoon, J. Y., and Park,G. J. Optimization <strong>of</strong> the eccentric check butterfly<br />

valveconsidering the flowcharacteristics and structural safety.Proc. IMechE, Part E: J. Process Mechanical<br />

Engineering,<strong>20</strong>08, 222(E1), 63–73. DOI: 10.1243/09544089JPME151.<br />

8 Song, X. G.,Wang, L., and Park, Y. C. Analysis and optimization <strong>of</strong> a butterfly valve disc. Proc. IMechE,<br />

Part E:J. Process Mechanical Engineering, <strong>20</strong>09, 223(E2), 81–89.DOI:. 10.1243/09544089 JPME236<br />

9 Control Valve Capacity Test Procedures,ANSI/ISA–S75.02–<strong>19</strong>96Crane Valves North America “Flow <strong>of</strong><br />

Fluids” Technical paper No.410<br />

10 Chunpeng Dou, Xinjiang Yang, ChangqingTian, Xianting Li, (<strong>20</strong>05) “Numerical Analysis on the<br />

Performance <strong>of</strong> Control Valve in variable Displacement Wobble Plate Compressor” which was published in<br />

“Journal <strong>of</strong> Mechanical Design” Vol127, by ASME.<br />

11 Emerson Control Valve Hand Book, Fourth Edition<br />

12 James A. Davis, and Mike Stewart, (<strong>20</strong>02) “Predicting Globe Control Valve Performance – Part I: CFD<br />

Modeling” which was published in “Journal <strong>of</strong> Fluids Engineering” Vol 124, by ASME<br />

13 James A. Davis, and Mike Stewart, (<strong>20</strong>02) “Predicting Globe Control Valve Performance – Part II:<br />

Experimental Verification” which was published in “Journal <strong>of</strong> Fluids Engineering” Vol 124, by ASME<br />

113


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

CFD APPLICATION IN PASSIVE BUILDING DESIGNS<br />

Ali A. F. Al-Hamadani 1 , S. K. Shukla 2 Alok K.Dwivedi 3<br />

1, 2 Department <strong>of</strong> Mechanical Engineering, Indian Institute <strong>of</strong> <strong>Technology</strong>, Banaras Hindu <strong>University</strong> Varanasi-<br />

221005, India<br />

3 SHEAT Colleges <strong>of</strong> Engineering, Babatpur, Varanasi<br />

2<br />

Corresponding Author; Telefax ; +91-0542-670285 Email: skshukla.mec@itbhu.ac.in<br />

Abstract<br />

The main factors which govern physical conditions and comfort are air temperature and air movement. These<br />

factors will assist the designer to know or to reach the suitable thermal comfort to attain the primitive<br />

knowledge, it used in passive building design. Thus, in this paper, simulation study has been performed to<br />

estimate the distribution <strong>of</strong> air temperature inside the common room with the direction <strong>of</strong> velocity and the indoor<br />

environment by using ANSYS Fluent 12.1. The simulation results show that radiation model assist better to<br />

understand the mixed convection, force convection with temperature in ventilated spaces.<br />

Keywords: CFD, Passive, Radiation, Building Design<br />

1.0 Introduction<br />

A systematic investigation <strong>of</strong> the ventilation, cooling and/or heating schemes is required for improving building<br />

design and climate system toward higher efficiency and lower energy consumption. Since field testing is both<br />

difficult and expensive, the use <strong>of</strong> accurate simulation would greatly assist the design <strong>of</strong> improve systems.<br />

Advanced in digital computing speed and capacity have made possible, the numerical solution <strong>of</strong> non-linear<br />

differential equations for fluid flows including wind-induced flows. It involves the numerical solution <strong>of</strong> the<br />

continuity equation and the conservation equations for energy and momentum. It can also include modeling <strong>of</strong><br />

particle transport by numerically solving the corresponding conservation equation <strong>of</strong> particles concentration.<br />

The one main attractive feature <strong>of</strong> computational fluid dynamic (CFD) is, its potential to assist investigation <strong>of</strong><br />

large scale structures <strong>of</strong> 3D flows, allowing incorporation <strong>of</strong> realistic boundary condition and obstructions. CFD<br />

allows the explicit calculation <strong>of</strong> average air velocity, also the details <strong>of</strong> the ventilation mechanism and its<br />

consequences on the microclimate can be understood [1].<br />

Advanced building design requests information about airflow in and around buildings. The information<br />

concerning airflow in buildings is air velocity, temperature, relative humidity, and contaminant concentrations<br />

that are important to assess thermal comfort and indoor air quality. The information on outdoor airflow is mainly<br />

air velocity and pressure distributions that are crucial for thermal comfort and building structure designs.<br />

Traditionally, the information is obtained by experimental measurements in an environmental chamber for indoor<br />

airflow and in a wind tunnel for outdoor airflow. The experimental studies are expensive and time consuming.<br />

On the other hand, developments in computer technology and turbulence modeling enable designers to obtain the<br />

information by Computational Fluid Dynamics (CFD).<br />

CFD s<strong>of</strong>tware’s rich parameterization can be categorized into two distinct sets. One set <strong>of</strong> CFD parameters,<br />

called the physical parameter set as shown in Figure 1(a), contains real-life attributes <strong>of</strong> the building layout.<br />

Examples include characterizations <strong>of</strong> objects in the building (such as building geometry, a television set with<br />

certain temperature, or the window with a certain heat influx) and flow conditions in the buildings (such as the<br />

airflow from an HVAC system). The second set <strong>of</strong> CFD parameters is the computational parameter set as shown<br />

in Figure 1(b). These variables include the computational mesh topology, error thresholds, turbulence models,<br />

phantom computational steps, and solver relaxation factors. These parameters help the underlining CFD s<strong>of</strong>tware<br />

converge quickly to an accurate solution [2].Therefore the indoor air motion and heat transfer in passive building<br />

can be predicted with assist <strong>of</strong> CFD.<br />

114


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 1: The physical parameter set includes information about the physical geometry <strong>of</strong> the<br />

problem. The computational parameters concern the numerical simulation <strong>of</strong> the model.<br />

The power <strong>of</strong> CFD is not purely quantitative. The graphical depictions <strong>of</strong> air movement and comfort within a<br />

space are a powerful communication tool for engineers, architects, and developers. These vivid depictions <strong>of</strong> the<br />

building operation can speed the acceptance <strong>of</strong> low-energy, passive design elements and allay the fears <strong>of</strong> some<br />

members <strong>of</strong> the design team[3].A commercial CFD package ANSYS Fluent 12.1 has been applied to simulated<br />

the model, thus the numerical technique used including geometry, numerical grids, boundary conditions and<br />

turbulence models. The ventilation <strong>of</strong> passive room had been simulated.<br />

2. 0 3-D CFD simulation<br />

2.1 Turbulent model<br />

The ventilation flow usually related with turbulent flow the standard k- turbulence model is based on transport<br />

equations for turbulence kinetic energy, k, and its rate <strong>of</strong> dissipation, , are obtained from the [5]:<br />

Following transport equations::<br />

And<br />

In these equations, G k represents the generation <strong>of</strong> turbulence kinetic energy due to the mean velocity gradients,<br />

G b is the generation <strong>of</strong> turbulence kinetic energy due to buoyancy. Y M represents the contribution <strong>of</strong> the<br />

fluctuating dilatation in compressible turbulence to the overall dissipation rate, C 1 ,C 2 , and C 3 are constants.<br />

σ k and σ are the turbulent Prandtl numbers for k and , respectively. S k and S are userdefined source terms<br />

2.2 Radiation model<br />

The surface-to-surface radiation model can be used to account for the radiation exchange in an enclosure <strong>of</strong> graydiffuse<br />

surfaces. The energy exchange between two surfaces depends in part on their size, separation distance,<br />

and orientation. These parameters are accounted for by a geometric function called a “view factor”. The energy<br />

reflected from surface k is<br />

(1)<br />

(2)<br />

where q out,k is the energy flux leaving the surface, ε k is the emissivity, σ is Boltzmann’s<br />

constant, and q in,k is the energy flux incident on the surface from the surroundings[5],<br />

the incident energy flux q in,k can be expressed in terms <strong>of</strong> the energy flux leaving all other surfaces as<br />

(3)<br />

where A k is the area <strong>of</strong> surface k and F jk is the view factor between surface k and surface<br />

j. For N surfaces, using the view factor reciprocity relationship gives the view factor f jk is the fraction <strong>of</strong> energy<br />

leaving surface k that is incident on surface j<br />

(4)<br />

(5)<br />

115


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2.3 Commercial CFD<br />

Commercial CFD s<strong>of</strong>tware (ANSYS Fluent 12.1and GAMBIT v2.4.6) was used to generate the mathematical<br />

grids <strong>of</strong> the room. Table 1 summarises the basic component <strong>of</strong> CFD simulation. A pre-processing is the first step<br />

in building and analysing a flow model. It includes geometry <strong>of</strong> the model, applying a mesh, and specifying the<br />

zone type. GAMBIT v2.4.6 was used for mesh generation for the 3D CFD model.<br />

Classification<br />

Table 1. The basic component <strong>of</strong> CFD simulation<br />

Setting <strong>of</strong> method<br />

Solver<br />

Pressure-Based,3-D simulation, steady state<br />

analysis(second order implicit)<br />

Gravity Y= 9.81 m/s 2<br />

Density model<br />

Temperature dependent<br />

Energy equation<br />

Activated<br />

Viscous model<br />

Radiation model<br />

scheme<br />

pressure<br />

Momentum,turbulent<br />

kinetic energy,turbulent<br />

dissipation rate<br />

Residual equation <strong>of</strong><br />

continuity<br />

standard k– e model, Standard wall functions<br />

S2S(surface to surface), view factors method ray<br />

tracing,faces per surface cluster <strong>20</strong>0,400,800,1<strong>20</strong>0<br />

simple<br />

Standard<br />

Second order upwind<br />

0.0001<br />

3. Result and discussion<br />

The simple example <strong>of</strong> room model as shown in Figure (2), considering the dimensions, x=4 m, y=3m, z=3m,<br />

and inlet vent, outlet vent with same dimension (x=1 m, y=0.1 m z=0.1) and window (x=1m, y=1 and z= 0.1 m ).<br />

The accuracy <strong>of</strong> numerical results in CFD modelling was mesh dependant: the finer mesh generally provides<br />

better results at the increased computational time. Further using a regular computational mesh made <strong>of</strong><br />

hexahedral control volumes also allows improving the accuracy <strong>of</strong> results and reducing the computational mesh<br />

[4]. Grids dependence was checked using two to four different meshes to ensure the suitable mesh. A hexahedral<br />

124000 cells mesh was selected to obtain better result with low simulation time as shown in Figure (3).<br />

Outlet vent<br />

Inlet vent<br />

Figure 2: The room <strong>of</strong> model with inlet, Outlet<br />

air and window<br />

Figure (3) Mesh <strong>of</strong> the room for 3D simulation<br />

116


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3.1 Analysis <strong>of</strong> radiation<br />

The computational time can be reduced by creating surface (cluster). The simulation had been implemented for<br />

surface cluster (<strong>20</strong>0,400,800 and 1<strong>20</strong>0) respectively. These cases are shown in Figures (4-7). Thus the Figure 6<br />

shows contours <strong>of</strong> surface cluster ID for 800 FPSC. This case shows better clustering compared to all <strong>of</strong> the other<br />

cases.<br />

Figure 4: Contours <strong>of</strong> Surface Cluster ID—<br />

<strong>20</strong>0 FPSC<br />

Figure 5: Contours <strong>of</strong> Surface Cluster<br />

ID—400 FPSC<br />

Figure 6: Contours <strong>of</strong> Surface<br />

Cluster ID—800 FPSC<br />

Figure 7: Contours <strong>of</strong> Surface<br />

Cluster ID—1<strong>20</strong>0 FPSC<br />

3.2 Analysis <strong>of</strong> indoor temperature<br />

The simulation was carried out on the room with closed and open window conditions. It is assumed that air<br />

entered from inlet vent by velocity 3m/s at 300 K, the temperature <strong>of</strong> walls <strong>of</strong> room is 300 o K, only and the ro<strong>of</strong><br />

is at 305 K,. In this case, the mixed convection was considered, and the radiation between surfaces were also<br />

simulated. The distribution <strong>of</strong> indoor temperature as shown in figures 8-9<br />

Figure 8: Contours <strong>of</strong> static temperature<br />

for close window<br />

Figure 9: Contours <strong>of</strong> static temperature<br />

for open window<br />

117


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3.2 Analysis <strong>of</strong> air velocity and distributed<br />

The movement <strong>of</strong> air inside room has been shown in Figures 10-11. It has been revealed that the air velocity near<br />

window increases due to open window case.<br />

Figure 10: Velocity vectors for close window<br />

Figure 11: Velocity vectors for open window<br />

3.3 Analysis <strong>of</strong> turbulent flow<br />

The Figures 11-12 show the turbulent energy under indoor environment. In this case it is seen that there is more<br />

turbulent in closed window than open window.<br />

.<br />

Figure 11: Velocity vectors by turbulent<br />

kinetic energy for closed window<br />

Figure 12: Velocity vectors by turbulent<br />

kinetic energy for open window<br />

Figure 13: Velocity vectors by turbulent<br />

dissipation rate for closed window<br />

Figure 14: Velocity vectors by turbulent<br />

dissipation rate for open window<br />

118


Proceedings <strong>of</strong> the National Conference on<br />

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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The velocity vector for dissipation rate in indoor room has been shown in Figures 13-14. It is depicted that there<br />

is considerable dissipation rate in closed window than the open window<br />

4.0 Conclusions<br />

Present study reveals that the ANSYS Fluent 12.1 is a good tool to do simulation <strong>of</strong> passive building design and<br />

the radiation model can be used preferably in the design <strong>of</strong> passive architectures.<br />

REFERENCES<br />

1. Mistriotis. A, De Jng. T, Wagemans. M. J. M, and bot. G. P. A, Computationa fluid dynamic (CFD) as a<br />

tool for the analysis <strong>of</strong> ventilation and indoor microclimate in agricultural building, netherland journal <strong>of</strong><br />

agricultural science 45(<strong>19</strong>97) 81-96.<br />

2. Charles R. Broderick, III and Qingyan Chen, A simple interface to CFD codes for building environment<br />

simulations, seventh international IBPSA conference RIO de Janeiro, Brazil August 13-15, <strong>20</strong>01.<br />

3. Justin Spencer and Zhiqiang Zhai, Fast Evaluation <strong>of</strong> Sustainable heating and cooling strategies for solar<br />

homes with integrated enegy and cfd modeling, Building Simulation <strong>20</strong>07.<br />

4. IORDANOU, GRIGORIOS (<strong>20</strong>09) Flat-Plate Solar Collectors for Water Heating with Improved Heat<br />

Transfer for Application in Climatic Conditions <strong>of</strong> the Mediterranean Region. Doctoral thesis, Durham<br />

<strong>University</strong>. Available at Durham E-Theses Online: http://etheses.dur.ac.uk/174/.<br />

5. Ansys fluent 12.0 Theory Guide, April <strong>20</strong>09.<br />

1<strong>19</strong>


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Energy Audit <strong>of</strong> 250 MW Thermal Power Stations PTPS, Panipat<br />

Vikrant Bhardwaj 1 , Rohit Garg 2 , Mandeep Chahal 3 , Baljeet Singh 4<br />

1<br />

Asstt. Pr<strong>of</strong>essor in Deptt. Of Mechanical Engineering,<br />

IIET, (Kinana) Jind (Haryana), India Email: vikrantwish@gmail.com<br />

2 Pr<strong>of</strong>essor in Deptt. Of Mechanical Engineering,<br />

IIET, (Kinana) Jind (Haryana), India Email: rohit_garg123@yahoo.com<br />

3<br />

Asstt. Pr<strong>of</strong>essor in Deptt. Of Mechanical Engineering,<br />

HCTM, Kaithal (Haryana), India Email: mandeepchahal17@yahoo.in<br />

4 Asstt. Pr<strong>of</strong>essor in Deptt. Of Mechanical Engineering,<br />

HCTM, Kaithal (Haryana), India Email: baljeetchahal86@gmail.com<br />

Abstract<br />

Energy conservation means, the need is to use energy efficiently and effectively.Energy Audit is a technical<br />

survey <strong>of</strong> a plant in which the machine/section wise/ department wise pattern <strong>of</strong> energy consumption studied and<br />

attempts to balance the total energy input correlating with production. As a result <strong>of</strong> the study the areas where<br />

the energy is wastefully used and the improvements are felt, are identified and corrective measures are<br />

recommended so that the overall plant efficiency could be improved.Fundamental understanding <strong>of</strong> the process<br />

is essential if we are to improve the overall efficiency <strong>of</strong> the system. In this work an energy audit <strong>of</strong> 250MW<br />

Power Plant (Coal – based) is presented at different loads. In thermal power station approximately 90% <strong>of</strong> the<br />

fuel i.e. Coal alone. In my work the overall plant efficiency observed 33.67% (210MW), 35.89% (232MW) and<br />

36.74% (250MW). The component efficiencies found 85.23% (Boiler), 41.<strong>19</strong>% (Turbo-Gen.) and 53.33%<br />

(condenser) at full load.<br />

1. Introduction<br />

Energy Audit: An energy audit is a technique for identifying energy losses, quantifying them, estimating<br />

conservation potential, evolving technological options for conservation and evaluating techno economics for the<br />

measures suggested e.g. Assist industries in reducing their energy consumption, To promote energy-efficient<br />

technologies among industry sectors, Disseminate information on energy efficiency through training programs<br />

and workshops, To promote transfer <strong>of</strong> energy-efficient and environmental-sound technologies to the industrial<br />

sectors in the context <strong>of</strong> climate change.<br />

Energy Audit Technique: The energy audit evaluates the efficiency <strong>of</strong> all process equipment/systems that<br />

require energy. The energy auditor begins at the utility meters, locating all energy sources coming into a facility.<br />

The auditor then identifies energy streams for each fuel, quantifies those energy streams into discrete functions,<br />

evaluates the efficiency <strong>of</strong> each <strong>of</strong> those functions, and identifies energy and cost savings opportunities.<br />

Total System Audit: This approach analysis the total system by detailed analysis as the total energy data is<br />

entered in a master database file. This contains design data and also the observed data. This approach gives the<br />

energy performance <strong>of</strong> the total system and identifies areas <strong>of</strong> improvements on energy cost or energy quantity<br />

basis. This method requires rigorous data entry and analysis.<br />

Problem Formulation<br />

In PTPS, Panipat 250 MW units is consideration for energy Audit for Energy Audit and Efficiencies <strong>of</strong> main<br />

sub-units as like Boiler, Turbine and generator, Condenser & Heater are calculated and compared are different<br />

loads which highlights in PTPS 250 MW units energy efficiency has to be improved to survive in Global Market.<br />

2. Working Cycle <strong>of</strong> Typical Coal Fired Power Station<br />

Layout shows a Coal Fired Power Station. Its main raw material is Coal, air and Water. The Coal brought to the<br />

station by trains or by the other means & this travels from Coal handling plant by conveyor belt to the<br />

coalbunkers, from where it is fed to the Pulverizing Mills, which grind it as fine as face as face powder. The<br />

finely powdered coal mixed with pre-heated air, is then blown into the Boiler by a fan called Primary Air Fan<br />

where it burns, more like a gas than as a solid in the conventional domestic or industrial grate, with additional<br />

amount <strong>of</strong> air called secondary air supplied by a Forced Draft Fan.As the coal has been ground, finely the<br />

resultant ash is also a fine powder. Some <strong>of</strong> it binds together to from lumps, which fall into the ash pits at the<br />

bottom <strong>of</strong> furnace. The water-quenched ash from the bottom <strong>of</strong> furnace is conveyed to pits subsequent disposal<br />

or sale. Most <strong>of</strong> ash, still in fine particles form is carried out <strong>of</strong> the boiler to the Precipitators as dust, The dust is<br />

then conveyed by water to disposal areas or to Bunkers for sale while the cleaned flue gases pass on through<br />

Induced Draft Fan to be discharged up the Chimney.<br />

1<strong>20</strong>


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 1<br />

Table 1. DATA OF 250 MW THERMAL POWER PLANT AT LOAD 250 MW<br />

Description Press Tem Flow Enthalpy Entropy<br />

S.I HPT 150 540 782 3414.6 741.73<br />

S.O. HPT& I Re-heater 38 340 710 2574.6 507.77<br />

S.O. Re-heat & I. IPT 38 540 710 3414.6 673.43<br />

S. O. IPT & I. LPT 8 340 630 2574.6 450.56<br />

6th Extraction HPT<br />

& I. HPH6<br />

38 340 70 2574.6 50.06<br />

3. Data Analysis<br />

Data Analysis <strong>of</strong> plant at 250 MW<br />

Boiler Section<br />

Inlet in Boiler<br />

(i) At (40) Coal = 1<strong>20</strong>T/hr<br />

= 1<strong>20</strong> x 1000/3600<br />

=33.33 Kg. /Sec.<br />

Calorific Value = (C.V) <strong>of</strong> Coal<br />

= 4860 K Cal/Kg<br />

Energy = 4860 x 33.33 x 4.2/1000<br />

121


= 680.33 MW<br />

(ii) At (2) Energy = 507.77 MW<br />

(iii) At (24) Energy = 472.26 MW<br />

Outlet from Boiler<br />

(iv) At (1) Energy = 741.73 MW<br />

(v) At (3) Energy = 673.44 MW<br />

(vi) Flue Gases<br />

Total Inlet<br />

Total Outlet<br />

Loss in Boiler<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

= (i) + (ii) + (iii)<br />

= 680.33 + 507.77 +472.26<br />

= 1660.36 MW<br />

= (iv) + (v) + (vi)<br />

= 741.73 + 673.44 + 0<br />

= 1415.17 MW<br />

= Inlet – Outlet<br />

= 1660.36 – 1415.17<br />

= 245.<strong>19</strong> MW<br />

Efficiency <strong>of</strong> Boiler = 1415.17 x 100/ 1660.36<br />

= 85.23 %<br />

Section Turbine & Gen.<br />

(i) HPT Inlet (1) = 741.73 MW<br />

Outlet (2) + (5) = 567.77 + 50.06<br />

= 557.83 MW<br />

Net Energy at HPT= 741.73 – 557.83<br />

= 183.9 MW<br />

(ii) IPT Inlet (3) = 673.44 MW<br />

Outlet (4) + (7) = 450.55+37.73<br />

= 488.28 MW<br />

Net Energy at IPT= 673.44 – 488.28<br />

= 14.84 MW<br />

(iii) LPT Inlet (4) = 450.56 MW<br />

=Outlet (9) + (11) + (13)<br />

= 17.71+12.47 +12.12<br />

= 42.3 MW<br />

Net Energy at LPT= 450.56 – 42.3<br />

= 408.26 MW<br />

Net Input at Turbine (HPT, IPT & LPT)<br />

=183.9 + 14.84 + 408.26<br />

= 607 MW<br />

Efficiency <strong>of</strong> Turbo Generator= 250 x 100/ 607<br />

= 41.<strong>19</strong> %<br />

Section Condenser:<br />

Condenser Efficiency= Actual Cooling Water Temp rise<br />

Max Possible Temp. Rise<br />

Overall station efficiency<br />

= Output <strong>of</strong> Station x 100<br />

= (T42 – T41) x100<br />

T 15 – T41<br />

= (38 – 30) x100<br />

45 – 30<br />

= 53.33 %<br />

122


Input <strong>of</strong> Station<br />

= Energy sent out (KW) .<br />

Fuel burnt (Kg) x Calorific value <strong>of</strong> fuel (K Cal/kg)<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fuel burnt (Coal) = 1<strong>20</strong> T/ Hr<br />

= 33.33 Kg/Sec<br />

C.V<br />

= 4860 K Cal/kg<br />

= 4860 x 4.2<br />

= <strong>20</strong>412 KW<br />

Heat Input =<strong>20</strong>412 x 33.33/10 = 680.33 MW<br />

Overall Efficiency <strong>of</strong> Plant= 250 x 100/680.33<br />

= 36.74 %<br />

Data Analysis for Table No.-1 (250 MW)<br />

Sr. No. 01 Pressure =150 Kg/cm²<br />

Temperature =540 ºC<br />

= 813 K<br />

Flow<br />

=782 T/Hr.<br />

=782 x 1000/3600<br />

=217.22 Kg/sec<br />

Enthalpy (CpxT) =4.2 x 813<br />

=3414.6 KJ/Kg<br />

Energy =217.22 x 3414.6/1000<br />

=741.73 MW<br />

4. MAIN RESULTS<br />

The efficiencies / effectiveness <strong>of</strong> typical 250 MW Plant at different loads are compared as follows:-<br />

Description<br />

Table 1<br />

250<br />

MW<br />

232<br />

MW<br />

2<strong>20</strong><br />

MW<br />

Boiler Efficiency 85.23% 85.<strong>20</strong>% 84.66%<br />

Turbine & Generator Efficiency 41.<strong>19</strong>% 31.51% 29.88%<br />

Condenser Efficiency 53.33% 46.67% 43%<br />

Heater LPH1 Effectiveness 0.46 0.5 0.51<br />

Heater LPH2 Effectiveness 0.14 0.12 0.12<br />

Heater LPH3 Effectiveness 0.13 0.13 0.13<br />

Heater HPH5 Effectiveness 0.13 0.14 0.12<br />

Heater HPH6 Effectiveness 0.29 0.31 0.33<br />

Overall Plant Efficiency 36.74% 35.89% 33.67%<br />

Coal Consumption 1<strong>20</strong> T/Hr 114 T/Hr 110 T/Hr<br />

123


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Graph 1<br />

250MW<br />

232MW<br />

210 MW<br />

100%<br />

90%<br />

85.23%<br />

85.<strong>20</strong>%<br />

84.66%<br />

80%<br />

70%<br />

60%<br />

50%<br />

40%<br />

30%<br />

41.<strong>19</strong>%<br />

31.51%<br />

29.88%<br />

53.33%<br />

46.67%<br />

43%<br />

<strong>20</strong>%<br />

10%<br />

0%<br />

Boiler Efficiency Turbine & Gen.<br />

Efficiency<br />

Condensor<br />

Efficiency<br />

250MW<br />

232MW<br />

210 MW<br />

50%<br />

40%<br />

36.74%<br />

35.89%<br />

33.67%<br />

30%<br />

<strong>20</strong>%<br />

10%<br />

0%<br />

Overall Plant Efficiency<br />

Graph 2<br />

5. CONCLUSIONS<br />

(1) Overall Plant efficiency at lower loads decreases so we should run the Plant at higher load.<br />

(2) Boiler has scaling problem which aggravates localized corrosion and affects the boiler life. Scale formation<br />

in the boiler is caused due to water hardness. A layer <strong>of</strong> scale on a boiler tube acts as an insulator and results in<br />

inefficient heat transfer and overheating <strong>of</strong> metal walls. It is estimated that about 2% coal consumption can be<br />

reduced or saved by eliminating scale accumulation in the boiler.<br />

(3) The decrease in the amount <strong>of</strong> steam flowing through the low pressure end <strong>of</strong> the turbine and the amount <strong>of</strong><br />

steam to be condensed.<br />

(4) The boiler efficiency found 84.66 % to 85.23 %; this can be increased up to 90 % to 95 % by adopting<br />

following recommendation.The effect <strong>of</strong> supplying only the theoretical amount <strong>of</strong> air for combustion with coal.<br />

Some coal remains into chemical combustion with the constituents <strong>of</strong> the fuel, which results great loss <strong>of</strong><br />

available heat as the gases are only partially brunt. In the case being considered 10% <strong>of</strong> the heat may be lost as<br />

unburant carbon in ash, and possibly a further 15 % app. Lost up chimney as unburant gas. Thus about 75 % <strong>of</strong><br />

the heat is liberated in the furnace.<br />

Admitting more air will reduce the losses considerable, as the chance <strong>of</strong> the carbon and hydrogen atoms meeting<br />

the necessary oxygen atoms has increased greatly.<br />

124


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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 2<br />

(5) Boiler efficiency is mainly attributed to dry flue gas, wet gas & sensible heat loss, which may reduced quite<br />

significantly by reducing the flue gas exhaust temperature. Reduction in flue gas temperature less than that <strong>of</strong> the<br />

dew point temperature may cause loss <strong>of</strong> boiler life even more than that saving money on flue cost because <strong>of</strong><br />

higher efficiency.<br />

(6) To increase the heat available compared to the heat rejected is to increase the superheated steam temperature.<br />

Unfortunately this is only possible to a very small degree because metallurgical limitations. Thus there is very<br />

little scope in this direction.<br />

(7) For improving condenser efficiency main factors is the improvement in quality <strong>of</strong> cooling water and close<br />

cycle. At present in plant using open cycle.<br />

(8) Overall efficiency <strong>of</strong> plant can be increased by using wash-coal which helps to eliminate the ash contents<br />

from the coal. By doing so, we can save the energy waste with ash.<br />

References<br />

1. Bergander, Mark J. Porter, R.W. (<strong>20</strong>03) “ Most troublesome component <strong>of</strong> electric power generation plant”,<br />

Energy conservation in coal fired boilers, Vol. 32, <strong>20</strong>03, Page No. 142-149<br />

2. Hatt, Roderick, M. & Lewis, W (<strong>20</strong>03) “Coal ash deposits in coal fired boilers” Energy conservation <strong>of</strong> coal<br />

fired boilers, Vol. 14, <strong>20</strong>03, Page No. 181-189<br />

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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Thermodynamic Analysis <strong>of</strong> Ground Source Heat Pump for Space Heating<br />

Using R-22<br />

Surender Nain 1 , Sanjeev Kumar 2 , Vikrant Bhardwaj 3 ,<br />

Narender Mann 4 , Parveen Kumar 5<br />

1<br />

Asstt. Pr<strong>of</strong>essor in Deptt. <strong>of</strong> Mechanical Engineering,<br />

HCTM, Kaithal (Haryana), India Email: nain2772@gmail.com<br />

2<br />

Asstt. Pr<strong>of</strong>essor in Deptt. <strong>of</strong> Mechanical Engineering,<br />

HCTM, Kaithal (Haryana), India Email: er.sanjeevkumar@rediffmail.com<br />

3<br />

Asstt. Pr<strong>of</strong>essor in Deptt. <strong>of</strong> Mechanical Engineering,<br />

I.I.E.T, Kinana, Jind (Haryana), India Email: vikrantwish@gmail.com<br />

4 Asstt. Pr<strong>of</strong>essor in Deptt. <strong>of</strong> Mechanical Engineering,<br />

HCTM, Kaithal (Haryana), India Email: mann.narender@gmail.com<br />

5<br />

Lecturer in Deptt. <strong>of</strong> Mechanical Engineering,<br />

HCTM, Kaithal (Haryana), India Email: parveenmech36@gmail.com<br />

Abstract<br />

In the coming decades, global environmental issues will significantly affect the patterns <strong>of</strong> energy used around<br />

the world. Any future efforts to limit carbon emission likely to alter the composition <strong>of</strong> total energy-related<br />

carbon emissions by energy sources. Air pollutions are becoming an important environmental concern.<br />

1. Introduction<br />

In the coming decades, global environmental issues will significantly affect the patterns <strong>of</strong> energy used around<br />

the world. Any future efforts to limit carbon emission likely to alter the composition <strong>of</strong> total energy-related<br />

carbon emissions by energy sources. Air pollutions are becoming an important environmental concern. With<br />

increasing worldwide awareness <strong>of</strong> the serious environmental problems due to fossil fuel composition , efforts<br />

are being made to develop energy-efficient and environmental friendly system by utilization <strong>of</strong> non polluting<br />

renewable energy sources, such a solar energy, industrial waste heat geo thermal water etc. In order to minimize<br />

co2 emission from centralized power stations research attempts are being foc used on reduction <strong>of</strong> electricity<br />

consumption in much energy intensive application. One such application is space heating, where there is a lot <strong>of</strong><br />

scope for reducing electricity consumptions by substituting with other sources <strong>of</strong> heat. Ground source heat pump<br />

(GSHP) is concerned as one <strong>of</strong> the alternate energy sources for space heating since it is environmental friendly<br />

and sustainable. Ground source heat pump systems (also refried to as GSHP , earth energy system and Geoexchange<br />

systems ) have received considerable attention in recent decades as an alternative energy source and it<br />

could play an significant role in reducing the consumption <strong>of</strong> centrally produced electricity, thus leading to<br />

reduction in co2 emissions . Geo thermal energy is renewable energy resource that can be used to provide<br />

electricity heating and cooling <strong>of</strong> commercial and domestic buildings and other facilities.<br />

2. Literature Review<br />

Omar carried out a study in the energy company, EnBW energies BadenWurttemberg AG, to estimate the<br />

average and total co2 saving <strong>of</strong> 1105 installed GSHP systems in Germany. The co2 emission for the studied<br />

scenario <strong>of</strong> a SHP unit for heating is 149 g CO2/kwh, respectively depending on the considered electrical mix<br />

compared to 229 g co2/kwh for a conventional heating mix, indicating that at least 35% <strong>of</strong> additional co2<br />

emission could be avoided with the application <strong>of</strong> GSHP system. In <strong>20</strong>00, for example, the electrical energy<br />

generated by geo thermal energy was 49.3 billion kHz/year, representing only 0.3% <strong>of</strong> total global electrical<br />

energy.<br />

Lund showed that using the regional electricity mix, which consists <strong>of</strong> 55% nuclear power, co2 power up to<br />

72% can be achieved. The average co2 saves for one installed GHSP unit ranges therefore between around 1800<br />

and 4000 kg per year depending upon the supplied and purchased electricity mix. Assuming an average driven<br />

kilo meters per year <strong>of</strong> 15,000 km for one family house hold, the resulting co2 emission are around 2400 kg per<br />

year, which is slightly higher than the annual co2 saving <strong>of</strong> one electrical GSHP unit the German electricity mix.<br />

Nevertheless, the application <strong>of</strong> GSHP unit is always able to compensate the co2 emissions caused by driving a<br />

car for 15000 km per year or reduce the co2 emission <strong>of</strong> one person per year by minimum <strong>of</strong> <strong>20</strong>%. The total<br />

minimum annual co2 savings due to the subsidy programs was about <strong>20</strong>00 tons. Thus, The use <strong>of</strong> GSHP for<br />

heating and cooling for residential and commercial building and significantly reduce the emission <strong>of</strong> global<br />

126


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

green house gases such as co2 and so2 . A study by American EPA has demonstrated that residential fossil fuel<br />

heating system is in the USA produced anywhere from 1.2 to 36 times the environmental co2emissions from<br />

15% to 77% could be avoided through the application <strong>of</strong> GHSP systems .<br />

3. Experimentation<br />

For a general steady state, steady flow process, the four balance equations, namely mass, energy, entropy and<br />

energy balance equations are applied to ground source heat pump (GSHP) in ordered to find the heat input, the<br />

rate <strong>of</strong> energy decreased, the energy and exergy efficiencies the mass and energy balance equations as well as the<br />

exergy destruction obtained using the entropy and exergy balance equation for each <strong>of</strong> GSHP componets are<br />

discussed in the following sections. Fig shows schematic diagram <strong>of</strong> GSHP considered for thermodynamic<br />

analysis. The GSHP system consists <strong>of</strong> compressor, condenser, expansion valve, evaporator, fan-coil unit and<br />

ground heat exchanger. It is assumed that the flow is steady through every component <strong>of</strong> the GSHP system heat<br />

loss is ignored the governing equation for the individual components <strong>of</strong> the systems are derived as follows :<br />

Compressor<br />

Using the notation used to represents various stage points in GSHP system; the mass balance equation for<br />

compressor can be expressed as<br />

1 =2 = r<br />

assuming no heat loss, using the energy balance equation the work input to the compressor can be expressed as<br />

comp = r (h2-h1)<br />

The exergy destruction, xdest,comp can be computed using exergy generation and energy balance equations .<br />

Using these equation an expression for xdest,comp is given as follows<br />

xdest,comp = r (Ψ1- Ψ2 ) + comp,act<br />

Energy for any component can be found out using the formulas:<br />

Exergy Ψ = (h-h0)-T0(s-s0)<br />

Condenser<br />

Mass balance for refrigerant flow in the condenser can be denoted as<br />

2 = 3 = r<br />

similarly the mass balance for air flow in the fan coil unit which is connected to the condenser for heat<br />

extraction, can be expressed as<br />

5 = 6 = w<br />

the energy balance for refrigerant and air sides are given by<br />

cond = r (h2-h3)<br />

cond= fc= w =Cw (T5-T6)<br />

The exergy destruction in the condenser is expressed as<br />

Èxdest,cond =r(Ψ2- Ψ3)+ w(Ψ6- Ψ5)<br />

127


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Expansion valve<br />

The mass balance for the refrigerant flow through the expansion valve is expressed as<br />

3 =4 = r<br />

in the absence <strong>of</strong> heat loss the energy balance is<br />

h3=h4<br />

the exergy distruction through their expansion valve can be denoted as<br />

Èxdest,valve = r(Ψ3- Ψ4)<br />

Evaporator<br />

The mass balance equation for refrigerant flow through the evaporator is denoted as<br />

128


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4 =1 = r<br />

similarly the mass balance equation for brine water flow through the bore heat exchanger which is coupled to the<br />

evaporator for heat transfer is given as<br />

7 =8 = bw<br />

energy balance equation for evaporator shows that<br />

evapo = r (h1-h4) ; evapo= gh<br />

The exergy distruction through the evaporator can be denoted as<br />

Èxdest,evap = r(Ψ4- Ψ1)+ bw(Ψ8- Ψ7)<br />

Fan-coil unit<br />

The mass balance equation for air flow through fan-coil unit is expressed as<br />

in =air,out = air<br />

the exergy destruction through fan coil unit can be denoted as<br />

Èxdest,fc = w(Ψ5- Ψ6)+ fc(1-T0/Tin)<br />

Ground source heat exchanger<br />

The mass balance equation for brine water flow through ground source heat exchanger is given by<br />

7 =8 = bw<br />

the energy balance equation for ground source heat exchanger is denoted as<br />

gh = bw Cp,bw (T8-T7) ; evap= gh<br />

The exergy destruction in the ground source is expressed as<br />

Èxdest gh= bw(Ψ7- Ψ8)+ gh(1-T0/Tsoil)<br />

The exergy destruction in the circulating pump may be calculated from following equation<br />

Èxdest,pump= Wpump- bw(Ψout- Ψin)<br />

Performance parameters<br />

The performance <strong>of</strong> GSHP unit can be estimated using parameters as defined below<br />

COPhp =cond /Wcomp<br />

Where cond is the heat transfer rate <strong>of</strong> the condenser (the space heating load), Wcomp is the rate <strong>of</strong> work<br />

input to the compressor<br />

From equation<br />

COPhp =cond /Wcomp<br />

=4/1.3522=2.958<br />

129


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Property data for different component <strong>of</strong> GSHP (R22)<br />

S. no. Description Fluid Temp T<br />

(c)<br />

Pressure<br />

P(bar)<br />

Specific<br />

Enthalpy<br />

Specific<br />

Entropy<br />

0 _______ Refrigerant 10 1.0132 4<strong>19</strong>.8 1.949<br />

0` ________ Water 10 1.0132 42.18 0.151<br />

0`` _________ Brine water 10 1.0132 42.18 0.151<br />

1 Compressor<br />

inlet<br />

2 Compressor<br />

outlet<br />

3 Condenser<br />

outlet<br />

4 Evaporator<br />

inlet<br />

5 Fan coil<br />

Inlet<br />

6 Fan coil Out<br />

Let<br />

Refrigerant -6 3.141 404.6 1.782<br />

refrigerant 99.2 <strong>19</strong>.11 464.7 1.823<br />

refrigrant 40.8 <strong>19</strong>.11 464.7 1.172<br />

refrigrant -10.99 3.14 251.45 1.<strong>19</strong>8<br />

water 45 2.50 188.64 0.6381<br />

water 39.9 2.50 167.34 0.5707<br />

7<br />

8<br />

GHE water<br />

Pump inlet<br />

GHE water<br />

Pump outlet<br />

Brine water<br />

Brine water<br />

15<br />

<strong>20</strong><br />

2.50<br />

3.50<br />

63.22<br />

84.25<br />

0.224<br />

0.296<br />

Exergetic, thermodynamic analysis data for GSHP system R22<br />

Component<br />

Éxdest<br />

(kw)<br />

Uttilized<br />

power(kw)<br />

<br />

(KW)<br />

<br />

(KW)<br />

<br />

%<br />

IP<br />

(w)<br />

Compressor 0.4792 1.3522 0.873 1.3522 64.56 169.3<br />

Condenser 0.1026 4 0.1481 0.5276 80.29 <strong>20</strong>.2<br />

Exp valve 0.1326 _ 0.7971 .9297 85.74 18.9<br />

Evaporator 0.31 2.7576 .0934 .2<strong>19</strong>7 42.51 179.9<br />

Fan coil unit .3081 4 0.11 0.4181 26.30 227.1<br />

GHE 0.0185 2.7567 .0935 0.11<strong>20</strong> 83.48 3<br />

GSHP 1.0275 8.1089 2.1816 3.0223 72.18 388.3<br />

Overall<br />

system<br />

1.3541 14.8656 2.3851 3.5544 67.41 618.4<br />

Estimation <strong>of</strong> reduction in co2 emission for R22<br />

Assuming that the approximate heat load for a room in is about 4 kw and a heater <strong>of</strong> 4 kw capacity is used for<br />

space heating for 6 hr during a day , the total electricity consumed by a heater during three months <strong>of</strong> winter<br />

=4*6*30*3=2160 kw hr<br />

130


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The aviliabe data for Indian power scenario shows that 1 kw h consumption for electricity emits 0.8<strong>20</strong> kg <strong>of</strong> co2<br />

.<br />

Hence the quantity <strong>of</strong> co2 emitted using a heater for space heating<br />

=2160*0.8<strong>20</strong> =1771.2 kg<br />

The thermodyanamic analysis shows that GSHJP proposed in the present work has a cop <strong>of</strong> 2.958. hence in<br />

orderd to provide 4 kw <strong>of</strong> heating , the electricity required will be =4/2.958<br />

=1.3522 kw<br />

Hence total % reduction in electricity consumption and co2 emission is =66.<strong>19</strong>% for both.<br />

Result for R22 refrigerant<br />

REFRIGRANT<br />

R22<br />

Exergy destruction (kw) 1.3541<br />

Improvement potential (w) 618.4<br />

COP 2.958<br />

Co2 Reduction % 66.<strong>19</strong><br />

4. Conclusions<br />

In the present study, the results were evaluated to determine the performance <strong>of</strong> a GSHP unit a dth e overall<br />

system. These evaluations may be classified into two groups, energetic and exegetic evaluations. The exergy<br />

evaluation values <strong>of</strong> each <strong>of</strong> the components along with the potential for improvement were discussed some<br />

important conclusions that may be drawn from the present study are listed below:<br />

1. the value for cop <strong>of</strong> the heat pump was obtained to be 2.958 for R22<br />

2. the exergy efficiency for the GSHP unit and the whole system are obtained to be 72.18 and 61.14 %<br />

respectively for R22<br />

3. total exergy destruction for GSHP unit and overall system was obtained as 1.02251 kw and 1.3541 kw<br />

respectively for R22<br />

4. total quantity saving <strong>of</strong> co2 emission for the given system for space heating is 1172.42 kg co2 for R22<br />

5. Refrigerant R22 give better result than R410A and R 507 on same condition.<br />

6. Total % for saving is co2 emission as well as electricity consumption using R22 for space heating is<br />

66.<strong>19</strong> % for both<br />

References<br />

1. Hikmet E.,Mustafa I. and Mehmet E, Techno Economic Appraisal <strong>of</strong> a ground source heat pump system for<br />

a heating season in eastern Turkey,vol.47,pp.1281-1297,(<strong>20</strong>06)<br />

2. Omer A.M., Ground source heat pump systems and applications,vol.12,pp.344-371,(<strong>20</strong>08)<br />

131


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

EFFECT OF ROUGHNESS ON SECONDARY FLOW IN A RECTILINEAR<br />

TURBINE CASCADE<br />

Vinod Kumar Singoria 1 , Deepika Sharma 2 , Shamsher 3<br />

Dept. <strong>of</strong> Mechanical Engineering<br />

Delhi Technological <strong>University</strong>, (Formerly Delhi College <strong>of</strong> Engineering)<br />

vinodsingoria@msn.com<br />

Abstract<br />

Three dimensional geometry <strong>of</strong> rectilinear cascade <strong>of</strong> four reaction blades is created in the Gambit® 2.2.3 s<strong>of</strong>tware<br />

and flow behavior has been studied using FLUENT 6.2. Air with an inlet velocity <strong>of</strong> 102m/s is passed through the<br />

cascade. The cascade is open to atmosphere at the exit. Initially, both surfaces <strong>of</strong> the blade <strong>of</strong> the cascade are kept<br />

as smooth and secondary loss is analyzed. This secondary flow loss is then compared with the blades on which a<br />

roughness <strong>of</strong> 500 µm is applied on suction surface and pressure surface individually as well as on both the surfaces<br />

together. It is observed that in a smooth blade average total loss is 14.7% whereas in case <strong>of</strong> blades having both the<br />

surfaces rough this loss gets almost doubled and becomes 27.7%. When roughness is applied to all the suction<br />

surfaces only then average total loss is 24.7% and if roughness is present only on the pressure surfaces then average<br />

total loss is 18.2%. But the corresponding average secondary loss decreases from 1.7% in case <strong>of</strong> smooth blades to<br />

1.5% for rough blades. This average secondary loss is 1.9% for the blades on which roughness is present on all the<br />

pressure and 1.3% in case when roughness is applied to only suction surfaces <strong>of</strong> the blades.<br />

1. Background<br />

Energy is the basic need <strong>of</strong> any country. Around 70% <strong>of</strong> total power generation in India is contributed by steam and<br />

gas power plant. With the growing need <strong>of</strong> energy conservation, constant efforts are actively pursued throughout the<br />

world to improve the efficiency <strong>of</strong> the power plants for meeting the energy need <strong>of</strong> the world as well as for proper<br />

utilization and saving <strong>of</strong> fuel. The efficiency <strong>of</strong> any gas or thermal power plant usually depends on the efficiency<br />

and working <strong>of</strong> the turbines and hence turbines are the basic component <strong>of</strong> any power plant which needs to be<br />

improved for improving the efficiency <strong>of</strong> the plant. The viscous diffusion in the flow through turbine cascade results<br />

in the decrease in integrated flux <strong>of</strong> total pressure through the cascade. Since this decrease in total pressure flux is<br />

related to the amount <strong>of</strong> kinetic and potential energy lost in the cascade, hence this pressure flux is termed as ‘total<br />

pressure loss’ or simply ‘loss’. This total pressure loss has significant effect on the efficiency <strong>of</strong> the cascade and<br />

hence it should be minimized. The historical classification and division <strong>of</strong> loss into ‘pr<strong>of</strong>ile loss’ and ‘end loss’<br />

continues to be widely used although it is now clearly recognized that the loss generation mechanisms are seldom<br />

independent. The first is the loss due to boundary layer on the blade surface and is termed as ‘pr<strong>of</strong>ile loss’ due to its<br />

dependence on the surface <strong>of</strong> blade pr<strong>of</strong>ile. The remaining part <strong>of</strong> total pressure loss depends on the presence <strong>of</strong><br />

solid endwalls and is termed as ‘endwall or secondary losses’. The secondary losses include loss from the boundary<br />

wall on the endwall wetted surface, loss due to flow separation, diffusion <strong>of</strong> passage secondary vortex and additional<br />

loss due to change in blade surface boundary layers caused by secondary flow. End loss forms a major part <strong>of</strong><br />

internal aerodynamic losses occurring in turbine. Phenomena <strong>of</strong> secondary loss are important in turbomachinery<br />

mainly for two reasons. Firstly, it causes pressure loss in a stage & secondly, it makes stage exit flow non uniform,<br />

which could cause increased pressure losses in a downstream row.<br />

Thus the improvement in the efficiency <strong>of</strong> turbomachinery becomes the key research area. For getting the improved<br />

efficiency <strong>of</strong> turbomachine it became essential to analyze the flow field and associated loss generation in turbine. It<br />

is essential to study the various parameters effecting the turbine flow field, so as to vary secondary losses and hence<br />

the turbine efficiency. This has to be studied using rectilinear turbine cascade in which air enters at the cascade inlet,<br />

flows between the blade passages and then moved to cascade outlet while flowing between the tailboards to the<br />

atmosphere.<br />

Secondary flows are a mean flow in the transverse plane superimposed upon the axial mean flow. Various<br />

researchers analyzed the secondary flow, the causes <strong>of</strong> secondary flow and the losses occurred due to secondary<br />

flow. Langston et al. [1] was one <strong>of</strong> the first to study the evolution <strong>of</strong> secondary flows using hot wire and flow<br />

visualization techniques to qualitatively assess flow patterns at boundary layer, near the end wall region <strong>of</strong> a cascade.<br />

He concluded that pressure surface leg <strong>of</strong> horseshoe vortex drifts towards the adjacent suction surface and termed as<br />

132


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

passage vortex. This passage vortex strengthens the counter vortex. Different experiments were performed by<br />

Marchal et al. [2], Sieverding et al. [3], Wang et al. [4] and Sharma et al. [5] which confirmed the conclusions <strong>of</strong><br />

Langston et al. [1]. Later on experiments were performed for reducing the secondary loss. In the literature two<br />

methods were proposed for secondary loss reduction. One is leading edge modification and other is end wall<br />

contouring. There are two main designs for leading edge modification is: the fillet and the bulb. Young J. Moon et al.<br />

[6] analyzed the effect <strong>of</strong> end wall fencing for reducing the secondary flow using k-ξ turbulence model. They also<br />

justified the optimized positioning <strong>of</strong> the endwall fencing for reducing the secondary flow losses, because the end<br />

wall fencing prevents the merging <strong>of</strong> pressure side horse shoe vortex with the passage vortex and hence total pressure<br />

loss decreases. Arun K. Saha et al. [7] analyzed the turbulent flow through a three dimensional non-axisymmetrical<br />

blade passage and observed that endwall contouring reduces the pitchwise pressure gradient near the endwall which<br />

reduces the chances <strong>of</strong> flow separation. Toyotaka Sonoda et al. [8] use axisymmetrical end wall contouring method<br />

for reducing the secondary losses in high pressure turbine having low aspect ratio. Brear et al. in [9] tried to reduce<br />

this pressure surface separation by modifying the leading edge geometry. They concluded that increasing the blade<br />

thickness at the pressure surface decrease the strength <strong>of</strong> secondary flow by increasing the momentum near the wall.<br />

Shih et al. [10] observed effects <strong>of</strong> leading-edge airfoil fillet on the flow in a turbine. The increased size <strong>of</strong> the<br />

stagnation zones on the endwalls about the airfoil’s leading edge lowers the flow speed and velocity gradients there,<br />

which in turns reduces turbulence production. G. I. Mahmood et al. [11] studied the secondary structure in a blade<br />

passage with and without leading edge fillet and observed that the size and strength <strong>of</strong> the passage vortex become<br />

smaller with the fillets. T. Korakianitis et al. [12] has proposed a direct design method based on specifying blade<br />

surface-curvature distributions so as to minimize the chances <strong>of</strong> flow separation. Qi Lei et al. [13] analyzed the effect<br />

<strong>of</strong> leading edge modification on the secondary loss. They used vortex generator for introducing counter rotating<br />

vortex which oppose the passage vortex and hence reduce the secondary flow losses.<br />

Much work has been done to understand the occurrence and modeling <strong>of</strong> secondary flow and end loss phenomenon.<br />

Moreover researchers had tried to reduce the secondary loss in any cascade in order to get higher aerodynamic efficiency<br />

<strong>of</strong> the power plant. It is a well known fact that roughness over the blade surface increases the pr<strong>of</strong>ile loss in the cascade.<br />

But effect <strong>of</strong> roughness on the secondary flow and corresponding losses has not studied much. The secondary loss in<br />

smooth cascade has been compared with the secondary loss in the cascade having rough surface. This work is done in<br />

order to find out the effect <strong>of</strong> roughness present on the blade surfaces <strong>of</strong> the turbine cascade on the secondary loss<br />

2. Modeling<br />

The present computational study has been carried out using Computational Fluid Dynamics (CFD). The brief <strong>of</strong> CFD<br />

s<strong>of</strong>tware used and description <strong>of</strong> problem and boundary conditions is presented here.<br />

2.1 CFD simulation<br />

CFD is a computational technology that uses numerical methods and algorithms to solve and analyze problems that<br />

enables us to study the dynamics <strong>of</strong> flow. CFD uses numerical methods to solve the fundamental nonlinear<br />

differential equations that describe fluid flow (the Navier-Stokes and allied equations), for predefined<br />

geometries and boundary conditions.<br />

Using CFD, one can build geometry and provide proper boundary conditions representing the virtual prototype<br />

and then the computational s<strong>of</strong>tware predicts the fluid dynamics and performance <strong>of</strong> the prototype. Three-dimensional<br />

model <strong>of</strong> 6030 cascade geometry has been made with the help <strong>of</strong> Gambit® 2.2.3 as pre processor & FLUENT® 6.2 is<br />

used as solver & post processor for flow simulation. Theoretically, to analyze the fluid flow, the basic<br />

conservation equations have to be solved.<br />

a) Conservation <strong>of</strong> momentum (Navier-Stokes equation)<br />

∂ ∂<br />

∂p<br />

∂τ<br />

ij<br />

( ρ u<br />

i<br />

) + ( ρu<br />

iu<br />

j<br />

) = − + + ρg<br />

i<br />

+ Fi<br />

(2.1)<br />

∂t<br />

∂x<br />

∂x<br />

∂x<br />

b) Conservation <strong>of</strong> mass (Continuity equation)<br />

∂ρ<br />

+<br />

∂<br />

i m<br />

∂t<br />

∂xi<br />

c) Conservation <strong>of</strong> energy (Energy Equation)<br />

j<br />

(ρu<br />

) = S<br />

j<br />

j<br />

(2.2)<br />

133


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

∂<br />

( ρE)<br />

+<br />

∂<br />

( ui<br />

( ρ E + p))<br />

=<br />

∂ ∂T<br />

( keff<br />

− ∑ ' h ' j '<br />

+ u<br />

j j j j<br />

(τ<br />

ij<br />

)<br />

eff<br />

) + S h (2.3)<br />

∂t<br />

∂xi<br />

∂x i ∂xi<br />

FLUENT® converts unsolvable governing equations (Navier-Stokes equations) to a solvable set <strong>of</strong> algebraic equations<br />

for a finite set <strong>of</strong> points within the space under consideration. By visiting and solving the equations cell by cell as well as<br />

an iteration technique, all detailed information for velocity, pressure, temperature, and chemical species within that space<br />

are acquired.<br />

Turbulence modeling should be realistic as far as possible for obtaining a better result. The turbulence in turbomachinery<br />

flows is affected by rotation, curvature, three- dimensionality, separation, free stream turbulence, compressibility, large<br />

scale unsteadiness, heat transfer and other effects. Fluid flows <strong>of</strong> practical relevance are mostly turbulent which is<br />

responsible for transport <strong>of</strong> mass, momentum, heat, etc. in the flow. Turbulence models approximate these transport<br />

processes in terms <strong>of</strong> mean flow field by empirical formulations. Turbulence models modify the original unsteady Navier<br />

Stokes equations by introduction <strong>of</strong> averaged fluctuating components to produce Reynolds Averaged Navier Stokes<br />

(RANS) equations.<br />

The most widely used models for turbomachinery application is theκ -ε model (14). In this model, the turbulent kinetic<br />

energy (κ ) and the energy dissipation rate (ε ) are considered as the properties, which govern the turbulent flow<br />

phenomena. Standard κ -ω model is able to predict<br />

separation but misses out on some <strong>of</strong> the transport effect. The Realizable κ -ε turbulence model <strong>of</strong> Shih et al. [15] has<br />

been selected for solution <strong>of</strong> present problem. This model is expected to provide more accurate results since it contains<br />

additional terms in the transport equations for κ andε that are more suitable for stagnation flows and flows with high<br />

streamline curvature.<br />

2.2 Description <strong>of</strong> Computational Domain<br />

The present work is to analyze the secondary loss in smooth cascade and then comparing this loss with the secondary loss<br />

in the cascade having roughness <strong>of</strong> 500µm computationally using commercially available s<strong>of</strong>tware FLUENT® code. The<br />

FLUENT® code is based on finite volume technique and collocated grid method is used to compute the flow domain.<br />

The 6030 cascade pr<strong>of</strong>ile consists <strong>of</strong> three flow channels using four test blades placed in rectilinear cascade test section<br />

with appropriate stagger angle, chord, pitch, and inlet fluid flow angle and inlet/outlet section for fluid (air) to flow has<br />

been studied.<br />

A three dimensional model <strong>of</strong> the pr<strong>of</strong>ile 6030 (reaction) was created, with the help <strong>of</strong> Gambit® and the dimensions <strong>of</strong><br />

the model were kept same as the experiment performed by Samsher[16]. But due to the limitation <strong>of</strong> the available<br />

system processing <strong>of</strong> this pr<strong>of</strong>ile having five flow channels was not possible so the same pr<strong>of</strong>ile was designed in Gambit<br />

with four blades and three flow channels. Dimensions <strong>of</strong> the cascade & flow parameters for test section are shown in<br />

Table 1.<br />

Table 3.1 Cascade dimensions and flow parameter [16]<br />

Parameters Pr<strong>of</strong>ile 6030<br />

Chord (mm), c 50<br />

Pitch (mm), S 22<br />

Height (mm), l 95<br />

Blade stagger angle 70°<br />

Inlet flow angle 65°<br />

Number <strong>of</strong> blades 4<br />

Number <strong>of</strong> channels 3<br />

Working fluid<br />

Air<br />

Inlet air temperature 30°C<br />

134


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig. 1: Shape <strong>of</strong> turbine blade 6030 cascade model<br />

First <strong>of</strong> all a 2D model was created and then this 2-D model was converted into 3-D by sweeping the faces <strong>of</strong> the 2-D<br />

model by blade height. Flow is assumed to be symmetric about the mid span plane. After creating the desired volume<br />

which is subjected to fluid flow meshing <strong>of</strong> the same is done<br />

Fig. 2: 3-D meshing near the leading edge <strong>of</strong> blade 6030<br />

2.3 Boundary and Operating Conditions<br />

The atmospheric temperature is assumed to be constant at 27 °C, in experiment performed by Samsher [16] it varied from<br />

<strong>20</strong>°C to 35 °C. The velocity at the inlet is given as 102 m/s. The pressure outlet value at exit is assigned as zero gauge<br />

pressure, as the exit is directly exposed to atmosphere. The exit measurement plane is at 15 % distance <strong>of</strong> chord distance.<br />

Initially blade surfaces were kept smooth and results were obtained. In addition to these input conditions for study <strong>of</strong><br />

secondary flow loss, a roughness <strong>of</strong> 500µm was also applied on pressure and suction surfaces individually and then on both<br />

the surfaces together to see the effect <strong>of</strong> roughness on secondary flow.<br />

135


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig.3 : Measurement plane at 15% <strong>of</strong> the chord<br />

15 separate boundary zones were created from various faces & boundary types were assigned as follows<br />

Boundary zone<br />

Inlet faces<br />

Outlet faces<br />

Suction surface <strong>of</strong> blade 1<br />

Suction surface <strong>of</strong> blade 2<br />

Suction surface <strong>of</strong> blade 3<br />

Pressure surface <strong>of</strong> blade 2<br />

Pressure surface <strong>of</strong> blade 3<br />

Pressure surface <strong>of</strong> blade 4<br />

Lower inlet<br />

Upper inlet<br />

Lower outlet<br />

Upper outlet<br />

Boundary type<br />

Velocity inlet<br />

Pressure outlet<br />

Wall<br />

Wall<br />

Wall<br />

Wall<br />

Wall<br />

Wall<br />

Wall<br />

Wall<br />

Wall<br />

Wall<br />

2.4 Loss Calculation<br />

Since, the phenomenon <strong>of</strong> secondary flow is observed only at the end wall and at the mid space, it is assumed the loss is due<br />

to pr<strong>of</strong>ile loss, and at the end wall it will be sum <strong>of</strong> pr<strong>of</strong>ile loss and secondary loss. Thus to segregate secondary loss at the<br />

end wall pr<strong>of</strong>ile loss at the mid space was subtracted. The value <strong>of</strong> energy loss coefficient is given by eq 3.4<br />

136


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

⎡ ⎡<br />

γ<br />

P01<br />

− P02<br />

⎤<br />

2<br />

⎤⎤<br />

γ −1<br />

1 ⎢1<br />

⎥⎢<br />

⎡ P<br />

1 −<br />

s<br />

− − ⎢<br />

⎥⎥<br />

γ<br />

ξ<br />

y<br />

= ⎡ P2<br />

⎤<br />

⎣ ⎣ P01<br />

− P2<br />

⎦⎣<br />

P<br />

s s<br />

01 ⎦<br />

⎦<br />

(2.4)<br />

⎢ ⎥<br />

γ −1<br />

γ −1<br />

⎣ P01<br />

⎦ ⎡ ⎤<br />

γ ⎡<br />

⎤ γ<br />

⎢ ⎡ P2<br />

⎤ ⎡<br />

01<br />

−<br />

02<br />

⎤<br />

2<br />

⎤<br />

1−<br />

⎥<br />

⎢1<br />

− ⎢ ⎥⎢<br />

⎡ s<br />

P P P<br />

1 −<br />

s<br />

⎢ ⎢ ⎥ ⎥<br />

⎥⎥<br />

01<br />

⎣ ⎣ 01<br />

−<br />

2 ⎦⎣<br />

01 ⎦<br />

⎢<br />

⎣ P ⎦ P P<br />

s<br />

P<br />

⎥<br />

⎦<br />

⎣ ⎦<br />

γ −1<br />

3. Result and Discussion<br />

Initially the turbine cascade was designed by Gambit®. The boundary types were defined in the pre-processor itself.<br />

The exported mesh <strong>of</strong> the cascade was analyzed using the Fluent 6.2 as solver. The detailed boundary conditions<br />

were described in Fluent. The flow field <strong>of</strong> smooth turbine cascade was analyzed. The flow, pressure, velocity<br />

vector, flux were analyzed at appropriate location. Average total loss coefficients were computed from simulation<br />

results along blade pitch. Results were compared with experimental values <strong>of</strong> % loss coefficients measured along the<br />

pitch by Samsher [16] and shown in Fig. 4.<br />

Fig 4: Validation <strong>of</strong> computational result with the experimental result obtained by Samsher[16]<br />

There is good agreement between trend <strong>of</strong> computational results & experimental data. Aim <strong>of</strong> validation is to show that<br />

present numerical model used for simulation is reliable & can be used with confidence for further analysis & parametric<br />

studies.<br />

After validating the simulation model, the focus got shifted to the actual area <strong>of</strong> interest. The aim <strong>of</strong> this project is to find<br />

out the secondary loss in smooth and rough cascade and then analyzing the variation <strong>of</strong> secondary loss with roughness.<br />

Average total loss coefficients were computed from simulation results along the complete blade span. Average loss<br />

coefficients were computed at 2 mm interval for first 10 mm height from bottom end wall. Thereafter it was computed at<br />

every 5 mm interval till 85 mm blade height. Finally for the last 10 mm height it was again computed at every 2 mm<br />

interval. At the inlet, total pressure and at the exit, total as well as static pressure were being noted down along the whole<br />

blade span.<br />

The total (combined) losses in a blade cascade are estimated by the energy loss coefficient ζ , which is essentially the sum<br />

<strong>of</strong> pr<strong>of</strong>ile loss coefficient & end loss coefficient as given by Kostyuk and Frolov (<strong>19</strong>88) in equation 4.1.<br />

ζ (total) = ζ (pr) + ζ (sec) (3.1)<br />

Loss coefficient calculated at blade mid span, where the flow is two-dimensional & influence <strong>of</strong> end wall effect is<br />

not present, constitutes pr<strong>of</strong>ile losses and is representative <strong>of</strong> two dimensional reference flows. Thus end loss<br />

137


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

coefficient along blade height is calculated as the difference between the total and pr<strong>of</strong>ile energy loss coefficients in<br />

a cascade. Using the simulation result end losses along blade span which include all losses in end wall region are<br />

obtained by subtracting mid span value <strong>of</strong> pr<strong>of</strong>ile loss from individual average loss along the blade height.<br />

The pr<strong>of</strong>ile loss increases as the roughness is being applied to various surfaces. On applying roughness <strong>of</strong> magnitude<br />

500µm on pressure surface the computed averaged pr<strong>of</strong>ile loss is 16.3%, roughness on suction surface increases the<br />

pr<strong>of</strong>ile loss to 23.4% and finally when both the surfaces are rough then the value <strong>of</strong> pr<strong>of</strong>ile loss increases to 26.2%.<br />

Roughness on the blade surface increases the pr<strong>of</strong>ile loss due to thickening <strong>of</strong> boundary layer and expected<br />

separation. The main aim <strong>of</strong> this work is to analyze the secondary loss with the applied roughness. It was observed<br />

the average secondary loss in smooth blade is 1.7%. When a roughness <strong>of</strong> 500µm is applied to all the suction<br />

surfaces then average secondary loss is reduced to 1.3%, it increases to 1.5% when roughness is applied on both the<br />

surfaces and then it further reaches a value <strong>of</strong> 1.9% when roughness is applied to all the pressure surfaces. When<br />

roughness is present on all the suction surfaces the secondary loss is least. The probable reason <strong>of</strong> minimum<br />

secondary loss in this case can be accounted due to lack <strong>of</strong> mixing <strong>of</strong> passage vortex with the suction side vortex.<br />

This decreases the overall secondary loss. When roughness is present on PS as well as SS together then the<br />

secondary loss again increases to 1.7%. This increase in secondary loss can occur because <strong>of</strong> thickening <strong>of</strong> boundary<br />

layer due to roughness which leads to flow separation. Moreover the present <strong>of</strong> humps at hub and casing occur<br />

because <strong>of</strong> the formation <strong>of</strong> vortex cores that leads to increase in local energy loss coefficient. Variation <strong>of</strong> total loss<br />

in spanwise direction is shown in Fig 5<br />

Fig. 5: Comparison <strong>of</strong> secondary loss in a) smooth blades, b) all rough c) pressure surface rough d)<br />

suction surface rough.<br />

It is observed from the Fig. 5 that the loss coefficient is high at hub and casing due to the endwall boundary layers.<br />

The local increase in loss coefficient is observed corresponding to the secondary vortex cores near the hub and casing<br />

in all the four cases. As observed from the various energy loss vs non-dimensional span (y/S) curves in Fig. 5, in<br />

between 2-6% <strong>of</strong> the span adverse pressure gradient is present which causes humps near the hub and casing.<br />

Contour plots <strong>of</strong> total pressure distribution for the cascade having both the surfaces rough over entire computational<br />

domain at 1% span and 50% span are shown in Fig. 6 and Fig. 7. After entering cascade section total pressure drops<br />

due to expansion <strong>of</strong> fluid over the cascade section. At exit <strong>of</strong> cascade wakes are formed where total pressure drops<br />

significantly. However in core flow region, pressure drop is insignificant. At significant distance from trailing edge<br />

intermixing <strong>of</strong> core flow and wake takes place and eventually total pressure drops.<br />

At very close to end wall region wake bands are much broader & are much more diffused at very exit from blade<br />

trailing edge because <strong>of</strong> end wall boundary layer interaction as seen in Fig.6.<br />

138


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig. 6: Total pressure distributions in wake region at 1% span for the cascade having both the<br />

surface rough.<br />

Fig. 7: Total pressure distributions in wake region at 50% span for the cascade having both the<br />

surface rough<br />

139


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4. Conclusions<br />

• The pattern <strong>of</strong> variation <strong>of</strong> energy loss coefficient in spanwise direction (y/S) is same for smooth as well as rough<br />

blades. Moreover the Fig.5 shows that energy loss coefficient is least for smooth blades and it reaches the maximum<br />

value in case <strong>of</strong> the blade on which roughness is introduced on pressure as well as suction surface.<br />

• It is observed that applying roughness on blade surface definitely increases the pr<strong>of</strong>ile loss as well as total energy loss<br />

coefficient. But if both the surface <strong>of</strong> the blade get rough then the average secondary loss decreases by 11.76% against<br />

the value <strong>of</strong> secondary loss in a smooth cascade. If roughness is present only on suction surface then the average<br />

secondary loss is 1.3% against the average value <strong>of</strong> secondary loss <strong>of</strong> 1.7%. Moreover the average secondary loss is<br />

1.9% if roughness is applied to only pressure surface. Hence if roughness is present only on the suction surfaces then<br />

secondary loss can decreases by 23.5% in comparison <strong>of</strong> smooth blade<br />

• Due to the endwall boundary layers the loss coefficient is high at hub and casing.<br />

• Humps are observed near the hub and casing due to secondary vortex which increases the local energy loss coefficient<br />

Keywords: CFD, cascade, energy loss, roughness<br />

Nomenclature<br />

ρ<br />

Density<br />

u i Velocity vector<br />

S m Momentum Source Term<br />

P Static Pressure<br />

ρ Gravitational Body Force<br />

F i<br />

τ<br />

g i<br />

ij<br />

K eff<br />

J j’<br />

S h<br />

T<br />

E<br />

h<br />

P 2s<br />

P o1<br />

P o2<br />

γ<br />

ζ y<br />

External Body Force<br />

Stress Tensor<br />

Effective Thermal Conductivity<br />

Diffusion Flux<br />

Source term includes heat <strong>of</strong> chemical reaction<br />

Temperature<br />

Energy term<br />

Enthalpy<br />

Static pressure at outlet<br />

Total pressure at inlet<br />

Total pressure at outlet<br />

Ratio <strong>of</strong> specific heats for air<br />

Local energy loss coefficient<br />

References<br />

[1] Langston L. S., Nice M.L. and Hooper R.M., <strong>19</strong>77, “Three-Dimensional Flow within a Turbine Cascade Passage,<br />

"ASME Journal <strong>of</strong> Engineering for Power, 99, 21–28.<br />

[2] Marchal P., and Sieverding C.H., <strong>19</strong>77, “Secondary Flows Within Turbomachinery Bladings,” Secondary Flows<br />

in Turbomachines,” AGARD-CP-214, 11, 1–<strong>19</strong>.<br />

[3] Sieverding C.H and, Bosch P. Van den, <strong>19</strong>83, “The Use <strong>of</strong> Coloured Smoke to Visualise Secondary Flows in a<br />

Turbine-Blade Cascade, " ASME Journal <strong>of</strong> Fluid Mechanics, 134,85-89.<br />

[4] Wang H.P., Olson S.J., Goldstein R.J., Eckert E.R.G., <strong>19</strong>97, “Flow visualization in a linear turbine cascade <strong>of</strong> high<br />

performance turbine blades,” ASME Journal <strong>of</strong> Turbomachinery, 1<strong>19</strong>, 1-8.<br />

[5] Sharma O.P. and Butler T.L, <strong>19</strong>87, “Predictions <strong>of</strong> Endwall Losses and Secondary Flows in Axial Flow Turbine<br />

Cascades,” ASME Journal <strong>of</strong> Turbo machinery, 109, 229-236.<br />

[6] Moon, Young J. and Koh Sung-Ryong, <strong>20</strong>00, “Counter-rotating streamwise vortex formation in turbine cascade with<br />

endwall fencing,” Computers And Fluids, 30, 473-490.<br />

[7] Saha Arun K. and Acharya Sumanta, <strong>20</strong>08, “Computations <strong>of</strong> Turbulent Flow and Heat Transfer Through a<br />

Three-Dimensional Nonaxisymmetric Blade Passage,” ASME Journal <strong>of</strong> Turbomachinery, 130, 031008-1-<br />

031008-10.<br />

140


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[8] Sonoda Toyotaka, Hasenjäger Martina, Arima Toshiyuki and Sendh<strong>of</strong>f Bernhard, <strong>20</strong>09, “Effect <strong>of</strong> End Wall<br />

Contouring on Performance <strong>of</strong> Ultra-Low Aspect Ratio Transonic Turbine Inlet Guide Vanes,” ASME Journal <strong>of</strong><br />

Turbomachinery, 131, 0110<strong>20</strong>-1- 0110<strong>20</strong>-11.<br />

[9] Brear Michael J., Hodson Howard P., Gonzalez Palom and Harvey Neil W., <strong>20</strong>02, “Pressure Surface Separations<br />

in Low-Pressure Turbines—Part 2: Interactions With the Secondary Flow,” Transactions <strong>of</strong> the ASME, 124, <strong>20</strong>02,<br />

402-409.<br />

[10] Shih T. I-P. and Lin Y.L, <strong>20</strong>03, “Controlling Secondary-Flow Structure by Leading-Edge Airfoil Fillet and Inlet<br />

Swirl to Reduce Aerodynamic Loss and Surface Heat Transfer,” Transactions <strong>of</strong> the ASME, 125, 48-56.<br />

[11] Mahmood, G.I. and Acharya S., <strong>20</strong>07, “Experimental Investigation <strong>of</strong> Secondary Flow Structure in a Blade<br />

Passage With and Without Leading Edge Fillets,” ASME Journal <strong>of</strong> Fluids Engineering, 129, , pp. 253-262.<br />

[12] Korakianitis T. and Hamakhan I. A., <strong>20</strong>10, “Aerodynamic Performance Effects <strong>of</strong> Leading-Edge Geometry in Gas-<br />

Turbine Blades,” Applied Energy, 87,1591–1601.<br />

[13] Lei Qi, Zhengping Zou, Peng Wang, Teng Cao and Huoxing Liu, <strong>20</strong>11, “Control <strong>of</strong> Secondary Flow Loss in<br />

Turbine Cascade by Streamwise Vortex ,” Computers & Fluids, 54, 45-55.<br />

[14] Launder B. E. and Spalding D. B,<strong>19</strong>74, “The Numerical Computation <strong>of</strong> Turbulent Flows, Computer Methods in<br />

Applied Mechanics and Engineering,” 3 , 269-289.<br />

[15] Shih. T. H., Liou W.W., Shabbir A. and Zhu J., <strong>19</strong>95, “A New κ -ε Eddy Viscosity Model For High Reynolds<br />

Number Turbulent Flows –Models Development & Validation,” Computer And Fluids, 24, 227-238.<br />

[16] Samsher, <strong>20</strong>02, “Effect Of Blade Surface Roughness on Pr<strong>of</strong>ile Loss and Exit Angle in A Rectilinear Steam<br />

Turbine Cascade,” Ph.D. Thesis, Mech. Engg. Dept. IIT Delhi<br />

141


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

AN OVERALL EVALUATION OF FLOW CHARACTERISTICS AND<br />

PERFORMANCE PARAMETERS OF Y-SHAPED DIFFUSING DUCT<br />

WITH SAME ANGLE OF TURN AND DIFFERENT CENTERLINE<br />

LENGTH & RADIUS OF CURVATURE<br />

Netrapal Singh 1 , Abdur Rahim 2 , Md. Islam 3<br />

1 Research Scholar, Department <strong>of</strong> Mechanical Engineering, JMI Delhi, India<br />

2 Associate Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, JMI Delhi, India<br />

3 Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, JMI Delhi, India<br />

Abstract<br />

The several set <strong>of</strong> experiments have been carried out to compare the flow and performance characteristics <strong>of</strong><br />

both Y-ducts made <strong>of</strong> epoxy resin having centerline length(300mm&600mm) and radius <strong>of</strong><br />

curvature(382mm&764mm).for both sets <strong>of</strong> y-ducts area ratio and aspect ratio keep constant i.e. 2 with turning<br />

angle 22.5 0 /22.5 0 . The inlet shape <strong>of</strong> both limbs <strong>of</strong> Y duct is rectangular while the outlet is circular. All the<br />

experiments have been carried out for a fixed velocity ratio 1.2(suction to free stream velocity). The maximum<br />

average inlet velocity at the inlet <strong>of</strong> duct is 15.06m/s.The flow in duct is created by suction with the help <strong>of</strong><br />

pipeline network which directly connected at the inlet <strong>of</strong> centrifugal blower with the help <strong>of</strong> control valve<br />

followed by a sliding door. The all parameters are measured with the help <strong>of</strong> a calibrated five hole probe. The<br />

results are presented in the form <strong>of</strong> 3-D plots for longitudinal velocity at inlet, contour plots for velocity and<br />

pressure as well as vector plots for secondary velocity along with wall pressure and mass averaged pressure<br />

recovery coefficients and loss coefficients. The surfer graphic package based on finite volume method is used for<br />

all plots.<br />

Keywords Y-Shaped Diffusing Duct, turning angle, Centerline length, Radius <strong>of</strong> curvature, C P and C Loss .<br />

1. Introduction<br />

The Y-shaped ducts are used as intake ducts in aircrafts, as air intake is a crucial component <strong>of</strong> the propulsion<br />

system <strong>of</strong> modern combat aircraft. From aerodynamic point <strong>of</strong> view, small and short intake is desirable to<br />

minimize the loss while maintaining the mass flow requirements and meeting the space constraint <strong>of</strong> the aircraft.<br />

These ducts fulfill the requirements <strong>of</strong> higher flow and less distortion, due to space constraints and geometrical<br />

variations, diffusion make the flow characteristics quite complex. Curvature <strong>of</strong> limbs <strong>of</strong> duct generates<br />

centrifugal forces, which get balanced by the pressure gradient in the plane <strong>of</strong> the bend. The central part <strong>of</strong> the<br />

fluid is forced outwards to satisfy the continuity resulting in generation <strong>of</strong> secondary flows.<br />

Martin and Holzhauser (<strong>19</strong>49) have conducted experiments for pressure recovery and mass flow characteristics<br />

in a single and twin submerge intake duct system on the both side <strong>of</strong> the fuselage at various angles <strong>of</strong> the side lip.<br />

They have showed that the twin intake air induction system had unstable air flow characteristics. Intake must<br />

meet the engine mass flow requirement for a combat aircraft steady and symmetric condition over a wide range<br />

<strong>of</strong> aircraft speed and altitude ensuring higher pressure recovery and less distorted flow (Whitford, <strong>19</strong>87). This<br />

makes the compressor more sensitive to the flow field at the inlet <strong>of</strong> the engines and hence performance <strong>of</strong><br />

aircraft engine also depends on the flow characteristics at the end <strong>of</strong> the intake duct.Sudhakar and Ananthkishnan<br />

(<strong>19</strong>95) have explained the jump phenomenon caused due to transition from symmetric to asymmetric operation<br />

in Y-duct in supersonic flight.Ahmed and Kumar (<strong>20</strong>02) have studied the mechanism <strong>of</strong> flow instability at<br />

supersonic speed on twin intake duct. They have shown the presence <strong>of</strong> flow instability in the form <strong>of</strong> shock<br />

oscillation at moderate exit area and it is initiated when the terminal shock is expelled from the inside <strong>of</strong> the<br />

intake. An experimental study has been done by Sullery et al. (<strong>20</strong>02) to reduce the exit flow distortion and<br />

improving the total pressure recovery in two-dimensional s-diffuser using various fences and vortex generators.<br />

Their results indicate that substantial improvement in static pressure rise and flow quality is possible with<br />

judicious deployment <strong>of</strong> fences and vortex generators. Gorton (<strong>20</strong>04) also did similar experimentation along with<br />

the computational investigation on different flush mounted inlets. The reversal <strong>of</strong> the pressure recovery trend<br />

with increasing inlet mass-flow at low and high Mach numbers was predicted by CFD. However, in the CFD<br />

simulation they observed that CFD results show larger losses than experimental results. Patel et al (<strong>20</strong>05) have<br />

examined the effect <strong>of</strong> different inflow conditions on the flow characteristics <strong>of</strong> the Y-Shaped rectangular duct<br />

having 22.5°/22.5° angle <strong>of</strong> turn and AR 2.0. Their studies have shown that static pressure recovery decreases<br />

with increase <strong>of</strong> skewness and strong secondary flow exist throughout length <strong>of</strong> the diffuser. They have also<br />

observed deflection <strong>of</strong> flow toward the outer wall along the length <strong>of</strong> the diffuser.<br />

Experimental facility & Y - duct:<br />

142


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Experimental investigation has been carried out to establish the flow and performance characteristics <strong>of</strong> Y-<br />

shaped rectangular duct-fuselage assembly with fixed velocity ratio (1.2) i.e. suction to free stream velocity by<br />

adjusting the control valve and inlet throttle valve (figure-1(a)). The experimental investigation has been carried<br />

out at a free stream velocity 15.06 m/s by adjusting the opening <strong>of</strong> the sliding gate provided at the suction <strong>of</strong><br />

blower. Although higher velocities could have been obtained by the blower, it was not feasible to operate at<br />

higher flow rates. This was due to constraints <strong>of</strong> the starter unit <strong>of</strong> the blower and the noise generated at the<br />

higher flow rates. Due to these constraints, the velocity <strong>of</strong> 15.06 m/s (R n =0.685 ×10 5 ) was the maximum<br />

achievable in the set-up. Measurements have been made at ten planes at turning angle <strong>of</strong> 0° (inlet), 11.25°, 22.5°,<br />

22.5°/11.25° in both limbs (four+four) and than merger & outlet section (Singh et al, <strong>20</strong>12) along the length <strong>of</strong><br />

the duct (figure 1(b)).The number <strong>of</strong> measuring stations at each plane in the radial direction varies from four to<br />

ten, with at each station <strong>19</strong> or more measurements points in the lateral direction for velocity and pressures. At<br />

every station, the probe was inserted through the slot provided on the top wall and it was traversed along the<br />

lateral direction. Inserts made-up <strong>of</strong> Perspex with step height equal to the top wall thickness (12 mm) <strong>of</strong> the duct<br />

were used to cover the unused portion <strong>of</strong> the slots while carrying out the probe measurements(figure(c)). The<br />

atmospheric pressure and temperature were recorded twice during the run <strong>of</strong> each experiment in a day.<br />

To obtain the different parameters, the probes were traversed at the pre-selected locations in the lateral direction.<br />

The number <strong>of</strong> measurement locations at a measurement planes were between 76 and 248. To measure the<br />

velocity and pressure distribution, the pre-calibrated five-hole probe (Bryer and Pankhurst, <strong>19</strong>71) was first<br />

mounted with the traversing mechanism and then inserted into the duct. The five tubes <strong>of</strong> the five-hole probe &<br />

the two side tubes <strong>of</strong> the pitot static tube were connected with the multi-tube inclined manometer having an<br />

accuracy <strong>of</strong> 0.1 mm (figure 8). In addition, the two side tubes <strong>of</strong> the orifice meter were also connected across an<br />

inclined U-tube water manometer. At each point <strong>of</strong> measurement, the probe was rotated in the horizontal plane<br />

about its vertical axis such a way that the two side tubes read the same pressure that was monitored on the<br />

inclined multi-tube water manometer. The zero angle for the probe was fixed with the flow direction at the inlet.<br />

The positioning <strong>of</strong> the sensing head <strong>of</strong>fset due to probe rotation was always brought back to its original position<br />

using the traverse mechanism. After the probe alignment the angular position <strong>of</strong> the probe was recorded with an<br />

accuracy <strong>of</strong> ± 0.5° (resolution <strong>of</strong> the protractor) and the readings from all tubes <strong>of</strong> the five-hole probe recorded<br />

from the inclined multi-tube water manometer.From these measurements and calibration curves, velocities and<br />

pressures were evaluated using the atmospheric pressure and temperature readings. These steps were repeated at<br />

each measuring point.<br />

The measured velocity by the five-hole probe is resolved into two components as longitudinal and cross-flow<br />

velocities. For normalization <strong>of</strong> velocity and pressure terms, the mass-averaged longitudinal velocity and massaveraged<br />

dynamic pressure at section-inlet are used respectively. The results are presented in the form <strong>of</strong> 3-D<br />

plots for normalized longitudinal velocity and vector plots for normalized cross-flow velocity. For 3-D and<br />

vector plots, ‘SURFER’ s<strong>of</strong>tware graphics package is used, which uses ‘Kriging’ method. Kriging is a<br />

geostatistical gridding method, which produces a regularly spaced, rectangular array <strong>of</strong> Z values from irregularly<br />

spaced XYZ data. Using the ‘XYZ’ data, the grid file is generated and thereafter ‘Cubic Spline’ method is used<br />

for smoothening the grid which is a rectangular region comprised <strong>of</strong> evenly spaced rows and columns. The grid<br />

files are used to produce 3-D and vector plots.<br />

2. Results & discussions<br />

Longitudinal Velocity Distribution<br />

Both the inlets <strong>of</strong> ducts shows more or less symmetric fluid flow contours except to the walls. Due to curvature<br />

effect, fluid flow towards concave wall in the first half bend and continuously developing along the same<br />

curvature in the second half [convex wall in the second half].The inflexion plane shows separation <strong>of</strong> flow at the<br />

convex wall. The two flow regimes mixed with each other at merger plane resulting uniform intensity <strong>of</strong> pair <strong>of</strong><br />

vortices. Central region occupy the core flow and decay in a uniform manner from central region to outer walls.<br />

At the exit plane weak intensities pair <strong>of</strong> vortices slowly-slowly disappeared which signifies smooth merger with<br />

sufficient space along with axial length to settle the flow i.e. nearly uniform flow. The normalized longitudinal<br />

velocity (U long /U ave(in) ) contour plots <strong>of</strong> different cross-sections at 10° & <strong>20</strong>° yaw for the intake duct A(Right<br />

Limb) and duct B(Left Limb). The contours <strong>of</strong> Right Limb & Left Limb <strong>of</strong> section 1, 2 & 3 shows asymmetric<br />

flow magnitudes due to 10° & <strong>20</strong>° yaw at right side up to inflexion plane. These figures are not presented due to<br />

constraints on space.<br />

Figure 2(b, c) & Figure 3(b, c) <strong>of</strong> normalized longitudinal 3-D velocity (U long /U ave(in) ) contour plots also supports<br />

this flow behavior in which skin friction <strong>of</strong> forebody/fuselage plays important role due to that flow divert its<br />

direction at both the inlets <strong>of</strong> duct.<br />

Cross flow velocity distribution<br />

143


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Normalized cross flow velocity (U sec /U ave(in) ) distribution at different planes for the 22.5 0 /22.5 0 , Y-shaped<br />

diffusing duct also analyzed & found that there is no significant variation observed in the cross flow velocity<br />

distribution upto section (4) for 22.5 0 /22.5 0 , in Y-shaped diffusing duct. The cross flow velocity pattern is nearly<br />

similar throughout, in both inlet limbs <strong>of</strong> Y-duct. At the merger, two streams are mixed with each other, centrally<br />

core flow with almost uniform intensity <strong>of</strong> pair <strong>of</strong> vortices found. The secondary flow pattern seen at the exit<br />

plane shows, presence <strong>of</strong> two pair <strong>of</strong> vortices, with central pair having weak intensity. These figures are not<br />

presented due to constraints on space.<br />

3-D Wire Mesh Longitudinal Velocity Distribution<br />

Figure 2(a,b,c) & Figure 3(a,b,c) shows normalized longitudinal 3-D velocity (U long /U ave(in) ) contour plots at 0° ,<br />

10° & <strong>20</strong>° yaw angles at inlet cross-sections for the intake duct A(Right Limb) and duct B(Left Limb). The 3-D<br />

wire mesh plot supports velocity distribution at both the inlets. These plots also clarifies that 0° yaw angle have<br />

better performance comparatively with 10° & <strong>20</strong>° yaw angles in both ducts. Hence as yaw angles increases<br />

performance deteriorates. The flow uniformity is better in 600 C L in comparison with 300 mm C L .<br />

Total and Static Pressure Variations<br />

The total and static pressure distributions at the various sections, supports the velocity distribution. The variation<br />

in the static pressure distribution at the merger plane ranging between (-2.5 to -1.5), and for exit plane ranging<br />

between (-1.6 to -2.6) for 0° yaw angle, and for 10° yaw angle the merger plane range is (-3.7 to -1.7 to -3.2),<br />

and at the exit plane it is order <strong>of</strong> (-3.2 to -1.7 to -3.2) and for <strong>20</strong>° yaw angle the merger plane range is (-1.5 to -<br />

2.5), and at the exit plane it is order <strong>of</strong> (-1.6 to -2.0 to -1.4).The total pressure distribution is almost identical to<br />

the longitudinal velocity distribution. These figures are not presented due to constraints on space.<br />

Wall pressure distribution<br />

The curved wall averaged static pressure coefficient variations for different locations with different yaw angles<br />

along the length <strong>of</strong> the both ducts are presented in Fig. 4 & Fig. 6. At the inlet, there is no significant variation in<br />

the static pressure coefficient for all the tapping and this supports the longitudinal velocity distribution at the<br />

inlet. Due to corner effect <strong>of</strong> curvature some drop observed initially which further increases. The wall pressure<br />

coefficient increases continuously along the outer wall <strong>of</strong> the first bend and inner wall <strong>of</strong> the second bend,<br />

whereas on the opposite side it increases up to the point <strong>of</strong> inflexion and is followed by a fall. This shows the<br />

movement <strong>of</strong> the fluid core towards the concave surface. As the flow moves downstream, the static pressure<br />

coefficient starts to increase again due to accumulation <strong>of</strong> fluid near the inner surface <strong>of</strong> the second bend.<br />

Performance Characteristics<br />

Variations <strong>of</strong> the mass-averaged static pressure recovery coefficient and total pressure loss coefficient with<br />

different yaw angles for both the limbs are presented in Fig. 5 & Fig. 7. For limb A, the mass-averaged static<br />

pressure recovery coefficient increases continuously in the first bend and a slight reduction in the rate <strong>of</strong><br />

recovery coefficient is observed near to the inflexion plane due to a change in the direction <strong>of</strong> curvature, which<br />

leads to turbulent mixing. In the second bend, the fluid recovers its lost energy and the loss coefficient is nearly<br />

constant up to the exit <strong>of</strong> diffusing duct, except at X/L=0.45 & X/L=0.75,where some depression occurs. This<br />

may be due to the growth <strong>of</strong> boundary layer and increase in the losses due to rapid mixing. More or less similar<br />

trend found in limb B. It is observed that the variation <strong>of</strong> total pressure loss is almost linear along the whole<br />

length <strong>of</strong> the duct. The values <strong>of</strong> static pressure recovery coefficient and total pressure loss coefficient are 0.38,<br />

0.37, 0.35 and 0.25, 0.24, 0.23 respectively for the yaw angles <strong>of</strong> 0 0 , 10 0 and <strong>20</strong> 0 for 300mm C L and The overall<br />

static pressure recovery coefficient for 600 mm C L ducts with the angle <strong>of</strong> turn <strong>of</strong> 22.5°/22.5° are 0.51, 0.50 and<br />

0.48 with respect <strong>of</strong> yaw angles <strong>of</strong> 0 0 ,10 0 ,<strong>20</strong> 0 . The corresponding values <strong>of</strong> loss coefficient are 0.39, 0.38 and<br />

0.37, respectively.<br />

3. Conclusions<br />

1. The nearly uniform pattern <strong>of</strong> contours as well as 3-D wire-mesh plots at inlet signifies flow stability in<br />

settling chamber i.e. in front <strong>of</strong> both the inlet limbs.<br />

2. The high magnitude core flow clearly depicts the reasoning <strong>of</strong> suction controlled flow.<br />

3. From inlet to merger and further up-to exit, as curvature increases recovery coefficient also increases and it<br />

is proportionate to fluid flow from inlet to exit and the loss coefficient is nearly constant, with this turning<br />

angle.<br />

4. The overall performance <strong>of</strong> duct with 600 mm C L & 764 mm R C shows better flow stabilization along with<br />

pressure recovery in comparison with duct <strong>of</strong> 300 mm C L & 382 mm R C with same turning angle and area<br />

ratio.<br />

144


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5. The duct/diffuser effectiveness (as defined C p / C p (ideal) ) was found 68% for duct with 600 mm C L & 764 mm<br />

R C while the duct/diffuser effectiveness (as defined C p / C p (ideal) ) was found 50.7% for duct <strong>of</strong> 300 mm C L &<br />

382 mm R C .<br />

6. At the merger, two streams are mixed with each other, centrally core flow with almost uniform intensity <strong>of</strong><br />

pair <strong>of</strong> vortices found. The secondary flow pattern seen at the exit plane shows presence <strong>of</strong> two pair <strong>of</strong><br />

vortices with central pair having weak intensity. When two streams mixed at the merger plane distortion<br />

occurs in the flows and it is finally settle down at the exit and flow distribution is uniform at the exit.<br />

Notations<br />

AR: area ratio (Outlet area <strong>of</strong> the duct / Inlet area <strong>of</strong> both limbs <strong>of</strong><br />

the duct)<br />

C P: coeff.<strong>of</strong> static pressure recovery (=(Ps o - Ps i )/P dyn(in) )<br />

U ave(in) :mass-averaged velocity at inlet,<br />

(m/sec)<br />

CV: convex surface<br />

C Loss: coeff. <strong>of</strong> total pressure loss (=(Po i - Po o ) / P dyn(in) ) P wall: wall static pressure, (N/m 2 )<br />

Ps i: mass-averaged static pressure at inlet, (N/m 2 )<br />

Ps o: mass-averaged static pressure at outlet, (N/m 2 )<br />

CC: concave surface<br />

L: axial length along duct, (m)<br />

Po i: mass-averaged total pressure at inlet, (N/m 2 ) ρ : fluid density, (kg/m 3 )<br />

Po o : mass-averaged total pressure at outlet, (N/m 2 )<br />

P dyn(in) : dynamic pressure at inlet (=1/2 ρU 2 ave(in) ), (N/m 2 )<br />

h: height <strong>of</strong> duct at inlet,(mm)<br />

w: width <strong>of</strong> duct at inlet,(mm)<br />

X: distance along the centerline <strong>of</strong> the duct from the inlet plane, (m) C L : centerline length (mm)<br />

Y: distance perpendicular to the centerline <strong>of</strong> the duct from the inlet<br />

plane, (m)<br />

θ : rotation angle (angle <strong>of</strong> rotation <strong>of</strong> the five-hole probe), (deg)<br />

U long :velocity in the axial direction,<br />

(m/sec)<br />

R C : radius <strong>of</strong> curvature (mm).<br />

C p (ideal) = [1-{1/ (AR) 2 }]<br />

Acknowledgement<br />

The author is very grateful to Pr<strong>of</strong>essor V. Seshadri & Pr<strong>of</strong>essor S. N. Singh, Applied Mechanics Department,<br />

IIT Delhi, for their support & help during the period <strong>of</strong> experimentation and many useful discussions. I am also<br />

very grateful <strong>of</strong> staff members <strong>of</strong> different labs for their commitment and support, as provided during the tenure.<br />

References<br />

[1] Martin, N.J., and Holzhauser, C.A., “An experimental investigation at large scale <strong>of</strong> single and twin NACA<br />

submerged side intakes at several angles <strong>of</strong> sideslip”, NACA RM-A9F<strong>20</strong>, Aug. <strong>19</strong>49.<br />

[2] Whitford, F <strong>19</strong>87,”Design for Air Combat” Jane publication London.<br />

[3] Sudhakar K. and Ananthkishanan N, <strong>19</strong>95, ‘Jump phenomenon in Y-shaped intake ducts’, J. Aircraft, 33 (2),<br />

pp 438-439.<br />

[4] Ahmed S and Kumar V., <strong>20</strong>02, ‘Investigation <strong>of</strong> Flow Instability in Pitot Intake at Mach number <strong>of</strong> 1.6’,<br />

Proc. 9 th Asian Congress <strong>of</strong> Fluid Mechanics, Isfahan, Iran<br />

[5] Sullery, R. K., Mishra, S. and Pradeep, A. M., <strong>20</strong>02. "Application <strong>of</strong> boundary layer fences and vortex<br />

generators in improving performance <strong>of</strong> S-duct diffusers", Trans. ASME., Journal <strong>of</strong> Fluid Engineering, vol.<br />

124, pp. 136 - 142.<br />

[6] Gorton, S.A., Owens, L. R., Jenkins, L. N., Allan, B. G., Schuster, E. P., <strong>20</strong>04, ‘Active flow control on a<br />

boundary-layer-ingesting inlet’, NASA-AIAA-<strong>20</strong>04-1<strong>20</strong>3<br />

145


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[7] Patel T., Singh S. N. and Seshadri V., <strong>20</strong>05, ‘Characteristics <strong>of</strong> Y- shaped rectangular diffusing duct at<br />

different inflow condition’ J. Aircraft, 42 (1), pp 113-1<strong>20</strong>.<br />

[8] Singh, Netrapal., Rahim, Abdur., and Islam, Md.,’ Flow Characteristics <strong>of</strong> a Symmetric Y-Shaped Diffusing<br />

Duct at Different Cross Sections With Zero Yaw Angle’ Indian Journal <strong>of</strong> Engineering and Materials,<br />

<strong>20</strong>11.(Under Publication).<br />

[9] Bryer, D. W. and Pankhurst, R. C., <strong>19</strong>71.“Pressure-probe methods for determining wind speed and flow<br />

direction”, Pub. Her Majesty’s Stationery Office, London<br />

146


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

147


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Left Limb<br />

(Velocity Ratio = 1.2)<br />

(CL = 300 mm & RC=382 mm)<br />

RightLimb<br />

Ulong / Uave.<br />

Ulong / Uave.<br />

y/h<br />

x/h<br />

(a)<br />

y/h<br />

x/h<br />

Section-1 Inlet- 0 degree<br />

Section-1 Inlet- 0 degree<br />

Left Limb<br />

RightLimb<br />

Ulong / Uave.<br />

Ulong / Uave.<br />

y/h<br />

Section-1 Inlet- 10 degree<br />

x/h<br />

(b)<br />

y/h<br />

Section-1 Inlet- 10 degree<br />

x/h<br />

Section-1 Inlet- <strong>20</strong> degree<br />

Section-1 Inlet- <strong>20</strong> degree<br />

Ulong / Uave.<br />

Left Limb<br />

Ulong / Uave.<br />

RightLimb<br />

y/h<br />

x/h<br />

(c)<br />

y/h<br />

x/h<br />

Fig.2(a,b,c): 3 D-Normalised Vlong Wire-mesh Plots at 0,10,<strong>20</strong> Degree Yaw <strong>of</strong> Both Inlets.<br />

148


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Left Limb<br />

(Velocity Ratio =1.2)<br />

(CL=600 mm & RC=764 mm)<br />

Right Limb<br />

Ulong/Uave.<br />

y/h<br />

y/h<br />

x/h<br />

x/h<br />

Inlet Left<br />

(a) 0 degree yaw<br />

Inlet Right<br />

y/h<br />

x/h<br />

y/h<br />

x/h<br />

Inlet Left<br />

(b) 10 degree yaw<br />

Inlet Right<br />

Ulong/Uave.<br />

Ulong/Uave.<br />

Ulong/Uave.<br />

Ulong/Uave.<br />

Ulong/Uave.<br />

y/h<br />

x/h<br />

y/h<br />

x/h<br />

Inlet Left (c) <strong>20</strong> degree yaw Inlet Right<br />

Figure 3 (a,b,c) : 3 D-Normalised Vlong Wire-mesh Plots at 0,10,<strong>20</strong> Degree Yaw <strong>of</strong> Both Inlets.<br />

149


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

PWall0 PWall10 PWall<strong>20</strong><br />

X/L<br />

-0.3<br />

X/L 0.15 0.35 0.5 0.65 0.8<br />

-0.414<br />

-0.6<br />

-0.597<br />

-0.688<br />

-0.667<br />

-0.588<br />

-0.529<br />

-0.747<br />

P wall<br />

-0.9<br />

-0.93<br />

-1.021<br />

-1<br />

-0.921<br />

-0.862<br />

-1.08<br />

-1.2<br />

-1.263<br />

-1.354<br />

-1.333<br />

-1.254<br />

-1.<strong>19</strong>5<br />

-1.5<br />

Fig.4: Wall pressure distribution <strong>of</strong> different yaw along duct length.<br />

Cp-A0<br />

X/L<br />

C & C<br />

0.4<br />

0.35<br />

0.3<br />

0.25<br />

0.2<br />

0.15<br />

Cp-A10<br />

Cp-A<strong>20</strong><br />

Cp-B0<br />

Cp-B10<br />

Cp-B<strong>20</strong><br />

C loss-A0<br />

C loss-A10<br />

C loss-A<strong>20</strong><br />

C loss-B0<br />

C loss-B10<br />

C loss-B<strong>20</strong><br />

0.1<br />

0.05<br />

0<br />

X/L 0 0.1 0.2 0.4 0.6 0.8 0.9<br />

Fig.5:Variation <strong>of</strong> performance parameters along duct length.<br />

150


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

PWall0 PWall10 PWall<strong>20</strong><br />

X / L<br />

-0.3<br />

0 0.2 0.4 0.6 0.8 1<br />

-0.414<br />

-0.6<br />

-0.597<br />

-0.688 -0.667<br />

-0.588<br />

-0.529<br />

-0.784<br />

Pwall<br />

-0.9<br />

-1.2<br />

-0.967<br />

-1.317<br />

-1.058 -1.037<br />

-1.408 -1.387<br />

-0.958<br />

-1.308<br />

-0.899<br />

-1.249<br />

-1.134<br />

-1.5<br />

Figure 6 :w all pressure distribution for different yaw along duct length<br />

Cp & C loss<br />

0.5<br />

0.4<br />

0.3<br />

0.2<br />

Cp-A0<br />

Cp-A10<br />

Cp-A<strong>20</strong><br />

Cp-B0<br />

Cp-B10<br />

Cp-B<strong>20</strong><br />

C loss-A0<br />

C loss-A10<br />

C loss-A<strong>20</strong><br />

C loss-B0<br />

C loss-B10<br />

C loss-B<strong>20</strong><br />

X / L<br />

0.1<br />

0<br />

0 0.2 0.4 0.6 0.8 1<br />

Figure 7 :Variation <strong>of</strong> performance parameters w ith different yaw along duct<br />

length<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

(a): Centrifugal blower with motor assembly<br />

(b): Flexible joint & Diverging cone<br />

(c): Traversing unit & probe (300 mm)<br />

(d): Y-duct with fore-body (300 mm)<br />

(e): Showing different measurement<br />

Sections (600mm)<br />

(f): Data collection <strong>of</strong> different tubes,<br />

orifice meter & five hole probe<br />

(g): Entire experimental set-up<br />

(h): Back view <strong>of</strong> pipeline network with<br />

inclined multi-tube water manometer<br />

Showing photographs <strong>of</strong> 300 mm & 600 mm centerline length for test Y-ducts<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

REVIEW OF DIFFERENT TECHNOLOGIES IN THE<br />

SOLAR ABSORPTION AIR-CONDITIONING SYSTEMS<br />

Vinod Sehrawat a , Tarun Gupta a , Raj Kumar b<br />

a<br />

Department <strong>of</strong> Mechanical Engineering, NGF College <strong>of</strong> Engineering and <strong>Technology</strong>, Palwal, Haryana, India,<br />

email: vinodsehrawat@yahoo.com, tarungupta<strong>19</strong>76@yahoo.com<br />

b Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad<br />

Abstract<br />

The aim <strong>of</strong> this article is to review the currently available solar air-conditioning technologies, their energy<br />

saving potential and technical limitations. The scope <strong>of</strong> this article is to brief the processes and to consolidate<br />

the commercially available solar cooling technologies for comparison. Although a large potential market exists<br />

for this technology, existing solar cooling systems are not yet competitive with conventional electricity-driven or<br />

gas-fired air-conditioning systems because <strong>of</strong> their high initial costs. In this paper, the technologies working only<br />

on liquid absorption cycle are discussed in brief. The paper looks at ways <strong>of</strong> improving the performance <strong>of</strong> the<br />

solar air-conditioning (chiller) subsystems by using the different technology.<br />

Keywords: Solar Air-conditioning; Absorption chiller; Lithium bromide and water; Generator Temperature<br />

1. Introduction<br />

In a country like India, the availability <strong>of</strong> solar irradiation is abundant for most part <strong>of</strong> the year. Solar airconditioning<br />

is a particularly attractive application because <strong>of</strong> the near coincidence <strong>of</strong> peak cooling loads with<br />

the intensity <strong>of</strong> available solar energy. The earth receives in just 1 h, more energy from the sun than what we<br />

consume in the whole world for 1 year [1]. Its application was proven to be most economical, as most systems in<br />

individual uses requires but a few kilowatt <strong>of</strong> power. The solar cooling technologies are mainly classified into<br />

two main groups depending on the energy supply: a thermal/work driven system and electricity (Photovoltaic)<br />

driven system [2]. Each group can further be classified as the following:<br />

1. Thermal/work driven system based on absorption refrigeration cycle; adsorption refrigeration cycle; chemical<br />

reaction refrigeration cycle; desiccant cooling cycle and ejector refrigeration cycle<br />

2. Electricity (Photovoltaic) driven system based on vapour compression refrigeration cycle; thermo-electric<br />

refrigeration cycle and stirling refrigeration cycle.<br />

Of the different cycles mentioned above, the absorption refrigeration cycle appears to be one <strong>of</strong> the most<br />

promising methods [3]. There are two cycles which are used for absorption cooling. These are (i) liquid<br />

absorption cycle with liquid absorbents (e.g. LiBr-H 2 O, H 2 O-NH 3 , NH 3- LiNO 3 etc.); solid absorption cycle with<br />

solid absorbents (e.g. Zeolites-H 2 O, CaCl 2 -NH 3 , Silicagel-H 2 O, NH 3- LiNO 3 etc.). In absorption cycle cooling<br />

systems, LiBr-H 2 O and H 2 O-NH 3 are the major working pairs employed in these systems. Lithium–bromide (Li-<br />

Br) is commonly used for cooling applications and provides chilled water at 5°C. An ammonium–water working<br />

pair is used in refrigeration and can provide chilled water below 0°C. Among a variety <strong>of</strong> promising solar<br />

thermal cooling technologies, a Li-Br based cooling system driven by solar thermal energy <strong>of</strong>fers highperformance,<br />

simplicity and reliability. A typical solar thermal cooling system consists <strong>of</strong> solar heat collector,<br />

absorption chiller, hotwater storage tank, cooling tower, pumps, valves, and additional components. A solar<br />

thermal cooling system uses solar thermal collectors to produce heat that operates a conventional absorption or<br />

adsorption chiller that is thermally driven. The decreasing costs <strong>of</strong> solar panels and increasingly gained<br />

experience in their applications have made solar thermal cooling system more affordable and attractive than ever.<br />

Based upon technology reviews and available data, Xu and Tengfang [4] concluded that it provides significant<br />

energy savings potential (approximately 56%) over conventional compressor-based 23 chillers, while cost <strong>of</strong><br />

saving was conservatively estimated as $7.9/kWh. It was estimated that 80% <strong>of</strong> the market for cooling<br />

requirements in food processing would be possible – corresponding to a potential energy savings <strong>of</strong> 681 GWh<br />

per year in California. It has been found that LiBr-H 2 O has following advantages: (i) a higher COP than for the<br />

other working fluids; (ii) the low cost and excellent performance <strong>of</strong> this working fluid combination make it the<br />

favourable choice for use in solar cooling cycles.<br />

But its range <strong>of</strong> operation is limited due to the crystallization at the point <strong>of</strong> the recuperator discharge into the<br />

absorber and stopping solution flows through the device. Also the other disadvantages associated with the<br />

ammonia-water system are as follow by comparison:<br />

• Generally, H 2 O-NH 3 systems operate at a 10-15% lower solar fraction than LiBr-H 2 O systems.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

• It requires a higher generator inlet temperature. Generally, LiBr-H 2 O absorption units require generator<br />

inlet temperatures <strong>of</strong> 70-88°C, while H 2 O-NH 3 absorption units require temperatures <strong>of</strong> 90-180°C;<br />

which results in the H 2 O-NH 3 cooling systems achieving a lower COP when using flat-plate collectors.<br />

• It requires higher pressures and hence higher pumping power.<br />

• A more complex system requiring a rectifier to separate ammonia and water vapour at the generator outlet<br />

is required.<br />

• There are restrictions on in-building applications <strong>of</strong> ammonia-water cooling units because <strong>of</strong> the hazards<br />

associated with the use <strong>of</strong> ammonia.<br />

For these reasons the purpose <strong>of</strong> this study is to review the operation <strong>of</strong> various solar absorption air-conditioning<br />

systems with lithium bromide and water as the working fluids. The major components in the LiBr-H 2 O solar airconditioning<br />

systems are chillers and solar collectors and the different cooling technologies are discussed in the<br />

next section.<br />

2. Cooling Technologies<br />

2.1. Single-effect absorption air-conditioning system<br />

The schematic diagram <strong>of</strong> the single effect system is shown in Fig.1. In this system, the solar energy is gained<br />

through the collector and is accumulated in the hot water storage tank. Then, the hot water in the storage tank is<br />

supplied to the generator to boil <strong>of</strong>f water vapour from a LiBr-H 2 O solution. The water vapour is then cooled<br />

down in the condenser and passed to the evaporator where it is again evaporated at low pressure, thereby cooling<br />

the required space.<br />

Fig. 1. Single-effect solar air-conditioning system. [2]<br />

Meanwhile, the strong solution leaving the generator to the absorber passes through a heat exchanger in order to<br />

preheat the weak solution entering the generator. In the absorber, the strong solution absorbs the water vapour<br />

coming from the evaporator. Cooling water from the cooling tower removes the heat by mixing and<br />

condensation. An auxiliary energy source is also provided so as to supply the hot water to the generator, when<br />

available solar energy is not sufficient to heat the water to the required temperature level needed by the<br />

generator.<br />

2.2. Single-effect system with refrigerant storage<br />

In this system, an additional feature <strong>of</strong> refrigerant storage is provided that includes the usual generator,<br />

condenser, evaporator and absorber together with a sensible heat exchanger, a mechanical pump and pressure<br />

reducing valves or equivalent. A refrigerant store is associated with the condenser while an absorber store is<br />

associated with the absorber. Fig. 2 shows the schematic <strong>of</strong> the single-effect cooling system with refrigerant<br />

storage [6]. Basically, the idea is to provide a storage volume in association with the condenser where the<br />

refrigerant can be accumulated during the hours <strong>of</strong> high solar insolation. Then this stored liquid refrigerant can<br />

be expanded at other times to meet the varying loads. Storage is also needed in the absorber to accommodate not<br />

only the refrigerant but also sufficient absorbent to keep the concentration within allowable limits. Heat rejection<br />

is accomplished by a cooling tower from which water is circulated through the absorber, condenser store and<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

condenser in series. Other water circuits could be used: indeed there may be some advantages to be gained in<br />

using parallel operation, notably the cooler water available for the condenser and the possibility <strong>of</strong> shutting <strong>of</strong>f<br />

flow to the condenser altogether when there is no generation. Room air is circulated through the evaporator, and<br />

is maintained at a constant temperature, within the limits <strong>of</strong> the room thermostat and air-conditioner, by<br />

operating an on-<strong>of</strong>f valve in the refrigerant line before the evaporator<br />

Fig. 2. Flow chart <strong>of</strong> the single effect system with refrigerant storage. [6]<br />

A solar air-conditioning system based on the above concept and geographical data was modeled in Brisbane,<br />

Australia [7]. They reported that the generation <strong>of</strong> refrigerant ceases several hours before the sunset because <strong>of</strong><br />

the high boiling point <strong>of</strong> the solution that became highly concentrated with so much refrigerant in the store.<br />

During the night as the refrigerant flows from the store to the absorber, the evaporator cooling rate continually<br />

decreases as the solution concentration decreases and causes a higher pressure and temperature in the evaporator.<br />

The other disadvantages <strong>of</strong> this system could be<br />

• the generation power is not easily matched with the absorption and refrigeration power;<br />

• although the machine could store sufficient refrigerant during a typical day to allow overnight operation,<br />

the performance <strong>of</strong> the chiller is very low because <strong>of</strong> the decrease in concentration <strong>of</strong> the solution and<br />

the increase <strong>of</strong> the temperature and pressure in the system.<br />

Wilbur et al. [8] worked on a similar system and their experience showed that the systems with refrigerant<br />

storage and heat rejection buffer, require smaller cooling towers than conventional units. Also the Single-effect<br />

system with refrigerant storage <strong>of</strong>fers certain advantages over other methods which include:<br />

• the energy storage per unit volume is high as higher latent heat <strong>of</strong> evaporation, compared to available<br />

sensible heat changes, is involved;<br />

• losses are low as the storage occurs at or near room temperature;<br />

• further advantages arise when the storage is applied to the LiBr-H 2 O cycle as water has one <strong>of</strong> the highest<br />

enthalpies <strong>of</strong> evaporation;<br />

• the storage pressure is low so that the strength <strong>of</strong> the storage vessel is not critical.<br />

2.3. Single-effect system with hot water storage<br />

The efficiency <strong>of</strong> the system can be further improved by using two hot storage units for the collection <strong>of</strong> solar<br />

energy in different temperature ranges [9]. One storage would provide 70-75% <strong>of</strong> the total heat required at the<br />

lowest temperature which can be utilized effectively at the part-load conditions. Typical temperature may be<br />

from 50-70°C depending on the building load pattern and the expected pattern <strong>of</strong> ambient temperature. The<br />

remaining 25-30% <strong>of</strong> the storage volume would be in a smaller tank with more insolation in order to store the<br />

heat collected in 85-95°C. Still higher temperatures may be achieved in this storage if it can be pressurized to<br />

prevent boiling, and if collectors are used which are capable <strong>of</strong> operating at higher temperature levels with good<br />

efficiency. Latent heat storage may be particularly worthwhile in the higher-temperature unit since it tends to<br />

reduce its physical size for a given amount <strong>of</strong> kWh stored, and provides more heat at the levels needed for fullload<br />

operation without significant change in temperature. Fig 3 shows the schematic diagram for dual storage<br />

system.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig 3. Schematic diagram for dual storage system [9]<br />

In Fig. 3, the pump P circulates the liquid from either the low or high temperature storage. Valves 1 and 2 are<br />

opened when the system is to add heat to the low temperature storage L, and valves 3 and 4 are opened for<br />

adding heat to the higher temperature storage H. Control C determines when the pump operates and which valves<br />

are opened. The advantages <strong>of</strong> the above system are that separation <strong>of</strong> the storage into a high and low<br />

temperature subsystems may increase the heat collected by a given collector array by a factor <strong>of</strong> 1.30-1.50,<br />

depending on location and type <strong>of</strong> collectors. At the same time, the COP on a seasonal basis may rise from<br />

approximately 0.65 to 0.75, a 15% improvement. Taken together these benefits may decrease the required<br />

collector area to cool a given building by 30-40% which is a considerable saving.<br />

2.4. Double-effect convertible system<br />

As technical development <strong>of</strong> absorption chillers allowed for lower generating temperatures as low as 73°C, the<br />

percentage <strong>of</strong> the solar contribution to air-conditioning became higher. However, if it worked at a lower COP<br />

with the same generation temperature when conventional fuel was used as the auxiliary, it would not be<br />

considered sensible. Some years ago an absorption chiller was introduced [10] that worked in double effect<br />

principle by using fuel at a higher COP, and in single effect using solar energy, so as to achieve a higher COP.<br />

The principle <strong>of</strong> the system is explained using Fig.4. It is a double effect absorption chiller where in the weak<br />

solution is circulated in series. As shown in Fig.4, in addition to the components listed in the single effect<br />

system, the double effect convertible system has a high pressure generator, a secondary heat exchanger and a<br />

heat recovery unit [11].<br />

Fig. 4 Single/double effect convertible absorption cooling system [11]<br />

The high-pressure generator for steam is independently located from the low-pressure generator for solar and hot<br />

water vapour from the high-pressure generator before being condensed. A high-pressure generator gives a<br />

primary effect and a low-pressure generator a secondary effect, thus being called a double-effect. Therefore, a<br />

double effect cycle requires lower heat input to produce the same cooling effect, when compared to a single<br />

effect system resulting in higher COP. During the refrigeration circulation, the water vapour produced in the<br />

high-pressure generator, heats the solution in the low-pressure generator, thereby giving up its heat, and then is<br />

passed to the condenser. Meanwhile, the generated water vapour in the low-pressure generator also passes to the<br />

condenser. The condensed water vapour is then passed to the evaporator to collect heat from the space to be<br />

cooled, thereby producing the refrigerating effect. Obviously, compared to the single effect system, the double<br />

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Proceedings <strong>of</strong> the National Conference on<br />

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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

effect cycle has an additional advantage <strong>of</strong> having a reduced condensing demand. Similarly, in the solution<br />

circulation, the double effect is again realized by circulating the solution from the absorber to the high-pressure<br />

generator through the primary and secondary heat exchangers and the heat recovery unit. This process preheats<br />

the weak solution. Also, the strong solution from the high-pressure generator is circulated to the low-pressure<br />

generator and is then allowed to pass through the primary heat exchanger back to the absorber, for mixing. The<br />

performance <strong>of</strong> the smaller machines is almost the same as the larger ones. They use the bubble pumping effect<br />

in transporting the LiBr solution from the generator absorber, while larger ones use a circulating pump for that<br />

purpose. When double effect and single effect systems were comparatively studied then the following<br />

observations were made [12]. The driving temperature required for the process is above 80°C for single-effect<br />

and 140–160°C for double-effect machines. The condensation heat produced by the top cycle is used to drive the<br />

generator <strong>of</strong> the lower cycle. Subsequently, a COP <strong>of</strong> the order <strong>of</strong> 1.1 can be achieved, whereas the single-effect<br />

system is bound by thermodynamic restrictions, which dictate that the useful cooling can never exceed the heat<br />

input. In practise, COP for large capacity machines lies in the range <strong>of</strong> 0.7–0.8. R&D activity is currently<br />

directed into developing three- and four-effect systems that could reach COP <strong>of</strong> the order <strong>of</strong> 1.7–2.2, but such<br />

systems require higher driving temperatures making them less suitable for solar applications (Altener Project<br />

<strong>20</strong>02). Rabah [13] also developed a solar cooling system based on solar/natural gas single effect lithium bromide<br />

absorption chillers. The overall performance <strong>of</strong> the absorption chiller system is analysed and discussed. For an<br />

evaporator temperature <strong>of</strong> 5°C, when the condenser temperature is varied from 28°C to 36°C and generator<br />

temperatures is varied from 54°C to 83°C the maximum COP was 0.82. For a refrigeration capacity <strong>of</strong> 10 kW,<br />

the quantity <strong>of</strong> natural gas used to provide auxiliary load is very small and consequently the CO 2 gas emissions is<br />

very small (the maximum mass flow rate <strong>of</strong> CO 2 is less than 3 kg/ hr).<br />

2.5. Two-stage system<br />

A key figure to describe the performance <strong>of</strong> a thermally driven chiller is the thermal Coefficient <strong>of</strong> Performance<br />

(COP), defined as the produced cold per unit <strong>of</strong> driving heat. Single-effect absorption systems are limited in COP<br />

to about 0.7 for LiBr–water and to 0.6 for ammonia–water [14]. The drawback <strong>of</strong> the single stage cooling system<br />

is high generator temperature and thus high initial cost for solar collector. Therefore, to reduce the initial cost <strong>of</strong><br />

the system, the important variable is the generator temperature, which if lowered, could help reduce the solar<br />

collector cost by using collector models <strong>of</strong> a lower temperature range by using a two-stage LiBr absorption<br />

chiller instead <strong>of</strong> single-stage chiller Alizadeh et al. [15] have pointed out the advantage <strong>of</strong> lowering the<br />

generator temperature:<br />

1. the ordinary flat-plate collectors can be employed, thereby bringing down the cost <strong>of</strong> the system; and<br />

2. crystallization <strong>of</strong> LiBr-H2O solution could be avoided.<br />

In order to search for an approach to a more economical solution <strong>of</strong> solar cooling, a two-stage LiBr absorption<br />

chiller prototype, working on lower temperature heat source, has been designed and tested successfully by Huang<br />

et al. [16]. Fig. 5 shows the flowchart <strong>of</strong> the two-stage absorption chiller.<br />

Fig. 5. Schematic diagram <strong>of</strong> the two-stage absorption chiller. [16]<br />

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The cycle is divided into high-pressure stage and low-pressure stage. Diluted LiBr solution in the high-pressure<br />

generator is heated by hot water. Generated water vapour is condensed in the condenser. The condensed water<br />

flows into the evaporator (low-pressure stage) to be evaporated, producing the refrigerating effect. A<br />

concentrated solution from the high-pressure generator enters into the high-pressure absorber and absorbs water<br />

vapour generated from the low-pressure generator, thus changing back to a diluted solution. This solution is then<br />

pumped back to the high-pressure generator, completing a high-pressure cycle. The concentrated solution in the<br />

low-pressure generator goes down into the low-pressure absorber and absorbs water vapour from the evaporator.<br />

The diluted solution from the low-pressure absorber is then pumped back to the low-pressure generator,<br />

completing a low-pressure cycle. Thus, refrigerant water is made in the high-pressure stage and the absorbentconcentrated<br />

solution is made in the low-pressure stage. So, through the high-pressure absorption process, the<br />

generation process in the low-pressure generator occurs under a lower pressure, completing a full refrigeration<br />

cycle. The two-stage system, however, can use heat sources <strong>of</strong> a lower temperature to achieve better cooling<br />

effect under more severe conditions. A solar powered two-stage absorption air-conditioning system was installed<br />

in China [17] that had a cooling power <strong>of</strong> 100 kW, with collector areas <strong>of</strong> 500 m 2 . The nominal generating<br />

temperature <strong>of</strong> the chiller was about 65-75°C, and the COP <strong>of</strong> the chiller iwas greater than 0.4. Kaushik and<br />

Kumar [18] introduced a two-stage dual fluid absorption refrigeration. Fig. 6 shows the schematic diagram <strong>of</strong><br />

this system, which consists <strong>of</strong> two stages.<br />

Fig. 6. Schematic diagram two-stage dual fluid absorption refrigeration system [18]<br />

The first stage uses a LiBr-H 2 O combination, while the second stage uses a H 2 O-NH 3 combination. The first<br />

stage is assumed to operate with the condenser and absorber maintained at a temperature <strong>of</strong> 30°C by the<br />

circulation <strong>of</strong> cooling water, and the evaporator operated at a temperature <strong>of</strong> 5°C. In the second stage, the<br />

absorber is assumed to be maintained at 5°C by the evaporator <strong>of</strong> the first stage. The operation principles at the<br />

second stage are the same as for the first except that a rectifier is needed for the purification <strong>of</strong> ammonia vapour.<br />

Therefore, a rectifier is needed only at the second stage and is avoided at the first stage. An evaporator<br />

temperature as low as -<strong>20</strong>°C can easily be produced at the second stage. Through the system analysis, it was<br />

found that at the second stage, low condenser temperatures could yield a better performance at lower generator<br />

temperatures but at higher generator temperatures, a high value <strong>of</strong> COP is obtained at a higher condenser<br />

temperature. Secondly, an increase in the COP value with the evaporator temperature is more within the lower<br />

generator temperature range than for the higher generator temperatures. Furthermore, it is evident that lower<br />

evaporator temperatures require either higher generator temperatures or lower absorber temperatures. A twostage<br />

dual fluid absorption system can be operated with ordinary flat-plate collectors at the first stage and<br />

evacuated tube solar collectors at the second stage for the production <strong>of</strong> very low evaporator temperatures. The<br />

COP <strong>of</strong> the system is lower than the LiBr-H 2 O two-stage system, but higher than the H 2 O-NH 3 two-stage system.<br />

The two-stage system has the following advantages:<br />

• the cooling system can work steadily though solar input is unsteady;<br />

• the lower generator inlet and outlet temperatures both increase instantaneously and daily efficiencies <strong>of</strong><br />

solar collector system;<br />

• a required lower operating temperature provides the possibility to use a simpler model <strong>of</strong> a solar collector,<br />

e.g., flat-plate collectors, instead <strong>of</strong> vacuum tube collectors , which are 3-4 times more expensive than<br />

the flat-plate collectors, thus reducing the construction cost <strong>of</strong> the solar system.<br />

The disadvantages <strong>of</strong> this system are the complexity <strong>of</strong> the chiller's construction, and the COP at the nominal<br />

generator temperature is lower than the single-effect one. Also, the amount <strong>of</strong> cooling water needed is double<br />

than that <strong>of</strong> the single-effect one, so that the cooling tower should be larger.<br />

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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2.6. Dual-cycle system<br />

Although, the above mentioned absorption systems use solar energy directly with minimum conversion, they<br />

have a drawback i.e. they consume considerable quantities <strong>of</strong> water for the cooling tower. This is a serious<br />

limitation for its use in arid regions for which the solution could be dual cycle. It has the advantage <strong>of</strong> avoiding<br />

the use <strong>of</strong> the wet cooling tower. S<strong>of</strong>rata et al. [<strong>19</strong>] have introduced the LiBr-absorption cycle which avoids the<br />

use <strong>of</strong> a wet cooling tower. However, its COP is very low. Fig. 7 shows the schematic diagram <strong>of</strong> dual cycle<br />

system.<br />

Fig. 7 Schematic diagram <strong>of</strong> dual cycle system[<strong>19</strong>]<br />

The dual cycle consists <strong>of</strong> a high and a low-temperature cycle. Each cycle is similar to a conventional singleeffect<br />

absorption cycle. The main heat energy supplier to the generator <strong>of</strong> the high temperature level cycle<br />

(HTLC) may be solar energy. The HTLC absorber rejects its heat to the atmosphere and this is the main<br />

advantage <strong>of</strong> using such a cycle. The cooling effect <strong>of</strong> the system will be through the low temperature level cycle<br />

(LTLC) evaporator. At this stage, the heat exchange between the system as a whole and the environment has<br />

been accomplished. The interchange <strong>of</strong> heat between the HTLC and LTLC occurs as follows. The HTLC<br />

condenser supplies heat energy to the LTLC generator. The temperature level <strong>of</strong> this heat supply should be high<br />

enough to generate water vapour in the LTLC. The HTLC evaporator will serve as a heat sink for both the<br />

absorber and the condenser <strong>of</strong> the LTLC. At this stage, also, the heat exchange between the two cycles has been<br />

completed. The heat balance requires, for both the HTLC and the LTLC, that the sum <strong>of</strong> the heat supplied to the<br />

generator and the cooling effect by the evaporator must equal the heat rejected by the condenser and the<br />

absorber. Simultaneously, for the best design, the LTLC condenser heat must just equal the heat required for the<br />

LTLC generator. In addition, the cooling effect <strong>of</strong> the HTLC must equal the sum <strong>of</strong> the heat rejected by the<br />

LTLC <strong>of</strong> the absorber and the condenser. With these points in mind and to satisfy the physical constraints<br />

(crystallization and water icing) <strong>of</strong> the LiBr-H 2 O working pair, tedious calculations may be needed to construct<br />

the dual cycle. Since the dual system requires higher generating temperatures, evacuated tube collectors should<br />

be used. In addition, the whole system is very complicated as compared with the single-effect one. The dual<br />

system is appropriate for locations where solar energy is available but where water is scarce, as the cooling tower<br />

may be eliminated.<br />

2.7. Triple-effect system and multistage system<br />

Most solar-powered absorption cooling projects to-date have utilized single-effect systems, with low-temperature<br />

solar collectors. Developments in gas-fired absorption systems in recent years, mainly in the USA and Japan, for<br />

LiBr–water chillers, have made available in the market double-effect systems with COP in the range 1.0–1.2.<br />

Triple-effect systems are available with COP <strong>of</strong> about 1.7 [<strong>20</strong>]. These systems may be adapted to and employed<br />

in a solar-powered installation with high temperature solar collectors. Fig. 8 compares the performance <strong>of</strong> several<br />

multi-effect chillers, showing the COP as a function <strong>of</strong> the solar heat supply temperature for typical single-,<br />

double-and triple-effect chillers with the same component size and under the same operating conditions. The<br />

corresponding Carnot performance curve is also shown for comparison. The single-effect system gives best<br />

results in the temperature range 80–100°C; for a higher supply temperature, it is worth switching to a double<br />

effect system, up to about 160°C, and then to a triple-effect. A typical generator temperature <strong>of</strong> approximately<br />

250°C is used for the heat input to the topping cycle. The attainable cooling COP for a triple-effect machine is<br />

approximately 1.5.<br />

159


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig. 8. Coefficient <strong>of</strong> Performance (COP) as a function <strong>of</strong> (solar) heat supply temperature for single-, doubleand<br />

triple-effect LiBr–water absorption chillers[<strong>20</strong>]<br />

4. Conclusion<br />

Of the two main technologies <strong>of</strong> solar cooling systems discussed in this paper, the emphasis is placed on the<br />

cooling technology rather than on the thermal technology, which places an important factor in increasing the<br />

COP <strong>of</strong> the refrigeration systems. It is shown that although the single-effect system with refrigerant storage has<br />

the advantage <strong>of</strong> accumulating refrigerant during the hours <strong>of</strong> high solar insolation, the double-effect convertible<br />

system has a higher overall COP. And the two-stage system has the advantage <strong>of</strong> lowering the generator<br />

temperature, which improves the system performance and the use <strong>of</strong> conventional flat-plate collectors to achieve<br />

high COP. Producing refrigeration and/or air conditioning from solar energy remains an inviting prospect, given<br />

that a typical building’s cooling load peaks within 2 or 3 h <strong>of</strong> the time <strong>of</strong> maximum solar irradiation [21]. The<br />

main problem <strong>of</strong> solar absorption air-conditioning systems is low coefficient <strong>of</strong> performance and high initial<br />

costs. Improvements such as reduced collector area, because <strong>of</strong> improved system performance, and reduced<br />

collector cost could lower the cost <strong>of</strong> solar components. ew trends gradually developed towards the redesign <strong>of</strong><br />

the chiller generator for operation at temperatures lower than 100°C. It is <strong>of</strong> vital importance to select the right<br />

equipment for each application, depending on the desired performance specifications. Careful analysis <strong>of</strong> internal<br />

loads is required to size and specify the equipment correctly [12]. There are many other experiments carried out<br />

by researchers, nevertheless, further improvements should be made to the solar powered air-conditioning systems<br />

in order to compete with the conventional air-conditioning systems. It is indeed a challenge to convince the<br />

consumer to start implementing capital intensive energy efficiency improvements such as solar air conditioning.<br />

Payback periods longer than five years are generally not opted for within the industry; however, with solar air<br />

conditioning, in particular, payback could be much longer, especially if no subsidies for the initial investment are<br />

available. Therefore, it is important to present the benefits <strong>of</strong> such investments in a wider context <strong>of</strong> energy crisis<br />

and environmentally friendly goals. The major stakeholders need to break free from considering only the<br />

financial payback and long-term benefits <strong>of</strong> solar cooling should be embraced in a large scale.<br />

References<br />

[1] Mirunalini Thirugnanasambandam, S. Iniyan, Ranko Goic. A review <strong>of</strong> solar thermal technologies. In:<br />

Renewable and Sustainable Energy Reviews, Volume 14, Issue 1, January <strong>20</strong>10, Pages 312-322.<br />

[2] Mittal V, Kasana KS, Thakur NS. The study <strong>of</strong> solar absorption air-conditioning systems. In:Journal <strong>of</strong><br />

Energy in Southern Africa. Vol 16 No 4 • November <strong>20</strong>05;59-66.<br />

[3] ASHRAE. Absorption air-conditioning and refrigeration equipment. In: ASHRAE Guide and Data Book,<br />

Equipment. Chapter 14. New York: ASHRAE, <strong>19</strong>72.<br />

[4] Xu, Tengfang. Developing information on energy savings and associated costs and benefits <strong>of</strong> energy efficient<br />

emerging technologies applicable in California. 04-26-<strong>20</strong>11.Lawrence Berkeley National Laboratory.<br />

[5] Z.F. Li, K. Sumathy. In: Renewable and Sustainable Energy Reviews 4 (<strong>20</strong>00) 267-293.<br />

[6] Grassie SL, Sheridan NR. Modeling <strong>of</strong> a solar-powered absorption air-conditioning system with refrigerant<br />

storage. Solar Energy <strong>19</strong>77;<strong>19</strong>:691-700.<br />

[7] Sheridan NR, Kaushik SC. A novel latent heat storage for solar space heating systems: refrigerant storage.<br />

Applied Energy 9:165-72.<br />

[8] Wilbur PJ, Mitchell CE. Solar absorption air-conditioning alternatives. Solar Energy <strong>19</strong>75;17:<strong>19</strong>3-99.<br />

[9] Kreider JF, Kreith F. Solar systems for space cooling. In: Solar energy handbook. New York: McGraw-Hill,<br />

<strong>19</strong>81.<br />

[10] Sayigh AAM, McVeigh, JC. Solar absorption cooling. In: Solar Air-conditioning and Refrigeration. Chapter<br />

3. UK: Pergamon Press Ltd.<br />

[11] Dai YQ. <strong>Technology</strong> and application <strong>of</strong> LiBr absorption refrigeration. In: China: Chinese mechanical<br />

engineering industry publication, <strong>19</strong>97.<br />

160


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[12] Paula Naukkarinen; Solar air conditioning and its role in alleviating the energy crisis <strong>of</strong> the Mediterranean<br />

hotels In:International Journal <strong>of</strong> Sustainable Energy, Vol. 28, Nos. 1–3, March–September <strong>20</strong>09, 93–100.<br />

[13] Rabah Gomri, Simulation study on the performance <strong>of</strong> solar/natural gas absorption cooling chillers. In :<br />

Energy Conversion and Management, <strong>20</strong>12.<br />

[14] G.Y. Han. A review <strong>of</strong> thermally activated cooling technologies for combined cooling, heating and power<br />

systems Progress. In Energy and Combustion <strong>Science</strong>, Volume 37, Issue 2, April <strong>20</strong>11, Pages 172-<strong>20</strong>3<br />

[15] Alizadeh S, Bahar F, Geoola F. Design and optimization <strong>of</strong> an absorption refrigeration system operated by<br />

solar energy. Solar Energy <strong>19</strong>79;22:149-54. 292 Z.F. Li, K. Sumathy / Renewable and Sustainable Energy<br />

Reviews 4 (<strong>20</strong>00) 267-293.<br />

[16] Huang ZC, Xia WH, Ma WB. A 2-stage LiBr absorption chiller for solar cooling. In: Proceedings <strong>of</strong> the<br />

Biennial Congress <strong>of</strong> ISES, Denver, Colorado, USA, <strong>19</strong>-23 August, <strong>19</strong>91. vol. 2. p. 1643-48.<br />

[17] Guangzhou Institute <strong>of</strong> Energy Conversion. Progress reports on the solar-powered air-conditioning and hot<br />

water providing system. Guangzhou institute <strong>of</strong> energy conversion, Chinese Academy <strong>of</strong> <strong>Science</strong>s, <strong>19</strong>98.<br />

[18] Kaushik SC, Kumar R. Computer-aided conceptual thermodynamic design <strong>of</strong> a two-stage dual fluid<br />

absorption cycle for solar refrigeration. Solar Energy <strong>19</strong>85;35:401-07.<br />

[<strong>19</strong>] S<strong>of</strong>rata HM, Khoshaim B, Nasser A, Megahed M. A solar-powered Li-Br dual cycle. Applied Energy<br />

<strong>19</strong>81;9:185-91.<br />

[<strong>20</strong>] Balaras, Grossman, Henning, Carlos. Solar air conditioning in Europe—an overview. In:Renewable and<br />

Sustainable Energy Reviews Vol 11 (<strong>20</strong>07) 299–314<br />

[21] Todd Otanicar, Robert A. Taylor, Patrick E. Phelan. Prospects for solar cooling – An economic and<br />

environmental assessment. In: Solar Energy, Volume 86, Issue 5, May <strong>20</strong>12, Pages 1287–1299<br />

161


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

ENERGY METHOD FOR PERFORMANCE EVALUATION OF A<br />

BOILER IN A COAL FIRED THERMAL POWER PLANT: A REVIEW<br />

Mukesh Gupta, Raj Kumar, Manmohan Kakkar<br />

Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, India<br />

mukesh.mg@gmail.com, rkumar_08@yahoo.com, manmohankakkar@gmail.com<br />

Abstract<br />

Boiler is one <strong>of</strong> the most important components for any power generation system. Performance <strong>of</strong> a boiler, like<br />

efficiency and evaporation ratio directly affects the overall performance <strong>of</strong> the electricity generation process and<br />

it reduces with time, due to poor combustion, heat transfer fouling and poor operation and maintenance. The<br />

easiest and most cost effective method [1] is to estimate the efficiency value on five broad elements: (1) Boiler<br />

stack temperature (2) Heat content <strong>of</strong> fuel (3) Fuel specification (4) Excess air levels (5) Ambient air<br />

temperature and relative humidity. The current study puts forward an effective methodology for the performance<br />

evaluation <strong>of</strong> a boiler based on the work done by some <strong>of</strong> the experts in the field <strong>of</strong> thermal/ energy studies and<br />

enlists some <strong>of</strong> the factors that affect the performance <strong>of</strong> a boiler.<br />

1. Introduction<br />

A boiler is an enclosed vessel that provides a means for combustion heat to be transferred into water until it<br />

becomes heated water or steam. The hot water or steam under pressure is then usable for transferring the heat to<br />

a process. The boiler suppliers and sales personnel will <strong>of</strong>ten cite various numbers, like the boiler has a thermal<br />

efficiency <strong>of</strong> 85%, combustion efficiency <strong>of</strong> 87%, a boiler efficiency <strong>of</strong> 80%, and a fuel-to-steam efficiency <strong>of</strong><br />

83%. What does these mean<br />

Typically,<br />

1) Thermal efficiency reflects how well the boiler vessel transfers heat. The figure usually excludes radiation<br />

and convection losses.<br />

2) Combustion efficiency typically indicates the ability <strong>of</strong> the burner to use fuel completely without<br />

generating carbon monoxide or leaving hydrocarbons unburned.<br />

3) Boiler efficiency could mean almost anything. Any fuel-use figure must compare energy put into the<br />

boiler with energy coming out.<br />

4) "Fuel to steam efficiency" is accepted as a true input/output value.<br />

Keshavarz M. et. al. [1] proposed a discrete time piecewise affine (PWA) model for a boiler- turbine unit. In<br />

order to control the system a model predictive control strategy has been employed which calculates the control<br />

law as an affine function <strong>of</strong> the states. The use <strong>of</strong> the MPC enhances the performance <strong>of</strong> the system.<br />

Miroslav Kljajić et. al. [2] carried out a survey on 65 boilers in Serbia and developed a neural network<br />

methodology to predict and improve the boiler efficiency. By creating a database and employing s<strong>of</strong>t computing<br />

techniques a wide range <strong>of</strong> possibilities have been proposed which can be used to improve the boiler efficiency.<br />

The easiest and most cost effective method [1] is to estimate the efficiency value on five broad elements: (1)<br />

Boiler stack temperature (2) Heat content <strong>of</strong> fuel (3) Fuel specification (4) Excess air levels (5) Ambient air<br />

temperature and relative humidity.<br />

Niu Z. et. al. [3] concluded that boilers <strong>of</strong> a particular type will behave differently due to manufacturing or<br />

assembly tolerances. In addition, the performance <strong>of</strong> a boiler will vary at different times <strong>of</strong> its service life. They<br />

simulated the boiler model in which the heat transfer in the combustion chamber is simulated by the zone<br />

method; heat transfer in the secondary superheater, the reheater, the primary superheater, and the economizer is<br />

simulated by lump parameter analysis. The main advantage <strong>of</strong> this method is that it may be applied to<br />

different boiler systems with different configurations. The uncertainty factors, such as water tube deposits,<br />

component deterioration and so on, are considered by modification factors which are determined from on-line<br />

measurements. Another feature <strong>of</strong> the boiler system simulation is that the major parts <strong>of</strong> the boiler system are<br />

simulated and coupled together to analyze some important operational parameters which impose a significant<br />

effect on boiler efficiency, such as main stream temperature, reheat temperature and reheat pressure drop.<br />

162


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

This paper presents the novel work done by the leading researchers in the field <strong>of</strong> power plant and thermal<br />

engineering with particular reference to the performance evaluation <strong>of</strong> a boiler which is one <strong>of</strong> the most<br />

important components <strong>of</strong> a coal fired thermal power plant.<br />

2. Boiler Performance Evaluation<br />

The boiler system comprises <strong>of</strong>: feed water system, steam system and fuel system. The feed water system<br />

provides water to the boiler and regulates it automatically to meet the steam demand. Steam is directed through a<br />

piping system to the point <strong>of</strong> use. Throughout the system, steam pressure is regulated using valves and checked<br />

with steam pressure gauges. The fuel system includes all equipment used to provide fuel to generate the<br />

necessary heat. The equipment required in the fuel system depends on the type <strong>of</strong> fuel used in the system. A<br />

typical boiler room schematic is shown in Fig.1.<br />

Steam to Turbine<br />

Exhaust Gases<br />

Vent<br />

Stack<br />

Safety Valve Vents<br />

Economiser<br />

De- Aerator<br />

Pumps<br />

Safety Valves<br />

FGR<br />

Vent<br />

Boiler<br />

Burner<br />

Water Source<br />

Fuel<br />

Brine<br />

Chemical Feed<br />

Blowdown Separator<br />

Separators<br />

Figure 1. Schematic Diagram <strong>of</strong> a Boiler Room<br />

The water supplied to the boiler that is converted into steam is called feed water. The two sources <strong>of</strong> feed water<br />

are: (1) Condensate or condensed steam returned from the processes and (2) Makeup water (treated raw water)<br />

which must come from outside the boiler room and plant processes. For higher boiler efficiencies, the feed water<br />

is preheated by economizer, using the waste heat in the flue gas.<br />

Two approaches are generally followed to assess the performance <strong>of</strong> a boiler considering the Energy based<br />

approach<br />

There are two methods [4] <strong>of</strong> assessing boiler efficiency using the energy based criterion<br />

1. Input – output or direct method<br />

2. Heat loss or indirect method.<br />

163


2.1 Direct Method for Calculating Boiler Efficiency<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Direct method compares the energy gain <strong>of</strong> the working fluid (water and steam) to the energy content <strong>of</strong> the fuel.<br />

This is also known as ‘input-output method’ due to the fact that it needs only the useful output (steam) and the<br />

heat input (i.e. fuel) for evaluating the efficiency. The efficiency is than estimated using equation below:<br />

η = (Enthalpy <strong>of</strong> Steam – Enthalpy <strong>of</strong> Feed Water) / Heat released in boiler (1)<br />

Merits and Demerits <strong>of</strong> Direct Method<br />

Merits<br />

Plant people can evaluate quickly the efficiency <strong>of</strong> boilers<br />

Requires few parameters for computation<br />

Needs few instruments for monitoring<br />

Demerits<br />

Does not give clues to the operator as to why efficiency <strong>of</strong> system is lower<br />

Does not calculate various losses accountable for various efficiency levels<br />

Evaporation ratio and efficiency may mislead, if the steam is highly wet due to water carryover<br />

2.2 Indirect Method or Heat Loss Method for Calculating Boiler Efficiency<br />

Here the efficiency is estimated by summing the losses and comparing with the heat input. The major heat losses<br />

from boiler are due to (1) High temperature flue gases leaving the stack (2) Moisture in fuel and combustion air<br />

(3) Combustion <strong>of</strong> hydrogen (4) Heat in un- burnt combustibles in refuse (5) Radiation from boiler surfaces (6)<br />

Un- accounted losses. In the indirect method all the losses are summed up and the efficiency is calculated using<br />

the equation below:<br />

η = (Heat Input – Heat Losses) / Heat Input (2)<br />

The indirect method [5] does not account for:<br />

Standby losses: Efficiency test is to be carried out, when the boiler is operating under a steady load.<br />

Therefore, the combustion efficiency test does not reveal standby losses, which occur between firing<br />

intervals<br />

Blow down loss: The amount <strong>of</strong> energy wasted by blow down varies over a wide range.<br />

Soot blower steam: The amount <strong>of</strong> steam used by soot blowers is variable that depends on the type<br />

<strong>of</strong> fuel.<br />

Auxiliary equipment energy consumption: The combustion efficiency test does not account for the<br />

energy usage by auxiliary equipments, such as burners, fans, and pumps.<br />

3. Discussion<br />

Based on the current study the following factors have been identified as the main causes which affect the boiler<br />

performance:<br />

Proper water treatment programme and blow down control<br />

Draft control<br />

Excess air control<br />

Percentage loading <strong>of</strong> boiler<br />

Steam generation pressure and temperature<br />

Boiler insulation<br />

Quality <strong>of</strong> fuel<br />

4. Conclusions<br />

Durkin T. [6] encourages a thorough look at the way many systems are being designed and operated, and at what<br />

boiler efficiency ratings mean. For both economic and environmental reasons, a heating system design using<br />

condensing boilers and low-temperature heat (130°F [54°C] maximum) is advocated. He conducted experiments<br />

and presented the effects <strong>of</strong> inlet water temperature and return water temperature on the efficiency <strong>of</strong> a boiler as<br />

shown in Fig 2 and 3 respectively.<br />

164


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 2. Effect <strong>of</strong> Inlet water temperature on Boiler Efficiency<br />

Figure 3. Effect <strong>of</strong> Return Water temperature on Boiler Efficiency<br />

The current study puts forward an effective methodology for the performance evaluation <strong>of</strong> a boiler<br />

based on the work done by some <strong>of</strong> the experts in the field <strong>of</strong> thermal/ energy studies and enlists some<br />

<strong>of</strong> the factors that affect the performance <strong>of</strong> a boiler.<br />

References<br />

1. M. Keshavarz, M. Barkhordari Yazdi, M.R. Jahed-Motlagh, “Piecewise affine modeling and<br />

control <strong>of</strong> a boiler–turbine unit”, Applied Thermal Engineering, Volume 30, Issues 8–9, June <strong>20</strong>10, Pages<br />

781-791.<br />

165


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. Miroslav Kljajić, Dušan Gvozdenac, Srdjan Vukmirović,” Use <strong>of</strong> Neural Networks for modeling<br />

and predicting boiler's operating performance”, Energy, March <strong>20</strong>12.<br />

3. Zhongsheng Niu, Kau-Fui V. Wong, “Adaptive simulation <strong>of</strong> boiler unit performance”, Energy<br />

Conversion and Management, Volume 39, Issue 13, 1 September <strong>19</strong>98, Pages 1383-1394.<br />

4. Energy Performance Assessment <strong>of</strong> Boilers, Bureau <strong>of</strong> Energy Efficiency, March <strong>20</strong>08.<br />

5. M.A. Rosen, “Assessing Energy Technologies and Environmental Impacts with the Principles <strong>of</strong><br />

Thermodynamics”, Applied Energy, 72, 427 – 441, <strong>20</strong>02.<br />

6. T. H. Durkin, “Boiler System Efficiency”, ASHRAE Journal (Vol. 48, July <strong>20</strong>06.<br />

166


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

SHELL SIDE CFD ANALYSIS OF A SMALL SHELL-AND-TUBE HEAT<br />

EXCHANGER CONSIDERING THE EFFECTS OF BAFFLE<br />

INCLINATION ON FLUID FLOW<br />

Abdur Rahim 1* , S.M.Saad Jameel 2<br />

Department <strong>of</strong> Mechanical Engg, Faculty <strong>of</strong> Engineering and <strong>Technology</strong>,<br />

Jamia Millia Islamia, New Delhi – 110025, India.<br />

E-mail: 1 rahim_ark@rediffmail.com, 2 saadj11@gmail.com<br />

Abstract<br />

The shell side design <strong>of</strong> a shell-and-tube heat exchanger; in particular the baffle cut and baffles inclination<br />

dependencies <strong>of</strong> the heat transfer coefficient and the pressure drop are investigated by numerically modeling a<br />

small heat exchanger. The flow and temperature fields inside the shell are resolved using a commercial CFD<br />

s<strong>of</strong>tware tool STAR CCM+ v6.06. In this present work, attempts were made to investigate the impacts <strong>of</strong> various<br />

baffle inclination angles on fluid flow and the heat transfer characteristics <strong>of</strong> a shell-and-tube heat exchanger for<br />

three different baffles inclination angles namely 0°, 10° and <strong>20</strong>°. The simulation results for various shell and<br />

tube heat exchangers, one with segmental baffles perpendicular to fluid flow and two with segmental baffles<br />

inclined to the direction <strong>of</strong> fluid flow are compared for their performance. The results are observed to be<br />

sensitive to the turbulence model selection. For a given baffle cut <strong>of</strong> 36 %, the heat exchanger performance is<br />

investigated by varying mass flow rate and baffle inclination angle. From the CFD simulation results, the shell<br />

side outlet temperature, pressure drop, recirculation near the baffles, heat transfer, optimal mass flow rate and<br />

the optimum baffle inclination angle for the given heat exchanger geometry are determined<br />

Keywords: Shell-and-tube heat exchanger, CFD, Conjugate Heat Transfer, Pressure drop, Baffle inclination<br />

angle, turbulence models.<br />

1. Introduction<br />

Heat exchangers have always been an important part to the lifecycle and operation <strong>of</strong> many systems. A heat<br />

exchanger is a device built for efficient heat transfer from one medium to another in order to carry and process<br />

energy. Typically one medium is cooled while the other is heated. They are widely used in petroleum refineries,<br />

chemical plants, petrochemical plants, natural gas processing, Air conditioning, refrigeration and automotive<br />

applications. One common example <strong>of</strong> a heat exchanger is the radiator in a car, in which it transfers heat from the<br />

water (hot engine-cooling fluid) in the radiator to the air passing through the radiator. There are two main types<br />

<strong>of</strong> heat exchangers.<br />

• Direct contact heat exchanger, where both media between which heat is exchanged are in<br />

direct contact with each other.<br />

• Indirect contact heat exchanger, where both media are separated by a wall through which heat<br />

is transferred so that they never mix.<br />

Shell and tube type heat exchanger is an indirect contact type heat exchanger as it consists <strong>of</strong> a series <strong>of</strong> tubes,<br />

through which one <strong>of</strong> the fluids runs. The shell is a container for the shell fluid. Usually, it is cylindrical in shape<br />

with a circular cross section, although shells <strong>of</strong> different shapes are used in specific applications. For this<br />

particular study E shell is considered, which is generally a one pass shell. E shell is the most commonly used due<br />

to its low cost and simplicity, and has the highest log-mean temperature-difference (LMTD) correction factor.<br />

Although the tubes may have single or multiple passes, there is one pass on the shell side, while the other fluid<br />

flows within the shell over the tubes to be heated or cooled. Shell-and-tube heat exchangers in various sizes are<br />

widely used in industrial operations and energy conversion systems. Tubular Exchanger Manufacturers<br />

Association (TEMA) regularly publishes standards and design recommendations.<br />

The tube side and shell side fluids are separated by a tube sheet, Gaddis [1], Schlunder [2], Mukherjee [3]. The<br />

heat exchanger model used in this study is a small sized one, as compared to the main stream, all <strong>of</strong> the leakage<br />

and<br />

bypass streams do not exist or are negligible, Ender Ozden and Ilker Tari [4] , Uday Kapale and Satish Chand<br />

[5], Thirumarimurugan et al. [6]. Baffles are used to support the tubes for structural rigidity, preventing tube<br />

vibration and sagging and to divert the flow across the bundle to obtain a higher heat transfer coefficient. Baffle<br />

spacing (B) is the centre line distance between two adjacent baffles, Sparrow and Reifschneider [7], Li and<br />

Kottke [8], Su Thet Mon Than et al. [9]. Baffle is provided with a cut (Bc) which is expressed as the percentage<br />

<strong>of</strong> the segment height to shell inside diameter. Baffle cut can vary between 15% and 45% <strong>of</strong> the shell inside<br />

167


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

diameter, Kakac and Liu [10], Gay et al. [11], Emerson [12]. In the present study 36% baffle cut (Bc) is<br />

considered. In general, conventional<br />

shell and tube heat exchangers result in high shell-side pressure drop and formation <strong>of</strong> recirculation zones near<br />

the baffles. Most <strong>of</strong> the researches now a day are carried on helical baffles, which give better performance then<br />

single segmental baffles but they involve high manufacturing cost, installation cost and maintenance cost. The<br />

effectiveness and cost are two important parameters in heat exchanger design. So, In order to improve the<br />

thermal performance at a reasonable cost <strong>of</strong> the Shell and tube heat exchanger, baffles in the present study are<br />

provided with some inclination in order to maintain a reasonable pressure drop across the exchanger Yong-Gang<br />

Lei et al. [13]. The complexity with experimental techniques involves quantitative description <strong>of</strong> flow<br />

phenomena using measurements dealing with one quantity at a time for a limited range <strong>of</strong> problem and operating<br />

conditions. Computational Fluid Dynamics is now an established industrial design tool, <strong>of</strong>fering obvious<br />

advantages Versteeg and Malalasekera [14].<br />

In this study, a full 360° CFD model <strong>of</strong> shell and tube heat exchanger is considered. By modeling the geometry<br />

as accurately as possible, the flow structure and the temperature distribution inside the shell are obtained.<br />

In this study, a small shell-and-tube heat exchanger is modeled for CFD simulations. A commercial CFD<br />

package, STAR CCM+ version6 [16], is used together with Hyper Mesh for mesh generation s<strong>of</strong>tware.<br />

Sensitivity <strong>of</strong> the simulation results to modeling choices such as mesh and turbulence model is investigated.<br />

After selecting a suitable<br />

mesh, a discretization scheme and a turbulence model, simulations are performed for two different shell side<br />

flow rates by varying baffle inclination and 36 % baffle cut. The simulation results are used for calculating shell<br />

side heat transfer coefficient and pressure drop.<br />

2. Modeling Details<br />

In this study, a small heat exchanger is selected in order to increase the model detail and to make solid<br />

observations about the flow inside the shell. Some <strong>of</strong> the design parameters and the predetermined geometric<br />

parameters are presented in Table 1. The geometric model with six baffles is shown in Figure1 36% baffle cut<br />

value is selected to place the cut just below or above the central row <strong>of</strong> tubes. The working fluid <strong>of</strong> the shell side<br />

is water. Since the properties <strong>of</strong> water are defined as constants in the STARCCM+ database, to improve the<br />

accuracy; they are redefined using piecewise-linear functions <strong>of</strong> temperature by using the “Thermo-Physical<br />

Properties <strong>of</strong> Saturated Water” tables available in the literature [15].<br />

In this study six baffles are placed along the shell in alternating orientations with cut facing up, cut facing down,<br />

cut facing up again etc, in order to create flow paths across the tube bundle. The geometric model is optimized by<br />

varying the baffle inclination angle i.e., 0°, 10° and <strong>20</strong>°. The computational modeling involves pre-processing,<br />

solving and post- processing. The geometry modeling <strong>of</strong> shell and tube heat exchanger is explained below.<br />

2.1. Geometry modeling<br />

The model is designed according to TEMA (Tubular Exchanger Manufacturers Association) Standards Gaddis<br />

(<strong>20</strong>07), using STARCCM+ s<strong>of</strong>tware as shown in Fig. 1. Design parameters and fixed geometric parameters have<br />

been taken similar to Ender Ozden and Ilker Tari (<strong>20</strong>10), as indicated in Tab. 1.<br />

Figure 1. Isometric view <strong>of</strong> arrangement <strong>of</strong> baffles and tubes <strong>of</strong> shell and tube heat exchanger with 10°<br />

baffle inclination.<br />

Table 1. Geometric dimensions <strong>of</strong> shell and tube heat exchanger.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Heat exchanger length, L<br />

Shell inner diameter, Di<br />

Tube outer diameter, do<br />

Tube bundle geometry and pitch<br />

Triangular,<br />

600 mm<br />

90 mm<br />

<strong>20</strong> mm<br />

30 mm<br />

Number <strong>of</strong> tubes, Nt 7<br />

Number <strong>of</strong> baffles. Nb 6<br />

Central baffle spacing, B<br />

86 mm<br />

Baffle inclination angle, θ 0° ,10° and <strong>20</strong>°<br />

2.2 Governing equations<br />

The governing equations <strong>of</strong> the flow are modified according to the conditions <strong>of</strong> the simulated case. Since the<br />

problem is assumed to be steady, time dependent parameters are dropped from the equations. The resulting<br />

equations are:<br />

Conservation <strong>of</strong> mass: ∇ρVr) = 0 (1)<br />

x-momentum: ∇.(ρuVr) = - ∂p/∂x +∂τxx/∂x +∂τyx/∂y + ∂τzx/∂z (2)<br />

y-momentum: ∇.(ρvVr) = - ∂p/∂y +∂τxy/∂x +∂τzy/∂y + ∂τzx/∂z +ρg (3)<br />

z-momentum: ∇.(ρwVr) = - ∂p/∂z +∂τxz/∂x +∂τyz/∂y + ∂τzz/∂z +ρg (4)<br />

Energy: ∇.(ρeVr) = -p∇.Vr + ∇.(k.∇T) +qϕ <br />

In Eq. (5), ϕ is the dissipation function that can be calculated from<br />

ϕ = µ [ 2[(∂u/∂x)² + (∂v/∂y)² + (∂w/∂z)²] + (∂u/∂y +∂v/∂x)² +(∂u/∂z +∂w/∂z)² +(∂v/∂z + ∂w/∂y)²] + λ(∇.Vr)²<br />

(6)<br />

2.3. Boundary conditions<br />

Boundary conditions:-<br />

1. The working fluid <strong>of</strong> the shell side is water,<br />

2. The shell inlet temperature is set to 300 K,<br />

3. The constant wall temperature <strong>of</strong> 450 K is assigned to the tube walls,<br />

4. Zero gauge pressure is assigned to the outlet nozzle,<br />

5. The inlet velocity pr<strong>of</strong>ile is assumed to be uniform,<br />

6. No slip condition is assigned to all surfaces,<br />

7. The zero heat flux boundary condition is assigned to the shell outer wall (excluding the baffle shell interfaces),<br />

assuming the shell is perfectly insulated.<br />

2.4. Mesh selection<br />

Mesh generation is performed using STARCCM+. The surfaces <strong>of</strong> the model are meshed using triangular<br />

elements. The shell volume is meshed using tetragonal elements. Mesh size selected for six baffle case: the<br />

coarse mesh with approximately 292388 elements have taken. The entire geometry is divided into three fluid<br />

domains Fluid_Inlet, Fluid_Shell and Fluid_Outlet and six solid domains namely Solid_Baffle1 to Solid_Baffle6<br />

for six baffles respectively.<br />

2.5. Turbulence model<br />

Since the flow in this study is turbulent, turbulence effects should be taken into account using turbulence<br />

modeling. The choice <strong>of</strong> turbulence model is very critical in CFD simulations. However, there is no universal<br />

criterion for selecting a turbulence model.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

In this study, k-ε turbulence model are tried. The standard k-ε model is a semi-empirical model based on model<br />

transport equations for the turbulence kinetic energy k and its dissipation rate ε. For steady state, k and ε are<br />

obtained from the following transport equations:<br />

(7)<br />

(8)<br />

∂/∂xi (ρkui) = ∂/∂xj [ (µ + µi/σk) ∂k/∂xj] + Gk + Gb -ρε + Sk<br />

∂/∂xi (ρεui) = ∂/∂xj [ (µ + µi/σε) ∂ε/∂xj] +C1ε ε/k(Gk +C3εGb) –C2ερε²/k + Sk<br />

And the turbulent viscosity is defined by the following equation:<br />

(9)<br />

µt = ρCµk²/ε<br />

The model constants have the following values:<br />

C1ε = 1.44, C2ε = 1.92, Cµ = 0.09, σk = 1, σε = 1.3<br />

3. Results and Discussion<br />

3.1 Validation<br />

Simulation results are obtained for different mass flow rates <strong>of</strong> shell side fluid ranging from1 kg/s and 2 kg/s.<br />

The simulated results for 1 kg/s fluid flow rate for model with 0° baffle inclination angle are validated with the<br />

data available in the literature Ender Ozden and Ilker Tari (<strong>20</strong>10). It is found that the exit temperature at the shell<br />

outlet is matching with the literature results and the deviation between the two is less than 1 %.<br />

The simulation results for 1 kg/s mass flow rate for models with 0°, 10° and <strong>20</strong>° baffle inclination are obtained. It<br />

is seen that the temperature gradually increases from 300 K at the inlet to 330 K at the outlet <strong>of</strong> the shell side.<br />

The average temperature at the outlet surface is nearly 326 K for all the three models. There is no much variation<br />

<strong>of</strong> temperature for all the three cases considered. The maximum pressure for models with 0°, 10° and <strong>20</strong>° baffle<br />

inclinations are 172<strong>20</strong>.5,8474.66 and13705.9 Pascal respectively. The pressure drop is less for <strong>20</strong>° baffle<br />

inclination compared to other two models due to smoother guidance <strong>of</strong> the flow. The maximum velocity is nearly<br />

equal to 1.595 m/s for all the three models at the inlet and exit surface and the velocity magnitude reduces to zero<br />

at the baffles surface. It can be seen that compared to 0° baffle inclination angle, 10°& <strong>20</strong>° baffle inclination<br />

angles, provide a smoother flow with the inclined baffles guiding the fluid flow.<br />

From the stream line contour <strong>of</strong> Fig. 3-5, it is found that recirculation near the baffles induces turbulence eddies<br />

which would result in more pressure drop for model with θ = 0° where as recirculation are lesser for model with<br />

θ = 10° and the recirculation formed for model with θ = <strong>20</strong>° are much less in comparison to the other two models<br />

which indicates the resulting pressure drop is optimum as shown in Fig. 6.<br />

Table 3. Outlet temperature, Shell-side pressure drop values, Heat transfer coefficient for various baffle<br />

inclinations and mass flow rates.<br />

Baffles<br />

Inclination<br />

Angle<br />

(degree)<br />

Mass flow rate = 1 kg/s<br />

Shell side Shell side Heat Heat<br />

Outlet temp pressure transfer transfer<br />

(K) Drop (W) coeff.<br />

(Pascal) (W/m 2 K)<br />

Mass flow rate = 2 kg/s<br />

Shell side Shell side Heat Heat<br />

Outlet temp pressure transfer transfer<br />

(K) Drop (W) coeff.<br />

(Pascal)<br />

(W/m 2 K)<br />

0° 325.65 3210.46 106094.6 2928.4 327.39 172<strong>20</strong>.5 226216.5 6453<br />

10° 324.69 3082.04 104046.9 2872.79 321.45 8474.66 180765.3 4930.2<br />

<strong>20</strong>° 329.75 2356.2 123318 3474.12 326.48 13705.9 255624.6 6072.0<br />

From the CFD simulation results, for fixed tube wall and shell inlet temperatures, shell side outlet temperature.<br />

pressure drop values, heat transfer and heat transfer coefficient for varying fluid flow rates are provided in Table<br />

3 and it is found that the shell outlet temperature decreases with increasing mass flow rates as expected even the<br />

variation is minimal. It is found that for three mass flow rates1 kg/s & 2 kg/s there is no much effect on outlet<br />

170


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

temperature <strong>of</strong> the shell even though the baffle inclination is increased from 0° to <strong>20</strong>°. However the shell-side<br />

pressure drop is decreased with increase in baffle inclination angle i.e., as the inclination angle is increased from<br />

0° to <strong>20</strong>°. The pressure drop is decreased by 4 %, for heat exchanger with 10° baffle inclination angle and by 26<br />

% for heat exchanger with <strong>20</strong>° baffle inclination compared to 0° baffle inclination heat exchanger. Hence it can<br />

be observed that shell and tube heat exchanger with <strong>20</strong>° baffle inclination angle results in a reasonable pressure<br />

drop. Hence it can be concluded shell and tube heat exchanger with <strong>20</strong>° baffle inclination angle results in better<br />

performance compared to 10° and 0° inclination angles.<br />

Figure 2. Cut section showing velocity path lines along the shell for 0° baffle inclination angle for 1kg/s<br />

Figure 3. Cut section showing velocity path lines along the shell for 10° baffle inclination angle for 1kg/s<br />

171


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 4. Cut section showing velocity path lines along the shell for <strong>20</strong>° baffle inclination angle for 1 kg/s<br />

4. Conclusions<br />

The shell side <strong>of</strong> a small shell-and-tube heat exchanger is modeled with sufficient detail to resolve the flow and<br />

temperature fields. Following conclusions are drawn from the present study:<br />

1. For the given geometry, the mass flow rate must be below 2 kg/s, if it is increased beyond 2 kg/s the pressure<br />

drop increases rapidly with little variation in outlet temperature.<br />

2. The pressure drop is decreased by 4 %, for heat exchanger with 10° baffle inclination angle and by 26 %, for<br />

heat exchanger with <strong>20</strong>° baffle inclination angle.<br />

3. The maximum baffle inclination angle can be <strong>20</strong>°, if the angle is beyond <strong>20</strong>°, the centre row <strong>of</strong> tubes are not<br />

supported. Hence the baffle cannot be used effectively.<br />

4. Hence it can be concluded that shell-and-tube heat exchanger with <strong>20</strong>° baffle inclination angle results in better<br />

performance compared to 10° and 0° inclination angles.<br />

Nomenclature<br />

x, y, z position coordinates, [-]<br />

u, v, w velocity components, [ms -1 ]<br />

do<br />

tube outer diameter, [mm]<br />

q Heat flux as a source term, [Wm -2 ]<br />

θ<br />

baffle inclination angle, [degrees]<br />

B<br />

central baffle spacing, [mm]<br />

Bc baffle cut, [%]<br />

Di<br />

shell inner diameter, [mm]<br />

L<br />

heat exchanger length, [mm]<br />

Nb number <strong>of</strong> baffles, [-]<br />

Nt number <strong>of</strong> tubes, [-]<br />

T<br />

temperature, [K]<br />

Vr velocity vector, [-]<br />

Greek symbols<br />

ρ<br />

[Kgm-3]<br />

τ [Nm -2 ]<br />

ϕ Dissipation function [-]<br />

References<br />

[1]. Gaddis, D., editor. Standards <strong>of</strong> the Tubular Exchanger Manufacturers Association, ninth ed, Tarrytown<br />

(NY): TEMA Inc, <strong>20</strong>07.<br />

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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[2]. Schlunder, E.V, Heat Exchanger Design Handbook, Hemisphere Publishing Corp., New York, Bureau <strong>of</strong><br />

Energy Efficiency, <strong>19</strong>83.<br />

[3]. Mukherjee, R., Practical Thermal Design <strong>of</strong> Shell-and-Tube Heat Exchangers, Begell House.Inc, New York,<br />

<strong>20</strong>04.<br />

[4]. Ender Ozden, Ilker Tari, Shell side CFD analysis <strong>of</strong> a small shell-and-tube heat exchanger, Energy<br />

Conversion and Management 51 (<strong>20</strong>10), pp. 1004 – 1014.<br />

[5]. Uday Kapale, C., Satish Chand, Modeling for shell-side pressure drop for liquid flow in shell-and-tube heat<br />

exchanger, International Journal <strong>of</strong> Heat and Mass Transfer 49 (<strong>20</strong>06), pp. 601–610<br />

[6]. Thirumarimurugan, M., Kannadasan, T., Ramasamy, E., Performance Analysis <strong>of</strong> Shell and Tube Heat<br />

Exchanger Using Miscible System, American Journal <strong>of</strong> Applied <strong>Science</strong>s 5 (<strong>20</strong>08), pp. 548-552.<br />

[7]. Sparrows, E. M., Reifschneider, L. G., Effect <strong>of</strong> inter baffle spacing on heat transfer and pressure drop in a<br />

shell-and-tube heat exchanger, International Journal <strong>of</strong> Heat and Mass Transfer 29 (<strong>19</strong>86), pp. 1617-1628.<br />

[8]. Li, H., Kottke, V., Effect <strong>of</strong> baffle spacing on pressure drop and local heat transfer in shell and tube heat<br />

exchangers for staggered tube arrangement, Int. J. Heat Mass Transfer 41<br />

(<strong>19</strong>98), 10, pp. 1303–1311<br />

[9]. Su Thet Mon Than, Khin Aung Lin, Mi Sandar Mon, Heat Exchanger Design, WorldAcademy <strong>of</strong> <strong>Science</strong>,<br />

Engineering and <strong>Technology</strong> 46, <strong>20</strong>08.<br />

[10]. Kakac, S., Liu, H., Heat Exchangers Selection, Rating and Thermal Design, CRC press,second ed,<br />

Washington D.C., <strong>20</strong>02, pp. 318–335<br />

[11]. Gay, B., Mackley, N.V., Jenkins, J. D., Shell-side heat transfer in baffled cylindrical shell andtube<br />

exchangers, Int. J. Heat Mass Transfer <strong>19</strong> (<strong>19</strong>76), pp. 995-1002.<br />

[12]. Emerson, W.H., Shell-side pressure drop and heat transfer with turbulent flow in segmentally baffled shelltube<br />

heat exchangers, Int. J. Heat Mass Transfer 6 (<strong>19</strong>63), pp. 649–668.<br />

[13]. Yong-Gang Lei, Ya-Ling He, Rui Li, Ya-Fu Gao, Effects <strong>of</strong> baffle inclination angle on flow and heat<br />

transfer <strong>of</strong> a heat exchanger with helical baffles, Chemical Engineering and Processing 47 (<strong>20</strong>08), pp. 2336–<br />

2345.<br />

[14]. Versteeg, H.K., Malalasekera, W., An introduction to computational fluid dynamics: the finite volume<br />

method, first ed, Essex (England): Pearson, <strong>19</strong>95.<br />

[15] Incropera FP, Dewitt DP. Fundamentals <strong>of</strong> heat and mass transfer. 4th ed. New York: J. Wiley; <strong>19</strong>96.<br />

[16] STAR-CCM+ version 6. Starccm+ 6 User’s Guide. CDADAPCO Inc.<br />

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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

PERFORMANCE BASED COMPARATIVE ANALYSIS OF THERMAL<br />

POWER PLANT: A REVIEW<br />

Man Mohan Kakkar, Raj Kumar & Mukesh Gupta<br />

Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad (Haryana)<br />

India<br />

Abstract<br />

Coal based thermal power stations are the leaders in electricity generation in India. In this paper, the author<br />

attempts to investigate the gap between demand & supply and cost reduction in order to make the existing power<br />

plants more efficient. Efficient power generation is expected to make more power available at a lower cost for<br />

economic and other activities, which in turn shall make the country more competitive. The focus <strong>of</strong> the study is<br />

on the coal fired thermal power plants in the country. The performance calculation and rectification measures<br />

are essential for performance evaluation and efficiency enhancement.<br />

Keywords: Thermal Power Plant, Performance Evaluation, Efficiencies, Energy<br />

1. Introduction<br />

Electricity is essential in the economic development <strong>of</strong> any nation. Due to rapid growth <strong>of</strong> economy and<br />

industrial development in India, the demand for use <strong>of</strong> electricity has increased rapidly. Power generation<br />

capacity in India is 70 percent thermal, with the remaining being hydro and nuclear. Thermal generation is<br />

mainly based on steam generation using a coal-fired boiler. Power Plant play very important role in improving<br />

the economic condition, competitive advantage, life style, so on, <strong>of</strong> people in any country. Many research studies<br />

have been carried out on specific subsystems <strong>of</strong> the Power Plant, for example , turbine, boilers and turbo<br />

generators, in a bid to improve the reliability, safety , security, efficiency, productivity, and availability <strong>of</strong> the<br />

subsystems individually and therefore <strong>of</strong> the plant as a whole. Some researchers have tried to develop models for<br />

subsystems working in series /parallel combination. Commercial s<strong>of</strong>tware for evaluating the performance <strong>of</strong> a<br />

subsystem is also available. The authors are, however, not aware <strong>of</strong> any study that integrates all the subsystems<br />

and systems <strong>of</strong> a power plant.<br />

It has been shown by a number <strong>of</strong> researchers that the performance <strong>of</strong> any system is a function <strong>of</strong> the structure <strong>of</strong><br />

the system. The understanding <strong>of</strong> the structure, that is, system and connectivity between different systems and<br />

down to component level, is useful for estimating the contribution <strong>of</strong> different attributes <strong>of</strong> the performance <strong>of</strong><br />

the system. Any Production system should be kept failure free (as far as possible) under the given operative<br />

conditions to achieve the set goals <strong>of</strong> economical production and long run performance. A highly reliable system<br />

tends <strong>of</strong> increases the efficiency <strong>of</strong> production.<br />

According to Behera and Dash (<strong>20</strong>10) study non- parametric Data Envelopment Analysis (DEA) to estimate the<br />

relative technical efficiency and scale efficiencies <strong>of</strong> coal-based power plant in India. Distribution <strong>of</strong> the less<br />

efficient plants in different sectors, regions, their peer groups and the return to scale properties are analysed [1].<br />

Behra et al. (<strong>20</strong>09) attempts to investigate to estimate the relative performance <strong>of</strong> the coal fired powergenerating<br />

plants in India and explore the key determinants <strong>of</strong> the inefficient units [2].<br />

Chitkara (<strong>19</strong>99) applied Data Envelopment Analysis (DEA) to evaluate the operational inefficiencies <strong>of</strong><br />

generating units. Three parameters viz. generation per unit <strong>of</strong> coal consumed, generation per unit oil consumed<br />

and generation per unit <strong>of</strong> auxiliary power consumption have been considered as indicators <strong>of</strong> performance [3].<br />

Shanmugar and Kulshreshtha (<strong>20</strong>05) employ the stochastic frontier production function methodology for<br />

panel data to measure the technical efficiency (TE) <strong>of</strong> coal- based thermal power plants [4].<br />

Mohan et al. (<strong>20</strong>03) developed a methodology for optimum selection, benchmarking sensitivity analysis, plant<br />

modification-replacement /reconfiguration, maintenance strategy analysis, selection and outage planning, and<br />

performance [5].<br />

Gupta et al. (<strong>20</strong>09) discusses the development <strong>of</strong> a Markov model for performance evaluation <strong>of</strong> coal handling<br />

unit <strong>of</strong> a thermal power plant using Probabilistic approach. Coal handling unit consists <strong>of</strong> two subsystems with<br />

two possible states i.e. working and failed. This developed model helps in comparative evaluation <strong>of</strong> alternative<br />

maintenance strategies.<br />

174


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Gupta and Tewari (<strong>20</strong>09) discuss the stochastic analysis and performance evaluation <strong>of</strong> condensate system <strong>of</strong> a<br />

thermal power plant. On the basis <strong>of</strong> this study performance <strong>of</strong> each subsystem <strong>of</strong> condensate system is evaluated<br />

and then maintenance decisions are made for subsystems.<br />

Gupta and Tewari (<strong>20</strong>09) developed a Probabilistic model, considering some assumptions. The proposed model<br />

provides an integrated modelling and analysis frame work for performance evaluation <strong>of</strong> the flue gas and air<br />

system <strong>of</strong> the thermal plant [6-8].<br />

Mandal (<strong>20</strong>08) highlights some <strong>of</strong> design improvements which target reduced emissions and expanded<br />

operability, and explores some <strong>of</strong> the boiler implications for the ultra-supercritical conditions, needed to achieve<br />

the high cycle efficiencies for the future [9].<br />

Prasad et al. (<strong>19</strong>99) developed a simulation for investigation purposes. The twin key aspects <strong>of</strong> the performance<br />

monitoring, i.e. monitoring <strong>of</strong> performance indices and controllable parameters are addressed in more effective<br />

and novel ways [10].<br />

Liu et al. (<strong>20</strong>10) results show that the most important variable in the DEA model is the “heating value <strong>of</strong> total<br />

fuels”. Finding from this study can be beneficial in improving some <strong>of</strong> the exiting power plants and for more<br />

efficient operational strategies and related policy-making for future power plants [11].<br />

Gupta et al. (<strong>20</strong>09) discusses performance evaluation <strong>of</strong> the steam and water system in a thermal power plant,<br />

with the help <strong>of</strong> developed probabilistic model. The system consists with two possible states: working and failed<br />

[12].<br />

Garg et al. (<strong>20</strong>07) presents a computational methodology for a computer – based solution to the problem <strong>of</strong><br />

evaluation and selection <strong>of</strong> an optimum power plant. This methodology is named as multiple attribute decision<br />

making (MADM) methodology and consists <strong>of</strong> elimination search and technique for order preference by<br />

similarity to ideal solution (TOPSIS) approach [13].<br />

Look and Saur, (<strong>19</strong>86) presents that the evaluation <strong>of</strong> the performance <strong>of</strong> a thermal plant is geared basically<br />

towards the determination <strong>of</strong> the energy efficiency <strong>of</strong> the plant. A plant’s energy efficiency has definite<br />

economic significance since the heat input at high temperature represents the energy that must be purchased (oil,<br />

natural gas, etc) and the net energy output represents the returns for the purchase [14].<br />

Utgikar et al, (<strong>19</strong>94) discussed that energy plays a vital role in a country’s economic development and it is<br />

expected to be more significant in the coming years due to increasing demand, consequently, energy<br />

conservation and efficient use <strong>of</strong> energy becomes a major supply option [15].<br />

This paper aims at the determination <strong>of</strong> the performance <strong>of</strong> thermal plant, with the intent <strong>of</strong> appreciating those<br />

conditions favourable or unfavourable for good performance as might be common to all thermal plants <strong>of</strong> its<br />

kind, as well as such conditions that might be unique to India, also, to suggest possible means <strong>of</strong> ensuring<br />

improvements. The performance is discussed based on the plant’s overall efficiency, boiler, thermal and turbine<br />

efficiencies. An estimated overall efficiency is compared with a calculated overall efficiency.<br />

2. Methodology<br />

It has been observed that an energy analysis was carried out on the system as a whole as well as on the major<br />

components <strong>of</strong> the plant i.e. the boiler, turbine, and condenser. Information on the following parameters was used<br />

for the analysis <strong>of</strong> power plant [16].<br />

i. Gross energy generated (MWH)<br />

ii. Energy used in the plant (MWH)<br />

iii. Energy sent out (MWH)<br />

iv. Fuel Coal consumed (MT)<br />

v. Running hours (hrs)<br />

vi. Equipment availability<br />

vii. Total number <strong>of</strong> forced and planned outages.<br />

viii. Conditions responsible for forced outages.<br />

Other data acquired from the plant include:<br />

ix. The unit heat rate (KJ/KWH)<br />

x. The unit net heat rate (K/KWH)<br />

xi. Generator efficiency.<br />

175


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2.1. Assumptions [16]<br />

As per literature survey, the following assumptions are considered for the efficient operation <strong>of</strong> power plant.<br />

1. Net heat rate in KJ/KWH was taken to be equal for all the units in operation.<br />

2. The thermodynamic parameters at the various state points are the same in all the units in operation.<br />

3. In calculating the boiler and turbine efficiencies, the enthalpies at the relevant state points were taken to<br />

be equal to the initial values based on the commissioning energy balance.<br />

4. Heat rate equals the initial value based on the commissioning energy balance.<br />

5. Plant operated at maximum continuous rating through out the period in review.<br />

6. Generator efficiency is constant at 98%.<br />

7. Efficiency is taken to be constant.<br />

2.2. Constraints & limiting factors<br />

1. Poor record keeping practice.<br />

2. Constant fluctuation and irregularity <strong>of</strong> plant loading due to the constant fluctuations in the transmission<br />

efficiency <strong>of</strong> the national grid as controlled by the national control centre.<br />

3. Breakdown <strong>of</strong> equipment.<br />

2.3. Performance evaluation [16]<br />

Energy analysis <strong>of</strong> the thermal plant involves the following calculations<br />

Estimated overall efficiency<br />

ŋoe = Energy transfer to fluid<br />

Fuel energy Consumed (1)<br />

Boiler efficiency<br />

β = Heat transfer to fluid (2)<br />

Fuel Energy Consumed<br />

Heat transfer to fluid is calculated as net heat rate (KJ/KWh)*Gross energy generated (KWh)<br />

Internal turbine efficiency<br />

τ = Heat drop in turbine<br />

Net energy sent to turbine (3)<br />

Where,<br />

Heat drop in turbine = [(H 1 -H 2 ) + (H 3 -H 4 )]*Running time (hrs) per unit available<br />

H 1 =Total heat <strong>of</strong> Steam at the stop valve (KJ/H)<br />

H 2 = Total heat <strong>of</strong> Steam to reheat (KJ/H)<br />

H 3 = Total heat <strong>of</strong> Steam to turbine from reheated (KJ/H)<br />

H 4 = Total heat <strong>of</strong> Steam at exhaust (KJ/H)<br />

Net heat energy sent to the turbine = net heat rate* gross energy generated per unit available<br />

Condenser effectiveness<br />

Є = 1 – Exp (-Ntu) (4)<br />

Where,<br />

Ntu= [t 2 -t 1 )/ LMTD<br />

T1= Inlet temperature <strong>of</strong> condenser cooling water ( o C)<br />

T2 =Outlet temperature <strong>of</strong> condenser cooling water ( o C)<br />

LMTD = Logarithmic mean temperature difference<br />

176


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Thermal efficiency<br />

ŋ t = 3412 (5)<br />

γ*heat rate<br />

Where, γ = generator efficiency<br />

Heat rate is in Btu/Kwh, 1 Kwh = 3412 Btu<br />

Calculated overall efficiency<br />

ŋ oc = ŋ t * β * τ * γ (6)<br />

The estimated overall efficiency, ŋ oe, would be compared with the calculated overall efficiency, ŋ oc, using<br />

statistical testing.<br />

T = X – µ o (7)<br />

s/√n<br />

Where, the mean estimated overall efficiency ŋ oe is taking as our hypothesis (null hypothesis, µ o ). We shall<br />

accept the hypothesis if the test suggests that it is true, except for a small error probability, α, called the<br />

significance level <strong>of</strong> the test, otherwise the hypothesis is rejected.<br />

Where,<br />

X = 1/nΣ j =1X j<br />

S 2 = 1/(n-1)Σ j =1/(X j -X) 2<br />

Using the t-distribution with n-1 degrees <strong>of</strong> freedom (n=number <strong>of</strong> years under consideration). X and S are the<br />

mean and standard deviation respectively <strong>of</strong> the calculated overall efficiency. Choosing a significance level <strong>of</strong><br />

5% (α=5%) from the t- distribution table, we obtained a critical value, c, such that,<br />

P(T≤ c) = α = 5% or P(T≤ ĉ) =1- α = 95%<br />

So that c=ĉ because <strong>of</strong> the symmetry <strong>of</strong> the distribution<br />

If the hypothesis is true, we have a chance <strong>of</strong> only α (=5%) that we observe a value t <strong>of</strong> T (calculated from our<br />

sample) that will fall between – α and –c. Nevertheless we do observe such a t, we assert that the hypothesis<br />

(mean estimated overall efficiency) cannot be true and we reject it. Then we accept the alternative (mean<br />

calculated overall efficiency). If however, t≥ c, we accept the hypothesis.<br />

2.4 Discussion<br />

From the literature review the following recommendations needs to be incorporated to improve the performance<br />

and efficiency <strong>of</strong> the plant have been made for each <strong>of</strong> the units covering maintenance and operational aspects.<br />

The recommendations have been divided into three categories viz short term, medium term and long term<br />

respectively.<br />

The short term recommendations are those which can be implemented immediately at a low cost. These relate to<br />

improving vacuum, mill operation, boiler operation, ESP (better housekeeping, on time deashing to avoid ash<br />

carry over and electrical maintenance) etc and all other equipment and systems as are considered important for<br />

improvement <strong>of</strong> plant efficiency.<br />

The medium term recommendations pertain to those works which can be taken up during major shut down or<br />

during overhauling. These recommendations relate to attending to coal firing system, air dampers, flue gas<br />

system, cooling towers etc.<br />

The long term recommendations cover renovation and modernization aspects <strong>of</strong> the plant considering the<br />

available poor quality coal for power generation.<br />

2.5 Suggestions for system improvement<br />

By extensive literature survey and interaction with project personnel at power plants spread all over the country<br />

suggested that substantial improvements in their performance are feasible with improvements in management<br />

systems. These are indicated below which may be analyzed from case to case and unit to unit.<br />

• Each unit should have a “Performance Monitoring schedule all Major systems in power plant including the<br />

auxiliaries (Coal handling plant, ash handling plant, water treatment plants and compressors). Monthly<br />

performance tests should be conducted to evaluate boiler efficiency, condenser performance, turbine cylinder<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

efficiency, LP/HP heater performance, turbine heat rate etc. These figures should be checked with the design, last<br />

month’s performance, best performance <strong>of</strong> the unit and best performance <strong>of</strong> similar other units in the station.<br />

• Milling system maintenance and air preheated maintenance should be given the top priority based on the<br />

performance monitoring parameters and ensure timely replacement <strong>of</strong> worn out parts to ensure reliable output.<br />

• Grid monitoring <strong>of</strong> Oxygen and CO to ensure a complete combustion and control combustion air to limit the<br />

dry gas losses.<br />

• Installation <strong>of</strong> reliable rotary gravimetric feeders to ensure the coal quantity feed into the mill and indirectly to<br />

boiler to get an online assessment <strong>of</strong> boiler performance.<br />

• Up gradation <strong>of</strong> C&I system to replace the obsolete technology and installation <strong>of</strong> more close loop controls to<br />

avoid manual interference.<br />

• Major maintenance <strong>of</strong> CW system and cooling towers to achieve quality and Retr<strong>of</strong>itting <strong>of</strong> Electro hydraulic<br />

control system with auto starting <strong>of</strong> turbine system with motorized drains to meet the new grid codes and fast<br />

response to variation in demand and auto operation,<br />

• Shift wise monitoring <strong>of</strong> operating controllable parameters and merit order operation concept to gain efficiency<br />

and availability.<br />

• The results <strong>of</strong> monthly performance monitoring <strong>of</strong> the station should be discussed in a meeting taken by the<br />

Head <strong>of</strong> the plant and remedial action plan including action on urgent financial issues, should be decided in the<br />

meeting.<br />

• Provision <strong>of</strong> computer s<strong>of</strong>tware for performance monitoring, maintenance planning and for simulation studies<br />

at the plant site may be considered. Spare planning and inventory management tools to be incorporated to avoid<br />

the delay in maintenance duration and non availability <strong>of</strong> spares.<br />

• Annual overhaul <strong>of</strong> units and auxiliaries should be done regularly based on the performance deterioration.<br />

Assessment to be made before and after to access the techno economical gain as far as possible. Activities to, be<br />

planned as far as possible on account <strong>of</strong> system demands.<br />

• Manufacturer’s maintenance manuals for different equipments and operating guide lines should be available in<br />

plant <strong>of</strong>fice. Senior <strong>of</strong>ficers during their inspections should ascertain that the instructions <strong>of</strong> the manuals are<br />

being followed.<br />

• Retr<strong>of</strong>itting energy efficient hydro drive system for conveyors more than75 KW capacity<br />

• Important work instructions pertaining to particular equipments should be displayed close to the equipment at<br />

an appropriate place.<br />

• CFD modeled ducts to reduce the duct pressure losses and implementing VVF drives to reduce the auxiliary<br />

power consumption to be incorporated to update the unit performance to meet the latest demands.<br />

• Retr<strong>of</strong>itting dry rotary compressors with HOC (heat <strong>of</strong> compressor for regeneration) drier in place <strong>of</strong> old<br />

compressors to maintain better instrument air and service air to meet the modern pneumatic instruments.<br />

• Retr<strong>of</strong>itting the latest development in purification like RO system etc to make quality DM water from the<br />

deteriorated input water available.<br />

• Retr<strong>of</strong>itting the dry bottom ash system with recirculation to reduce the water consumption and utilization <strong>of</strong><br />

bottom ash.<br />

• Charging the auxiliary header from CRH at rated load condition to reduce the energy loss <strong>of</strong> conversion to low<br />

pressure steam.<br />

• Utilizing the waste heat to retr<strong>of</strong>it the VAM (Vapor absorption machines) refrigeration system in place <strong>of</strong><br />

HVAC system.<br />

• Energy efficient lighting system to utilize the latest LEDs to reduce the life cycle cost.<br />

• One <strong>of</strong> the major causes for the poor performance is the poor housekeeping which needs immediate attention<br />

and close monitoring by top management. It has already proven that this will reduce the maintenance cost and<br />

increase the availability.<br />

• Establishing a separate company at loading point or a centralized location ( coal conditioning company) to<br />

condition or blend the coal and supply the proper size coal (1mm to 5mm size) in ensured quality ( without<br />

stones and controlled calorific value and ash content) can reduce the losses to minimum and reduce the auxiliary<br />

power consumption . They can do the blending and first grinding and separation; This Company can utilize the<br />

low calorific reject coal in the low capacity CFBC/PFBC technology and meet the heat and power requirement<br />

for coal conditioning. This will ensure reliability and availability <strong>of</strong> high capacity<br />

Most efficient units and reduce the partial and force outage to minimum. Major partial outages were observed<br />

due to variation and non availability <strong>of</strong> coal for bigger capacity high efficiency units. This will reduce the high<br />

quality grinding media consumption and outage <strong>of</strong> high capacity units.<br />

3. Conclusion<br />

In this paper, a review on energy analysis <strong>of</strong> the thermal power station has been carried out using the methods <strong>of</strong><br />

thermodynamic analysis by considering the ratio <strong>of</strong> energy generated per annum to the amount <strong>of</strong> the fuel<br />

consumed and the other involves products <strong>of</strong> the plants thermal efficiency and the efficiencies <strong>of</strong> the boiler,<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

turbines and generator. In this paper, the various performance evaluation parameters are suggested which are<br />

mentioned in section 2.3. Based on these parameters, three categories <strong>of</strong> recommendations are incorporated<br />

which are short term, medium term and long term. The short term, medium term and long term categories <strong>of</strong><br />

recommendations suggests the overall working performance <strong>of</strong> the plant. Lesser consumption <strong>of</strong> input will not<br />

only reduce the cost <strong>of</strong> electricity generation there by enhancing the competitiveness but also make available the<br />

scarce inputs to generate more and more electricity.<br />

References<br />

[1] Santosh K. Brhera, and Ambika P. dash, Performance analysis <strong>of</strong> coal fired power plant in India<br />

Proceedings <strong>of</strong> the <strong>20</strong>10 International Conference on Industrial Engineering and Operations<br />

Management Dhaka, Bangladesh, January 9-10, <strong>20</strong>10<br />

[2] Behera S.K, Dash A.P, Farooquie J.A, (<strong>20</strong>09), Performance evaluation and efficiency analysis <strong>of</strong> coal<br />

Fired Thermal Power Plants in India<br />

[3] Chitkara Puneet, a Data Envelopment Analysis Approach to Evaluation <strong>of</strong><br />

Operational Inefficiencies in Power Generating Units: A Case Study <strong>of</strong> Study <strong>of</strong> Indian Power Plants,<br />

IEEE Transactions on Power System, Vol.14, No.2, May<strong>19</strong>99<br />

[4] K .R. Shanmugam and Kulshreshtha Praveen, Efficiency analysis <strong>of</strong> coal-based thermal power<br />

generation in India during post-reform era, Int. J. Global Energy Issues, Vol. 23, No.1, <strong>20</strong>05<br />

[5] Mohan, M., Gandhi, O.P., and Agrawal, V.P., Systems modeling <strong>of</strong> a coal based steam power plant<br />

proceeding <strong>of</strong> the Institution <strong>of</strong> Mechanical Engineers, Part A: Journal <strong>of</strong> Power and Energy, volume<br />

217, pages 259-277, number 3, <strong>20</strong>03<br />

[6] Gupta S., Tewari P.C., Sharma A.K.,A Markov Model for Performance Evaluation <strong>of</strong> Coal Handling<br />

Unit <strong>of</strong> a Thermal Power Plant, Journal <strong>of</strong> Industrial and System Engineering Vol.3, No.2,pp 85-96<br />

[7] Gupta S., Tewari P.C.,Simulation Model for stochastic Analysis and Performance Evaluation <strong>of</strong><br />

Condensate System <strong>of</strong> a Thermal Power Plant, Bangladesh J. Sic. Ind. Res. 44(4), 387,398,<strong>20</strong>09<br />

[8] Gupta S., Tewari P.C., Simulation modeling and analysis <strong>of</strong> a complex system <strong>of</strong> a thermal power plant,<br />

Journal <strong>of</strong> Industrial Engineering and Management Vol.2, No.2,pp 387-406<br />

[9] Pradip Kumar Mandal, (<strong>20</strong>01) Efficiency improvement in Pulverized coal based power stations.<br />

[10] Hogg, B.W. and Swidenbank E.and Prasad G., A Novel Performance Monitoring Strategy for<br />

Economical Thermal Power Operation, IEEE Transactions on Energy Conversion, Vol.14, No.3,<br />

September<strong>19</strong>99<br />

[11] C.H. Liu, Sue J Lin, and Charles Lewis, Evaluation <strong>of</strong> thermal power plant operational performance in<br />

Taiwan by data envelopment analysis, Energy Policy Journal <strong>of</strong> Elsevier,vol 38, Issue 2, pp1049-<br />

1058,<strong>20</strong>10<br />

[12] Gupta S., Tewari P.C., Sharma A.K, A Probalistic model for performance evaluation <strong>of</strong> steam and water<br />

system <strong>of</strong> a thermal power plant. International Journal <strong>of</strong> Management <strong>Science</strong> and Engineering<br />

Management vol.4, No3, pp.177-187, <strong>20</strong>09.<br />

[13] Garg R.K., Agrawal V.P., Gupta V.K., Coding, Evaluation and Selection <strong>of</strong> Thermal Power Plants-A<br />

MADM approach, Electrical Power and Energy System 29 (<strong>20</strong>07) 657-668<br />

[14] Look, D.C and Sauer, H.J., Engineering Thermodynamics, pp257-3<strong>19</strong>, <strong>19</strong>86.<br />

[15] Utgikar,P.S, Dubey,S.P and Rao,P.J.P, Thermo economic Analysis <strong>of</strong> Gas Turbine Cogeneration Plant,<br />

A Case Study, Proceeding <strong>of</strong> Institute <strong>of</strong> Mechanical Engineering, VOL.<strong>20</strong>9,PP45-54.<strong>19</strong>95.<br />

[16] www.unilag.edu.ng/opendoc.php<br />

179


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Exergetic Analysis <strong>of</strong> Combustion Chamber <strong>of</strong> a Combined Heat and Power<br />

System<br />

Nikhil Dev, Rajesh Attri<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, India<br />

nikhildevgarg@yahoo.com<br />

Abstract<br />

In the present analysis mathematical modeling for a 30MW cogeneration cycle is done and effect <strong>of</strong> cycle<br />

pressure ratio, inlet air temperature and turbine inlet temperature (TIT) is studied for the combustion chamber.<br />

Cogeneration is the production <strong>of</strong> electrical energy and useful thermal energy from the same energy source that<br />

is why it is called combined heat and power (CHP) system. From the results it is being found that there is an<br />

increase <strong>of</strong> exergy destruction by 31.30% when the inlet air temperature is increased from 5°C to 50°C.<br />

Increased exergy destruction shows that performance <strong>of</strong> combustion chamber deteriorates with the increase in<br />

inlet air temperature. A different pattern for the exergy destruction is observed when compressor pressure ratio<br />

is increased. From a compression ratio <strong>of</strong> 5 to 15 there is a decrease <strong>of</strong> exergy destruction in combustion<br />

chamber and after that it increases. After a compression ratio <strong>of</strong> 26, performance <strong>of</strong> system starts deteriorate<br />

and regenerator is no longer useful. That is why in the present analysis exergy destruction in the combustion<br />

chamber is studied only upto a pressure ratio <strong>of</strong> 26.<br />

Keywords: cogeneration; compressor; inlet air temperature; pressure ratio; TIT.<br />

1. Introduction<br />

A combustor converts the chemical energy in the fuel to heat energy which is transferred to the working fluid [1-<br />

4]. There are several different approaches for modeling <strong>of</strong> reactors. These include stoichiometric, equilibrium,<br />

kinetic, etc. The design <strong>of</strong> gas turbine combustion system is a complex process involving fluid dynamics,<br />

combustion and mechanical design. The most common fuel for gas turbines are liquid petroleum distillates and<br />

natural gas. Combustion in the normal, open-cycle, gas turbine is a continuous process in which fuel is burned in<br />

the air supplied by the compressor and electric spark is required for initiating the combustion process and<br />

thereafter the flame must be self-sustained [5-10]. Gas turbine combustion is a steady flow process in which a<br />

hydrocarbon fuel is burned with a large amount <strong>of</strong> excess air, to keep the turbine inlet temperature at an<br />

appropriate value. Now a day’s control <strong>of</strong> emissions has become the most important factor in the design <strong>of</strong><br />

industrial gas turbine. Combustion equations express conservation <strong>of</strong> mass in molecular terms following the<br />

rearrangement <strong>of</strong> molecules during the combustion process. The oxygen required for stoichiometric combustion<br />

can be found from the general equation:<br />

C x H y + nO 2 → aCO 2 + bH 2 O<br />

Where<br />

a = x, b = (y/2) and n = x + (y/4)<br />

Each kilogram <strong>of</strong> oxygen will be accompanied by (76.7/23.3) kg <strong>of</strong> nitrogen, which is normally considered to be<br />

inert and to appear unchanged in the exhaust; at the temperatures in the primary zone, however, small amount <strong>of</strong><br />

oxides <strong>of</strong> nitrogen are formed. The combustion equation assumes complete combustion <strong>of</strong> carbon to CO 2 , but<br />

incomplete combustion can result in to small amounts <strong>of</strong> carbon monoxide and unburned hydrocarbons (UHC)<br />

being present in the exhaust [11]. The gas turbine uses a large quantity <strong>of</strong> excess air, resulting in considerable<br />

oxygen in the exhaust; the amount can be deducted from the total oxygen in the incoming air less that required<br />

for combustion. Thus the exhaust <strong>of</strong> any gas turbine consist primary <strong>of</strong> N 2 , O 2 , CO 2 and H 2 O and composition<br />

can be expressed in terms <strong>of</strong> either gravimetric (by mass) or molar (by volume) composition. The main factors <strong>of</strong><br />

importance in assessing combustion chamber performance are (a) pressure loss, (b) combustion efficiency, (c)<br />

outlet temperature distribution, (d) stability limits and (e) combustion intensity. Till now not much attention is<br />

being paid on the concentration <strong>of</strong> the different constituents <strong>of</strong> combustion products [11-16]. In the present<br />

analysis a computer program is being executed in the s<strong>of</strong>tware Engineering Equation Solver (EES) for a 30 MW<br />

gas turbine. Results are analyzed for different concentration <strong>of</strong> combustion products.<br />

2. Mathematical Modeling<br />

The scheme outlined below has been numerically studied using a code developed in EES. The code is based on<br />

fundamental thermodynamic relations, including real gas behavior and pressure losses.<br />

180


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure: 1 Schematic flow diagram <strong>of</strong> Co-Generation Cycle<br />

In the present system ambient air is coming to air compressor and after compression its temperature and pressure<br />

is increased. This compressed air is passed through regenerator. In regenerator compressed air is entering from<br />

one side and combustion gases coming out <strong>of</strong> gas turbine from the other. High temperature combustion gases<br />

transfer their heat to the compressed air. After gaining heat this compressed air comes to combustion chamber<br />

and fuel is added in it. After burning in air chemical energy <strong>of</strong> fuel is converted into thermal energy.<br />

Temperature <strong>of</strong> combustion products coming out <strong>of</strong> combustion chamber depends upon turbine inlet temperature.<br />

Combustion product temperature is controlled by making A/F mixture a lean mixture. Gasses coming out from<br />

gas turbine are having a large amount <strong>of</strong> thermal energy. Some part <strong>of</strong> this thermal energy is transferred to<br />

compressed air in regenerator and remaining part is absorbed by high pressure water in steam generator. Flue gas<br />

temperature coming out <strong>of</strong> steam generator is dependent upon the dew point temperature <strong>of</strong> flue gases. This dew<br />

point temperature decides the temperature at which flue gases must enter the stack. Each component is modeled<br />

by mass and energy balances. If the system operates in a steady-state, steady flow condition and all the<br />

nonreacting gases are arbitrarily assigned as zero thermo mechanical enthalpy, entropy, and exergy at the<br />

condition <strong>of</strong> ambient pressure and temperature regardless <strong>of</strong> their chemical composition, then the entropy <strong>of</strong><br />

mixing different gaseous components can be neglected, and the general exergy-balance equation is given by<br />

For single stream flow<br />

Specific exergy is given by<br />

. n . . . .<br />

∑ ∑ ∑<br />

E = ( E ) i + me − me − E<br />

W Q D<br />

i=<br />

1<br />

in out<br />

. . . . .<br />

E = ( E ) + me − me − me<br />

W Q in out D<br />

⎛ T T ⎞ <br />

P ⎡<br />

<br />

⎛1+<br />

wa<br />

⎞<br />

( ) 1 ln (1 ) ln (1 )ln <br />

⎛ w ⎞⎤<br />

e = C<br />

pa<br />

+ wC<br />

pv<br />

Ta ⎜ − − ⎟ + + w RaTa + RaTa<br />

⎢ + w ⎜ wln<br />

T 1 ⎟ + ⎜ ⎟⎥<br />

⎝ a<br />

Ta ⎠ Pa<br />

⎢⎣<br />

⎝ + w ⎠ ⎝ wa<br />

⎠⎥⎦<br />

Where w = 1.608w<br />

The mass, energy, and exergy balances <strong>of</strong> the component <strong>of</strong> the plant are given below.<br />

2.1. Air Compressors<br />

The inlet and outlet humidity ratios will be the same. The energy balance yields the compressor work<br />

compressor outlet temperature.<br />

w<br />

ai<br />

= w<br />

ao<br />

Wc<br />

and<br />

T<br />

T<br />

a o<br />

a i<br />

=<br />

[ r ]<br />

c<br />

γ c − 1<br />

γ cη<br />

c<br />

W<br />

c<br />

= h<br />

a o<br />

− h<br />

a i<br />

The exergy balance for the compressor gives the exergy destruction e DC as following<br />

e = W + ( e − e )<br />

DC C ai ao<br />

181


2.2. Gas Turbines<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

For the expansion ratio, r e temperature at the exit <strong>of</strong> the turbine isentropic process can be calculated by<br />

( γ g −1)<br />

γ g<br />

gos gi e<br />

T = T ( r )<br />

The actual temperature T go at the exit <strong>of</strong> the turbine can be calculated by<br />

T<br />

ηT<br />

=<br />

T<br />

And the inlet and outlet humidity ratios will be the same<br />

w<br />

gi<br />

gi<br />

gi<br />

−T<br />

−T<br />

= w<br />

The energy balance yields the turbine work W T given by the following relation<br />

go<br />

gos<br />

go<br />

WT = hgi − hgo<br />

The exergy balance for the turbine gives the exergy destruction e DT as following<br />

2.3. Combustor<br />

e = ( e − e ) − W<br />

DT gi go T<br />

Mass <strong>of</strong> fuel supplied can be calculated by energy balance between the energy supplied by the fuel and change in<br />

enthalpy <strong>of</strong> combustion products due to this heat addition. Change in enthalpy <strong>of</strong> air after adding fuel in<br />

combustion chamber is<br />

η m CV = h − h = h − h<br />

cc f go gi<br />

3 2<br />

The exergy balance <strong>of</strong> the combustion chamber yields exergy destruction<br />

Where<br />

and ∆ g = ∆H −T ( s − s )<br />

r r av P R<br />

eDCC = m<br />

fCCe fCC<br />

+ eai − ego<br />

e = ∆ g + R T<br />

fCC r f a<br />

(s P −s R ) is the entropy change during the combustion process and is given as<br />

where<br />

⎡ Tgo pgo ⎤ ⎡ Tgo pgo<br />

⎤<br />

sP − sR = xa ⎢C pa<br />

ln − Ra ln ⎥+ xv ⎢C pv<br />

ln −Rv<br />

ln ⎥<br />

⎣ Tai pai ⎦ ⎣ Tai pai<br />

⎦<br />

x a<br />

1<br />

= and<br />

1 + w<br />

ln<br />

p<br />

x<br />

p<br />

v<br />

f<br />

a<br />

w<br />

=<br />

1 + w <br />

The effect <strong>of</strong> water vapor present in fuel is neglected and humidity ratio at combustion chamber outlet will be<br />

higher than inlet.<br />

2.4. Air Preheater (regenerator)<br />

Temperature <strong>of</strong> air (T ao ) at the exit <strong>of</strong> a heat exchanger can be calculated by<br />

Tao<br />

−T<br />

Heat Exchanger Effectiveness =<br />

T −T<br />

Applying the energy balance equation on the heat exchanger yields<br />

gi<br />

ai<br />

ai<br />

182


Proceedings <strong>of</strong> the National Conference on<br />

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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

( − ) = ( − )<br />

m h h m h h<br />

a rai rao p rgo rgi<br />

Here h rai and h rao represents the enthalpy <strong>of</strong> air at the regenerator inlet and outlet respectively and h rgi and h rgo<br />

represents the enthalpy <strong>of</strong> combustion products at the regenerator inlet and outlet respectively. The exergy<br />

balance <strong>of</strong> the heat exchanger (HE) yields exergy destruction.<br />

Exergy Destruction in HE = (e ai − e ao ) + (e gi − e go )<br />

2.5. Heat Recovery Steam Generator (HRSG)<br />

For regenerator and steam generator simple mass and enthalpy balance equations are used. The amount <strong>of</strong> heat<br />

transferred to water may be calculated as<br />

Qp = hgi − hgo<br />

Temperature <strong>of</strong> gas at regenerator outlet may be given as<br />

( − ) = ( − )<br />

m h h m h h<br />

p gi go w wi wo<br />

Exergy destroyed in HRSG can be calculated by<br />

Exergy Destruction in HRSG = (e gi − e go ) − m w (e wo − e wi )<br />

Inlet and outlet humidity ratio will remain same.<br />

Mathematical modeling described above is used for the cogeneration cycle. A program is executed in s<strong>of</strong>tware<br />

EES to study cogeneration cycle performance for different parameters. Real gas and water properties are inbuilt<br />

in the s<strong>of</strong>tware. Results obtained are discussed in the following section.<br />

3. Results and Discussion<br />

The conventional definition <strong>of</strong> efficiency <strong>of</strong> a combustor indicates how much thermal energy is available for use<br />

from the stored chemical energy <strong>of</strong> the fuel. The losses in a combustor that accounts for the decrease in the<br />

efficiency are due to unburnt fuel, incomplete combustion and heat loss to the surrounding across the combustor<br />

wall. For typical atmospheric combustion systems, about 1/3rd <strong>of</strong> the fuel exergy becomes unavailable due to the<br />

inherent irreversibilities in the combustor. Most <strong>of</strong> this irreversibility is associated with the internal heat transfer<br />

within the combustor between the products and reactants. Such heat transfer becomes inevitable in both<br />

premixed and diffusion flames, where highly energetic product molecules are free to exchange energy with<br />

unreacted fuel and air molecules. Lior [15] and Lior et al. [16] outlined the necessity <strong>of</strong> second-law-based<br />

analysis <strong>of</strong> combustion processes with the following objectives:<br />

(1) Identification <strong>of</strong> the specific phenomena/processes that have large exergy losses or irreversibilities,<br />

(2) Understanding <strong>of</strong> why these losses occur,<br />

(3) Evaluation <strong>of</strong> how they change with the changes in the process parameters and configuration, and<br />

(4) As a consequence <strong>of</strong> all the above, suggestions on how the process could be improved.<br />

A combustion system, in general, is a multicomponent and multiphase system. The physical processes occurring<br />

in the system can be classified broadly in two groups, namely: (i) transport processes and (ii) chemical reactions.<br />

The transport processes pertain to the transport <strong>of</strong> mass momentum and energy, which involve the processes <strong>of</strong><br />

diffusion and convection <strong>of</strong> those quantities. The turbulence plays an additional key role by transporting mass<br />

momentum and energy through turbulent eddies along with the transport <strong>of</strong> the quantities through molecular<br />

diffusion and flow-aided convection. The transport processes are inherently irreversible due to thermodynamic<br />

dissipation in the processes occurring under a finite potential gradient. The oxidation between fuel and oxidizer<br />

in a combustion system takes place through a number <strong>of</strong> reaction steps involving the production <strong>of</strong> intermediate<br />

species in the form <strong>of</strong> compounds, elements, radicals, molecules and atoms. The rate <strong>of</strong> any chemical reaction is<br />

guided either by the kinetics <strong>of</strong> the reaction or by the rate <strong>of</strong> diffusive transport <strong>of</strong> the reacting molecules to come<br />

in contact for possible collision for reaction. One way <strong>of</strong> analyzing the performance <strong>of</strong> a combustor is by the<br />

exergy balance across the combustor. Considering the fuel and air entering the combustor either separately, or in<br />

the form <strong>of</strong> a mixture, it is possible to calculate the exergy flow rate at the inlet to the combustor. It will comprise<br />

the chemical exergy <strong>of</strong> the fuel and the thermomechanical (or physical) exergy <strong>of</strong> the fuel and air. With the<br />

increase in inlet air temperature exergy destruction in the combustion chamber is increased. In the combustion<br />

chamber chemical energy <strong>of</strong> fuel is converted into thermal energy and some part <strong>of</strong> Gibbs free energy is lost in<br />

the process due to which exergy destruction takes place. As the inlet air temperature (IAT) increases exergy<br />

183


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

destruction in the combustion chamber (CC) increases. There is an increase <strong>of</strong> exergy destruction by 31.30%<br />

when the inlet air temperature is increased from 5°C to 50°C. Increased exergy destruction shows that<br />

performance <strong>of</strong> combustion chamber deteriorates with the increase in inlet air temperature. A different pattern for<br />

the exergy destruction is observed when cycle pressure ratio (CR) is increased.<br />

Exergy destruction in combustion<br />

chamber<br />

30000<br />

25000<br />

<strong>20</strong>000<br />

15000<br />

10000<br />

5000<br />

0<br />

5 10 15 <strong>20</strong> 25 30 35 40 45 50<br />

Ambient air temperature (°C)<br />

Figure: 1 Exergy destruction in combustion chamber with change in IAT<br />

From a compression ratio <strong>of</strong> 5 to 15 there is a decrease <strong>of</strong> exergy destruction in combustion chamber and after<br />

that it increases. After a compression ratio <strong>of</strong> 26, performance <strong>of</strong> system starts deteriorate and regenerator is no<br />

longer useful. That is why in the present analysis exergy destruction in the combustion chamber is studied only<br />

upto a pressure ratio <strong>of</strong> 26.<br />

Exergy Destruction in Combustion<br />

Chamber<br />

27000<br />

26500<br />

26000<br />

25500<br />

25000<br />

24500<br />

24000<br />

23500<br />

23000<br />

22500<br />

5 10 15 <strong>20</strong> 25 26<br />

Compressor Pressure Ratio<br />

Figure: 2. Exergy destruction in combustion chamber with change in CR<br />

As the inlet air temperature increases fuel consumption also increases. As it may be seen in the figure.3, there is<br />

an increase <strong>of</strong> 11.65% in fuel consumption with an increase in IAT from 5°C to 50°C. As it may be seen from<br />

the equation <strong>of</strong> combustion chamber exergy destruction that as the mass <strong>of</strong> fuel injected will increase, exergy<br />

destruction in combustion chamber will also increase.<br />

Mass <strong>of</strong> fuel injected in<br />

combustion chamber(g/Kg <strong>of</strong> air)<br />

1.7<br />

1.65<br />

1.6<br />

1.55<br />

1.5<br />

1.45<br />

1.4<br />

5 10 15 <strong>20</strong> 25 30 35 40 45 50<br />

Ambient air temperature (°C)<br />

Figure.3. Fuel consumption in combustion chamber with change in IAT<br />

184


Proceedings <strong>of</strong> the National Conference on<br />

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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Compression ratio <strong>of</strong> compressor also affects the mass <strong>of</strong> fuel to be injected in combustion chamber but in an<br />

irregular fashion. Upto a pressure ratio <strong>of</strong> 15 there is decrease in fuel consumption and after that it starts<br />

increasing. Similar pattern is observed for the exergy destruction in combustion chamber.<br />

Mass <strong>of</strong> fuel injected in combustion<br />

chamber (g/Kg <strong>of</strong> air)<br />

1.8<br />

1.75<br />

1.7<br />

1.65<br />

1.6<br />

1.55<br />

1.5<br />

5 10 15 <strong>20</strong> 25 26<br />

Cycle pressure ratio<br />

Figure: 4. Fuel consumption in combustion chamber with change in CR<br />

As the turbine inlet temperature increases, exergy destruction in combustion chamber decreases (figure.5). It is<br />

due to the reason that, increase in temperature inside the combustion chamber increases the fuel utilization<br />

efficiency. Due to increased fuel utilization efficiency, exergy destruction in combustion chamber is decreased.<br />

With increase in TIT from 900°C to 1300°C, exergy destruction is decreased by 6.22%.<br />

Exergy destruction in combustion<br />

chamber<br />

27000<br />

26500<br />

26000<br />

25500<br />

25000<br />

24500<br />

24000<br />

900 950 1000 1050 1100 1150 1<strong>20</strong>0 1250 1300<br />

Turbine inlet temperature (°C)<br />

Figure: 5. Exergy destruction in combustion chamber with change in turbine inlet temperature (°C)<br />

If heat is transferred from a high temperature to lower temperature then its quality goes down and exergy<br />

destruction takes place. Exergy (or available energy, or availability) is the maximum useful work that can be<br />

extracted from a quantity <strong>of</strong> energy and refers to the quality <strong>of</strong> energy. Thus, though the energy is conserved in<br />

the process <strong>of</strong> conversion, its quality deteriorates and less work can be obtained with each conversion. The<br />

various irreversible processes encountered within the combustor leads to certain degree <strong>of</strong> exergy loss. It is<br />

observed that the second-law efficiency is the maximum for the stoichiometric supply <strong>of</strong> air. The lower product<br />

gas temperature at the exit for a lean mixture as a result <strong>of</strong> the excess air supply reduces the second-law<br />

efficiency <strong>of</strong> the combustor. This is despite the fact that all the energy stored in the fuel is contained in the<br />

product gas with the complete combustion <strong>of</strong> the fuel in case <strong>of</strong> a lean fuel–air mixture in the adiabatic<br />

combustor. Therefore, it is clear that neither the completeness <strong>of</strong> combustion nor the energy content <strong>of</strong> the<br />

product gas determines the exergy-based performance <strong>of</strong> the combustor. As the product gas temperature at the<br />

combustor exit decreases with the increase in the excess supply <strong>of</strong> air, the maximum ability <strong>of</strong> it to perform<br />

useful work decreases. Therefore, the second-law efficiency decreases. The same decrease in exergetic efficiency<br />

is also observed with the insufficient supply <strong>of</strong> air, when the exit temperature decreases because <strong>of</strong> the<br />

incomplete release <strong>of</strong> fuel’s stored energy. The maximum efficiency, which is obtained with the stoichiometric<br />

185


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

supply <strong>of</strong> air, may be considered as the ideal situation for every inlet air temperature. This ideal efficiency again<br />

increases with the increase in the inlet air temperature which increases the temperature <strong>of</strong> the product gas.<br />

Adebiyi [17] showed from a similar analysis in an adiabatic combustor, assuming complete combustion without<br />

dissociation and constant specific heats <strong>of</strong> air and product gas, that the maximum second-law efficiency<br />

attainable for a combustion engine is 70% with CH 4 as the fuel and keeping the product temperature within the<br />

acceptable limit guided by the metallurgical constraint. The second-law efficiency obtained from the exergy<br />

approach gives a direct measurement <strong>of</strong> the performance <strong>of</strong> the combustor. The larger the irreversibilities, lower<br />

will be the value <strong>of</strong> the second-law efficiency. However, this approach does not throw any light on the causes <strong>of</strong><br />

the irreversibilities. In a combustor, several transport and chemical processes take place simultaneously, which<br />

are irreversible. The contribution <strong>of</strong> the processes towards entropy generation at different locations within the<br />

combustor is required to be known to investigate the primary causes <strong>of</strong> exergy loss. It is also not practically<br />

possible to improve the performance <strong>of</strong> a combustor without such information.<br />

The present approach fails to provide this data and calls for a methodology, which considers the irreversibility as<br />

a field variable to find its distribution within the entire combustor. In the flow field <strong>of</strong> a combustor, the<br />

nonequilibrium conditions are due to the exchange <strong>of</strong> momentum, energy and mass <strong>of</strong> different species<br />

(multicomponent) within the fluid and at the solid boundaries. These nonequilibrium phenomena cause a<br />

continuous generation <strong>of</strong> entropy in the flow field. The entropy generation is due to the irreversible nature <strong>of</strong> heat<br />

transfer, mass diffusion, viscous effects within the fluid and at the solid boundaries, chemical reaction, coupling<br />

effects between heat and mass transfers and body force effects. Every irreversible process can be viewed as the<br />

relevant flux driven by the corresponding potential, e.g. the flux <strong>of</strong> heat is driven by the temperature gradient.<br />

The highest exergy exists in the fuel, which represents the maximum potential <strong>of</strong> the fuel to perform work. When<br />

this chemical energy is transformed into thermal energy, some portion (which depends on the final temperature)<br />

<strong>of</strong> the initial availability is destroyed. The amount <strong>of</strong> the exergy that is destroyed increases for lower final<br />

temperatures <strong>of</strong> the product, i.e. for lower flame temperature. The higher initial temperature <strong>of</strong> the reactant<br />

decreases the destruction in exergy in the combustion process due to the higher temperature <strong>of</strong> the product,<br />

which retains more exergy contained in it.<br />

Nomenclature<br />

E = Exergy rate (kJ/s)<br />

Hf = Heat supplied by fuel {kJ/kg (dry air)}<br />

∆Hr = Heat <strong>of</strong> reaction <strong>of</strong> fuel (kJ/kg <strong>of</strong> fuel)<br />

R = Gas constant (kJ/kg K)<br />

T = Absolute temperature (K)<br />

TP = Process heat temperature (°C)<br />

W = Work (kJ/kg (dry air))<br />

cp = Specific heat at constant pressure (kJ/kg K)<br />

cv = Specific heat at constant pressure (kJ/kg K)<br />

e = Specific exergy (kJ/kg (dry air))<br />

eP = Specific exergy associated with process heat (kJ/kg (dry air))<br />

gr = Gibbs function <strong>of</strong> fuel (kJ/kg)<br />

h = Enthalpy (kJ/kg (dry air))<br />

hf = Enthalpy <strong>of</strong> saturated water at process steam pressure (kJ/kg)<br />

hg = Enthalpy <strong>of</strong> saturated vapor at process steam pressure (kJ/kg)<br />

m = Mass (kg)<br />

n = Number <strong>of</strong> moles<br />

p = Pressure (bar)<br />

Q p = Process heat (kJ/kg (dry air))<br />

re = Expansion ratio<br />

rp = Pressure ratio<br />

s = Entropy (kJ/kg K)<br />

t = Temperature (°C)<br />

v = Specific volume (m 3 /kg)<br />

Greek Symbols<br />

ω = Humidity ratio (kilogram <strong>of</strong> water vapor per kilogram <strong>of</strong> dry air)<br />

φ = Relative humidity (%)<br />

ε = Effectiveness (%)<br />

η = Efficiency (%)<br />

186


γ = Specific heat ratio<br />

λ = Fuel- air ratio on molar basis<br />

Subscripts<br />

C = Compressor<br />

CC = Combustion chamber<br />

D = Destruction<br />

HRSG = Heat recovery steam generator<br />

P = Product<br />

Q = Heat<br />

R = Reactant<br />

T = Turbine<br />

W = Work<br />

a = Ambient air<br />

av = Average<br />

f = Fuel<br />

g = Gas<br />

i = Inlet<br />

l = Liquid<br />

o = Outlet<br />

r = Regenerator<br />

s = Isentropic<br />

v = Water vapor<br />

w = Water<br />

1,2,3, = State points in the cycle<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

References<br />

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Progress in Energy and Combustion <strong>Science</strong> 34 (<strong>20</strong>08) 351–376<br />

15. Lior N. Irreversibility in combustion. Invited Keynote Paper. Proc ECOS, <strong>20</strong>01, p. 39–48.<br />

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17. Adebiyi GA. Limits <strong>of</strong> performance for alternate fuel energy to mechanical work conversion systems.<br />

ASME J Energy Resources Technol <strong>20</strong>06; 128:229–35.<br />

18. Turns SA. An introduction to combustion. 2nd ed. New York: McGraw-Hill; <strong>20</strong>00.<br />

187


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

APPLICATIONS OF ARTIFICIAL NEURAL NETWORK IN SOLAR<br />

THERMAL SYSTEMS: A REVIEW<br />

Naveen Sharma 1 , Manish Kumar Chauhan 2 and Rajesh Kumar 3<br />

1,2,3<br />

Department <strong>of</strong> Mechanical and Industrial Engineering, Indian Institute <strong>of</strong> <strong>Technology</strong>, Roorkee (U.K.)-<br />

247667<br />

1 sharma.naveen28@yahoo.com<br />

2 manishku.25@gmail.com<br />

3 barman_rk44@yahoo.co.in<br />

Abstract<br />

Artificial intelligence (AI) techniques <strong>of</strong>fer an alternative way to tackle complex and ill-defined problems to<br />

conventional techniques. They have biologically inspired computer programs design to simulate in such a way<br />

as human brain processes information. They can congregate acquaintance by identifying the patterns and<br />

relationships in data and learn through experience and able to handle noisy, incomplete data, non linear<br />

problems and prediction <strong>of</strong> data. ANNs have been the potential <strong>of</strong> combining and incorporating both literaturebased<br />

and experimental data to solve complicated practical problems. They have been found application in<br />

various areas like control, forecasting, medicine, pattern recognition, manufacturing, optimization, signal<br />

processing and social/psychological sciences and are becoming more and more popular nowadays. The current<br />

review work throw light on the application <strong>of</strong> the AI-techniques in solar energy systems; for modelling and<br />

design <strong>of</strong> mainly solar air heater, solar water heater and solar radiation estimation. Published literature<br />

incorporated in this review work shows the potential <strong>of</strong> ANNs as a design tool for the optimal solar energy<br />

systems.<br />

Keywords: Artificial Intelligence; Solar Energy Systems; Solar Air Heater; Solar Water Heater; Photovoltaic<br />

Systems.<br />

1. INTRODUCTION<br />

Artificial Neural Network (ANN) has been discovered nearly 50 years before but from last <strong>20</strong> years the<br />

application s<strong>of</strong>tware were introduced and are used to solve practical problems. ANN is basically an informationprocessing<br />

paradigm inspired by the biological nervous systems, like the brain [1]. ANN composed <strong>of</strong> a large<br />

number <strong>of</strong> highly interconnected processing elements known as neurons. ANNs have the ability to learn from<br />

examples, like humans. The training algorithm <strong>of</strong> ANN application was firstly developed and demonstrated by<br />

Hebb in <strong>19</strong>49. During the network training stage, processing elements are subjected to a set <strong>of</strong> finite training sets,<br />

and after that neurons adjusted their weights as per the learning method or to obtain a specific target output<br />

according to a particular input. Such a situation is shown in Fig 1. Typically many such input/ target pairs are<br />

needed to train a network.<br />

ANN technique has the advantages <strong>of</strong> high speed <strong>of</strong> calculation; useful in solving the non-linear problems; do<br />

not required any previous knowledge <strong>of</strong> system model; simplicity; provide good search and capability <strong>of</strong><br />

network to learn from examples [2]. Nowadays, ANNs are widely used as an alternative technology to faced<br />

highly complex, incomplete data sets, fuzzy or incomplete information and ill-defined problems. ANN technique<br />

has disadvantaged also, because <strong>of</strong> its inability to distinguish which parameter may causing a low reading. ANNs<br />

have been implemented to problems related to the fields <strong>of</strong> optimization, pattern recognition, image processing<br />

and forecasting etc.<br />

Input<br />

NN including connections<br />

(weights) between neurons<br />

Output<br />

Target<br />

Compare<br />

188<br />

Adjust Weights


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig. 1 Simple ANN network<br />

Recently, ANN applied for the estimation <strong>of</strong> the power <strong>of</strong> solar stirling heat engine which has been optimized by<br />

Particle Swarm Optimization (PSO) [3]. They used 300 data samples generated by a random number generator<br />

for network training and 100 samples for testing the network’s integrity and robustness. They compared the<br />

performance obtained from the PSO-ANN model with experimental output data [4] and found to be in good<br />

agreement. The results demonstrate the effectiveness <strong>of</strong> the PSO-ANN model.<br />

APPLICATION OF ANN<br />

A. Solar Air Heater<br />

Kalogirou [5] used artificial intelligence methods such as ANN and GA, to optimize solar systems. The Typical<br />

Meteorological Year (TMY) data used for system simulation with TRNSYS is considered for Nicosia, Cyprus.<br />

Petrakis et al. [6] estimated the TMY for Nicosia, Cyprus using Filkenstein-Schafer statistical method, for a<br />

duration <strong>of</strong> 7 year from <strong>19</strong>86-<strong>19</strong>92. The results obtained from TRNSYS are used to train the ANN and<br />

developed a correlation between collector area and storage tank size from which life cycle savings can estimate.<br />

Genetic Algorithm is implemented to evaluate the optimum size <strong>of</strong> these to parameters, for maximizing the life<br />

cycle savings. In this study, the present methodology had been implemented on an industrial process heat system<br />

having flat plate collectors and results show an increase in life cycle savings <strong>of</strong> 4.9 % and 3.1 % for subsidized<br />

and non subsidized fuel prices respectively. Kalogirou [7] implemented ANN for the estimation <strong>of</strong> performance<br />

parameters <strong>of</strong> flat-plate solar collectors. In this study, Six ANN models were proposed for the estimation <strong>of</strong><br />

collector coefficients, both at wind and no wind conditions, collector time constant, collector stagnation<br />

temperature, incidence angle modifier coefficients at transverse and longitudinal directions, and collector heat<br />

capacity. The input data for training, testing and validation <strong>of</strong> ANN are obtained from LTS database [8], which<br />

consists <strong>of</strong> data <strong>of</strong> 130 thermal solar collectors and the database also includes a number <strong>of</strong> data taken from<br />

testing solar collectors at the SPF laboratory in Switzerland. The results obtained through ANN is compared with<br />

actual experimental values and found the differences in incidence angle modifier are very small (maximum<br />

0.0057), maximum difference in collector time constant is equal to 4.2 s, the maximum difference in stagnation<br />

temperature is 6.6°C or 3.2 % and for collector heat capacity is 1.38 kJ/K. The maximum differences in thermal<br />

performance for temperature difference <strong>of</strong> 10°C and 50°C at wind condition are 1.7 % and 1.9 %, and at no wind<br />

condition are 4.5 % and 4.5 %. The accuracy <strong>of</strong> estimation can be increased by using more cases to database,<br />

because the network has the capability <strong>of</strong> learning from new examples. Varun and Siddhartha [9] and Varun et al.<br />

[10] also estimated the thermal performance <strong>of</strong> flat plate solar air heater considering the same set <strong>of</strong> parameters<br />

with different optimization techniques. The comparison different techniques have been shown in Table I.<br />

S. No. Solar System<br />

Table 1:Comparison <strong>of</strong> thermal performance for flat plate solar air heater<br />

Technique<br />

Net Outcome<br />

Implemented<br />

Flat plate solar air<br />

heater<br />

(at I = 800 w/m 2 ,<br />

∆t = 10°c )<br />

(∆η th = Thermal performance)<br />

1.<br />

Kalogirou<br />

(<strong>20</strong>06) [7]<br />

ANN<br />

∆η th = 1.7%<br />

(wind condition)<br />

∆η th =4.5%<br />

(no wind condition)<br />

2.<br />

Varun and<br />

Siddhartha (<strong>20</strong>09) [9]<br />

GA<br />

∆η th = 8.6%<br />

3.<br />

Varun et al. (<strong>20</strong>11)<br />

[10]<br />

SIPT<br />

∆η th = 6.4%<br />

Solar Water Heating System<br />

189


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Kalogirou et al. [11] applied Artificial Neural Network (ANN) to estimate the useful energy extracted and the<br />

temperature rise in the stored water <strong>of</strong> Solar Domestic Heating Water System (SDHWS). The data from 33 sets<br />

were randomly selected. 30 sets were used for training and testing and the remaining 3 were randomly selected<br />

for validation <strong>of</strong> model. The input data included was collector area (from 1.81 m 2 to 4.38 m 2 ), storage tank heat<br />

loss coefficient (U-value), tank type, total daily solar radiation, mean ambient air temperature, storage volume,<br />

water temperature in storage tank and type <strong>of</strong> system. A multilayer feed forward neural network consists <strong>of</strong> an<br />

input layer (2 neurons), some hidden layers (8 neurons) and an output layer (2 neurons). The results for the<br />

useful energy extracted from the system and temperature rise in stored water was 0.9722 and 0.9751 respectively.<br />

The ANN method can use at different weather conditions and for completely unknown systems. The results<br />

obtained within 7.1 % and 9.7 %. Its performance can be improved by knowing collector performance<br />

characteristics.<br />

Kalogirou et al. [12] estimated useful energy extracted from the thermosyphon solar water system and the stored<br />

water temperature rise. For this an ANN network has been trained to handle a number <strong>of</strong> unusual cases using<br />

performance data for four types <strong>of</strong> systems, with same collector panel and varying weather conditions. The result<br />

obtained maximum deviations <strong>of</strong> 1 MJ and 2.2 o C using random data for both with performance equations<br />

developed from the experimental measurements and with the artificial neural network. The predicted values<br />

enlightened the effectiveness <strong>of</strong> the proposed ANN method for the estimation <strong>of</strong> the performance <strong>of</strong> the<br />

particular thermosyphon solar water system in any <strong>of</strong> the configurations considered in this study. 30<br />

thermosyphon solar domestic water-heating systems have been tested and modeled as per the procedures<br />

outlined in the standard ISO 9459-2, for three different locations in Greece [13].<br />

Out <strong>of</strong> these, data <strong>of</strong> 27 systems were used for training and testing the network and data <strong>of</strong> remaining 3 have<br />

been used for validation. Two networks were trained for solar energy output estimation first for storage-tank<br />

capacity and another for the system and the average quantity <strong>of</strong> hot water required per month at desired<br />

temperatures <strong>of</strong> 35 and 40 o C. The R 2 -value set was: for first network was equal to 0.9993 and for second were<br />

equal to 0.9848 and 0.9926 for the two output parameters for the training data [13].<br />

A similar type <strong>of</strong> approach has been adopted for predicting the long-term performance <strong>of</strong> three forcedcirculation-type<br />

solar domestic water-heating systems [14]. The maximum percentage differences <strong>of</strong> 1.9 and<br />

5.5% have been obtained for the two networks, when unknown data have been used, respectively.<br />

B. Solar Radiation Estimation<br />

ANNs applied to predict global solar radiation in the areas that were not covered by direct measurement<br />

instrumentation [15]. In this study, input data considered for the network are such as: the location, month, mean<br />

temperature, mean relative humidity, mean pressure, mean vapor pressure, mean wind speed and sunshine<br />

duration. An ANN model proposed by Mubriu et al. [16] efficiently used to estimate monthly average daily<br />

global solar radiation on a horizontal surface. They used data obtained from three different sites for training a<br />

neural network and formulating an empirical model and one site for checking the ANN and Empirical models. In<br />

this study a feed-forward back propagation neural network with on hidden layer consisting <strong>of</strong> 15 neurons with<br />

tangent sigmoid as the transfer function was used. The input data included was sunshine hours, cloud cover,<br />

maximum temperature together with latitude, altitude and longitude <strong>of</strong> location. The maximum temperature and<br />

cloud cover data was obtained from Uganda Meteorological Department from <strong>19</strong>93 to <strong>20</strong>05. The result shows<br />

that the mean bias error (MBE) <strong>of</strong> 0.059 MJ/m 2 and root mean square error (RMSE) <strong>of</strong> 0.385 MJ/m 2 . Due to the<br />

ability <strong>of</strong> reliably capturing non linearity nature <strong>of</strong> solar radiation, the developed ANN model proved to be<br />

superior over empirical model. Global solar irradiation can be estimated from different ANN models [15-23] and<br />

the results are compared for the correlation coefficients and the absolute percentage error for these different<br />

models are shown in Table II.<br />

Table 2:Comparison <strong>of</strong> global solar radiation model for correlation coefficients and the absolute percentage<br />

error<br />

Root<br />

S.<br />

Model by<br />

Mean Correlation<br />

No<br />

Year<br />

author<br />

Absolute coefficient<br />

.<br />

Error<br />

1<br />

Alwai and<br />

Hinai [15]<br />

<strong>19</strong>98 7.3 0.989<br />

2<br />

Mihalakakou<br />

et al. [17]<br />

<strong>20</strong>00 0.2 0.96<br />

3 Sozen et al. <strong>20</strong>04 6.7 0.99<br />

<strong>19</strong>0


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[18]<br />

4<br />

Tymvious et<br />

al. [<strong>19</strong>]<br />

<strong>20</strong>05 0.12 0.77-0.88<br />

5<br />

Mubiru and<br />

Banda [<strong>20</strong>]<br />

<strong>20</strong>08 0.3 0.974<br />

6 Mubiru [16] <strong>20</strong>08 0.1 0.997<br />

7<br />

Moustris et<br />

al. [21]<br />

<strong>20</strong>08 0.9 0.99<br />

8<br />

Alam et al.<br />

[22]<br />

<strong>20</strong>09 4.5 > 0.85<br />

9<br />

Elizondo et<br />

al. [23]<br />

2.92-3.64 0.52-0.74<br />

The authors [18, 24 and 25] used latitude, longitude, altitude and sunshine duration as the input values to the<br />

neural network. They used the ANN for modeling monthly mean daily values <strong>of</strong> global solar radiation. They [25]<br />

compared its performance with that <strong>of</strong> a MLP model and a classical regression model and found average MAPE<br />

for the MLP network is 12.6 and that <strong>of</strong> average MAPE for RBF networks is 10.1. The solar potential is<br />

estimated using ANN [18]. They reported that the estimated values <strong>of</strong> maximum mean absolute percentage error<br />

was found to be less than 6.7% and r 2 values to be about 99.89% for the testing stations. In some <strong>of</strong> the neural<br />

net-work models [23], the daily observed values <strong>of</strong> minimum and maximum air temperature and precipitation<br />

along with the daily premeditated values for day-length and clear sky radiation were also used as the inputs.<br />

Magnier and Haghighat [26] studied building behaviour through simulation using ANN and then combined ANN<br />

with Genetic Algorithm (NSGA-2) for optimization <strong>of</strong> thermal comfort and energy consumption in a residential<br />

house. The input variables used in this study corresponded to thermostat programming, variables <strong>of</strong> HVAC<br />

system settings from ASHRAE Comfort Range and Passive Solar Design. In this study response surface<br />

approximation is implemented, which is basically a multi layer feed forward ANN consists <strong>of</strong> an input layer (<strong>20</strong><br />

neurons), some hidden layer (<strong>20</strong> neurons) and an output layer (5 neurons). The ANN was validate with 45 cases<br />

and compared with simulation outputs. The results shows an average relative error for total energy consumption<br />

is 0.5%, for a PMV is 3.9% and for cumulative time with discomfort is 5.2% were significant. To achieve this<br />

accuracy 450 training cases, corresponding to 225 times numbers <strong>of</strong> variables were required.<br />

In this optimization study, <strong>20</strong> continuous variables were set up. For an absolute average PMV <strong>of</strong> 0.064 the<br />

corresponding annual energy consumption is 18,342 kWh, annual energy consumption <strong>of</strong> 15,441 kWh for an<br />

absolute average PMV <strong>of</strong> 0.152. The results enlightened that the ANN performed well in terms <strong>of</strong> energy<br />

consumption, but underestimate the value <strong>of</strong> PMV. Hence, further more systematic studies are required to<br />

determine the accuracy <strong>of</strong> ANN in the vicinity <strong>of</strong> optimal solution. The use <strong>of</strong> daylight in buildings greatly<br />

reduces the electricity consumption. The previous studies concern the utilization <strong>of</strong> daylight for satisfying<br />

different objectives such as: to increase occupant satisfaction and improve worker productivity [27, 28] and with<br />

appropriate shading device control which results in lower energy consumption and maintain the occupant<br />

comfort [29, 30].<br />

Lah et al. [31] applied fuzzy logic to control the functioning <strong>of</strong> the smooth moving roller blind as a regulation<br />

device to ensure the desired inside illuminance. The objective <strong>of</strong> this study is to develop and design <strong>of</strong> the fuzzy<br />

controller to control the positioning <strong>of</strong> the roller blind according to available solar radiation which act as external<br />

disturbance. The results show that the desired inside illuminance (750-1500 lx) with roller blind movement in<br />

summer, means the inside luminous efficacy in the range from 2 to 10 lm/W depending on sky conditions for the<br />

controller integrated in a self-adaptive building. When the radiation is less intense (means in mornings and<br />

evenings), then the roller blind opened more than 90% and the solar luminous efficacy was also high, up to 15<br />

lm/W. Fuzzy logic approach applied by Sen [32] for estimating solar radiation by measuring sunshine duration<br />

for three sites with monthly average <strong>of</strong> daily irradiances in the western part <strong>of</strong> Turkey. Furthermore, a new<br />

model based on neuro-fuzzy has been developed by Mellit et al. [33] for predicting the sequences <strong>of</strong> monthly<br />

clearness index as well as for generating solar radiation. Both fuzzy logic and neural networks have been applied<br />

for predicting hourly global radiation from satellite images and conclude that that fuzzy and neural network<br />

models are much better than regression models [34]. A comparative study <strong>of</strong> Angstroms and ANN<br />

methodologies has been carried out by Tymvios et al. [<strong>19</strong>] for estimation <strong>of</strong> global solar radiation. They reported<br />

that ANN methodology is a suitable substitute for the traditional approach in order to estimate global solar<br />

radiation mainly in situations where radiation measurements are not readily available.<br />

<strong>19</strong>1


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

An ANN model has been developed to predict diffuse fraction in hourly and daily scale [35] in the plain areas <strong>of</strong><br />

Egypt and compared its performance with two linear regression models. They reported that the result obtained<br />

from ANN model is more suitable for prediction <strong>of</strong> the diffuse fraction in hourly and daily scales than the<br />

regression models. Furthermore, a new methodology based on artificial neural networks (ANN) has been<br />

implemented to evaluate the luminous efficacy <strong>of</strong> diffuse, direct and global solar radiation with clear sky<br />

conditions [36]. With the help <strong>of</strong> standard statistical techniques developing a non-local model considering all<br />

physical processes is nearly impossible. The results show that an ANN model is simpler than the SMARTS<br />

(Simple Model <strong>of</strong> the Atmospheric Radiative Transfer) radiation model and able to accurately highlight the<br />

variations <strong>of</strong> the three components <strong>of</strong> luminous efficacy caused due to solar zenith angle, various atmospheric<br />

absorption and scattering processes. The developed ANN model can be used without using detailed atmospheric<br />

information or empirical models, if radiometric measurements and perceptible water data (or temperature and<br />

relative humidity data) are available.<br />

Recently, model based on artificial neural network with wavelet analysis has been used for solar radiation<br />

estimation. A hybrid model based on this were developed by Cao and Cao [37] and used for forecasting<br />

sequences <strong>of</strong> total daily solar radiation. Cao and Lin [38] proposed a new model based on diagonal recurrent<br />

wavelet neural network (DRWNN) and a special designed training algorithm for forecasting global solar<br />

irradiance. Mellit et al. [39] implemented an adaptive neural-network topology with the wavelet transformation<br />

embedded in the hidden units for forecasting daily total solar radiation. They investigated several structures<br />

which have been beneficial in resolving the missing data problem. A hybrid model based on a neural network<br />

with Markov chain has been proposed for generating total daily solar radiation [40] at long term and it was<br />

implemented for Algeria. The unknown validation data set generated very accurate forecast with an RMSE error<br />

less than 8% between the predicted and measured data. A recurrent neural network with MLP network used for<br />

generating solar radiation synthetic series [41]. In this study, the MLP and other two models has been compared<br />

and found that values <strong>of</strong> the annual irradiance <strong>of</strong> synthetic year estimated by MLP method were nearer to the real<br />

data than other two methods.<br />

For more detailed investigation regarding the application <strong>of</strong> the artificial intelligence techniques for modeling<br />

and forecasting <strong>of</strong> the solar radiation and solar energy modeling techniques the reader can follow some <strong>of</strong> the<br />

good reviews presented in [42, 43].<br />

2. CONCLUSIONS<br />

In the present study, a review <strong>of</strong> AI techniques used in solar energy systems has been carried out. From this<br />

study, following conclusions have been drawn:<br />

1. Use <strong>of</strong> Artificial Intelligence techniques result in achieving substantial improvement in efficiency and<br />

predicting the optimal set <strong>of</strong> design and operating variables for the solar energy systems.<br />

2. From this study, it is clear that after training the ANN model has the potential to predict the satisfactory<br />

results for unknown data.<br />

3. From figure 2, it is clear that ANN predicted more accurate optimal set <strong>of</strong> variables after the model has been<br />

trained and validated well.<br />

4. In solar energy systems, there is a lot <strong>of</strong> scope for using combination <strong>of</strong> AI techniques with other<br />

optimization techniques in order to improve the performance <strong>of</strong> the system.<br />

5. AI techniques may be applied on roughened solar air heater, which is a scope for future work.<br />

Life cycle savings (LCS) and Life cycle assessment (LCA) has been also carried out for solar energy systems<br />

using AI techniques.<br />

3. REFERENCES<br />

[1] C.M. Bishop, Neural networks for pattern recognition, Oxford <strong>University</strong> Press, Oxford, <strong>19</strong>95.<br />

[2] D. Saxena, S.N. Singh, K.S. Verma, Application <strong>of</strong> computational intelligence in emerging power systems,<br />

International Journal <strong>of</strong> Engineering, <strong>Science</strong> and <strong>Technology</strong>, 2 (<strong>20</strong>10) 1-7.<br />

[3] M.H. Ahmadi, M.A. Ahmadi, S.S.G. Aghaj, Prediction <strong>of</strong> Power in Solar Stirling Heat Engine by Evolving<br />

Particle Swarm Optimization and Neural Network, International Journal <strong>of</strong> Computer Applications, 34 (1)<br />

(<strong>20</strong>11) <strong>20</strong>-24.<br />

[4] Y. Li, Y. H, W. Wang, Optimization <strong>of</strong> Solar-powered stirling heat engine with finite-time<br />

thermodynamics, Renewable Energy 36 (<strong>20</strong>11) 421-427.<br />

[5] S.A. Kalogirou, Optimization <strong>of</strong> solar systems using artificial neural-networks and genetic algorithms,<br />

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[6] M. Petrakis, H. Kambezides, S. Lykoudis, A. Adamopoulos, P. Kassomenos, I. Michaelides, S. Kalogirou,<br />

G. Roditis, I. Chrysis, A. Hadjigianni, Generation <strong>of</strong> a typical meteorological year for Nicosia, Cyprus,<br />

Renewable Energy, 13(<strong>19</strong>98) 318-388.<br />

<strong>19</strong>2


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

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algorithm, Applied Energy, 87 (<strong>20</strong>10) 1793-1799.<br />

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[13] S.A. Kalogirou, S. panteliou, Thermosyphon solar domestic water heating systems long term performance<br />

prediction using artificial neural networks. Solar Energy Journal, in press.<br />

[14] Kalogirou S. Forced circulation solar domestic water heating systems long-term performance prediction<br />

using artificial neural networks. Applied Energy, 66(1) (<strong>20</strong>00) 63-74.<br />

[15] S. Alawi, H. Hinai, An ANN based approach for predicting global solar radiation in locations with no direct<br />

measurement instrumentation, Renewable Energy, 14 (<strong>19</strong>98) <strong>19</strong>9–<strong>20</strong>4.<br />

[16] J. Mubriu, E. J. K. B. Banda, Estimation <strong>of</strong> monthly average daily global solar irradiation using artificial<br />

neural networks, Solar Energy, 82 (<strong>20</strong>08) 181-187.<br />

[17] G. Mihalakakou, M. Santamouris, D.N. Asimakopoulos, The total solar radiation time series simulation in<br />

Athens using neural networks, Theoretical and Applied Climatology, 66 (<strong>20</strong>00) 185–<strong>19</strong>7.<br />

[18] A. Sozen, E. Arcaklioglu, M. Ozalp, Estimation <strong>of</strong> solar potential in Turkey by artificial neural networks<br />

using meteorological and geographical data, Energy Conversion and Management, 45 (<strong>20</strong>04) 3033–3052.<br />

[<strong>19</strong>] F.S. Tymvios, C.P. Jacovides, S.C. Michaelides, C. Scouteli, Comparative study <strong>of</strong> Angstrom’s and<br />

artificial networks’ methodologies in estimating global solar radiation, Solar Energy, 78 (<strong>20</strong>05) 752–762.<br />

[<strong>20</strong>] J. Mubiru, Predicting total solar irradiation values using artificial neural networks, Renewable Energy, 33<br />

(<strong>20</strong>08) 2329–2332.<br />

[21] K. Moustris, A.G. Paliatsos, A. Bloutsos, K. Nikolaidis, I. Koronaki, K. Kavadias, Use <strong>of</strong> neural networks<br />

for the creation <strong>of</strong> hourly global and diffuse solar irradiance data at representative locations in Greece,<br />

Renewable Energy, 33 (<strong>20</strong>08) 928–932.<br />

[22] S. Alam, S.C. Kaushik , S.N. Garg, Assessment <strong>of</strong> diffuse solar energy under general sky condition using<br />

artificial neural network, Applied Energy, 86 (<strong>20</strong>09) 554–564.<br />

[23] D. Elizondo, G. Hoogenboom, R.W. Mcclendon, Development <strong>of</strong> a neural network model to predict daily<br />

solar radiation, Agricultural and Forest Meteorology 71 (<strong>19</strong>94) 115–132.<br />

[24] M. Mohandes, S. Rehman, T.O. Halawani, Estimation <strong>of</strong> global solar radiation using artificial neural<br />

networks, Renewable Energy 14 (<strong>19</strong>98) 179–184.<br />

[25] M. Mohandes, A. Balghonaim, M. Kassas, S. Rehman, T.O. Halawani, Use <strong>of</strong> radial basis functions for<br />

estimating monthly mean daily solar radiation, Solar Energy 68 (<strong>20</strong>00) 161–168.<br />

[26] L. Magnier, F. Haghighat, Multiobjective optimization <strong>of</strong> building design using TRNSYS simulations,<br />

genetic algorithm, and Artificial Neural Network, Building and Environment, 45 (<strong>20</strong>10) 739-746.<br />

[27] I.G. Capeluto. The influence <strong>of</strong> the urban environment on the availability <strong>of</strong> the daylighting in <strong>of</strong>fice<br />

buildings in Israel. Building and Environment, 38 (<strong>20</strong>03), 752–754.<br />

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Building and Environment, 32 (<strong>19</strong>97) 81–85.<br />

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<strong>of</strong> system performance. Building and Environment, 35 (<strong>20</strong>00) 663– 676.<br />

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and Buildings, 36 (<strong>20</strong>01) 149–155.<br />

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307–321.<br />

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monthly clearness index and daily solar radiation data in remote areas: application for sizing a stand-alone<br />

PV system, Renewable Energy 33 (<strong>20</strong>08) 1570–1590.<br />

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estimation from satellite-derived cloud index, Energy 30 (<strong>20</strong>05) 1685–1697.<br />

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network, as compared to linear regression models, Energy 32 (<strong>20</strong>07) 1513–1523.<br />

<strong>19</strong>3


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[36] G. Lopez, C.A. Gueymard, Clear-sky solar luminous efficacy determination using artificial neural network,<br />

Solar Energy, 81 (<strong>20</strong>07) 929–939.<br />

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Applied Thermal Engineering 25 (<strong>20</strong>05) 161–172.<br />

[38] J. Cao, X. Lin, Application <strong>of</strong> the diagonal recurrent wavelet neural network to solar irradiation forecast<br />

assisted with fuzzy technique, Engineering Applications <strong>of</strong> Artificial Intelligence 21 (<strong>20</strong>08) 1255–1263.<br />

[39] A. Mellit, M. Benghanem, S.A. Kalogirou, An adaptive wavelet-network model for forecasting daily total<br />

solar radiation. Applied Energy 83 (<strong>20</strong>06) 705–722.<br />

[40] A. Mellit, M. Benghanem, A.H. Arab, A. Guessoum, A simplified model for generating sequences <strong>of</strong><br />

global radiation data for isolated sites: using artificial neural network and a library <strong>of</strong> Markov Transition<br />

Matrices, Solar Energy 79 (<strong>20</strong>05) 468–482.<br />

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network multilayer Perceptron, Solar Energy 72 (<strong>20</strong>02) 441–446.<br />

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International journal <strong>of</strong> Artificial Intelligence and S<strong>of</strong>t Computing 1 (<strong>20</strong>08) 52–76.<br />

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Sustainable Energy Reviews 16 (<strong>20</strong>12) 2864-2869.<br />

<strong>19</strong>4


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

THERMODYNAMIC ANALYSIS FOR IMPROVEMENT IN THERMAL<br />

PERFORMANCE OF A SIMPLE GAS TURBINE CYCLE THROUGH<br />

RETROFITTING TECHNIQUES (INLET AIR EVAPORATIVE<br />

COOLING, STEAM INJECTION & COMBINED IAC AND STIG)<br />

Shyam Agarwal* 1 and R.S. Mishra 1<br />

1 Department <strong>of</strong> Mechanical Engineering, Delhi College <strong>of</strong> Engineering, Bawana Road, Delhi-110042, India<br />

* Corresponding author – Tel.: 91+9013353987; E-mail address: sh_agar@rediff.com<br />

Abstract<br />

Retr<strong>of</strong>itting technologies [inlet evaporative cooling system and steam injected gas turbine] have been applied on<br />

simple gas turbine cycle for performance improvement followed by parametric analysis. The performance<br />

improvement has been thermodynamically analysed and discussed for retr<strong>of</strong>itted techniques followed by<br />

performance studies. The parametric study predicts that retr<strong>of</strong>itting techniques (FCS and STIG) improves net<br />

power output, thermal efficiency, power generation efficiency , first law efficiency and exergetic efficiency<br />

(second law efficiency) while heat rate falls with a considerable increment in fuel consumption. Exergy analysis<br />

showed that combustion chamber and turbine are most sensitive components <strong>of</strong> retr<strong>of</strong>itted system. The results<br />

show that the power output , thermal efficiency , exergetic efficiency and fuel-air ratio have been enhanced 3.1%<br />

, 0.18%, 0.2% and 1.0% respectively while heat rate falls 0.6% by FCS technology. The power output , thermal<br />

efficiency , exergetic efficiency and fuel-air ratio have been improved 27.4% , 3.5%, 25.8% and 14.4%<br />

respectively while heat rate falls 10.2% by STIG technology. The analysis shows that STIG technology is better<br />

than FCS and the combined FCS & STIG technology enhance the power output , thermal efficiency , exergetic<br />

efficiency and fuel-air ratio 30.5% , 3.5%, 25.7% and 15.2% respectively and reduces the heat rate 10.4%.<br />

Keywords: Gas turbine, Retr<strong>of</strong>itting, FCS, STIG, Exergy<br />

Nomenclature<br />

AP Approach point ( 0 C)<br />

PP Pinch point( 0 C) Superscript<br />

TIT Turbine Inlet Temperature (K) , fraction <strong>of</strong> gas phase at dead state<br />

wbt Wet bulb temperature( 0 C) 1 fraction <strong>of</strong> gas phase before combustion<br />

M Molecular weight (kg/kmol) 2 fraction <strong>of</strong> gas phase after combustion<br />

E & Exergy rate (kW) CH chemical<br />

U Internal energy (kJ) PH Physical<br />

m& mass flow rate (kg/s) PT potential<br />

Subscripts<br />

Greek symbol<br />

sup superheated η efficiency<br />

Th thermal λ fuel-air ratio<br />

HRSG Heat recovery steam generator ω steam-injection ratio<br />

GEN Heat generator € Exergetic efficiency<br />

f fuel Acronyms and abbreviations<br />

REG Regenerator FCS Fog cooling system<br />

dbt Dry bulb temperature( 0 C) STIG Steam injection gas turbine<br />

1. Introduction<br />

Simple gas turbine power generation systems are widely used in Indian industries due to quick startup and<br />

shutdown capabilities. These units are mostly used to fulfil the peak load demand but unfortunately suffer from<br />

very low overall efficiency and reduction in power output during the summer season, when electricity demand is<br />

the highest. To investigate the anticipated power shortage, retr<strong>of</strong>itting projects have been seriously gaining<br />

momentum to covert these existing simple gas turbine systems into relatively advanced cycle units resulting in<br />

both improved efficiency and power output.<br />

<strong>19</strong>5


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

From the fundamnetal thermodynamic point <strong>of</strong> view, the reason for low thermal efficiency <strong>of</strong> simple gas turbine<br />

are high back work ratio (large part <strong>of</strong> turbine work used to compress the inlet air) and substantial amount <strong>of</strong><br />

available energy loss due to high temperature exhaust (<strong>of</strong>ter above 500 0 C) caused by shaft rotation <strong>of</strong> turbine at a<br />

relativelely high back pressure. This waste heat recovery from the gas turbine exhaust can be utilized to improve<br />

generation efficiency through various modifications to basic cycle such as gas to gas recuperation, steam<br />

injection, chemical recuperation, inlet air cooling and combined cycle etc. Among many well-established<br />

technologies, the combined cycle is rated as the most efficient way to recover the energy from the exhaust for<br />

boosting the capacity and efficiency <strong>of</strong> power generation. However, the combined cycle technology is unsuitable<br />

for daily on-<strong>of</strong>f operation pattern units due to low mobility (start-up time).<br />

Recently, the steam injection gas turbine (STIG) and inlet air cooling (IAC) by evaporation are the most common<br />

practices to enhance the performance <strong>of</strong> power generation. Both feature can be implemented in the existing basic<br />

system without major modification to the original system integration in a economic way. In the STIG technology,<br />

the steam generated from the heat-recovery generator (HRSG) is injected into the combustion chamber. Both<br />

steam from the HRSG and air from the compressor receive fuel energy in the combustion chamber and both<br />

simultaneously expand inside the existing turbine to boost the power output <strong>of</strong> turbine. It should be noted that the<br />

required injected steam pressure is obtained from a pump fitted in the steam unit. The net power output produced<br />

by steam is significantly higher than that <strong>of</strong> air in terms <strong>of</strong> per unit mass flow rate, due to very small pumping<br />

work compared to compressor. The thermodynamic processes <strong>of</strong> a simple cycle gas turbine can be approximately<br />

modeled as a Brayton cycle, in which the back work ratio is usually very high, and the exhaust temperature is<br />

<strong>of</strong>ten above 500 0 C. A high exhaust temperature implies there is plenty <strong>of</strong> useful energy rejected to the<br />

environment. The recovery <strong>of</strong> this wasted energy can otherwise be used to improve either the power generation<br />

capacity or efficiency via retr<strong>of</strong>itting to the basic cycle such as STIG and inlet air cooling by evaporation<br />

technology. Since, the specific heat <strong>of</strong> steam and hence enthalpy is relatively higher than air at a certain<br />

temperature, the STIG method is a very effective alternative to increase the efficiency and boost the power<br />

output <strong>of</strong> gas turbine. Kumar et al. 1 have been developed design methodology for parametric study and<br />

thermodynamic performance evaluation <strong>of</strong> a gas turbine cogeneration system (CGTS). Wang & Chiou 2<br />

suggested that application <strong>of</strong> IAC and STIG technique can boost the output and generation efficiency. They<br />

concluded that implementing both STIG and IAC features cause more than a 70% boost in power and <strong>20</strong>.4 %<br />

improvement in heat rate. Bouam et al. 3 have studied combustion chamber steam injection for gas turbine<br />

performance improvement during high ambient temperature operations. Their research study is to improve the<br />

principal characteristics <strong>of</strong> gas turbine used under extreme ambient condition in Algerian Sahara by injecting<br />

steam in the combustion chamber. Srinivas et al. 4 have worked out on sensitivity analysis <strong>of</strong> STIG based<br />

combined cycle with dual pressure HRSG. They concluded that steam injection decreases combustion chamber<br />

and gas reheater exergetic loss from 38.5 to 37.4% compared to the case without steam injection in the<br />

combustion chamber. Minciuc et al. 5 have presented thermodynamic analysis <strong>of</strong> tri-generation with absorption<br />

chilling machine. They have focused on solutions <strong>of</strong> tri-generation plants based on gas turbine or internal<br />

combustion engine with absorption chilling machine. Moran 6 has developed design and economic methodology<br />

for the gas turbine cogeneration system. Nishida et al. 7 have analyzed the performance characteristics <strong>of</strong> two<br />

configuration <strong>of</strong> regenerative steam-injection gas turbine (RSTIG) systems. They concluded that the thermal<br />

efficiencies <strong>of</strong> the RSTIG systems are higher than those <strong>of</strong> regenerative, water injected and STIG systems and<br />

the specific power is larger than that <strong>of</strong> regenerative cycle.<br />

The IAC technology is simply to cool down the inlet air entering the compressor with a cooler. Due to this, the<br />

compressor consumes less work and can compress more air per cycle to increase the capacity <strong>of</strong> the gas turbine.<br />

Different IAC options are evaporative cooling, mechanical chiller, absorption chiller and thermal energy storage,<br />

etc. applied in gas turbine power augmentation. Among them evaporative cooling is the cheapest one. Sinha &<br />

Bansode 8 have studied the effect <strong>of</strong> fog cooling system for inlet air cooling. They concluded that performance<br />

parameters indicative <strong>of</strong> inlet fogging effects have a definite correlation with the climate condition (humidity and<br />

temperature) and showed improvement in turbine power and heat rate with inlet fogging. Chaker et al. 9 have<br />

developed the formulation for fog droplet sizing analysis and discussed various nozzle types, measurement and<br />

testing. This study describes the different available measurement techniques, design aspects <strong>of</strong> nozzles, with<br />

experimental and provides recommendations for a standardized nozzle testing method for gas turbine inlet air<br />

fogging. Salvi & Pierpaloli 10 have studied optimization <strong>of</strong> inlet air cooling systems for steam injected gas<br />

turbines. They proposed the technique <strong>of</strong> compression inlet air cooling through an ejection system supplied by<br />

the exhaust heat <strong>of</strong> the gas turbine. Bassily 11 has studied the performance improvements <strong>of</strong> the intercooled,<br />

reheat and recuperated gas turbine cycle using absorption inlet-cooling and evaporative after-cooling. A<br />

parametric study <strong>of</strong> the effect <strong>of</strong> pressure ratio, ambient temperature, ambient relative-humidity, turbine’s inlettemperature<br />

(TIT), and the effectiveness <strong>of</strong> the recuperated heat-exchanger on the performance <strong>of</strong> varieties <strong>of</strong><br />

cycles is carried out. Bhargava & Homji 12 have studied parametric analysis <strong>of</strong> existing gas turbines with inlet<br />

<strong>19</strong>6


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

evaporative and overspray fogging. This study shows the effects <strong>of</strong> inlet fogging on a large number <strong>of</strong><br />

commercially available gas turbines.<br />

Although many efforts have been focused to apply either STIG technology or the IAC method to enhance the<br />

gas turbine’s performance, very limited studies are available regarding simultaneous integration <strong>of</strong> STIG and<br />

IAC for the same system. In this study, a simple cycle generation unit is carried as base data and STIG and IAC<br />

features are retr<strong>of</strong>itting by added in a sequencing <strong>of</strong> the system. The benefits obtained from either the STIG or<br />

IAC can be distinguished or the integration effect from the combined STIG and IAC can be realized. The<br />

performance analysis has been carried out by varying ambient temperature, humidity ratio and steam injection<br />

ratio.<br />

System Description<br />

The simple cycle gas turbine system integrated with both IAC and STIG featuring are shown in Figure 1. The<br />

basic unit includes compressor, combustor, gas turbine and a generator. A heat recovery steam generator (HRSG)<br />

was installed at the downstream exit <strong>of</strong> the turbine (state point 5) in order to recover the heat from the exhaust<br />

gases. The fraction <strong>of</strong> superheated steam generated from the HRSG is used for STIG (state point 9) and the<br />

remaining steam is used for process application. An evaporative fog cooling system (FCS) is installed to cool the<br />

ambient air (state point 1′ ) as shown in Fig. 1. Fog cooling is an active system which uses very fine fog droplets<br />

<strong>of</strong> high pressure water injected through special atomizing nozzles located at discrete points across the inlet duct<br />

at high pressure to create the cooling effect. The amount <strong>of</strong> fog is to be monitored base on dry and wet bulb<br />

ambient conditions to achieve the required cooling. A typical fog cooling system consists <strong>of</strong> a high pressure<br />

pump skid connected for feeding to an array <strong>of</strong> manifolds located at a suitable place across the compressor inlet<br />

duct. The manifolds have a requisite number <strong>of</strong> fog nozzles 6 which inject very fine droplets <strong>of</strong> water into the<br />

inlet air. The discharge through each nozzle is around 3ml/s and produces 3 billion droplets per second. The fine<br />

fog evaporates very fast, thus dropping inlet air temperature.<br />

Compressor<br />

Fogged & cooled<br />

air<br />

Fog cooling 1<br />

system<br />

Air<br />

Fuel<br />

Water<br />

Ambient air<br />

3<br />

f<br />

Combustion chamber<br />

Steam-injection ω<br />

9<br />

Combustion products<br />

Heat recovery<br />

steam generator<br />

4 Turbine<br />

5<br />

6<br />

G<br />

Remaining superheated<br />

P steam<br />

(1-ω)<br />

8<br />

Condensate water<br />

water<br />

7 Exhaust gases<br />

Fig. 1- Simple cycle gas turbine with fog cooling<br />

Modeling and Computer simulation<br />

Formulation<br />

The following assumptions have been considered for the present study:<br />

1. The composition <strong>of</strong> dry air has been assumed in terms <strong>of</strong> molar fraction <strong>of</strong> 1mole <strong>of</strong> air is: (N 2 = 0.78981, O 2 =<br />

0.<strong>20</strong>989, CO 2 = 0.00031 and H 2 O = 0).<br />

2. The heat loss from the combustion chamber is 2% <strong>of</strong> the fuel lower heating value. All other components<br />

operate without heat loss.<br />

3. Fog cooling system has been maintained for 100% saturation <strong>of</strong> ambient air at wet bulb temperature <strong>of</strong> air.<br />

3. The pressure <strong>of</strong> water injected from the nozzle into the evaporative cooling chamber has been assumed 138<br />

bar and converts into the fog (fine droplets), absorbs latent heat <strong>of</strong> air through adiabatic mixing.<br />

4. Combustion chamber has been maintained at constant temperature in the presence <strong>of</strong> steam (in case <strong>of</strong> steam<br />

injection).<br />

<strong>19</strong>7


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

A computer program has been developed to formulate and simulate the retr<strong>of</strong>itting techniques over simple gas<br />

turbine with a set <strong>of</strong> steady-state governing equations including mass, energy, entropy and exergy balances using<br />

control volume analysis sequentially for compressor, combustor, gas turbine and HRSG.<br />

For complete combustion <strong>of</strong> natural gas (methane) with steam injection in the combustion chamber, chemical<br />

equation takes the following form:<br />

[ X 1, N 2N<br />

+ X 1, O 2O<br />

+ X 1, CO 2CO<br />

+ X 1, H 2OH<br />

O] wH 2O<br />

λ CH +<br />

+<br />

4<br />

2<br />

2<br />

[ 1 + + w] [ X 2' , N 2N<br />

+ X 2' , O2O<br />

+ X 2' , CO2CO<br />

+ X 2' , H 2OH<br />

O]<br />

2<br />

→ λ<br />

2<br />

2<br />

2<br />

2<br />

… (1)<br />

X 1, N 2<br />

X 2 , N 2 =<br />

1+<br />

λ + w<br />

(2)<br />

X 1, O2<br />

− 2λ<br />

X 2 , O2<br />

=<br />

1+<br />

λ + w<br />

(3)<br />

X 1, CO2<br />

+ λ<br />

X 2 , CO2<br />

=<br />

1+<br />

λ + w<br />

(4)<br />

X 1, H 2O<br />

+ 2λ<br />

+ w<br />

X 2, H 2O<br />

=<br />

1+<br />

λ + w<br />

Mole fraction <strong>of</strong> N 2<br />

Mole fraction <strong>of</strong> O 2<br />

Mole fraction <strong>of</strong> CO 2<br />

Mole fraction <strong>of</strong> H 2 O<br />

(5)<br />

where ω is the steam injection ratio defined as the ratio <strong>of</strong> mass <strong>of</strong> steam injected to the mass <strong>of</strong> air supplied.<br />

= m &<br />

&<br />

ω , = m<br />

s<br />

mg<br />

s<br />

m a<br />

ω ′ & & , ω ′ = ω ( 1 + λ)<br />

,<br />

m&<br />

′′ =<br />

m&<br />

s<br />

ω ,<br />

f<br />

2<br />

ω ′ =<br />

ω<br />

λ<br />

′ (6)<br />

where ω is the mass <strong>of</strong> steam injected to the mass <strong>of</strong> air supplied, ω′ is the ratio <strong>of</strong> mass <strong>of</strong> steam injected to the<br />

mass <strong>of</strong> combustion gases formed and ω ′ is the ratio <strong>of</strong> mass <strong>of</strong> steam injected to the mass <strong>of</strong> fuel supplied 2 . The<br />

maximum amount <strong>of</strong> permitted STIG is <strong>20</strong>% <strong>of</strong> mass flow rate <strong>of</strong> inlet air 2 .<br />

The heat transfer between exhaust gases and condensate water has been taken place in water heat recovery boiler<br />

where superheated steam is generated.<br />

m h − h = m h −<br />

(7)<br />

exh<br />

( ) ( )<br />

6<br />

7<br />

w sup<br />

h cond<br />

where m exh and m w are mass flow rate <strong>of</strong> exhaust gases <strong>of</strong> turbine and condensate water, h 6 , h 7 , h sup and h cond are<br />

enthalpies <strong>of</strong> exhaust gases at state 6 and 7, super-heated steam and condensate water.<br />

T = T PP<br />

(8)<br />

PP sat<br />

+<br />

TAP<br />

= Tsat<br />

− AP<br />

(9)<br />

where T pp , T sat and T AP are Pinch point temperature, saturation temperature <strong>of</strong> water and approach point<br />

temperature. PP is the pinch-point difference and AP is the approach point difference from saturation<br />

temperature.<br />

The temperature <strong>of</strong> air after fog cooling can be obtained from an energy balance on the dry air, water spray and<br />

air-born water vapour before and after the system. Assuming adiabatic mixing, the energy gained by the sprayed<br />

water is balanced by the energy lost by the dry air, and the original air-born mixture, after cooling such that:<br />

m (h − h ) = m (h −h<br />

) +ω m (h −h<br />

)<br />

w v1 w1 a a1′<br />

a1 1′<br />

a v1′<br />

v1<br />

h<br />

where m w and<br />

w1′′<br />

−<br />

h<br />

h<br />

′′<br />

(10)<br />

are the mass flow rate and enthalpy <strong>of</strong> cooling water , m a is the mass flow rate <strong>of</strong> dry air,<br />

h<br />

(<br />

a1 ′ a1<br />

) is the enthalpy change <strong>of</strong> dry air, (<br />

v1 ′ −<br />

v1<br />

) is the enthalpy change <strong>of</strong> water vapour during<br />

cooling.<br />

The humidity ratio ( ω<br />

1′ ) can be specified as:<br />

0 .622 Pv<br />

1′<br />

ω<br />

1′<br />

=<br />

(11)<br />

P1′<br />

− Pv<br />

1′<br />

where P<br />

v1′<br />

is the partial pressure <strong>of</strong> water vapour and P<br />

1′ is the total atmospheric pressure. From conservation <strong>of</strong><br />

mass, the amount <strong>of</strong> water evaporated is equal to the mass <strong>of</strong> water vapour at point 1minus the water vapour<br />

originally in the air at point 1′ .<br />

h<br />

<strong>19</strong>8


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

∆ m )<br />

w<br />

= (<br />

1<br />

− ω1′<br />

m a<br />

ω (12)<br />

where ω<br />

1<br />

is the humidity ratio <strong>of</strong> air after cooling, The partial pressure <strong>of</strong> water vapour can be found from the<br />

respective relative humidity (φ ) by:<br />

P<br />

= φ<br />

(13)<br />

v<br />

P sat<br />

where P and<br />

sat<br />

P are the saturation pressures <strong>of</strong> water for the corresponding temperature. Pressure loss in the<br />

sat<br />

adiabatic mixing is neglected.<br />

The enthalpy, entropy, and exergy can be determined at each state point using mass and energy balances. The<br />

performance parameters required for the thermodynamic analysis <strong>of</strong> retr<strong>of</strong>itted systems are given below:<br />

Thermal Efficiency (η Th ): Thermal efficiency <strong>of</strong> a thermal system is defined as the ratio <strong>of</strong> net work output<br />

W & ) to the total heat input ( Q & ) <strong>of</strong> the fuel.<br />

f<br />

W&<br />

net<br />

=<br />

Th<br />

Q&<br />

(<br />

net<br />

η (14)<br />

f<br />

Generation Efficiency (η Gen ): Generation efficiency <strong>of</strong> a thermal system is defined as the ratio <strong>of</strong> electrical<br />

power output (W el ) to the total heat input <strong>of</strong> the fuel(Q f ).<br />

W<br />

el<br />

η =<br />

(15)<br />

Gen<br />

Q<br />

f<br />

Heat-Rate (HR in kJ/s/kW): Heat rate is defined as the ratio <strong>of</strong> heat produced by the fuel (<br />

W &<br />

Q&<br />

W&<br />

power output (<br />

HR<br />

el<br />

el<br />

) <strong>of</strong> the thermal system.<br />

Q & ) to the electrical<br />

f<br />

= (16)<br />

Specific Fuel-Consumption (SFC): Specific fuel–consumption <strong>of</strong> a thermal system is defined as the ratio <strong>of</strong><br />

mass <strong>of</strong> fuel to the net work output. It is reciprocal <strong>of</strong> specific net work (W spec ).<br />

SFC<br />

m&<br />

W&<br />

f<br />

= (17)<br />

net<br />

First–Law Efficiency (<br />

): The ratio <strong>of</strong> all the useful energy extracted from the system (electricity and process<br />

heat) to the energy <strong>of</strong> fuel input is known as first-law efficiency. First-law efficiency is also known as fuel<br />

utilization efficiency or utilization factor or energetic efficiency. By definition,<br />

where<br />

( W& + Q&<br />

)<br />

el Pr o<br />

η =<br />

(18)<br />

I<br />

Q&<br />

f<br />

is process heat rate.<br />

Second–Law Efficiency (<br />

): Since exergy is more valuable than energy according to the second law <strong>of</strong><br />

thermodynamics, it is useful to consider both output and input in terms <strong>of</strong> exergy. The amount <strong>of</strong> exergy supplied<br />

in the product to the amount <strong>of</strong> exergy associated with the fuel is a more accurate measure <strong>of</strong> thermodynamic<br />

performance <strong>of</strong> a system, which is called second-law efficiency. It is also called exergetic efficiency<br />

(effectiveness or rational efficiency). By definition,<br />

( W& + E&<br />

)<br />

el pro<br />

η =<br />

(<strong>19</strong>)<br />

II<br />

E&<br />

f<br />

where is the exergy content <strong>of</strong> process heat and is the exergy content <strong>of</strong> fuel input.<br />

E &<br />

Exergy-Destruction Rate (<br />

DR<br />

)-The component exergy destruction rate can be compared to the total exergy<br />

destruction rate within the system.<br />

E&<br />

E&<br />

D<br />

E& = (<strong>20</strong>)<br />

DR<br />

D, tot<br />

Results and Discussion<br />

In the present study following configurations with retr<strong>of</strong>itting have been studied in comparison to simple gas<br />

turbine cycle:<br />

(i) Simple gas turbine cycle with inlet air cooling (IAC)<br />

f<br />

<strong>19</strong>9


(ii) Simple gas turbine cycle with STIG<br />

(iii)Simple gas turbine cycle with both IAC and STIG.<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The initial conditions <strong>of</strong> these system analysis are as shown in Table 1. In the calculation the steady state<br />

operation is investigated without considering the turbine blade cooling. The performance analysis <strong>of</strong> these<br />

retr<strong>of</strong>itted gas turbine system is done by preparing a computer program in EES and validated with Moran 6 . The<br />

temperature, pressure and gas concentration in each component are calculated by taking into consideration <strong>of</strong> the<br />

compositions and proportions <strong>of</strong> gases and consequently various parameters (refer Table 1) and exergy loss <strong>of</strong><br />

these systems are estimated. The net power output and power generation efficiency are 30MW and 29.93%<br />

(shown in Table 2) respectively. Attachment <strong>of</strong> evaporative coolers with simple cycle slightly improves the<br />

performance parameters. Due to reduction in compressor work the net power output increases by 3%. The impact<br />

<strong>of</strong> evaporative cooling will be higher in dry summer season where dry bulb temperature is higher and R.H is<br />

lower.<br />

Simple gas turbine cycle with STIG (for steam injection ratio 0.1316) significantly improves the system<br />

efficiencies. The net power output increases by 27.4%. Combination <strong>of</strong> simple cycle with STIG and evaporative<br />

cooling further improves the system performance. It is quite obvious that contribution <strong>of</strong> STIG is quite<br />

significant.<br />

1.Comparison <strong>of</strong> simple cycle gas turbine with and without FCS shows that net power output increases by 3.1%<br />

and various efficiencies increase by 0.6% while heat rate decreases by 0.6% using FCS technology.<br />

2.Comparison <strong>of</strong> simple cycle gas turbine with and without STIG shows that net power output increases by<br />

27.4% and thermal efficiency increases by 11.4% while heat rate decreases by 10.2% using STIG technology.<br />

The power output, power generation efficiency improve appreciably while First-law efficiency and process heat<br />

fall with increasing amount <strong>of</strong> STIG.<br />

3.Comparison <strong>of</strong> simple cycle gas turbine with and without FCS and STIG shows that net power output increases<br />

by 30.5% and thermal efficiency increases by 11.59% while heat rate decreases by 10.4% using FCS and STIG<br />

combine technology. The generation efficiency and net power output increases while First-law efficiency<br />

(utilization factor) and process heat decreases with increasing amount <strong>of</strong> STIG.<br />

Table 1: Essential input parameters for simple gas turbine cycle and retr<strong>of</strong>itted systems<br />

Parameters<br />

Simple gas turbine<br />

cycle+Fog<br />

cooling+STIG<br />

Ambient air temperature at state 1′,in K 298.15<br />

Ambient air pressure at state1′, in bar 1.013<br />

Ambient air relative humidity at state1′, in % 60<br />

Spray water temperature at state1′, in K 298.15<br />

Spray water pressure at state1′, in bar 138<br />

Air inlet pressure to compressor (P 1 ), in bar 1.013<br />

Air inlet temperature to compressor, (T 1 ) in K 298.15<br />

Relative humidity <strong>of</strong> inlet air to compressor at 1, in % 100<br />

Pressure ratio <strong>of</strong> compressor (r p ) 10:1<br />

Isentropic efficiency <strong>of</strong> compressor (η SC), in % 0.86<br />

Isentropic efficiency <strong>of</strong> Turbine (η ST), in % 0.86<br />

Lower heating value <strong>of</strong> fuel (LHV), in kJ/kmol 802361<br />

Mass flow rate <strong>of</strong> air (m a ), in (kg/s) 81.4<br />

Turbine inlet temperature (TIT) or maximum cycle temperature (T 4 ), in K 15<strong>20</strong><br />

Injection pressure <strong>of</strong> fuel (methane) (P f ), in bar 12<br />

Injection temperature <strong>of</strong> fuel (methane) (T f ), in K 298.15<br />

Pressure drop in combustion chamber , in % 5<br />

Exhaust pressure <strong>of</strong> combustion products after HRSG (P 7 ), in bar 1.013<br />

Exhaust temperature <strong>of</strong> combustion products after HRSG (T 7 ) in K 403.15<br />

Pressure <strong>of</strong> steam generation (P 9 ) in bar <strong>20</strong><br />

Pressure <strong>of</strong> condensate water at inlet <strong>of</strong> HRSG (P 8 ), in bar <strong>20</strong><br />

Temperature <strong>of</strong> condensate water at inlet to HRSG (T 8 ), in K 298.15<br />

Pressure drop in HRSG on the gas side, in % 5<br />

Amount <strong>of</strong> steam injected , in (% <strong>of</strong> the mass flow rate <strong>of</strong> the air) 10<br />

Temperature <strong>of</strong> superheated steam STIG (T 9 ), in K 753.15<br />

Approach point , in K 2<br />

<strong>20</strong>0


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Pinch point, in K <strong>20</strong><br />

TABLE 2: Comparison <strong>of</strong> various performance parameters <strong>of</strong> simple gas turbine cycle and retr<strong>of</strong>itted cycles<br />

Performance Parameter<br />

Simple gas<br />

turbine<br />

cycle<br />

Simple gas<br />

turbine cycle<br />

with Fog<br />

cooling<br />

Simple gas<br />

turbine cycle<br />

with STIG<br />

Simple gas<br />

turbine<br />

cycle with<br />

Fog cooling<br />

& STIG<br />

First law efficiency (%) 30.54 30.72 72.57 72.69<br />

Second law efficiency (%) 29.51 29.70 55.3 55.2<br />

Power generation efficiency (%) 29.93 30.11 33.33 33.4<br />

Thermal efficiency (%) 30.54 30.72 34.01 34.08<br />

Fuel-air ratio 0.0431 0.04355 0.0493 0.04967<br />

Steam injection ratio (per kg <strong>of</strong> mass <strong>of</strong> --- --- 0.1316 0.13<br />

fuel)<br />

Heat rate (kW/kWh) 1<strong>20</strong>29 1<strong>19</strong>58 10800 10780<br />

Specific net work (kJ/kg <strong>of</strong> fuel) or 15274 15364 17012 17043<br />

specific power (kW/kg/s <strong>of</strong> fuel)<br />

Specific fuel consumption( kg/kWh) 0.2357 0.2343 0.2116 0.2112<br />

Work-heat ratio (kJ/kJ) --- --- 0.8823 0.8826<br />

Power-to-heat ratio (kW/kJ/s) --- --- 0.8647 0.8649<br />

Specific work ISO (kW-s/kg <strong>of</strong> air) 361.2 367.2 460.2 464.8<br />

Turbine work (MW) 56.48 57.31 64.71 65.54<br />

Compressor work (MW) 26.48 26.38 26.48 26.39<br />

Net Power output (MW) 30 30.93 38.23 39.15<br />

Electric work done (MW) 29.4 30.31 37.46 38.36<br />

Process heat (MW) --- --- 43.32 44.35<br />

Table 3 represents the comparison <strong>of</strong> exergy destruction rate in the components <strong>of</strong> simple cycle and retr<strong>of</strong>itted<br />

cycles. The exergy destruction rate represents the waste <strong>of</strong> available energy. Exergy destruction <strong>of</strong> all<br />

components have been calculated to enhance the understanding <strong>of</strong> cycle performance. Table 3 presents the<br />

exergy destruction <strong>of</strong> each cycle component after retr<strong>of</strong>itting. While examine the exergy destruction for all<br />

components, the combustor has the largest exergy destruction and shows the major location <strong>of</strong> thermodynamic<br />

inefficiency because <strong>of</strong> large irreversibility arising from the combustion reaction and heat transfer. Steam<br />

injection will increase the exergy destruction due to more mixing and combustion in the combustor. The exergylosses<br />

at position 7 (see Fig.1) is considered as exergy loss through stack. Since part <strong>of</strong> exhaust heat is recovered<br />

in HRSG, the exhaust exergy out <strong>of</strong> stack can be reduced substantially after retr<strong>of</strong>itting. The exergy losses<br />

through stack will not only waste the available exergy but also dump the thermal pollution to our living<br />

environment.<br />

Exergetic efficiency for each component can be defined as the ratio <strong>of</strong><br />

supplied to the component and<br />

E & to<br />

R<br />

E & . Where<br />

S<br />

E & is the exergy rate<br />

S<br />

E & is the exergy rate recovered from the component. For a retr<strong>of</strong>itted cycle with<br />

R<br />

fog cooling and STIG, exergetic efficiencies <strong>of</strong> compressor, turbine, combustor and HRSG are respectively 91%,<br />

93%, 68% and 75%, among which gas turbine and compressor have a higher exergetic efficiency. This implies<br />

most <strong>of</strong> the exergy destruction in compressor and combustor are inexistable. It is interesting to note that although<br />

the exergy destruction rate <strong>of</strong> combustor is the highest, exergy efficiency <strong>of</strong> the combustor is higher than that <strong>of</strong><br />

HRSG. Therefore, there is a greater improvement margin exists for HRSG than for combustor.<br />

Table 3: Comparison <strong>of</strong> exergy destruction in the components for simple gas turbine cycle and retr<strong>of</strong>itted cycles<br />

Components Simple gas turbine cycle Simple gas turbine<br />

cycle+Fog cooling<br />

Simple gas turbine<br />

cycle+STIG<br />

Simple gas turbine<br />

cycle+Fog<br />

cooling+STIG<br />

<strong>20</strong>1


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Exergy<br />

destructi<br />

on rate<br />

(MW)<br />

€ Exerg<br />

y<br />

destru<br />

ction<br />

rate<br />

(%)<br />

Percentage exergy destruction rate is the exergy destruction rate within a component as a percentage <strong>of</strong> the total exergy destruction rate<br />

within the simple gas turbine system.<br />

1.Comparison <strong>of</strong> simple cycle gas turbine with and without FCS shows that exergetic efficiency gets also<br />

improve by 0.64%. However fuel-air ratio increases by 1%. The exergy destruction gets reduced into compressor<br />

and turbine due to low inlet temperature <strong>of</strong> air.<br />

2.Comparison <strong>of</strong> simple cycle gas turbine with and without STIG shows that exergetic efficiency gets also<br />

improve by 87.4% however fuel-air ratio increases by 14.4%. Exergy destruction increases in each system<br />

component except air compressor due to mixing <strong>of</strong> steam and air. The exergetic efficiency improves appreciably<br />

exergy destruction rate (%) <strong>of</strong> combustion chamber falls with increasing amount <strong>of</strong> STIG.<br />

3.Comparison <strong>of</strong> simple cycle gas turbine with and without FCS and STIG shows that exergetic efficiency gets<br />

also improve by 87.06% however fuel-air ratio increases by 15.2%. The exergy destruction gets increased in<br />

each system component due increasing mass flow rate. Exergy destruction rate (%) <strong>of</strong> system component does<br />

not show much variation with relative humidity however with increasing amount <strong>of</strong> STIG, exergy destruction<br />

rate <strong>of</strong> each component increases except combustion chamber and compressor.<br />

r = 10, T0 = 25 0 C, R.H. = 60%, TIT = 1247 0 C<br />

Exergy<br />

destructi<br />

on rate<br />

(MW)<br />

€ Exer<br />

gy<br />

destr<br />

uctio<br />

n<br />

rate<br />

(%)<br />

Exer<br />

gy<br />

destr<br />

uctio<br />

n<br />

rate<br />

(MW<br />

)<br />

€ Exerg<br />

y<br />

destru<br />

ction<br />

rate<br />

(%)<br />

Exerg<br />

y<br />

destru<br />

ction<br />

rate<br />

(MW)<br />

€ Exerg<br />

y<br />

destru<br />

ction<br />

rate<br />

(%)<br />

Combustion chamber 33.31 0.67 46.47 34.22 0.67 46.42 39.63 0.69 63.89 40.66 0.68 63.72<br />

3<br />

Gas turbine 3.<strong>19</strong>3 0.95 4.16 3.336 0.95 4.53 5.018 0.93 8.09 5.075 0.93 7.95<br />

Air compressor or Air 1.892 0.93 2.47 2.366 0.91 3.2 1.892 0.93 3.05 2.367 0.91 3.71<br />

compressor assembly<br />

HRSG --- --- --- --- --- --- 13.11 0.75 21.14 13.283 0.75 <strong>20</strong>.82<br />

4<br />

Stack-loss 33.28 --- 46.43 33.8 --- 45.85 2.379 --- 3.83 2.421 --- 3.79<br />

Overall plant ( ∑ E & 71.675 --- 100 73.722 --- 100 62.03 --- 100 63.806 --- 100<br />

D<br />

)<br />

30<br />

30.93<br />

6<br />

39.15<br />

Power output (MW)<br />

38.23<br />

Total exergy destruction<br />

per MW <strong>of</strong><br />

2.39 --- --- 2.38 --- --- 1.623 --- --- 1.629 --- ---<br />

output(<br />

∑ & MW )<br />

E D<br />

Net work difference with respect<br />

to simple gas turbine<br />

<strong>20</strong><br />

15<br />

10<br />

5<br />

0<br />

-5<br />

0.93<br />

Simple cycle with<br />

fog cooling<br />

8.23<br />

Simple cycle with<br />

STIG (0.1)<br />

9.15<br />

Simple cycle with<br />

fog cooling and STIG<br />

(0.1)<br />

Cycles<br />

17.33<br />

Simple cycle with<br />

STIG (0.2)<br />

18.25<br />

Simple cycle with<br />

fog cooling and STIG<br />

(0.2)<br />

Fig. 2- Comparison <strong>of</strong> net work output for different cycles<br />

<strong>20</strong>2


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

r = 10, T0 = 25 0 C, R.H. = 60% , TIT = 1247 0 C<br />

Generation efficiency (%)<br />

40<br />

30<br />

<strong>20</strong><br />

10<br />

0<br />

29.93<br />

Simple cycle<br />

30.11<br />

33.33<br />

33.4<br />

37.66<br />

37.62<br />

Simple cycle with Simple cycle with Simple cycle with Simple cycle with Simple cycle with<br />

fog cooling STIG (0.1) fog cooling and STIG (0.2) fog cooling and<br />

STIG (0.1)<br />

STIG (0.2)<br />

Cycles<br />

Fig. 3- Comparison <strong>of</strong> Generation efficiency for different cycles<br />

The trend <strong>of</strong> graphs shows that the combination <strong>of</strong> fogging and STIG with simple cycle gas turbine cycle is a<br />

good approach to enhance the performance <strong>of</strong> the system on the basis <strong>of</strong> first law as well as second law. Fig.2 &<br />

3 predict that power output is maximum in case <strong>of</strong> simple cycle with fogging and STIG and generation efficiency<br />

is maximum for STIG only. The power output increases as the mass flow rate increases and generation efficiency<br />

reduces minutely due to higher fuel-air-ratio.<br />

Fig. 4- The effect <strong>of</strong> steam injection ratio on First-law efficiency, generation efficiency and process heat<br />

The Fig.4 shows the effect <strong>of</strong> STIG (0-0.2% <strong>of</strong> mass flow rate <strong>of</strong> air) on generation efficiency, first law<br />

efficiency and process heat for fixed inlet air conditions as the air gets saturated up to 100% R.H. The first law<br />

efficiency falls with the increasing amount <strong>of</strong> steam injection ratio. The reason for decrease in First-law<br />

efficiency is that the slope <strong>of</strong> process heat is sharper than the slope <strong>of</strong> generation efficiency. The generation<br />

efficiency increases while the process heat falls with increasing amount <strong>of</strong> steam injection ratio along with the<br />

fogging <strong>of</strong> air up to 100% R.H. The graph predicts that steam injection effects the generation ef ficiency, firstlaw<br />

efficiency and process heat more than the fog cooling <strong>of</strong> inlet.<br />

The exergy destruction rate (MW) for different system components with different amount <strong>of</strong> STIG has been<br />

shown in Fig.5. The power output increases for large amount <strong>of</strong> STIG due to increasing mass flow rate <strong>of</strong> air.<br />

While the exergy destruction rate increases into the Combustion chamber, turbine and HRSG. The exergy<br />

destruction in combustion chamber is highest among all the system components due to highest temperature <strong>of</strong><br />

combustion chamber. The graph predicts that steam injection increases the exergy destruction in combustion<br />

chamber due to mixing <strong>of</strong> high temperature superheated steam to the combustor highers the overall temperature.<br />

The exergy destruction rate (MW) per MW <strong>of</strong> power output for different system components with different<br />

amount <strong>of</strong> STIG has been shown in Fig.6. Due to significant increase in power output the rate <strong>of</strong> exergy<br />

destruction (MW) per MW <strong>of</strong> power output reduces for combustion chamber, compressor, HRSG and Stack -<br />

gases while increases for gas turbine due to increasing mass flow rate with steam <strong>of</strong> lower exergy.<br />

<strong>20</strong>3


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Exergy destruction rate (MW)<br />

r = 10, T0 = 25 0 C, R.H. = 60%, TIT = 1247 0 C<br />

60<br />

40<br />

<strong>20</strong><br />

0<br />

33.2<strong>19</strong><br />

40.662<br />

43.493<br />

Combustion<br />

chamber<br />

1.892<br />

2.367<br />

2.367<br />

3.281<br />

5.075<br />

7.22<br />

Compressor Gas Turbine HRSG Stack-gases<br />

Components<br />

0<br />

0<br />

13.283<br />

Simple cycle (PO =30MW)<br />

STIG (0.1) (PO = 39.15MW)<br />

STIG (0.2) (PO = 48.25MW)<br />

15.649<br />

33.279<br />

2.421<br />

2.85<br />

Fig. 5- Comparison <strong>of</strong> Exergy destruction rate <strong>of</strong> system components per MW <strong>of</strong> output for retr<strong>of</strong>itted cycle (Fog<br />

cooling and STIG) with simple cycle.<br />

Exergy destruction rate<br />

(MW )/MW <strong>of</strong> Power output<br />

r = 10, T0 = 25 0 C, R.H. = 60% , TIT = 1247 0 C<br />

1.5<br />

1<br />

0.5<br />

0<br />

1.104<br />

1.039<br />

0.901<br />

Combustion<br />

chamber<br />

0.063<br />

0.06<br />

0.049<br />

0.109<br />

0.13<br />

0.15<br />

Compressor Gas Turbine HRSG Stack-gases<br />

Components<br />

0.339<br />

Simple cycle (PO =30MW)<br />

STIG (0.1) (PO = 39.15MW)<br />

STIG (0.2) (PO = 48.25MW)<br />

0.324<br />

1.109<br />

0.062<br />

0.059<br />

Fig. 6- Comparison <strong>of</strong> Exergy destruction rate (MW) <strong>of</strong> system components for retr<strong>of</strong>itted cycle (Fog cooling<br />

and STIG) with simple cycle.<br />

2. Conclusions<br />

In this study, the performance characteristics <strong>of</strong> simple gas turbine retr<strong>of</strong>itted with either fog cooling system<br />

(FCS) or /and steam injected gas turbine (STIG) technology have been analyzed and the various efficiencies and<br />

net power output have been investigated, In addition, various performance parameters have also been compared<br />

on the basis <strong>of</strong> first law as well as second law (exergy) analysis.<br />

• During summer season as temperature increases, the density <strong>of</strong> ambient air decreases and hence the mass<br />

flow rate decreases which consequences low power output. The FCS technology reduces the ambient<br />

temperature and increases relative humidity which ultimately increases mass flow rate and hence power<br />

output increases. In this study, the power output improves by 3.1% and thermal efficiency by 0.6% using<br />

FCS technology retr<strong>of</strong>itted with simple cycle gas turbine.<br />

• As the exhaust gases leaving from the turbine have very high temperature and fundamental thermodynamic<br />

analysis predicted that low efficiency <strong>of</strong> gas turbine has been resulted. The methods used in the past to<br />

improve the efficiency were focused on either increasing the expansion work or decreasing the compression<br />

work. In this study, the modification <strong>of</strong> STIG and FCS to simple gas turbine enhanced the thermal efficiency<br />

up to 11.59% and the power output improved by 30.5%.<br />

Although the steam injection will increase the total exergy losses, the exergy loss per MW output is much<br />

smaller than that <strong>of</strong> simple cycle.<br />

• Presently, the STIG technology is applied only to the gas turbine cycle. It can be extended to the combined<br />

power-cycle which are now well established. The present study can be further extended for thermoeconomic<br />

or exergoeconomic analysis.<br />

3. References<br />

1 Nishida K, Takagi T, Kinoshita S, Regenerative steam-injection gas turbine systems, Applied Energy 81 (<strong>20</strong>05)<br />

231-246; Japan.<br />

2 Hawaj O M, Mutairi H, A combined power cycle with absorption air cooling, Energy 32 (<strong>20</strong>07) 971-982,<br />

Kuwait.<br />

3 Pelster S, Favrat D,Von Spakovsky M R, The thermo economic analysis and environomic modeling and<br />

optimization <strong>of</strong> the synthesis and operation <strong>of</strong> combined cycle with advanced options, Engineering for gas<br />

turbine and power, transaction <strong>of</strong> the ASME 123 (<strong>20</strong>01) 717-26.<br />

<strong>20</strong>4


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4 Bhargava R & Meher-Homji C B, Parametric analysis <strong>of</strong> existing gas turbines with inlet evaporative and<br />

overspray fogging, Journal <strong>of</strong> Engineering for gas turbines and power 127 (<strong>20</strong>05) 145; Houston.<br />

5 Chaker M, Homji C B M, Mee I I I T, Inlet fogging <strong>of</strong> gas turbine engines-part II: fog droplet sizing analysis,<br />

nozzle types, measurement and testing, Journal <strong>of</strong> engineering for gas turbines and power 126 (<strong>20</strong>04) 559,<br />

Monrovia.<br />

6 Bansode S, Sinha R, A thermodynamic analysis for gas turbine power optimization by fog cooling system,<br />

<strong>20</strong>th national and 9th International ISHMT-ASME heat and mass transfer conference (<strong>20</strong>10).<br />

7 Alexis G K, Performance parameters for the design <strong>of</strong> a combined refrigeration and electrical power<br />

cogeneration system, International journal <strong>of</strong> refrigeration 30 (<strong>20</strong>07) 1097-1103, Greece.<br />

8 Kumar A, Kachhwaha S S, Mishra R S, Thermodynamics analysis <strong>of</strong> a regenerative gas turbine cogeneration<br />

plant, Journal <strong>of</strong> Scientific & Industrial Research, 69 (<strong>20</strong>10) 225-231; India.<br />

9 Wang F J & Chiou J S, Integration <strong>of</strong> steam injection and inlet air cooling for a gas turbine generation system,<br />

Exergy conversion and Management, 45 (<strong>20</strong>04) 15-26, Taiwan; ROC.<br />

10 Bilgen E, Exergetic and engineering analysis <strong>of</strong> gas turbine based cogeneration systems, Energy 25 (<strong>20</strong>00)<br />

1215-1229, Canada.<br />

11 Ondryas I S, Wilson D A, Kawamoto M, Haub G L, Options in gas turbine power augmentation using inlet<br />

air chilling, Journal <strong>of</strong> Engineering for gas turbines and power 113 (<strong>19</strong>91) <strong>20</strong>5.<br />

<strong>20</strong>5


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Time Dependent Analysis <strong>of</strong> cooling load using FDM Approach<br />

Sachin Gupta 1 , Arvind Gupta 2<br />

1,<br />

Assistant Pr<strong>of</strong>essor, Mechanical Engineering Department<br />

Vaish College <strong>of</strong> Engineering, Rohtak<br />

2<br />

Associate Pr<strong>of</strong>essor, Mechanical Engineering Department<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad<br />

Abstract<br />

The present work analyses the variation <strong>of</strong> cooling load with time <strong>of</strong> a system having single entity with the use <strong>of</strong><br />

Finite Difference Method. Cooling load calculation is the major work performed in the air-conditioning system<br />

design. This should be performed as accurately as possible to reduce over design or under design <strong>of</strong> the system.<br />

Earlier work <strong>of</strong> analyzing cooling load with time involves Conduction Transfer Function (CTF) Method. Finite<br />

difference method is used for computation <strong>of</strong> transient heat conduction through the wall and ro<strong>of</strong>. Implicit finite<br />

difference method is chosen for its stability. Heat gain through window is calculated by taking solar heat gain<br />

coefficients (SHGC). Infiltration effect in the total cooling load is also discussed. The components <strong>of</strong> heat gain<br />

are finally categorized under convective and radiant portion. The convective portions are taken as cooling<br />

load. The radiant portions are changed to cooling load by multiplying them with radiant time factors. Finally<br />

an example <strong>of</strong> an auditorium is taken & cooling load is calculated at different instant <strong>of</strong> time which ultimately<br />

helps in the design <strong>of</strong> an air conditioning system.<br />

Keywords: Cooling Load, Finite Difference Method, Solar Heat Gain Coefficient<br />

1. Introduction<br />

The main objective <strong>of</strong> air conditioning is to maintain the conditions that are conducive to human comfort or<br />

necessary for a product or process within the conditioned space. Thus, equipment <strong>of</strong> proper capacity has to be<br />

installed and controlled throughout the year. To select a properly sized cooling unit, the peak or maximum load<br />

(block load) for each zone must be computed. Because this peak load may vary considerably for different types<br />

<strong>of</strong> buildings so each building type has to be considered; the block load for a single family detached house with one<br />

central system is the sum <strong>of</strong> all the room loads. If the house has a separate system for each zone, cooling load for<br />

each zone (i.e., the sum <strong>of</strong> all the loads for all rooms in each zone) is required. When a house is zoned with one<br />

central cooling system, the block load must be computed for the complete house as if it were one zone.<br />

Apartment buildings with a central cooling system require a block load calculation for the complete structure to<br />

size the central system.<br />

2. Literature Review<br />

Cooling load calculations are the major work performed in the air-conditioning system design. This should be<br />

performed as accurately as possible to reduce over design or under design <strong>of</strong> the system. Building heat transfer<br />

mechanisms are complex and as unpredictable as the weather and human behavior, both <strong>of</strong> which strongly<br />

influence load calculation results. Some <strong>of</strong> the factors that also influence results are heat gain through wall, ro<strong>of</strong><br />

and windows, infiltration <strong>of</strong> atmospheric air, ventilation, appliances load, and occupancy[1-4]. These factors<br />

combine to force engineers to develop procedures that minimize the load calculation complexity without<br />

compromising accuracy. Some s<strong>of</strong>tware use heat balance method for their calculation <strong>of</strong> cooling load [5-7].<br />

Heat balance method treat the whole problem by dividing the various heat gains into outside face heat balance,<br />

wall conduction process, inside face heat balance and air heat balance[8-9]. Hourly analysis program uses<br />

Transfer Function Method for solving heat conduction across the wall which is based on an idea known as the<br />

"Response Factor Principle". According to this principle for a specific room, the thermal response patterns (i.e.,<br />

how the heat gain is converted to load over a period <strong>of</strong> time) for each specific type <strong>of</strong> heat gain will always be the<br />

same. A cooling load calculation determines total sensible and latent cooling load due to heat gain 1.) Through<br />

structural components (walls, floors and ceilings) ; 2.) Through windows ; 3.) Caused by infiltration and<br />

ventilation and 4.) Due to occupancy, lighting and equipments. Finite Difference method (F.D.M.) is used for<br />

calculation <strong>of</strong> heat transfer through structural components. Amount <strong>of</strong> solar radiation is also calculated<br />

separately.<br />

3. Solar Radiation<br />

The total amount <strong>of</strong> solar radiation, It, normally incident on an inclined surface is given by<br />

I t I β I d I r<br />

<strong>20</strong>6


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

where<br />

Iβ--- component <strong>of</strong> direct radiation normal to a tilted surface<br />

I d--- Diffuse irradiance<br />

Ir --- Ground-reflected irradiance<br />

All the three terms have been calculated separately which will give the total amount <strong>of</strong> solar radiation falling on<br />

any surface.<br />

4. Heat Gain Through Structures<br />

Basically any building is composed <strong>of</strong> structures like walls, ro<strong>of</strong>s, and floor. The heat transfer through wall and<br />

ro<strong>of</strong> is similar as both structures are <strong>of</strong> the same nature and exposed to the same type <strong>of</strong> boundary conditions. For<br />

floors directly in contact with ground or over an underground basement that is neither ventilated nor<br />

conditioned, heat transfer may be neglected for cooling load estimates.<br />

Wall and ro<strong>of</strong> transmission loads account for heat transferred due to solar radiation striking the exterior surface<br />

<strong>of</strong> the wall, and due to the temperature difference between indoor and outdoor air. Calculation <strong>of</strong> heat transfer<br />

through a wall section with a variable temperature in the outdoor environment and with a variable solar radiation<br />

input on the outside surface requires the heat conduction equation with non-linear, time dependent boundary<br />

conditions. The governing differential equation for this kind <strong>of</strong> conduction is<br />

where T- local temperature at a point in the slab<br />

τ- time in second<br />

- thermal diffusivity <strong>of</strong> the slab, m 2 /sec<br />

x- length in m.<br />

At x=0, outside surface, the boundary condition is<br />

where Q r<br />

(τ is the net solar radiation heat transfer to the exterior at a particular time. In the above equation both To<br />

and Qr are functions <strong>of</strong> time.<br />

At x=L, the inside surface, the boundary condition is<br />

The initial conditions for above equations are specified temperature distribution in the wall at timeτ=0<br />

The non-linear, time dependent boundary condition at the outside surface is the primary obstacle in obtaining a<br />

solution to equation. To circumvent this difficulty the concept <strong>of</strong> the sol-air temperature is introduced .The solair<br />

temperature is the fictious temperature that in the absence <strong>of</strong> all radiation exchanges gives the same rate <strong>of</strong><br />

heat transfer to the exterior surface as actually occurs by solar radiation and convection. In terms <strong>of</strong> sol-air<br />

temperature the heat transfer to the outer surface is<br />

In terms <strong>of</strong> the actual outdoor temperature Ta the heat transfer<br />

rate is<br />

Above two equations may be used to obtain<br />

<strong>20</strong>7


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The termε∆R / h o varies from about zero for a vertical surface to about 4 o C for horizontal surface.<br />

The ratioα h o varies from 0.026 m 2 - 0 C/WS for a light colored surface to a maximum <strong>of</strong> about 0.053m 2 - 0 C/W for a darkcolored<br />

surface or any surface for which the permanent lightness cannot be anticipated.<br />

5. Numerical Analysis <strong>of</strong> the Basic Heat Equation<br />

There are various methods to treat the basic heat equations numerically. Some <strong>of</strong> the famous methods are finite<br />

element method, finite difference method, transform methods and time series method. From a computational<br />

standpoint; two methods that have been used widely are a finite difference procedure and conduction transfer<br />

function method. Besides giving surface temperatures, finite difference method gives the temperature<br />

distribution across the wall and this is one special advantage <strong>of</strong> it over conduction transfer function method. For<br />

the above mentioned reason finite difference method is selected.<br />

The finite difference method involves discrete approximations <strong>of</strong> first derivative as follows<br />

Approximations to the governing differential equations are obtained by replacing all continuous derivatives by<br />

discrete formulas such as those in above equation. The relation between the continuous, exact, solution and the<br />

discrete approximation is shown in fig.<br />

Finite difference equations will be developed with the dependent variable φ as a function <strong>of</strong> only one independent<br />

variable, x, i.eφ φx . The resulting formulas will then be used to approximate derivatives with respect to time or space. It<br />

is possible to solve the above heat conduction equation together with its boundary equations using methods<br />

like forward difference, backward difference and Crank-Nicolson. Due to numerical instabilities <strong>of</strong> forward<br />

difference method and numerical oscillation <strong>of</strong> Crank-Nickolson method m, the backward difference method is<br />

used in this work using backward difference, the PDE <strong>of</strong> heat conduction is discretized as follows.<br />

Wall discretization<br />

For all interior nodes above equation can be discretized using implicit method as<br />

Where<br />

<strong>20</strong>8


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Applying energy balance for surface node at the exterior portion, the following discrete equation is obtained<br />

For interior surface nodes<br />

Rearranging the above equation we can get the following equation for interior surface node.<br />

After arranging the above equations we will have a tri-diagonal matrix and a vector matrix. So solving the above<br />

matrix equation will give us the hourly temperature distribution across the layer <strong>of</strong> the wall.<br />

6. Heat Gain Through Ro<strong>of</strong><br />

Ro<strong>of</strong> used for buildings can be <strong>of</strong> two types. One with no air gap and the other with air gap in between.. The first<br />

type can be treated as a pure wall with some inclination and can be solved using procedures listed previously. The<br />

second case is similar to a natural convection effect in a body <strong>of</strong> fluid enclosed by surfaces <strong>of</strong> non-uniform<br />

temperature.<br />

For horizontal surfaces there are two different cases<br />

If the upper plate is at a higher temperature, no convection effects will arise, except possibly at the<br />

edges, and heat transfer will be entirely by conduction. The convection coefficient is merely k/s, where s<br />

is the distance between the enclosing surfaces. Therefore, the Nusselt number is 1.0.<br />

<br />

If the lower plate is warmer, an unstable condition results. Lighter layers <strong>of</strong> fluid are overlaid by denser<br />

layers. For a Grash<strong>of</strong> number based on S, less than 1700, no motion results, and the simple conduction<br />

rate pertains. For greater values natural convection pertains. So we can approximate the condition as a<br />

pure conduction and we can treat it in a similar manner to that <strong>of</strong> wall<br />

7. Procedure for calculation <strong>of</strong> cooling load for heat gain through ro<strong>of</strong><br />

1.) Define the location, wall orientation and construction feature <strong>of</strong> the wall in detail.<br />

2.) From the given inputs determine the direct and diffuse beam radiation.<br />

3.) Calculate sol-air temperature from the calculated radiation together with surface heat transfer coefficients.<br />

4.) Apply finite difference method to determine the inside surface temperature <strong>of</strong> the wall.<br />

5.) Determine the heat gain due to temperature difference between the wall surface and room temperature. Since<br />

this heat gain have both radiation and convection component split the heat gain accordingly. For heat gain<br />

through wall and ro<strong>of</strong> the convention is to take 37% as the radiation component and the rest as convection<br />

component.<br />

6.) Take the convection component directly as a cooling load and apply radiant time series factor for the<br />

radiation component.<br />

7.) Summing up results <strong>of</strong> number 6 will give the cooling load<br />

8. Heat Gain Through Glass Window<br />

Of the energy that is incident upon the glass, some is reflected and lost, some is transmitted through the glass,<br />

and some is absorbed by the glass as the energy passes through it. This small amount <strong>of</strong> energy raises the<br />

<strong>20</strong>9


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

temperature <strong>of</strong> the glass, and the glass eventually transmits this heat by convection partly to the room and partly to<br />

the exterior. For angles <strong>of</strong> incidence between 60 o and 0 o , ordinary single window glass transmits about 85% <strong>of</strong> the<br />

energy incident upon it. About 6% is absorbed and the remaining 9% is reflected. As the angle <strong>of</strong> incidence<br />

increases beyond 60 0 , the transmitted radiation falls <strong>of</strong>f to zero, the reflected amount increases. The absorption<br />

figure remains fairly constant at about 6% for angles <strong>of</strong> incidence up to 80 0.<br />

9. Solar Heat Gain Coefficient<br />

The total heat gain through fenestration consists <strong>of</strong> the directly transmitted solar radiation plus the in-ward<br />

flowing fraction <strong>of</strong> the solar radiation that is absorbed in the glazing system. Both parts contain beam and diffuse<br />

contributions. The transmitted portion goes directly on the surfaces within the zone and should be reradiated<br />

back before considering it as a cooling load. The second part, the inward flowing fraction <strong>of</strong> the absorbed solar<br />

radiation, gets involved in an interaction with other surfaces through long wave radiation exchange and with the<br />

zone air through convective heat transfer. The solar heat gain coefficient (SHGC) combines the transmitted<br />

solar radiation and the inward-flowing fraction <strong>of</strong> the absorbed radiation. The SHGC is defined as<br />

whereτ - solar transmittance <strong>of</strong> glazing<br />

αk -Solar absorptance <strong>of</strong> the K th layer <strong>of</strong> the glazing system<br />

nl -Number <strong>of</strong> layers<br />

Nk -inward flowing fraction <strong>of</strong> absorbed radiation in the k th layer<br />

The solar radiation, which passes through a sheet <strong>of</strong> window glazing, does not constitute an immediate load on<br />

the air conditioning system for the following two reasons<br />

Air is transparent to radiation <strong>of</strong> this kind, and<br />

A change <strong>of</strong> load on the air conditioning system is only caused by variation <strong>of</strong> the air temperature within the<br />

room.<br />

For the temperature <strong>of</strong> the air in the room to rise, the solar radiation entering through the window must first<br />

warm up the solid surfaces around the zone. These surfaces are then in a position to liberate some <strong>of</strong> the heat to<br />

the air by convection. Not all the heat will be librated immediately, because some <strong>of</strong> the energy is stored within<br />

the depth <strong>of</strong> the solid materials. The situation is analogues to that considered for heat gain through walls. There<br />

is, thus a decrement factor to be applied to the value <strong>of</strong> the instantaneous solar transmission through glass, and<br />

there is also a time lag to be considered. To account this time lag and decrement there is a radiant time factor<br />

(RTF), which is derived from heat balance method, to multiply the transmitted heat. RTFs used to calculate the<br />

cooling load on the basis <strong>of</strong> current and past heat gains. The series shows the portion <strong>of</strong> the radiant portion that is<br />

convected to the zone air for each hour. The radiant time series convert the radiant portion <strong>of</strong> heat gain<br />

according to the following equation<br />

where Qr,θ- radiant cooling load (Qr) for the current hourθ, W qr,θ- radiant heat gain for the current hour,W<br />

qr,θ-n - radiant heat gain n hours ago, n=1…23, W<br />

ro, r1.. r23- radiant time factors<br />

The radiant cooling load for the current hour, which is calculated using the above equation, will be added with<br />

the convective portion to determine the total cooling load for that hour.<br />

10. Procedure for Calculation <strong>of</strong> Cooling Load<br />

1.) Calculate the values <strong>of</strong> direct, diffuse and sky radiation on the surface.<br />

2.) Define the properties <strong>of</strong> the glass like emittance, absorptance and sensible heat gain coefficient.<br />

3.) Determine the sunlit area<br />

4.) Determine the direct radiation transmitted by multiplying direct radiation on the surface by sensible heat<br />

gain coefficient, SHGC, <strong>of</strong> the glass. If there is no internal blind the whole amount will be taken as radiant.<br />

In the presence <strong>of</strong> internal blinds take 63% as radiant and the rest as convective.<br />

5.) Determine scattered radiation transmitted by multiplying the summation <strong>of</strong> diffuse and sky radiation values<br />

210


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

with hemispherical sensible heat gain coefficient.<br />

6.) Multiply the direct radiation transmitted by sunlit area and scattered radiation transmitted by total area <strong>of</strong><br />

the window. Adding these two values will give instantaneous heat gain through window. But this value does<br />

not contribute any thing to the cooling load immediately as we already assume air to be completely transparent<br />

for radiation. So the heat gain through window should be first absorbed by components like furniture, floor etc<br />

and should be reradiated back to the room for it to be considered as a cooling load. To take this in to account we<br />

have a storage factor to multiply the instantaneous heat gain.<br />

7.) Determine the heat gain due to conduction through glass.<br />

8.) Add the convective heat gain with the scattered portion and split the summation in to radiative and<br />

convective component. The normal trend is to take 37% as convective and the rest as radiative.<br />

9.) Multiply the direct radiation by RTF for solar radiations and obtain the cooling load using equation.<br />

10.) Multiply the radiative component <strong>of</strong> by RTF given for non-solar radiation according to equation.<br />

11.) Summation <strong>of</strong> the results <strong>of</strong> number 9, 10, and convective component <strong>of</strong> number 8 will give hourly cooling<br />

load due to window heat gain.<br />

11. Heat Gain Through Infilitration & Ventilation<br />

Air exchange <strong>of</strong> outdoor air with the air already in a building can be divided into two broad classifications:<br />

infiltration and ventilation<br />

Infiltration<br />

Infiltration is uncontrolled flow <strong>of</strong> air through unintentional openings such as cracks in the walls and ceilings<br />

and through perimeter gaps <strong>of</strong> windows and doors driven by wind, temperature difference and internally<br />

induced pressures. It is caused by a greater air pressure on the outside <strong>of</strong> the building than the inside. The amount<br />

<strong>of</strong> infiltered air depends on the pressure difference, the number, size and the shape <strong>of</strong> cracks involved; the<br />

number, the length and width <strong>of</strong> the perimeter gaps <strong>of</strong> the windows and doors; and the nature <strong>of</strong> the flow in the<br />

crack or gap (laminar or turbulent). The relation connecting these quantities are given by<br />

where Vi - flow rate <strong>of</strong> leaking air<br />

∆p- pressure difference, if outside is greater than inside it is positive.<br />

n - flow exponent if flow in the crack is laminar, n=1 if turbulent, n=0.5<br />

Usually flow will be transitional thus n will be between 0.5 and 1<br />

C- flow coefficient, determined experimentally and includes the crack or opening size<br />

where∆pst-pressure difference caused by stack effect<br />

∆pw-pressure difference caused by wind effect<br />

∆pp-pressure difference caused by pressurizing the building<br />

Crack Wall Infiltration Per Floor or Room<br />

Where<br />

k- leakage coefficient (C=KA)<br />

A- wall area in m 2<br />

Crack Infiltration for Doors And Movable Windows<br />

where P – perimeter <strong>of</strong> the windows or door,in ‘m’<br />

k- Perimeter leakage coefficient (C=kxP).<br />

n-0.65<br />

Ventilation<br />

Ventilation is the intentional introduction <strong>of</strong> air from the outside into a building; it is further subdivided into<br />

natural ventilation and forced ventilation. Natural ventilation is the intentional flow <strong>of</strong> air through open<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

windows, doors, grilles, and other planned building envelope penetrations, and it is driven by natural and/or<br />

artificially produced pressure differentials. Forced ventilation is the intentional movement <strong>of</strong> air into and out <strong>of</strong><br />

a building using fans and intake and exhaust vents; it is also called mechanical ventilation.<br />

Most <strong>of</strong> the time the air introduced in to the building by ventilation is expressed in terms <strong>of</strong> air exchange per<br />

hour (ACH). Given ACH the mass flow rate in m 3 /s can be calculated by<br />

where<br />

n - number <strong>of</strong> air exchange per hour<br />

v - volume <strong>of</strong> the room<br />

12. Space Cooling Load Due to Infiltered And Ventilated Air<br />

Total heat gain qt corresponding to the change <strong>of</strong> a given standard flow rate Qs, summation <strong>of</strong> Qv and Qi, through<br />

an enthalpy difference∆h is<br />

where air density =1.2kg/m 3<br />

Sensible heat gain qs corresponding to the change <strong>of</strong> dry bulb temperature∆t for a given air flow (standard<br />

conditions) Qs is<br />

Latent heat gain q l corresponding to the change <strong>of</strong> humidity ratio∆W for given air flow (standard conditions) Qs<br />

is<br />

Where 2500 is the approximate heat content <strong>of</strong> 50% relative humidity vapor at 24 o c less the heat content <strong>of</strong><br />

water at 10 o c. 50% relative humidity at 24 o C is a common design conditions<br />

for the space.<br />

13. Procedure for Calculation <strong>of</strong> Cooling Load<br />

1.) Determine the total pressure difference between indoor and outdoor, which is the summation <strong>of</strong> pressure<br />

differences caused due to stack effect, pressurization and wi n d.<br />

2.) Determine airflow rate into the building due to the above pressure difference through cracks <strong>of</strong> wall, window<br />

and door. Also determine flow rates <strong>of</strong> air through door and window openings depending on their nature and<br />

means <strong>of</strong> operation.<br />

3.) Calculate the airflow rate due to ventilation and add it with air flow rate due to infiltration to find the total air<br />

flow rate.<br />

4.) After determining the total flow rate calculate the sensible and latent heat gain using equations .<br />

5.) As the infiltered air directly combines with the zone the sensible as well latent heat gains are taken directly as<br />

a cooling load without applying any type <strong>of</strong> modifications<br />

14. INTERNAL HEAT GAIN<br />

Heat Gain From Electric Lighting<br />

As lighting is <strong>of</strong>ten the major space load component, a precise account <strong>of</strong> this heat gain is required. The<br />

computation <strong>of</strong> this heat load is <strong>of</strong>ten very difficult due to the rate <strong>of</strong> heat gain at any given time being quite<br />

different from the heat equivalent <strong>of</strong> the power supplied instantaneously to these lights.<br />

The instantaneous heat gain from electric lighting may be computed from<br />

where<br />

QL - heat gain, W<br />

W - total light wattage<br />

FUL -lighting use factor<br />

FS _-lighting special allowance factor<br />

212


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The total light wattage is obtained from the ratings <strong>of</strong> all lamps installed, both for general illumination and for<br />

display use.<br />

The use factor is the ratio <strong>of</strong> the wattage in use, for the condition under which the load estimate is being made,<br />

to the total installed wattage. For commercial applications, such as stores, the use factor is unity<br />

The special allowance factor is for fluorescent fixtures that are either ventilated or installed so that only part <strong>of</strong><br />

the heat goes to the conditioned space. For fluorescent fixtures, the special allowance factor primarily accounts<br />

for ballast losses and can be as high as 2.<strong>19</strong> for 32W single-lump high-output fixtures on 227V circuits.<br />

Heat Gain from Occupants<br />

Human beings give <strong>of</strong>f heat at a metabolic rate, which depends on their rate <strong>of</strong> working. The sensible and latent<br />

heat proportion <strong>of</strong> the heat librated for any given activity depends on the value <strong>of</strong> the ambient dry bulb<br />

temperature; the lower the dry bulb temperature the larger the proportion <strong>of</strong> sensible heat dissipated.<br />

Deciding on the density <strong>of</strong> occupation is usually a problem for the designer. A normal density for an <strong>of</strong>fice<br />

block is 9m 2 per person, as an average for the whole conditioned floor area. The density <strong>of</strong> occupation may be as<br />

high as <strong>20</strong>m 2 per person in executive <strong>of</strong>fices or as low as 6m 2 per person in open <strong>of</strong>fice areas.<br />

Heat Gain from Equipments<br />

Instantaneous heat gain from equipment operated by electric motors within a conditioned space is calculated as<br />

Where<br />

Qem -heat equivalent <strong>of</strong> equipment operation, W<br />

P-motor power rating, W<br />

E M -motor efficiency, decimal fraction


program developed can be broadly classified into following major parts.<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

1.) A program for calculation <strong>of</strong> heat gain through wall and ro<strong>of</strong><br />

2.) A program for calculation <strong>of</strong> heat gain through window and door<br />

3.) A program for calculation <strong>of</strong> heat gain through infiltration & ventilation.<br />

4.) A program for calculation <strong>of</strong> internal heat gain.<br />

5.) A program for calculation <strong>of</strong> space cooling load from heat gain<br />

For developing these programs separate algorithm have been written for each case. So by running the program<br />

one can have the hourly cooling load <strong>of</strong> any building after putting the required<br />

input details.<br />

16. Comparison <strong>of</strong> Wall Heat Gain and Cooling Load Calculation by FDM & CTF<br />

method<br />

For a particular day Wall Heat Gain and then Cooling Load are calculated by using FDM and CTF method. The<br />

results found are summarized in the form <strong>of</strong> graph.<br />

The temperature distribution across the wall over 24 hour is shown in graph taking three nodes as representative<br />

nodes. From the results we can see that at 1hr the inside surface temperature is less than both outside and<br />

interior node for this particular location. The interior node has higher temperature during night as it has heat<br />

absorbed during daytime. During daytime the temperature distribution decreases as we go from outside to inside.<br />

Heat gain and cooling load variations with sol-air temperature are shown in graph. As we can see there is some<br />

time lag between the peak values <strong>of</strong> the three variables. The heat gain starts to rise after some time lag from the<br />

sol- air temperature starts to rise. This is because some time should pass before the heat absorbed in the outside<br />

surface reaches to the room. The radiant portion <strong>of</strong> the heat gain will not create an immediate load, as it has to<br />

be absorbed and reradiated back before creating a load. This will create some time gap between the peak values <strong>of</strong><br />

heat gain and cooling load.<br />

214


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Hourly variation <strong>of</strong> Total Cooling Load<br />

CONCLUSION<br />

In the present research work we have developed a program that is capable <strong>of</strong> computing the sensible and latent<br />

cooling loads <strong>of</strong> a building having single zone taking all the influential factors in to consideration.<br />

1.) We have used FDM which replaces the CTF method which is mostly used by other commercial s<strong>of</strong>twares.<br />

Finite Difference Method gives the temperature distribution across the wall and this is one special advantage<br />

<strong>of</strong> it over Conduction Transfer Function method.<br />

2.) We have also analysed infiltration effects deeply and this makes it more appropriate for cooling load<br />

estimation <strong>of</strong> structures that need precision analysis like cold rooms.<br />

3.) One can also use this research work for cooling load estimation <strong>of</strong> other single zone structures like<br />

Auditorium buildings.<br />

4.) Values obtained can also be taken for modifying the building orientation and construction material<br />

215


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

accordingly with the resulting cooling load at the design stage or can also be used for approximation <strong>of</strong><br />

energy requirement <strong>of</strong> actual buildings.<br />

REFERENCES<br />

1.) W.P,Jones M,sc., C.Eng., M.inst.F.I.H.V.E,(<strong>19</strong>94). Air Conditioning Engineering ,Fourth edition,Edward<br />

Arnol Member <strong>of</strong> Hodder Headline,Plc,London,.<br />

2.) Gerald W.Recktenwald,(<strong>20</strong>03). Finite Difference Equation Approximation To The Heat Transfer Equation.,<br />

3.) Adrian Bejan,J.A Jones, (<strong>19</strong>93). Pr<strong>of</strong>essor <strong>of</strong> Mechanical Engineering, Duke university, Heat Transfer ,John<br />

Will and Sons,Inc.<br />

4.) ASHARE Handbook, (<strong>20</strong>03).Fundamentals SI edition.<br />

5.) Curties O.Pedersen, Daniel E.Fisher, Jeffrey D, (<strong>20</strong>05). Splitler Richard J.liesen, Cooling And Heating Load<br />

Calculation Principles ,American Society <strong>of</strong> Heating Refrigeration and Air conditioning, Inc,Atlanta .<br />

6.) Computer Aided Heat Load Calculations and Coil Design for Air-conditioning Systems<br />

http://www.ieindia.org/publish/mc/0703/july03mc1.pdf<br />

7.) Heat Conduction In Buildings: Transient One Dimensional Finite Difference Wall Model<br />

www.adeptscience.co.uk/products/mathcad/add_ons/…/build_therm_samp.ht<br />

8.) Duffie, J.A,Beckman, (<strong>20</strong>06). John wiley, Solar Energy Of Thermal Process, 2 nd Edition Newyork.<br />

9.) Heat Transfer Through a Multilayer Wall www.H:\k<strong>of</strong>fe\Application Center Application Heat Transfer<br />

Through a Multilayer Wall.htm<br />

216


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

USE OF BIOGAS FOR COOKING PURPOSE IN A TECHNICAL<br />

INSTITUTE: A VIEW POINT<br />

SLIET, Longowal, Punjab, India<br />

e-mail: indrajsliet@yahoo.co.in<br />

Indraj Singh<br />

Abstract<br />

Energy crisis in world is increasing. There are limited resources <strong>of</strong> crude available on the earth. Price <strong>of</strong> LPG<br />

increasing day by day. There is a lot <strong>of</strong>f waste generated which have a problem <strong>of</strong> disposal. Bio gas production<br />

condition in India is very high. The temperature conditions for the production <strong>of</strong> bio gas are very favorable<br />

throughout the year and the availability <strong>of</strong> the bio degradable waste is in bulk. There is great need for the<br />

development <strong>of</strong> the plants which should be based on the Kitchen waste, industrial waste and municipality waste<br />

treatment. So author feel, there is a lot <strong>of</strong> potential to produce biogas from kitchen waste. SLIET is spreading in<br />

451 acre area. More than four thousand students are staying in 13 boys and girls hostels and five hundred<br />

families are also staying in residential area <strong>of</strong> SLIET campus. A survey is conducted at SLIET Longowal and<br />

kitchen waste data collected from different mess, residential areas, shopping complex and restaurant. Survey<br />

revealed that 600 kg/day <strong>of</strong> kitchen waste collected from residential area <strong>of</strong> faculty, staff, students mess and<br />

other location. Biogas <strong>of</strong> more than 32 kg/day (2 LPG Cylinder/day) can be produced by using the biogas plant.<br />

There is an expenditure <strong>of</strong> Rs 2.50 lacs in constructing a bio gas plant. Produced biogases have a potential to<br />

replace a LPG already utilized for a cooking purpose <strong>of</strong> 250 student capacity in a hostel. The payback period is<br />

around 1 year and 3 months approximately.<br />

Keywords: Kitchen Waste, Biogas Plant, Anaerobic Digesters<br />

1. Introduction<br />

The biogas results from organic material anaerobic fermentation. The most important biogas components are<br />

methane (CH 4 ), carbon dioxide (CO 2 ) and sulfuric components (H 2 S). The percentage composition <strong>of</strong> these<br />

components as: methane 65-70%, carbon dioxide 30-35%, sulfuric components 1-2%. The bio gas can be<br />

purified for its use in various applications.<br />

The viability <strong>of</strong> bio gas production in India is very high. The temperature conditions for the production <strong>of</strong> bio gas<br />

are very favourable throughout the year and the arability <strong>of</strong> the bio degradable waste is in bulk.<br />

It is also possible to earn carbon credits for biogas-based power or heat generation in India. For instance, in Apr<br />

<strong>20</strong>08, And hyodaya, a non-government agency working in the field <strong>of</strong> promoting water management and nonconventional<br />

energy and social development distributed the first installment <strong>of</strong> the biogas carbon credit to<br />

farmers in the state <strong>of</strong> Kerala. Andhyodaya had helped construct 15,000 biogas plants in the state and earned<br />

carbon credits. This trend is likely to grow further.<br />

The use <strong>of</strong> biogas for electricity generation in India is more recent, but this trend is accelerating. In many cities<br />

across India, sewage treatment centers and organic waste treatment plants (those treating organic municipal solid<br />

waste, for instance) already use anaerobic digesters to generate biogas and electricity. Some <strong>of</strong> the industries that<br />

generate significant amounts <strong>of</strong> solid or liquid organic waste also have installed digesters and gas engines for<br />

electricity production. Many <strong>of</strong> these require sizable investments, but it is estimated that they have a good return<br />

on investment as the main feedstock that they use is essentially free.<br />

1.1 Mechanism <strong>of</strong> Biogas Fermentation<br />

Reactions:<br />

The formation <strong>of</strong> methane from biomass follows in general the equation:<br />

The products include, for example, the following:<br />

Carbohydrates: C 6 H 12 O 6 → 3CO 2 + 3CH 4<br />

Fats: C 12 H 24 O 6 + 3H 2 O → 4.5CO 2 + 7.5CH 4<br />

Proteins: C 13 H 25 O 7 N 3 S + 6H 2 O → 6.5CO 2 + 6.5CH 4 + 3NH 3 + H 2 S<br />

Because the sulphur remains in the residue and part <strong>of</strong> the CO 2 binds to NH 3 , the result in general is a biogas<br />

composition <strong>of</strong> CH 4 :CO 2 = 71%:29%The ratio <strong>of</strong> CO 2 to CH 4 is determined by the reduction ratio <strong>of</strong> the<br />

organic raw material. During the fermentation <strong>of</strong> glucose (C 6 H 12 O 6 ), CH 4 and CO 2 , for example, develop in<br />

the ratio 1 : 1, since only if this is so is the balance <strong>of</strong> the redox values fulfilled: glucose has a reduction ratio <strong>of</strong><br />

217


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

+24, 2) CH 4 <strong>of</strong> +8, CO 2 <strong>of</strong> 0.The energy balance can be calculated as follows: Organic material, which is built<br />

up by photosynthesis<br />

CO 2 +H 2 O→CH 2 O+O 2 contain the energy.<br />

1.2 Design Parameter<br />

A) Selection <strong>of</strong> materials<br />

B) Total solid (TS) contains calculations <strong>of</strong> organic materials<br />

Solid part: Total solid contained in a certain amount <strong>of</strong> materials is usually used as the material unit to indicate<br />

the biogas- producing rate <strong>of</strong> the materials. Most favorable TS value desired is 08%.<br />

Liquid part: contain <strong>20</strong>% to 80 %.<br />

C) Favorable condition for good fermentation-<br />

Temperature: <strong>20</strong> o c to 35 o c.<br />

PH value: Neutral PH and ranges 6.8 to 7.2.<br />

C/N ratio: Ranges from <strong>20</strong>:1 to 30:1.<br />

Pressure: A minimum pressure <strong>of</strong> 6-10 cm <strong>of</strong> water column that is 1.2 bar is considered ideal for the proper<br />

functioning <strong>of</strong> plant. It should never be allowed to exceed 40-50 cm <strong>of</strong> water column.<br />

Seeding <strong>of</strong> Biomass with Bacteria: To start and accelerate fermentation processes, small amount <strong>of</strong> digested<br />

slurry, containing Methane-forming bacteria is added to the freshly charged plant. This is known Seeding.<br />

Mixing: Mixing has three important effects: Maintains uniformity in substrate concentration, temp. & other<br />

environmental factors. Minimise the formation <strong>of</strong> scum on the surface. Prevents the deposition <strong>of</strong> solid at the<br />

bottom.<br />

Hydraulic retention time (HRT): For digestion where temperature varies from <strong>20</strong> o c to 35 o C and HRT is<br />

greater than <strong>20</strong> days.<br />

TABLE-1<br />

Materials and their main<br />

Yield <strong>of</strong> Biogas<br />

Methane Content (%)<br />

components<br />

m 3 /kg<br />

Green Grass 0.630 70<br />

Leaves 0.210~0.294 58<br />

Carbohydrates 0.750 49<br />

Liquid 1.440 72<br />

Protein 0.980 50<br />

1.3 Properties <strong>of</strong> Biogas<br />

Composition: 60 to 70 per cent Methane, 30 to 40 per cent carbon dioxide, traces <strong>of</strong> hydrogen sulfide, ammonia<br />

and water vapor.<br />

It is about <strong>20</strong>% lighter than air (density is about 1.2 gm/litre).<br />

Calorific value is 18.7 to 26 MJ/ m3 (500 to 700 Btu/ ft3.)<br />

Calorific value without CO2: is between 33.5 to35.3 MJ/ m3<br />

Explosion limit: 5 to 14 % in air.<br />

Removal <strong>of</strong> CO2: Scrubbing with limewater or ethanol amine solution.<br />

Removal <strong>of</strong> H2S: Adsorption on a bed <strong>of</strong> iron sponge and wood shavings.<br />

Air to Methane ratio for complete combustion is 10 to 1 by volume.<br />

One cubic meter <strong>of</strong> biogas is equivalent to 1.613 liter <strong>of</strong> kerosene or 2.309 kg <strong>of</strong> LPG or<br />

0.213 kW <strong>of</strong> electricity.<br />

1.4 Different Wastes Under Consideration<br />

All biodegradable wastes can be use for the production <strong>of</strong> bio gas which may be listed as:<br />

1. Agriculture waste<br />

2. Household waste<br />

3. Industrial liquid waste<br />

4. Slaughterhouse wastes<br />

218


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5. Food processing wastes<br />

1.5 Utilization <strong>of</strong> Biogas<br />

1. The bio so produced can be use in various ways.<br />

2. Production <strong>of</strong> electricity.<br />

3. As the fuel in city buses.<br />

4. Supply through pipes to the nearby villages.<br />

2. Methodology<br />

2.1 Potentional <strong>of</strong> bio gas<br />

The development <strong>of</strong> simple biogas plants for rural households started in the <strong>19</strong>50s. A Massive increase in the<br />

number <strong>of</strong> biogas plants took place in the <strong>19</strong>70s through strong Government backing. Meanwhile, more than one<br />

million biogas plants exist in India. Out <strong>of</strong> this 95% <strong>of</strong> the existing plants are based on the cow dung. There is<br />

great need for the development <strong>of</strong> the plants which should be based on the industrial waste and municipality<br />

waste treatment. The aggregate potential for the biogas generation in India from the industrial, agriculture and<br />

municipality basis is 2700 MW but current production <strong>of</strong> electricity is only 60 MW. Punjab is the most important<br />

area where the potential for developing the bio gas plants is very high. This is because <strong>of</strong> the lead <strong>of</strong> the Punjab<br />

in agriculture sector. Punjab has a very high agriculture waste.<br />

SURVEY REPORT OF S.L.I.E.T<br />

A survey report was conducted to collect the data <strong>of</strong> kitchen waste available for the biogas in S.L.I.E.T.<br />

Sr.<br />

no<br />

Sources <strong>of</strong><br />

waste<br />

1. From faculty<br />

residential<br />

area<br />

Amount <strong>of</strong><br />

waste<br />

produced/day<br />

350kg<br />

Type <strong>of</strong><br />

waste<br />

Kitchen<br />

waste<br />

2. From messes 250kg Food<br />

waste<br />

3 Other 100kg<br />

Sources<br />

(Shopping<br />

complex<br />

etc.)<br />

Food&Ki<br />

tchen<br />

waste<br />

Current<br />

state <strong>of</strong><br />

treatment<br />

No<br />

treatment<br />

No<br />

treatment<br />

No<br />

treatment<br />

Waste available 0.6-0.7 ton/day. Total solid waste for proposed plant : <strong>20</strong>0kg (30% Moisture). Total effluent for<br />

treatment 0.6 ton/day<br />

2.2 Gas production data<br />

Available waste 0 .6 ton/day<br />

Bio Gas produced /kg <strong>of</strong> kitchen waste 0.3m 3<br />

Bio gas produced from 0.6 ton/day waste 180m 3<br />

After purification 80m 3<br />

1m 3 <strong>of</strong> bio gas 0.4kg <strong>of</strong> LPG<br />

80m 3 <strong>of</strong> bio gas 32kg/day<br />

(Approx 2.2 cylinders <strong>of</strong> LPG/d)<br />

Diesel Equavelent <strong>of</strong> Bio Gas Produced<br />

1 m 3 <strong>of</strong> bio gas 0.6 liter <strong>of</strong> diesel<br />

80 m 3 <strong>of</strong> bio gas 48 liter/day<br />

Manure Production Data<br />

The manure will be produced 1.3t/d in the form effluent and 600kg/day in solid form. The manure so produced<br />

has no smell and can be used as an efficient fertilizer.<br />

2.3 Scope <strong>of</strong> Equipments<br />

1. Mixing digester =1 (10m 3)<br />

2<strong>19</strong>


2 Digester =1 (8m3)<br />

3. Mixing unit=1 (4m 3 )<br />

4. Pipes as per requirement= 30 ft<br />

5. Electric motors =4 Nos<br />

6. Mixing paddles= 3 Nos<br />

7. Slurry pumps =2 Nos<br />

8. Shuttle valve =5 Nos<br />

9. Pressure gauges =3 Nos<br />

10. Temperature meter =2 Nos<br />

11. S<strong>of</strong>t covering EPDM membrane =2 Nos<br />

3. Economical Analysis<br />

Construction cost Rs70, 000/<br />

Cost <strong>of</strong> machinery Rs70, 000/<br />

Miscellaneous Rs 40,000/<br />

Running cost Rs70, 000/<br />

Total Rs 2, 50,000/<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3.1 Payback period<br />

It is observed that minimum 240 days critical kitchen waste is produced in SLIET.<br />

Biogas produced per day equivalent to 2 LPG cylinders.<br />

Cost <strong>of</strong> LPG cylinder = Rs4<strong>20</strong>/<br />

Income Per day 4<strong>20</strong>x2=Rs840/<br />

Income per annum (240x840) =Rs<strong>20</strong>1600/<br />

Expenditure=Rs2.5 lac<br />

So payback period is around 1 year and 3 months.<br />

4. Conclusion<br />

There is a potential <strong>of</strong> generation <strong>of</strong> 2 LPG energy equivalent cylinders in a day.Payback period is less than 1.5<br />

year. Manure as a by-product is available. Potential <strong>of</strong> decentralise <strong>of</strong> energy generation. Smokeless cooking is<br />

there so environmental balance and Pollution control.<br />

5. References<br />

[1] RANJEET SINGH, S. K. MANDAL, V. K. JAIN (<strong>20</strong>08), Development <strong>of</strong> mixed inoculum for methane<br />

enriched biogas production<br />

[2] KALE, S.P AND MEHELE, S.T. kitchen waste based biogas plant.pdf. Nuclear agriculture and<br />

Biotechnology/ Division.<br />

[3] KARVE .A.D. (<strong>20</strong>07), Compact biogas plant, a low cost digester for biogas from waste starch.<br />

http://www.arti-india.org.<br />

[4] The <strong>University</strong> <strong>of</strong> Southampton and Greenfinch Ltd. – Bio digestion <strong>of</strong> kitchen waste<br />

A comparative evaluation <strong>of</strong> mesophilic and thermophilic bio digestion for the stabilisation and sanitisation <strong>of</strong><br />

kitchen waste<br />

[5] HILKIAH IGONI, M. F. N. ABOWEI, M. J. AYOTAMUNO AND C. L. EZE (<strong>20</strong>08), Effect <strong>of</strong> Total Solids<br />

Concentration <strong>of</strong> Municipal Solid Waste on the Biogas Produced in an Anaerobic Continuous Digester.<br />

[6] KARVE OF PUNE A.D (<strong>20</strong>06). Compact biogas plant compact low-cost digester from waste starch.<br />

www.bioenergylists.org., M.C. JAIN, DINESH KUMAR (<strong>20</strong>00), the increased biogas production using<br />

microbial stimulants.<br />

[7] SHALINI SING, SUSHIL KUMAR<br />

[8]Tanzania Traditional Energy Development and Environment Organization (TaTEDO), BIOGAS<br />

TECHNOLOGY- Construction, Utilization and Operation Manual.<br />

2<strong>20</strong>


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

CFD MODELING FOR PNEUMATIC CONVEYING<br />

Arvind Kumar 1 , D.R. Kaushal 2 , Navneet Kumar 3<br />

1 Associate Pr<strong>of</strong>essor <strong>YMCA</strong>UST, Faridabad<br />

2 Associate Pr<strong>of</strong>essor, IIT, Delhi<br />

3 Research Scholar IIT, Delhi<br />

e-mail: arvindeem@yahoo.co.in<br />

Abstract<br />

CFD simulation is used to investigate the pressure drop prediction capabilities <strong>of</strong> CFD techniques for a 90 0 pipe<br />

bend in horizontal plane for an extended range <strong>of</strong> conveying conditions in a pneumatic pipe line system. The<br />

conveyed material was cement with a mean particle size (d 50 ) <strong>of</strong> 25 micron. In Test Rig, the 90 0 bend <strong>of</strong> 52mm<br />

internal diameter and D/d <strong>of</strong> 6 was configured horizontally. The computational grids for the horizontal pipe<br />

bend similar to that used in experiment. There is broad qualitative agreement in trends and flow patterns <strong>of</strong><br />

pneumatic conveying through pipeline system. For the high solids loading ratio the Eulerian solver and transient<br />

analysis and at lower solids loading ratios the mixture model and steady-state analysis were more appropriate.<br />

1. Introduction<br />

Pneumatic conveying is widely used in process industries to transport granular materials <strong>of</strong> different types<br />

because <strong>of</strong> its flexibility <strong>of</strong> layout compared with other mechanical conveying methods and environmentally<br />

friendliness. There are three common modes <strong>of</strong> transport <strong>of</strong> material in pneumatically conveying (i) The dilute<br />

phase where all the material is normally in suspension flow (ii) Dense phase plug flow for non-cohesive particles<br />

with high bulk permeability (iii) Dense phase bed flow for materials with suitable aeration and deaeration<br />

characteristics. Several CFD-based models are reported in the literature for the three modes <strong>of</strong> flow, Mason et al<br />

(<strong>19</strong>98) for dilute phase, Tsuji et al (<strong>19</strong>92), Xiang and McGlinchey (<strong>20</strong>04) for dense phase plug flow, Mason and<br />

Levy (<strong>20</strong>01) for dense phase flow.<br />

A CFD simulation is used to investigate the pressure drop prediction capabilities <strong>of</strong> CFD techniques<br />

across a 90 0 bend both in a horizontal plane for an extended range <strong>of</strong> conveying conditions in a pneumatic<br />

conveying system.<br />

Experimental data available in literature used for comparison<br />

The experimental data used in the present study for comparison with CFD predictions are <strong>of</strong><br />

McGlinchey et al (<strong>20</strong>07). The conveyed material was cement with a mean particle size (d 50 ) <strong>of</strong> approximately 25<br />

micron (d 10 = 6.5 micron, d 90 = 72.5 micron, approximately). In Test Rig, the 90 0 bend <strong>of</strong> 52mm internal<br />

diameter and D/d <strong>of</strong> 6 was configured horizontally with single-ended and differential pressure transducers as<br />

shown in Fig. 1 Different conveying conditions were achieved with superficial air velocities at the start <strong>of</strong> the<br />

conveying line<br />

Fig. 1 Bend geometry and pressure measurement locations (A and B) for pneumatic conveying through<br />

horizontal bend.<br />

221


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Mathematical model<br />

The use <strong>of</strong> a specific multiphase model (the discrete phase, mixture, Eulerian model) to characterize<br />

momentum transfer depends on the volume fraction <strong>of</strong> solid particles and on the fulfillment <strong>of</strong> the requirements<br />

which enable the selection <strong>of</strong> a given model.<br />

Geometries for CFD simulation<br />

The computational grid for the horizontal pipe bend similar to that used in experiments having size <strong>of</strong><br />

5m before bend and 0.8m after bend in horizontal plane and it has 52mm internal diameter. It consists <strong>of</strong> 3001<strong>20</strong><br />

hexahedral cells and 322344 nodes has been generated using GAMBIT s<strong>of</strong>tware.<br />

Grid Generation<br />

The body-fitted coordinate technique was used with the help <strong>of</strong> the Gambit s<strong>of</strong>tware package to<br />

generate three-dimensional grids for bend and straight sections, according to the actual dimensions <strong>of</strong> the test<br />

sections.<br />

Volume statistics:<br />

Minimum volume: 5.5X 10 -9 m 3<br />

Maximum volume: 9.6X 10 -8 m 3<br />

Total volume: 4.17 X 10 -2 m 3<br />

Face area statistics:<br />

Minimum face area: 1.38X 10 -6 m 2<br />

Maximum face area: 2.47 X 10 -4 m 2<br />

Fig. 2 Meshing at interior <strong>of</strong> pipe bend (horizontal to horizontal)<br />

Numerical Simulation<br />

The grid files generated by Gambit were used for the simulation in Fluent. The experimental conditions<br />

were approximated using the following assumptions<br />

• The flow was assumed to be isothermal<br />

• The flow was assumed to be incompressible<br />

• The flow was assumed unsteady.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

• Effects <strong>of</strong> gravity was accounted for to act in the negative z-direction<br />

• Multi phase simulations were carried out.<br />

• The pipe wall roughness was taken smooth<br />

• A non-slip boundary condition was imposed at the stationary walls, so that velocity at the wall is forced to be<br />

zero.<br />

The different model parameters have been defined as close as possible to the actual experimental<br />

conditions and Table 1 shows the selection <strong>of</strong> model parameters.<br />

Parameter selection<br />

Table 1 Selection <strong>of</strong> different simulation parameters<br />

Solver<br />

Formulation<br />

Time<br />

Space<br />

Velocity formulation<br />

Gradient option<br />

Multiphase<br />

Turbulent model<br />

Near-wall treatment<br />

k-ε multiphase model<br />

Segregated<br />

Implicit<br />

Un Steady<br />

3D<br />

Absolute<br />

Cell-based<br />

Eulerian/ Mixture<br />

Standard k-ε (2-equation)<br />

Standard wall function<br />

Per phase in Eulerian<br />

In the above simulation specifications, The Eulerian and mixture model is used in Fluent s<strong>of</strong>tware with standard<br />

equations. The discretization method called ‘Phase Coupled SIMPLE’ was selected for the pressure-velocity<br />

coupling while ‘First Order Upwind’ discretization method was used for other scalar parameters like momentum,<br />

volume fraction, turbulent kinetic energy etc. The simulations have been carried out for different test conditions<br />

in terms <strong>of</strong> solid loading ratio, superficial air flow velocity, and volumetric solid concentration and pressure drop<br />

values. Inlet boundary conditions such as inlet velocity, volume fraction <strong>of</strong> solid etc, have been defined<br />

according to the experimental parameters. Distribution <strong>of</strong> cross sectional velocity is reasonable to assume<br />

uniform at the bend inlet. At wall, no slip condition is assumed and the wall roughness constant was taken as 0.5.<br />

For the convenience <strong>of</strong> the simulations, spherical mono sized particles were assumed for all solid materials and<br />

with this assumption; particle mean diameters were used for the simulations. To define the boundary conditions<br />

at the inlet, the velocities <strong>of</strong> all the phases have to be given. The process <strong>of</strong> solving a multiphase system is<br />

inherently difficult, and usually one may encounter some stability or convergence problems. After each<br />

simulation, the velocity and pressure pr<strong>of</strong>iles and distribution <strong>of</strong> solid volume fractions <strong>of</strong> each phase were<br />

inspected. The variations <strong>of</strong> the above variables with the time were also examined according to the simulation<br />

results. Finally, pressure drops across the considered sections for different test conditions were calculated using<br />

simulation results and then compared with the experimental observations.<br />

Grid adaptation for y+<br />

It is essential to make sure that the depth <strong>of</strong> the wall-adjacent cells fall within the distance over which the loglaw<br />

is valid (30


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Grid independence test<br />

The grid independence tests were carried out by refining the initial grid for both type <strong>of</strong> grid geometry and<br />

appropriate number <strong>of</strong> cells present in the grid. This number was generated by applying the same cross-sectional<br />

meshes obtained from the optimum cross-sectional meshes <strong>of</strong> pipe for the single-phase flow There are 3001<strong>20</strong><br />

cells consists by horizontal to horizontal bend simulation grid by varying the number <strong>of</strong> cells for single phase<br />

flow and measured pressure drop for judging the optimum mesh sizes.<br />

Residual convergence<br />

The residual sum for each <strong>of</strong> the conserved variables is computed and stored. In the present simulations, the<br />

threshold values were set to a thousandth <strong>of</strong> the initial residual value <strong>of</strong> each variable. Fig. 3 shows the residuals<br />

for a baseline case for conveying cement.<br />

Fig. 3 A residual plot for bend simulation for pneumatic conveying through pipe line in horizontal plane,<br />

conveying cement at solid loading ratio.<br />

Boundary conditions<br />

At the inlet, velocity and concentrations <strong>of</strong> the phases were specified as estimated input parameters to match the<br />

experimental conditions <strong>of</strong> the tests. The inlet pressure was not specified and the outlet pressure was specified as<br />

an estimate <strong>of</strong> the experimental conditions. At the wall, the tangential and normal gas velocities were set to zero.<br />

The particle diameter and density were taken as a single value <strong>of</strong> 25 micron and 2500 kg/m 3 respectively and<br />

there was no mass transfer between the phases.<br />

CFD modeling results<br />

Three-dimensional concentration distributions and pressure drops are modeled using Eulerian two-phase and<br />

Mixture models for a 90 degree horizontal pipe bend having bend radius <strong>of</strong> 156 mm, pipe diameter <strong>of</strong> 52 mm<br />

(bend radius ratio R/r = 6) at different solids loading ratios (SLR; the ratio <strong>of</strong> solids to air mass flow rates) in the<br />

range <strong>of</strong> about 8 to 1<strong>19</strong> <strong>of</strong> cement (with mean particle diameter <strong>of</strong> 25 micron). The flow velocity was varied<br />

from 4.8 to 31 m/s. Modeling results are as given below.<br />

224


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Pressure drop<br />

Variation in pressure drop predictions by mixture model for conveying <strong>of</strong> cement at solid loading ratio is shown<br />

in Figs. 4 and 5. As expected, the pressure decreases along the flow constantly, where the effect <strong>of</strong> pipe bend on<br />

flow is absent. However, as the flow reaches near pipe bend, the decrease in pressure is not constant and it<br />

decreases rapidly in comparison to the horizontal pipeline. Further, the pressure changes across the pipe bend<br />

cross-section with increased pressure at outer wall <strong>of</strong> the pipe bend.<br />

The pressure gradient across the bend increases as the solid concentration or flow velocity increases. This<br />

increase in pressure gradient may be attributed to the increased interaction between particles at higher<br />

concentrations and flow velocities. The bend effect increases on downward side <strong>of</strong> the pipe as solid<br />

concentration increases as the larger pressure gradients take its effect to longer distances.<br />

Fig. 4 Three-dimensional pressure distribution pr<strong>of</strong>ile <strong>of</strong> pneumatic conveying pipe line in horizontal plane,<br />

conveying cement at solid loading ratio 1<strong>19</strong><br />

Fig. 5 Three-dimensional pressure distribution pr<strong>of</strong>ile <strong>of</strong> pneumatic conveying pipe line in horizontal plane,<br />

conveying cement at solid loading ratio 18<br />

225


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Concentration distribution<br />

Concentration pr<strong>of</strong>ile for solid loading ratio 1<strong>19</strong> <strong>of</strong> cement is shown in Fig. 6 exhibit typical bend effect. It is<br />

observed that in upstream side <strong>of</strong> bend flow behavior is similar to flow in straight pipe section, as the<br />

concentration <strong>of</strong> the flow is maximum towards bottom <strong>of</strong> the pipe, whereas effect <strong>of</strong> bend is clearly visible in the<br />

downstream <strong>of</strong> bend. The contour plots clearly show a high particle concentration at the long radius wall <strong>of</strong> the<br />

bend. In the vicinity <strong>of</strong> outlet, similar high particle concentration could be seen at the bottom area <strong>of</strong> the<br />

conveying pipe. This explains the behaviour <strong>of</strong> the solid particle inside the bend, specially, at the middle section<br />

<strong>of</strong> the bend where the solid particles are subjected to centrifugal forces and thrown towards the pipe wall. After<br />

fading away the centrifugal action, then, the particles are under the gravitational effect and tend to concentrate at<br />

the pipe bottom giving high solid volume fraction in the lower half <strong>of</strong> the pipe cross-section. The concentration<br />

distribution pr<strong>of</strong>ile slightly skewed towards the bottom wall as shown in Fig. 7<br />

Fig. 6 Three-dimensional concentration distribution pr<strong>of</strong>ile <strong>of</strong> pneumatic conveying pipe line in horizontal<br />

plane, conveying cement at solid loading ratio 1<strong>19</strong><br />

(a)<br />

(b)<br />

Fig. 7 Three-dimensional concentration distribution pr<strong>of</strong>ile <strong>of</strong> pneumatic conveying pipe line in horizontal plane<br />

at before bend (a) and (b) after bend, conveying cement at solid loading ratio 1<strong>19</strong><br />

226


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. Conclusions<br />

The ability <strong>of</strong> the FLUENT s<strong>of</strong>tware to predict the pressure drop across a 90 degree bend in a pneumatic<br />

conveying line transporting cement using standard input parameters is investigated. There is broad qualitative<br />

agreement in trends and flow patterns. For the high solids loading ratio (1<strong>20</strong>) the Eulerian solver and transient<br />

analysis was reasonably effective with the bend in the horizontal plane. At lower solids loading ratios the<br />

mixture model and steady-state analysis were more appropriate.<br />

References<br />

1. Mason, D.J. and Levy, A. (<strong>20</strong>01). A model for non-suspension gas-solids flow <strong>of</strong> fine powders in pipes.<br />

International Journal <strong>of</strong> Multiphase Flow, 27(3), 415-435.<br />

2. Levy, A. and Mason, D. J. (<strong>19</strong>98).The effect <strong>of</strong> a bend on the particle cross-section concentration and<br />

segregation in pneumatic conveying systems. Powder <strong>Technology</strong>, 98 (2), 95-103.<br />

3. Mason, D.J. Levy, A., Mooney, T.and Marjanovic, P. (<strong>19</strong>97). A comparison <strong>of</strong> analytical and numerical<br />

models with experimental data for gas-solid flow through a straight pipe at different inclinations. Powder<br />

<strong>Technology</strong>, 93(3), 253-260.<br />

4. Tsuji, Y., Tanaka, T. and Ishida, T. (<strong>19</strong>92). Lagrangian numerical simulation <strong>of</strong> plug flow <strong>of</strong> cohesionless<br />

particles in a horizontal pipe. Powder <strong>Technology</strong>, 71(3), 239-250.<br />

5. Xiang, J. and McGlinchey, D. (<strong>20</strong>04). Numerical simulation <strong>of</strong> particle motion in dense phase pneumatic<br />

conveying. Granular Matter, 6, 167-172.<br />

6. Mcglinchey, D., Cowell, A., Knight, E.A., Pugh, J.R., Mason, A. and Foster, B. (<strong>20</strong>07). Bend pressure<br />

drop predictions using the Euler-Euler model in dense phase pneumatic conveying. Particulate <strong>Science</strong><br />

and <strong>Technology</strong>, 25, 495-506.<br />

227


1 N.I.M.S. <strong>University</strong> Jaipur,<br />

2 <strong>YMCA</strong>UST Faridabad .<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

ELECTRONIC WASTE MANAGEMENT IN INDIA<br />

+91-947057<strong>19</strong>69,+91-844747<strong>19</strong>99.<br />

abhinavphd@gmail.com, sorabh012@gmail.com<br />

Abhinav Kumar Shrivastava 1 ,Sorabh 2<br />

ABSTRACT<br />

The electrical and electronic waste (e-waste) is one <strong>of</strong> the fastest growing waste streams in the world. The<br />

increasing “market penetration” in developing countries, “replacement market” in developed countries and<br />

“high obsolescence rate” make e-waste as one <strong>of</strong> the fastest growing waste streams. Environmental issues and<br />

trade associated with e-waste at local, transboundary and international level has driven many countries to<br />

introduce interventions.<br />

1. INTRODUCTION<br />

E-waste comprises <strong>of</strong> wastes generated from used electronic devices and house hold appliances which are not fit<br />

for their original intended use and are destined for recovery, recycling or disposal. Such wastes encompasses<br />

wide range <strong>of</strong> electrical and electronic devices such as computers, hand held cellular phones, personal stereos,<br />

including large household appliances such as refrigerators, air conditioners etc. E-wastes contain over 1000<br />

different substances many <strong>of</strong> which are toxic and potentially hazardous to environment and human health, if<br />

these are not handled in an environmentally sound manner.<br />

In accordance with the National Environmental Policy (NEP) and to address sustainable development concerns,<br />

there is a need to facilitate the recovery and/or reuse <strong>of</strong> useful materials from waste generated from a process<br />

and/or from the use <strong>of</strong> any material thereby, reducing the wastes destined for final disposal and to ensure the<br />

environmentally sound management <strong>of</strong> all materials. The NEP also encourages giving legal recognition and<br />

strengthening the informal sectors system for collection and recycling <strong>of</strong> various materials. In particular<br />

considering the high recyclable potential <strong>of</strong> e-waste such wastes should be subject to recycling in an<br />

environmentally sound manner.<br />

The growth <strong>of</strong> e-waste has significant economic and social impacts. The increase <strong>of</strong> electrical and electronic<br />

products, consumption rates and higher obsolescence rate leads to higher generation <strong>of</strong> e-waste. The increasing<br />

obsolescence rate <strong>of</strong> electronic products also adds to the huge import <strong>of</strong> used electronics products. The e-waste<br />

inventory based on this obsolescence rate in India for the year <strong>20</strong>05 has been estimated to be 146180.00 tonnes<br />

which is expected to exceed 8,00,000 tonnes by <strong>20</strong>12. There is no large scale organized e-waste recycling facility<br />

in India and there are two small e-waste dismantling facilities are functioning in Chennai and Bangalore, while<br />

most <strong>of</strong> the e-waste recycling units are operating in un-organized sector.<br />

The definitions in Hazardous Wastes (Management and Handling) Rules, <strong>19</strong>89 as amended in <strong>20</strong>03 include:<br />

(i) “Occupier” in relation to any factory or premises, means a person who has, control over the affairs <strong>of</strong> the<br />

factory or the premises an includes in relation <strong>of</strong> any substance, the person in possession <strong>of</strong> the substance;<br />

(ii) “Operator <strong>of</strong> facility” means a person who owns or operates a facility for collection, reception, treatment,<br />

storage or disposal <strong>of</strong> hazardous wastes;<br />

(iii) “Recycler” means an occupier who procures and processes hazardous materials for recovery;<br />

(iv) “Recycling” means reclamation and reprocessing <strong>of</strong> hazardous materials from a production process in an<br />

environmentally sound manner for the original purpose or for other purposes.<br />

(v) “Reuse” means hazardous materials that are used for the purpose for its original use or another use.<br />

(vi) “Registered recycler or re-refiner or reuser” means a recycler or re-refiner or reuser registered for<br />

reprocessing hazardous material with the Central Government in the Ministry <strong>of</strong> Environment and Forests or the<br />

Central Pollution Control Board, as the case may be, for recycling or reprocessing hazardous materials;<br />

228


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

(vii) “Recovery” means to any operation in the recycling activity wherein specific materials are recovered.<br />

REGULATORY REGIME FOR E-WASTE.<br />

The Hazardous Wastes (Management and Handling) Rules, <strong>20</strong>03.<br />

The Hazardous Waste (Management and handling) Rule, <strong>20</strong>03, defines “hazardous waste” as any waste which<br />

by reason <strong>of</strong> any <strong>of</strong> its physical, chemical, reactive, toxic, flammable, explosive or corrosive characteristics<br />

causes danger or likely to cause danger to health or environment, whether alone or when on contact with other<br />

wastes or substances, and shall include:<br />

Waste substances that are generated in the 36 processes indicated in column 2 <strong>of</strong> Schedule I and consist <strong>of</strong><br />

wholly or partly <strong>of</strong> the waste substances referred to in column 3 <strong>of</strong> same schedule.<br />

Waste substances that consist wholly or partly <strong>of</strong> substances indicated in five risks class (A,B,C,D,E) mentioned<br />

in Schedule 2, unless the concentration <strong>of</strong> substances is less than the limit indicated in the same Schedule.<br />

Waste substances that are indicated in Lists A and B <strong>of</strong> Schedule 3 (Part A) applicable only in cases <strong>of</strong> import<br />

and export <strong>of</strong> hazardous wastes in accordance with rules 12, 13 and 14 if they possess any <strong>of</strong> the hazardous<br />

characteristics listed in Part B <strong>of</strong> schedule 3.<br />

“Disposal” means deposit, treatment, recycling and recovery <strong>of</strong> any hazardous wastes. Important features <strong>of</strong><br />

Schedule 1, 2 and 3, which may cover E-waste, are given below.<br />

SCHEDULE 1<br />

Although, there is no direct reference <strong>of</strong> electronic waste in any column <strong>of</strong> Schedule 1 (which defines hazardous<br />

waste generated through different industrial processes), the “disposal process” <strong>of</strong> e-waste could be characterized<br />

as hazardous processes. The indicative list <strong>of</strong> these processes is given below.<br />

Secondary production and/ or use <strong>of</strong> Zinc<br />

Secondary production <strong>of</strong> copper<br />

Secondary production <strong>of</strong> lead<br />

Production and/ or use <strong>of</strong> cadmium and arsenic and their compounds<br />

Production <strong>of</strong> primary and secondary aluminum<br />

Production <strong>of</strong> iron and steel including other ferrous alloys (electric furnaces, steel rolling and finishing mills,<br />

coke oven and by product plan)<br />

Production or industrial use <strong>of</strong> materials made with oregano silicon compounds<br />

Electronic industry<br />

Waste treatment processes, e.g. incineration, distillation, separation and concentration techniques<br />

As per these regulations, once a waste product is classified as hazardous according to industrial process listed in<br />

Schedule 1, it is exempted from the concentration limit requirement set by Schedule 2 <strong>of</strong> Act, and is considered<br />

hazardous irrespective <strong>of</strong> its concentrations.<br />

SCHEDULE 2<br />

The Schedule 2 <strong>of</strong> the Hazardous Waste Management and Handling Rules <strong>20</strong>03, lists waste substances which<br />

should be considered hazardous unless their concentration is less than the limit indicated in the said Schedule.<br />

The various classes <strong>of</strong> substances listed in this Schedule relevant to E-waste are covered in Class A, B, C, D and<br />

E are given below. E-waste or its fractions coming broadly under Class A and B are given below.<br />

CLASS A: CONCENTRATION LIMIT: >= 50 MG/KG<br />

The indicative waste list, which could be part <strong>of</strong> E-waste or its fractions under this class are given below.<br />

Antimony and antimony compounds<br />

Beryllium and beryllium compounds<br />

Cadmium and cadmium compounds<br />

Chromium (VI) compounds<br />

229


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Mercury and mercury compounds<br />

Halogenated compounds <strong>of</strong> aromatic rings, e.g. polychlorinated biphenyls, polychloroteriphenyls and their<br />

derivatives<br />

Halogenated aromatic compounds<br />

CLASS B: CONCENTRATION LIMIT: >= 5,000 MG/KG<br />

The indicative waste list, which could be part <strong>of</strong> E-waste or its fractions under this class are given below.<br />

Cobalt compounds<br />

Copper compounds<br />

Lead and lead compounds<br />

Nickel compounds<br />

Inorganic tin compounds<br />

Vanadium compounds<br />

Tungsten compounds<br />

Silver compounds<br />

Halogenated aliphatic compounds<br />

Phenol and phenolic compounds<br />

Chlorine<br />

Bromine<br />

Halogen-containing compounds, which produce acidic vapors on contact with humid air or water<br />

SCHEDULE 3<br />

List <strong>of</strong> Hazardous Waste to be applicable only for imports and exports are mentioned in schedule 3. It define<br />

hazardous waste as “Wastes listed in lists ‘A ’ and ‘B ’ <strong>of</strong> part A <strong>of</strong> schedule 3 applicable only in case(s)<strong>of</strong><br />

export/import <strong>of</strong> hazardous wastes in accordance with rule 12, 13, and 14 only if they possess any <strong>of</strong> the<br />

hazardous characteristics in part B <strong>of</strong> said schedule”. This clause defines hazardous waste for the purpose <strong>of</strong><br />

import and export. It has divided hazardous waste into two parts, A and B. Part A <strong>of</strong> the schedule deals with two<br />

lists <strong>of</strong> waste to be applicable only for imports and exports purpose. Export and import <strong>of</strong> items listed in List A<br />

and B <strong>of</strong> part A are permitted only as raw materials for recycling or reuse.<br />

ELECTRONIC WASTE AND RELATED ITEMS LISTED IN PART A, LISTS OF<br />

WASTES APPLICABLE FOR IMPORT AND EXPORT<br />

Following are the electronic items being mentioned in list A:<br />

A1180- “Electrical and electronic assemblies or scraps containing components such as accumulators and other<br />

batteries included on list B, mercury-switches, glass from cathode ray tubes and other activated glass and PCBcapacitors,<br />

or contaminated with schedule 2 constituents (e.g. cadmium, mercury, lead, polychlorinated<br />

biphenyl)to an extent that they exhibit hazard characteristics indicated in part B <strong>of</strong> this schedule (see B1110)”.<br />

A1090 - Ashes from the incineration <strong>of</strong> insulated copper wire.<br />

A1150 - Precious metal ash from incineration <strong>of</strong> PCBs not included on list ‘B’<br />

A<strong>20</strong>10 - Glass waste from cathode ray tubes and other activated glass.<br />

A3180 -Wastes, substances and articles containing, consisting <strong>of</strong> or contaminated with polychlorinated biphenyls<br />

(PCB) and including any other poly brominates analogues <strong>of</strong> these compounds, at a concentration level <strong>of</strong> 50<br />

mg/kg or more.<br />

CASE STUDY:-<br />

MANUAL PRINTED CIRCUIT BOARD SEPARATION AND SOLDER RECOVERY<br />

The samples <strong>of</strong> solder collected in China and India in <strong>20</strong>04 and <strong>20</strong>05 respectively were very similar with<br />

compositions. These solders were the primarily alloy <strong>of</strong> lead (32.5%-36.5%) and tin (46.3% -49.56%) and a few<br />

other elements as antimony, bithmus, copper, silver and zinc which all were less than 1%.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The separation work was done at the “Beilin Area” <strong>of</strong> Guiyu Province in China, and only the removal <strong>of</strong><br />

components from circuit boards and recovery <strong>of</strong> metal solder was observed and so the samples collected from<br />

three workshops were analyzed for their metal content. On the other hand the samples collected from the Indian<br />

workshops were analyzed for the metal as well as the organic chemical treatment.<br />

The samples collected from India and China were containing high concentration <strong>of</strong> lead and tin as well as a range<br />

<strong>of</strong> other metals namely cadmium, copper, nickel, silver and zinc. But the other metals identified at Indian<br />

workshops in recycling were treated with environment friendly measures so that there may not be any damage to<br />

ecological balance as well as to reduce the “Occupational Safety Hazardous” for the personnel and workmen<br />

involved in the recycling processing <strong>of</strong> the E-Waste as elaborated in “Mechanical Recycling Process” as<br />

mentioned in the Figure “A”.<br />

ENVIRONMENTALLY SOUND MANAGEMENT FOR E-WASTE<br />

The Environmentally Sound Technologies for e-waste treatment involves complex treatment rationale is driven<br />

by “Material Flow”. This is compared with best available technology and E-waste treatment technology currently<br />

used in India.<br />

E-WASTE COMPOSITION AND RECYCLE POTENTIAL<br />

The consumption <strong>of</strong> e-waste and its recyclable potential is specific for each appliance. In order to handle this<br />

complexity, the parts/materials found in e-waste may be divided broadly into six categories as follows:<br />

Iron and steel, used for casings and frames<br />

Non-ferrous metals, especially copper used in cables, and aluminum<br />

Glass used for screens, windows<br />

Plastic used as casing, in cables and for circuit boards<br />

Electronic components<br />

Others (rubber, wood, ceramic etc.)<br />

ASSESSMENT OF HAZARDOUSNESS OF E-WASTE<br />

Guidelines for assessment <strong>of</strong> hazardousness <strong>of</strong> E-waste have been described in terms <strong>of</strong> basis, rational and<br />

approach and methodology.<br />

BASIS<br />

Assessment <strong>of</strong> hazardousness <strong>of</strong> E-waste or its component has been carried out based on Indian environmental<br />

regulations on hazardous waste, “The hazardous waste (Management and handling) Rules <strong>20</strong>03”.<br />

RATIONALE<br />

A number <strong>of</strong> global publications have mentioned that the scope <strong>of</strong> EU’s WEEE Directives and RoHS is narrow<br />

with respect to description <strong>of</strong> hazardousness <strong>of</strong> WEEE. Therefore, the Indian regulation has been taken as basis<br />

<strong>of</strong> determining hazardousness <strong>of</strong> E-waste, where Schedule 1 lists hazardous waste similar to ‘absolute” entry<br />

(irrespective <strong>of</strong> concentration) in “European Waste Catalogue” and Schedule 2 lists hazardous waste similar to “<br />

mirror” entry Greater than or equal to the threshold limit value in “European Waste Catalogue”.<br />

APPROACH AND METHODOLOGY<br />

The approach and methodology to determine the hazardousness has been described in following steps. This<br />

approach follows the basis used by “Department for Environment, Food and Natural Affairs”, Government <strong>of</strong><br />

United Kingdom to classify E-waste. However, it has been customized as per Indian situation.<br />

IDENTIFY THE E-WASTE CATEGORY ITEM<br />

The identification includes the E-waste items and its tentative year <strong>of</strong> manufacture. The year <strong>of</strong> manufacture<br />

gives a number <strong>of</strong> information ex. <strong>Technology</strong> and likely component present in the E-Waste.<br />

IDENTIFY THE E-WASTE COMPOSITION OR DETERMINE IT<br />

The identification <strong>of</strong> E-waste composition or its components can be determined by its year <strong>of</strong> manufacture.<br />

Ideally, industry association should maintain record <strong>of</strong> “Electrical and Electronic Equipment” composition,<br />

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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

which should be regularly updated to facilitate its treatment, once it becomes E-waste. In case <strong>of</strong> doubt, carry out<br />

testing <strong>of</strong> E-waste to find out the concentration.<br />

IDENTIFY POSSIBLE HAZARDOUS CONTENT IN E-WASTE<br />

If the E-waste has hazardous content, then refer schedule 1 and schedule 2 <strong>of</strong> “The hazardous waste<br />

(Management and handling) Rules <strong>20</strong>03”. A comparison <strong>of</strong> thresholds <strong>of</strong> hazardous substances followed in<br />

Europe with respect to that mentioned in Indian regulations, which may occur in E-waste.<br />

MECHANICAL RECYCLING PROCESS<br />

The first step is sorting process, where contaminated plastics such as laminated and/ or painted plastics are<br />

removed. The methods, which may be used for sorting, are grinding, cryogenic method, abrasion/ abrasive<br />

technique, solvent stripping method and high temperature aqueous based paint removal method. Any <strong>of</strong> the<br />

method is used for removal <strong>of</strong> paints and coating from waste plastics. The recycling process can be better<br />

explained from the following flow-chart (Figure-A).<br />

Figure-a : A Representative process flow diagram for the mechanical recycling <strong>of</strong> Post-consumer plastics (E-<br />

Waste).<br />

RECYCLING OPTIONS FOR MANAGING PLASTICS FROM END-OF-LIFE<br />

ELECTRONICS.<br />

Shear-shredder and hammer mills are generally used for size reduction and liberation <strong>of</strong> metals (coarse fraction)<br />

followed by granulation and milling for further size reduction. Granulators use a fixed screen or grate to control<br />

particle size, while hammer mills allow particles between hammers and the walls to exit the mills. Magnetic<br />

separators are used for ferrous metals separation, while eddy current separators are used for non ferrous metals<br />

separation. Air separation system is used to separate light fractions such as paper, labels and films. Resin<br />

identification can be carried out by using a number <strong>of</strong> techniques like turboelectric separator, high speed<br />

accelerator and X-ray fluorescence spectroscopy.<br />

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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

In hydro cyclones separation technique, plastic fractions are separated using density separation technique, which<br />

is made more effective by enhancing material wet ability. In turboelectric separation technique, plastic resins are<br />

new raw materials Pelletized.<br />

2. CONCLUSION:-<br />

IDENTIFY, WHETHER THE E-WASTE COMPONENT IS HAZARDOUS OR THE<br />

ENTIRE E-WASTE ITEM IS HAZARDOUS.<br />

The determination <strong>of</strong> hazardousness <strong>of</strong> E-waste from washing machine, refrigerator, computer monitor and<br />

personal computer. The contents <strong>of</strong> these E-waste items have been taken from the data <strong>of</strong> globally accepted data<br />

<strong>of</strong> industry associations.<br />

It can be concluded that E-waste generated from televisions, monitors and personal computers is hazardous. “The<br />

hazardous waste (Management and handling) Rules <strong>20</strong>03”. A comparison <strong>of</strong> the thresholds mentioned in Indian<br />

regulations with that <strong>of</strong> thresholds followed in Europe for E-waste shows that they are stricter. It can also be<br />

inferred that Ewaste/ components, which are hazardous in nature need to be covered under the purview <strong>of</strong> “The<br />

hazardous waste (Management and handling) Rules <strong>20</strong>03”, The Batteries (Management and Handling) Rules,<br />

<strong>20</strong>01, The Ozone Depleting Substances (Regulation and Control) Rules, <strong>20</strong>00.<br />

3. REFERENCES:<br />

1. Compendium on National WEEE Legislation United Nations <strong>University</strong>, United Nations Environment<br />

Program, <strong>20</strong>06.<br />

2. Implementation <strong>of</strong> the Waste Electrical and Electronic Equipment Directive in the EU, European Commission,<br />

Directorate General, Joint Research Centre, IPTS, <strong>20</strong>06.<br />

3. Information <strong>Technology</strong> (IT) and Telecommunication (Telecom) Waste in Canada –<strong>20</strong>03, Final Draft,<br />

Updated, Environment Canada, <strong>20</strong>03.<br />

4. IRGSSA (<strong>20</strong>04) Management, handling and practices <strong>of</strong> E-waste recycling in Delhi. IRGSSA, India.<br />

5. WEEE Directive (EU, <strong>20</strong>02a).<br />

LIST OF WEBSITES:<br />

1. www.usepa.gov/epaoswer/hazwaste/recycle/ecycling/index.htm<br />

2. www.defra.gov.uk/environment/waste/index.htm<br />

3. www.ec.gc.ca<br />

4. www.environment.gov.au<br />

5. http://ec.europa.eu/environment/waste/weee/index_en.htm<br />

6. www.ewasteguide.info<br />

7. www.basel.int<br />

8. www.unep.org<br />

9. http://www.unep.ch/ozone/index.shtml<br />

10. www.cpcb.nic.in/Hazardous%<strong>20</strong>Waste/default_Hazardous_Waste.html<br />

11. http://www.basel.int/industry/mppiwp/guid-info/index.html<br />

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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

ALTERNATIVES OF FREONS<br />

Praveen<br />

M.Tech student, <strong>YMCA</strong>UST,3 RD SEM, praveenchch@gmail.com<br />

ABSTRACT<br />

So both the chlorine and fluorine play role in the depletion <strong>of</strong> ozone layer .Chlor<strong>of</strong>luoro-carbons are responsible<br />

for the depletion <strong>of</strong> ozone layer. Hence all the CFCs like R11,R12,R113,R115,R502 are being phased out. So we<br />

need some alternatives. First alternative we found are HCFC.in this type <strong>of</strong> refregerants hydrogen is added to<br />

the CFCs . HCFCs are compounds containing carbon, hydrogen, chlorine and fluorine. The HCFCs have<br />

shorter atmospheric lifetimes than CFCs and deliver less reactive chlorine to the stratosphere where the "ozone<br />

layer" is found. . Because they still contain chlorine and have the potential to destroy stratospheric ozone, they<br />

are viewed only as temporary replacements for the CFCs.Ozone layer depletion by CFCs occurs by breakdown<br />

<strong>of</strong> chlorine atoms from refrigerants by UV radiation and reaction with ozone in stratosphere.Florine carry the<br />

chlorine atoms up to the stratosphereSecond alternatives we found are HFCs.Hydr<strong>of</strong>luorocarbons (HFCs) are<br />

compounds containing carbon, hydrogen, and fluorine. Because the HFCs contain no chlorine they do not<br />

directly affect stratospheric ozone. It has been postulated that extensive use <strong>of</strong> these chemicals in the future<br />

could contribute significantly to enhanced radiative atmospheric heating.The future replacement <strong>of</strong> CFCs as<br />

refrigerants areAmmonia in vapor compression systems, Carbon dioxide in vapour compression systems etc.<br />

1. INTRODUCTION<br />

A chlor<strong>of</strong>luorocarbon (CFC) is an organic compound that contains only carbon, chlorine, hydrogen and fluorine,<br />

produced as a volatile derivative <strong>of</strong> methane and ethane. They are also commonly known by the DuPont brand<br />

name Freon. The most common representative is dichlorodifluoromethane (R-12 or Freon-12). Many CFCs have<br />

been widely used as refrigerants, propellants (in aerosol applications), and solvents. The manufacture <strong>of</strong> such<br />

compounds has been phased out (and replaced with products such as R-410A) by the Montreal Protocol because<br />

they contribute to ozone depletion in the upper atmosphere.<br />

With the phased out<strong>of</strong> CFCs for the good <strong>of</strong> the ozone, decisions have to be made about replacing or converting<br />

existing refrigerants and refrigerant systems. There are three basic choices when deciding whether to repair or<br />

replace equipment containing refrigerants. The first option is to fix the equipment, recharging it with the original<br />

refrigerant, if it is available. Retr<strong>of</strong>itting should be considered if the original refrigerant has been phased out, like<br />

CFC-12. Many types <strong>of</strong> equipment can be retr<strong>of</strong>itted to use an alternative refrigerant. Retr<strong>of</strong>itted equipment<br />

typically has lower efficiency and less capacity than new equipment. The third choice is to replace the unit. This<br />

option has the highest initial cost, but in many cases may be the cheapest over the lifetime <strong>of</strong> the equipment,<br />

especially in vehicles, refrigerators, chillers, and central units. However, this may not be the case in industrial<br />

sized AC units due to the area over which the unit operates.<br />

Choosing between the options can be difficult. Economic and environmental factors play an important part in<br />

any decision, especially one that involves decreasing the amount <strong>of</strong> damage done to the ozone layer. Life-cycle<br />

cost analyses can help you select an economically practical option. Some <strong>of</strong> these life-cost analyses are presented<br />

below.<br />

The Montreal Protocol on Substances that Deplete the Ozone Layer (a protocol to the Vienna Convention for the<br />

Protection <strong>of</strong> the Ozone Layer) is an international treaty designed to protect the ozone layer by phasing out the<br />

production <strong>of</strong> numerous substances believed to be responsible for ozone depletion. The treaty was opened for<br />

signature on September 16, <strong>19</strong>87, and entered into force on January 1, <strong>19</strong>89, followed by a first meeting<br />

in Helsinki, May <strong>19</strong>89. Since then, it has undergone seven revisions, in <strong>19</strong>90 (London), <strong>19</strong>91 (Nairobi), <strong>19</strong>92<br />

(Copenhagen), <strong>19</strong>93 (Bangkok), <strong>19</strong>95 (Vienna), <strong>19</strong>97 (Montreal), and <strong>19</strong>99 (Beijing). It is believed that if the<br />

international agreement is adhered to, the ozone layer is expected to recover by <strong>20</strong>50. [1] Due to its widespread<br />

adoption and implementation it has been hailed as an example <strong>of</strong> exceptional international co-operation,<br />

with K<strong>of</strong>i Annan quoted as saying that "perhaps the single most successful international agreement to date has<br />

been the Montreal Protocol". [2] The two ozone treaties have been ratified by <strong>19</strong>7 states and the European<br />

Union [3] making them the most widely ratified treaties in United Nations history. [4]<br />

Chlor<strong>of</strong>luorocarbons (CFCs) Phase-out Management Plan<br />

The stated purpose <strong>of</strong> the treaty is that the signatory states "Recognizing that worldwide emissions <strong>of</strong> certain<br />

substances, including ST, can significantly deplete and otherwise modify the ozone layer in a manner that is<br />

likely to result in adverse effects on human health and the environment, ... Determined to protect the ozone layer<br />

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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

by taking precautionary measures to control equitably total global emissions <strong>of</strong> substances that deplete it, with<br />

the ultimate objective <strong>of</strong> their elimination on the basis <strong>of</strong> developments in scientific knowledge ...<br />

Acknowledging that special provision, including ST is required to meet the needs <strong>of</strong> developing countries..."shall<br />

accept a series <strong>of</strong> stepped limits on CFC use and production, including: from <strong>19</strong>91 to <strong>19</strong>92 its levels <strong>of</strong><br />

consumption and production <strong>of</strong> the controlled substances in Group I <strong>of</strong> Annex A do not exceed 150 percent <strong>of</strong> its<br />

calculated levels <strong>of</strong> production and consumption <strong>of</strong> those substances in <strong>19</strong>86;from <strong>19</strong>94 its calculated level <strong>of</strong><br />

consumption and production <strong>of</strong> the controlled substances in Group I <strong>of</strong> Annex A does not exceed, annually,<br />

twenty-five percent <strong>of</strong> its calculated level <strong>of</strong> consumption and production in <strong>19</strong>86.from <strong>19</strong>96 its calculated level<br />

<strong>of</strong> consumption and production <strong>of</strong> the controlled substances in Group I <strong>of</strong> Annex A does not exceed zero.<br />

There was a slower phase-out (to zero by <strong>20</strong>10) <strong>of</strong> other substances (halon 1211, 1301, 2402; CFCs 13, 111, 112,<br />

etc.) and some chemicals were given individual attention (Carbon tetrachloride 1,1,1-trichloroethane). The<br />

phasing-out <strong>of</strong> the less active HCFCs only began in <strong>19</strong>96 and will go on until a complete phasing-out is achieved<br />

by <strong>20</strong>30.<br />

Hydrochlor<strong>of</strong>luorocarbons (HCFCs) Phase-out Management Plan (HPMP)<br />

Under the Montreal Protocol on Substances that Deplete the Ozone Layer, especially Executive Committee<br />

(ExCom) 53/37 and ExCom 54/39, Parties to this Protocol agreed to set year <strong>20</strong>13 as the time to freeze the<br />

consumption and production <strong>of</strong> HCFCs. They also agreed to start reducing its consumption and production in<br />

<strong>20</strong>15. The time <strong>of</strong> freezing and reducing HCFCs is then known as <strong>20</strong>13/<strong>20</strong>15.<br />

The HCFCs are transitional CFCs replacements, used as refrigerants, solvents, blowing agents for plastic foam<br />

manufacture, and fire extinguishers. In term <strong>of</strong> Ozone Depleting Potential (ODP), in comparison to CFCs that<br />

have ODP 0.6 – 1.0, these HCFCs have less ODP, i.e. 0.01 – 0.5. Whereas in term <strong>of</strong> Global Warming<br />

Potential(GWP), in comparison to CFCs that have GWP 4,680 – 10,7<strong>20</strong>, HCFCs have less GWP, i.e. 76 – 2,270.<br />

There are a few exceptions for "essential uses", where no acceptable substitutes have been found (for example, in<br />

the metered dose inhalers commonly used to treat asthma and other respiratory problems [6] ) or Halon fire<br />

suppression systems used in submarines and aircraft (but not in general industry).<br />

The substances in Group I <strong>of</strong> Annex A are:<br />

CFCl 3 (CFC-11)<br />

CF 2 Cl 2 (CFC-12)<br />

C 2 F 3 Cl 3 (CFC-113)<br />

C 2 F 4 Cl 2 (CFC-114)<br />

C 2 F 5 Cl (CFC-115)<br />

The provisions <strong>of</strong> the Protocol include the requirement that the Parties to the Protocol base their future decisions<br />

on the current scientific, environmental, technical, and economic information that is assessed through panels<br />

drawn from the worldwide expert communities. To provide that input to the decision-making process, advances<br />

in understanding on these topics were assessed in <strong>19</strong>89, <strong>19</strong>91, <strong>19</strong>94, <strong>19</strong>98 and <strong>20</strong>02 in a series <strong>of</strong> reports<br />

entitled Scientific assessment <strong>of</strong> ozone depletion.<br />

Several reports have been published by various governmental and non-governmental organizations to present<br />

alternatives to the ozone depleting substances, since the substances have been used in various technical sectors,<br />

like in refrigerating, agriculture, energy production, and laboratory measurements [7][8][9]<br />

Ozone-depleting gas trends<br />

Since the Montreal Protocol came into effect, the atmospheric concentrations <strong>of</strong> the most important<br />

chlor<strong>of</strong>luorocarbons and related chlorinated hydrocarbons have either leveled <strong>of</strong>f or decreased. [14] Halon<br />

concentrations have continued to increase, as the halons presently stored in fire extinguishers are released, but<br />

their rate <strong>of</strong> increase has slowed and their abundances are expected to begin to decline by about <strong>20</strong><strong>20</strong>. Also, the<br />

concentration <strong>of</strong> the HCFCs increased drastically at least partly because for many uses CFCs (e.g. used as<br />

solvents or refrigerating agents) were substituted with HCFCs. While there have been reports <strong>of</strong> attempts by<br />

individuals to circumvent the ban, e.g. by smuggling CFCs from undeveloped to developed nations, the overall<br />

level <strong>of</strong> compliance has been high. In consequence, the Montreal Protocol has <strong>of</strong>ten been called the most<br />

successful international environmental agreement to date. In a <strong>20</strong>01 report, NASA found the ozone thinning over<br />

Antarctica had remained the same thickness for the previous three years, [15] however in <strong>20</strong>03 the ozone hole<br />

grew to its second largest size. [16] The most recent (<strong>20</strong>06) scientific evaluation <strong>of</strong> the effects <strong>of</strong> the Montreal<br />

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Protocol states, "The Montreal Protocol is working: There is clear evidence <strong>of</strong> a decrease in the atmospheric<br />

burden <strong>of</strong> ozone-depleting substances and some early signs <strong>of</strong> stratospheric ozone recovery." [17]<br />

Effect<br />

Unfortunately, the hydrochlor<strong>of</strong>luorocarbons, or HCFCs, and hydr<strong>of</strong>luorocarbons, or HFCs, are now thought to<br />

contribute to anthropogenic global warming. On a molecule-for-molecule basis, these compounds are up to<br />

10,000 times more potent greenhouse gases than carbon dioxide. The Montreal Protocol currently calls for a<br />

complete phase-out <strong>of</strong> HCFCs by <strong>20</strong>30, but does not place any restriction on HFCs. Since the CFCs themselves<br />

are equally powerful greenhouse gases, the mere substitution <strong>of</strong> HFCs for CFCs does not significantly increase<br />

the rate <strong>of</strong> anthropogenic global warming, but over time a steady increase in their use could increase the danger<br />

that human activity will change the climate. [18]<br />

Policy experts have advocated for increased efforts to link ozone protection efforts to climate protection<br />

efforts. [<strong>19</strong>][<strong>20</strong>][21] Policy decisions in one arena affect the costs and effectiveness <strong>of</strong> environmental improvements<br />

in the other.<br />

Benefits <strong>of</strong> the CFC Phase-out<br />

The CFC phase-out is already producing benefits for the environment, businesses, and individuals.<br />

First, it can protect the Ozone Layer. The chlor<strong>of</strong>luorocarbon (CFC) phase-out is an important turning point in<br />

the recovery <strong>of</strong> the ozone layer. Currently, we are experiencing depletion <strong>of</strong> approximately 5 percent at mid-<br />

latitudes, but if no action had been taken to limit CFCs, ozone depletion at mid-latitudes would eventually have<br />

reached <strong>20</strong> percent or more. Because <strong>of</strong> the phase-out, CFCs are no longer accumulating in the atmosphere at an<br />

accelerating rate. Scientists predict that maximum CFC levels will occur before the turn <strong>of</strong> the century. If<br />

international agreements are adhered to, the ozone layer is expected to recover around <strong>20</strong>50.<br />

Second, it can reduce Health Risks. The phase-out <strong>of</strong> CFCs is expected to have direct health benefits over the<br />

next century, including reduced incidence <strong>of</strong> skin cancer and cataracts, decreased risks to human immune<br />

systems, and increased protection <strong>of</strong> plant and animal life from excessive UV exposure. A United Nations<br />

Environment Programme (UNEP) study shows that a sustained 1 percent decrease in stratospheric ozone will<br />

result in about a 2 percent increase in the incidence <strong>of</strong> non-melanoma skin cancer, which can be fatal. With the<br />

successful phase-out <strong>of</strong> CFCs, however, EPA expects 295 million fewer cases <strong>of</strong> this form <strong>of</strong> skin cancer over<br />

the next century.<br />

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Third, it leads to New Technologies. The CFC phase-out prompted research into alternative methods for cleaning<br />

applications in electronic assemblies and precision parts. Users <strong>of</strong>ten found that the need for chemicals during<br />

cleaning processes was reduced or even eliminated, while maintaining product quality and reducing costs.<br />

Precision ball bearings, medical devices, and sophisticated electronics components are now being produced<br />

using aqueous cleaning. New "no-clean" technologies eliminate the cleaning process altogether for printed<br />

circuit boards.<br />

Fourth, it can save energy. The CFC phase-out provided an impetus to develop and invest in a new generation <strong>of</strong><br />

energy efficient air-conditioning and refrigeration equipment. Electric utilities have acknowledged this benefit<br />

by providing financial incentives for installing energy-efficient equipment. Aside from substantial lifetime<br />

energy and dollar savings, equipment upgrades also improve occupant comfort, system reliability, and operation<br />

and maintenance.<br />

Fifth, it can prevent pollution. The energy savings from equipment upgrades mean that less fossil fuels are<br />

burned at the power plant, leading to reduced emissions <strong>of</strong> air pollutants including carbon dioxide (CO2),<br />

nitrogen oxides (NOx), and sulfur dioxide (SO2). These pollutants are responsible for global warming and acid<br />

rain. By <strong>19</strong>98, chiller conversions and replacements are estimated to avoid emissions <strong>of</strong> 4 million tons <strong>of</strong> CO2,<br />

and 34,000 tons <strong>of</strong> SO2. The reduction in SO2 represents the annual emissions <strong>of</strong> one and a half-large coal fired<br />

power plant. (11)<br />

Mobile Systems<br />

CFC-12 was the dominant refrigerant in vehicle air-conditioning (AC) systems. In <strong>19</strong>94, all vehicle<br />

manufacturers switched to HFC-134a, a refrigerant that does not deplete the ozone layer. Most vehicles still<br />

using CFC-12 will be eliminated from the fleets as they are replaced. For remaining vehicles many different<br />

options exist. In particular, leaving a vehicle without air-conditioning may be a viable option when you consider<br />

the climate and the vehicle's type <strong>of</strong> duty. The best probable option while CFC-12 is still available at a<br />

reasonable price is to repair and recharge your vehicle's AC. The cost <strong>of</strong> a simple recharge exceeded $<strong>20</strong>0 in<br />

<strong>19</strong>98, so if the AC needs to be repaired or recharged again, CFC-12 may be unavailable or too expensive. The<br />

preferred alternative is to retr<strong>of</strong>it your AC system to HFC-134a. Such a retr<strong>of</strong>it entails changing several<br />

mechanical parts <strong>of</strong> the AC and the price starts at $250. Retr<strong>of</strong>itting to blend refrigerants is analogous to HFC-<br />

134a retr<strong>of</strong>its except blend retr<strong>of</strong>its are less efficient.<br />

A. The first generation replacement <strong>of</strong> CFCs as refrigerants (HCFC)<br />

HCFCs are compounds containing carbon, hydrogen, chlorine and fluorine. The HCFCs have shorter<br />

atmospheric lifetimes than CFCs and deliver less reactive chlorine to the stratosphere where the "ozone layer" is<br />

found. Consequently, it is expected that these chemicals will contribute much less to stratospheric ozone<br />

depletion than CFCs. Because they still contain chlorine and have the potential to destroy stratospheric ozone,<br />

they are viewed only as temporary replacements for the CFCs.<br />

HCFCs are less stable than CFCs because HCFC molecules contain carbon-hydrogen bonds. Hydrogen is<br />

attacked by the hydroxyl radical in the lower part <strong>of</strong> the atmosphere known as the troposphere. When HCFCs are<br />

oxidized in the troposphere, the chlorine released typically combines with other chemicals to form compounds<br />

that dissolve in water and ice and are removed from the atmosphere by precipitation. When HCFCs become<br />

destroyed in this way their chlorine does not reach the stratosphere and contribute to ozone destruction.<br />

A certain portion <strong>of</strong> HCFC molecules released to the atmosphere will reach the stratosphere and be destroyed<br />

there by photolysis (light-initiated decomposition). The chlorine released in the stratosphere can then participate<br />

in ozone depleting reactions as does chlorine liberated from the photolysis <strong>of</strong> CFCs. Because HCFCs are<br />

degraded significantly by two mechanisms in the atmosphere (as opposed to the CFCs which are destroyed<br />

almost exclusively by photolysis in the stratosphere), and because photolysis rates <strong>of</strong> HCFCs are generally<br />

slower than those for CFCs, proportionately less chlorine is released from HCFCs in the lower stratosphere when<br />

compared to CFCs. These properties explain why HCFCs are expected to deplete much less stratospheric ozone<br />

than equivalent amounts <strong>of</strong> CFCs. HCFCs phase-out dates the performances <strong>of</strong> three ozone-friendly<br />

Hydr<strong>of</strong>luorocarbon (HFC) refrigerants (R32, R134a and R152a) in a vapour compression refrigeration system<br />

were investigated experimentally and compared. The results obtained showed that R32 yielded undesirable<br />

characteristics, such as high pressure and low Coefficient <strong>of</strong> Performance (COP). Among the investigated<br />

refrigerants confirmed that R152a and R134a have approximately the same performance, but the best<br />

performance was obtained from the used <strong>of</strong> R152a in the system.<br />

237


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The COP <strong>of</strong> R152a obtained was higher than those <strong>of</strong> R134a and R32 by 2.5% and 14.7% respectively. Also,<br />

R152a <strong>of</strong>fers the best desirable environmental requirements; zero Ozone Depleting Potential (ODP) and very<br />

low Global Warming Potential (GWP).<br />

Chemical Name<br />

HCFC-21<br />

Dichlor<strong>of</strong>luoromethane<br />

HCFC-22<br />

Monochlorodifluoromethane<br />

HCFC-31<br />

Monochlor<strong>of</strong>luoromethane<br />

HCFC-121<br />

Tetrachlor<strong>of</strong>luoroethane<br />

HCFC-122<br />

Trichlorodifluoroethane<br />

HCFC-123<br />

Dichlorotrifluoroethane<br />

Table 2: HCFCs as alternative for CFCs<br />

Lifetime,<br />

in years<br />

ODP<br />

Ozone<br />

potential<br />

(CHFCl2)<br />

2.0 0.04<br />

(CHF2Cl)<br />

(CH2FCl)<br />

(C2HFCl4)<br />

(C2HF2Cl3)<br />

(C2HF3Cl2)<br />

depleting<br />

GWP<br />

Global<br />

potetial<br />

11.8 0.055 1700<br />

0.2<br />

0.01-0.04<br />

0.02-0.08<br />

1.4 0.02 93<br />

warming<br />

B. The second generation replacement <strong>of</strong> CFCs as refrigerants (HFCs)<br />

Table 3: HFCs as alternative for CFCs<br />

HFC-23 (CHF3) HFC-143a (CF3CH3 )<br />

HFC-32(CH2F2 )<br />

HFC-43-10mee (CF3CHF2CHFCH2FCF3)<br />

HFC-152a (CH3CHF2)<br />

HFC-227ea (CF3CHFCF3)<br />

HFC-125(CHF2CF3 ) HFC-236fa (CF3CH2CF3 )<br />

HFC-134a (CH2FCF3 )<br />

HFC-245fa (CF3CH2CHF2)<br />

Hydr<strong>of</strong>luorocarbons (HFCs) are compounds containing carbon, hydrogen, and fluorine. Certain chemicals within<br />

this class <strong>of</strong> compounds are viewed by industry and the scientific community as acceptable alternatives to CFCs<br />

and HCFCs on a long-term basis. Because the HFCs contain no chlorine they do not directly affect stratospheric<br />

ozone. Furthermore, mechanisms for ozone destruction involving fragments produced as HFCs are decomposed<br />

within the atmosphere (CF3 radicals) have been shown to be insignificant.All HFCs have an ozone depletion<br />

potential <strong>of</strong> 0.<br />

Like HCFCs, the HFCs contain hydrogen that is susceptible to attack by the hydroxyl radical. Oxidation <strong>of</strong> HFCs<br />

by the hydroxyl radical is believed to be the major destruction pathway for HFCs in atmosphere. Atmospheric<br />

lifetimes <strong>of</strong> the most commonly used HFCs (HFC-134a and HFC-152a) are limited to


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Ammonia<br />

invapor<br />

compression<br />

systems<br />

Carbon dioxide<br />

in vapour<br />

compression<br />

systems<br />

Yes, well tried<br />

and proven Higher Better Yes (chiller only)<br />

technology<br />

Yes<br />

principle)<br />

(in<br />

Porbably<br />

higher<br />

Currently<br />

lower<br />

No<br />

Strict compliance with safety<br />

standards & codes necessary to<br />

minimize toxicity hazards.<br />

More development needed to<br />

overcome poor efficiency.<br />

Might be best suited as a<br />

secondary refrigerant.<br />

2. CONCLUSION<br />

We now have some very good alternatives for the CFCs but still a great improvement is required in this way to<br />

achievethisLooking further down the road, carbon dioxide may someday replace today’s refrigerants. Though<br />

carbon dioxide is a "greenhouse gas" that may contribute to global warming, it is non-toxic, non-flammable,<br />

cheap and abundant. But to work as a refrigerant, carbon dioxide must be run at extremely high pressures - up to<br />

several thousand psi! As long as the gas is safely contained at high pressure, it works pretty well as a refrigerant.<br />

But such high pressures pose a potential danger to technicians who must ultimately work on such systems.<br />

Someday a perfect air conditioner may use no refrigerant whatsoever. Some time back, the Rovac Corporation in<br />

Rockledge, FL, announced it had developed a revolutionary A/C system that required no refrigerant at all, and<br />

used air itself as the working medium. The Rovac system used a "circulator" that was essentially an expander<br />

rather than a compressor. By expanding the volume <strong>of</strong> air, the drop in pressure produced a corresponding drop in<br />

temperature. The system supposedly required 35 to 40% less power than a refrigerant-based A/C system and<br />

provided equivalent cooling. Mitsubishi has licensed rights to the technology and was investigating it further.<br />

That was <strong>20</strong> years ago. We’re still waiting.<br />

Ten years ago, the Naval Postgraduate School in Monterey, CA, claimed it had developed a refrigeration process<br />

using an acoustic generator. Sound waves were used to create pressure changes that had a chilling effect. No<br />

word as to what ever happened to this technology.<br />

Although there are a lot <strong>of</strong> substitutes for CFCs as refrigerants, scientists continue to research new substitutes,<br />

which are less expensive, less destructive for ozone layer and more practical for industry. (16)<br />

3. REFERENCES<br />

1) Speth, J. G. <strong>20</strong>04. Red Sky at Morning: America and the Crisis <strong>of</strong> the Global Environment New Haven:<br />

Yale <strong>University</strong> Press, pp 95.<br />

2) The Ozone Hole-The Montreal Protocol on Substances that Deplete the Ozone Layer<br />

3) http://ozone.unep.org/Ratification_status<br />

4) UNEP press release: "South Sudan Joins Montreal Protocol and Commits to Phasing Out Ozone-Damaging<br />

Substances". Thomas Midgley, Jr and Albert L. Heene "Organic Fluorides as Refrigerants " I&EC, <strong>19</strong>37,<br />

22, 542-545.<br />

6) Exemption Information - The Ozone Secretariat Web Site<br />

7) Use <strong>of</strong> ozone depleting substances in laboratories. TemaNord<br />

<strong>20</strong>03:516. http://www.norden.org/pub/ebook/<strong>20</strong>03-516.<br />

8) The Technical and Economic Feasibility <strong>of</strong> Replacing Methyl Bromide in Developing Countries. Friends <strong>of</strong><br />

the Earth, Washington, 173 pp, <strong>19</strong>96<br />

9) Guidance on the DOE Facility Phaseout <strong>of</strong> Ozone-Depleting Substances.<br />

10) <strong>19</strong>95.http://homer.ornl.gov/nuclearsafety/nsea/oepa/guidance/ozone/phaseout.pdf<br />

11) http://www.epa.gov/ozone/geninfo/benefits.html (accessed 03/<strong>19</strong>/<strong>20</strong>03<br />

12) JasenNeese and Steve OravetzReplacing chlor<strong>of</strong>luorocarbon refrigerants U.S. Dept. <strong>of</strong> Agriculture, Forest<br />

13) Service, <strong>Technology</strong> & Development Program: Missoula, Mont., <strong>19</strong>98.<br />

14) Protection <strong>of</strong> the ozone layer, U.S. Environmental protection Agency: Washington, D.C., <strong>19</strong>95<br />

239


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

WASTE TO ENERGY: USING MSW OF KATRA TOWN FOR<br />

ELECTRICITY GENERATION<br />

Prabhat Shankar 1 Navdeep Malhotra 2 Sona Rani 3 Munish Kohli 4<br />

1 Student ,SME,SMVDU,<br />

2 Pr<strong>of</strong>. <strong>YMCA</strong>UST,<br />

3 .Asstt. Pr<strong>of</strong>. UIET, KU,<br />

4 Student SMVDU<br />

prabhat172@gmail.com<br />

Abstract<br />

India’s energy demands have increased very rapidly with the ever increasing population. The process <strong>of</strong><br />

urbanization and industrialization also add to this demand. Movement <strong>of</strong> India’s growth and economy in the last<br />

30 years averaging growth <strong>of</strong> 7% per year since <strong>20</strong>00. Today India rank forth in world energy consumption. The<br />

IEPR report has estimated by <strong>20</strong>30 energy requirement would go high by 5-6 % <strong>of</strong> current level. There is deficit<br />

in energy production and is equivalent to 16.8% <strong>of</strong> its peak demand as recorded on June <strong>20</strong>11. For sustaining<br />

the growth India is presently recording this gap to be narrowed. So an urgent challenge for mankind to develop<br />

low cost, non polluting energy production technology. Another problem <strong>of</strong> India is rising population and the<br />

waste generated by them. With the rate <strong>of</strong> urbanization 2.8% annual rate <strong>of</strong> change waste generation is only<br />

going to rise. Overwhelming 90% <strong>of</strong> waste produced in India is disposed in land filling leading to innumerable<br />

health and environmental hazards. This report aims to address both aforesaid issues taking case study <strong>of</strong> Katra<br />

town. Katra has a high floating population that will touch 10.5 million footfalls by the end <strong>of</strong> December <strong>20</strong>12.<br />

Report is focussing on converting “waste to energy” and need for better management <strong>of</strong> waste generated.<br />

1. INTRODUCTION<br />

Municipal Solid Waste is described as a stream <strong>of</strong> solid waste which is generated in urban areas from household,<br />

commercial establishments, industries and institutes. It does not however include biomedical waste, hazardous or<br />

radioactive waste. Municipal Solid Waste (MSW) is largely managed by disposal in landfill sites. Municipal<br />

Solid Waste contains organic and inorganic matter. Organic fraction can be recovered for gainful utilization<br />

through adoption <strong>of</strong> suitable waste processing technologies. When organic part <strong>of</strong> MSW is combusted, Waste -to<br />

- Energy technology is used in more or less the same way as fossil fuels are used in direct combustion process.<br />

Burning <strong>of</strong> MSW generates energy and the overall process results in reduction <strong>of</strong> 60% - 80% volume <strong>of</strong> waste.<br />

Considering the present status <strong>of</strong> MSW generation and non availability <strong>of</strong> landfill sites, Municipal solid waste<br />

management and its disposal has assumed a major environment challenge over the past few years. Past trends<br />

show that waste generation rates are increasing by 3-4 % per annum and the waste is likely to increase to 18,000<br />

tons per day by the year <strong>20</strong>21<br />

MUNICIPAL WASTE TO ELECTRICITY<br />

Municipal waste to electricity may very well be the power source for the future. There are many benefits which<br />

make municipal waste to electricity ideal for large scale use across the country and world As fossil fuels become<br />

more expensive and scarce, alternative energy sources like municipal waste to electricity will be utilized much<br />

more frequently. What is municipal waste to electricity, and why do many consider this process the future <strong>of</strong> the<br />

power industry This process takes municipal waste, which is simply household and business or commercial<br />

garbage, and uses it to generate electricity following a certain process. Garbage is something that will never run<br />

out, and tons <strong>of</strong> this waste is taken to landfills every single day. Many <strong>of</strong> the landfills and garbage dumps around<br />

the United States and the world are closed because the facilities are completely full, and it can take years or even<br />

decades for this waste to degrade and make more space available. Municipal waste to electricity can resolve two<br />

problems at the same time, the abundance <strong>of</strong> trash that is generated on a daily basis and which pollutes the earth,<br />

and the need for more environmentally friendly electricity generation. In this process, garbage is collected, taken<br />

to the facility, and incinerated. The heat which is generated is used to create steam, and this steam powers<br />

turbines that generate electricity. This process <strong>of</strong>fers many benefits which make it a top contender when it comes<br />

to meeting future electricity needs, and many energy experts believe that this source is the one which will be<br />

used to supply much <strong>of</strong> the electricity in the future. Municipal waste to electricity facilities and programs can be<br />

beneficial in many ways, and have many advantages over other renewable alternative energy sources. It is these<br />

numerous benefits and very few disadvantages that make this method such a leader in the energy and waste<br />

sectors. With municipal waste to electricity programs, there is no need to transport either for long distances. The<br />

local communities where these plants are situated will benefit, instead <strong>of</strong> a foreign company or royal family. The<br />

240


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

waste which is picked up from area companies and residences will be taken to the local processing plant, and this<br />

is where these same homes and businesses will get electricity from as well. There are far less emissions,<br />

including greenhouse gases and particle pollution, so the air and environment stay cleaner and suffer less damage.<br />

This will also help decrease the effect on global warming, because less carbon is released. The local economy<br />

benefits from the commerce, employment, and taxes that the company provides as well. These power plants<br />

usually practice recycling whenever possible as well, lowering their impact on the planet even more. The<br />

municipal waste to electricity process can also provide by products which are useful or pr<strong>of</strong>itable. This includes<br />

the ash left after the incineration process, among others. In addition, the source <strong>of</strong> the electricity is even better<br />

than free, because almost every home and business pays a fee for garbage collection. This means that the waste<br />

to electricity power plant not only sells the electricity generated back to area consumers, but can also generate<br />

revenue for accepting garbage, which is needed to provide the power. The materials required cost nothing, and<br />

actually make a pr<strong>of</strong>it for the plant. Because this power generation process addresses more than one need for the<br />

community, it is the most popular and viable solution to end foreign oil dependence and provide future energy<br />

needs, while keeping the local community clean and waste free. There are other solutions being considered, such<br />

as solar and wind energy as well as many others, but none <strong>of</strong> the other available technologies can <strong>of</strong>fer the same<br />

advantages that municipal waste to electricity can. This makes this technology and electricity generation process<br />

the best choice and most effective option when it comes to energy in the future. Relying on fossil fuels is no<br />

longer an option for the world, or the future. Fig. 1 shows the waste management hierarchy<br />

.<br />

Fig. 1: Waste Management Hierarchy<br />

Municipal solid waste to energy, also known as electricity production from solid municipal waste, may<br />

<strong>of</strong>fer one <strong>of</strong> the largest domestic opportunities for an alternative and renewable energy source that is good for the<br />

environment and the population at the same time. Tons <strong>of</strong> solid municipal waste is created every day in katra,<br />

and this can become a source <strong>of</strong> problems or a source <strong>of</strong> energy. The typical way that municipal solid waste<br />

management used to be done was by dumping all the waste into landfills, and letting them slowly decompose<br />

and reduce. This causes several problems, including greenhouse gases being released by the decomposing<br />

material, and the possibility <strong>of</strong> leachate that can enter the ground water with harmful contaminants. In addition,<br />

many landfills across the country are becoming full, and cannot hold any more solid municipal waste. Municipal<br />

solid waste to energy programs can help eliminate landfill crowding, and the process is eco friendly without any<br />

dangerous chemicals, toxins, or pollution. The process creates steam, which then is used to power a steam driven<br />

turbine engine that generates electricity for use in your home. This means garbage, also known as municipal<br />

solid waste may leave your home and become the electricity that flows back in it.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig. 2: Process Flow Chart<br />

The flow chart depicting conversion from waste to energy is shown in Fig. 2. Municipal solid waste to energy<br />

power plants can use one <strong>of</strong> four main types <strong>of</strong> technology, and these are refuse derived fuel, mass burn,<br />

pyrolysis, and modular controlled air. These plants are intended to burn municipal solid waste around the clock,<br />

and can be extremely efficient. One ton <strong>of</strong> municipal solid waste can provide five to six hundred hours <strong>of</strong> light or<br />

other electrical needs to your home. Since America makes millions <strong>of</strong> tons <strong>of</strong> the stuff, it is not hard to see the<br />

unlimited possibilities. Refuse derived fuel municipal solid waste to energy power plants, also called RDF<br />

facilities, have a processing area where recyclable products are taken out <strong>of</strong> the waste stream and used for the<br />

boiler, to create the heat. Fig. 3 shows the RDF processing system design. These plants can eliminate almost<br />

fourteen hundred tons <strong>of</strong> municipal solid waste each day, which takes a lot <strong>of</strong> pressure <strong>of</strong>f the landfills and the<br />

environment. Municipal solid waste to energy facilities may also use the mass burn technology. In this process,<br />

mixed municipal solid waste is dumped into the boilers with no preparation or sorting.<br />

Fig. 3: RDF Processing System Design<br />

The third type <strong>of</strong> electricity from municipal solid waste technology is the modular controlled air incineration<br />

system. These power plants can only utilize around fifty tons <strong>of</strong> municipal solid waste per day, and use two<br />

different combustion processes. The first chamber does not completely burn the waste, and creates a gas that is<br />

used in the second combustion chamber. These waste to energy plants are not very efficient, and cannot create<br />

electricity for resale to the utility companies. Pyrolysis is the fourth technology used in some methods <strong>of</strong><br />

municipal solid waste management. This process uses a chamber that has no oxygen and a high temperature to<br />

decompose wastes that are organic. When Pyrolysis and gasification occur together, the process is more efficient<br />

and cost effective.<br />

150<br />

100<br />

50<br />

0<br />

Total Waste Generation<br />

(million tonnes)<br />

<strong>19</strong>47<br />

<strong>19</strong>97<br />

<strong>20</strong>05<br />

<strong>20</strong>10<br />

<strong>20</strong>15<br />

<strong>20</strong><strong>20</strong><br />

Fig.4: Waste Generation(Source: TIFAC & DST, Govt. Of India)<br />

242


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Electricity production from municipal solid waste can be very efficient, depending on the method that is used.<br />

The level <strong>of</strong> carbon or greenhouse gas emissions and environmental friendliness will also depend on the<br />

processing method used to generate the electricity. Generating electricity from municipal solid waste, which you<br />

discard every day, can be a terrific way to get the energy the world needs, without putting any more strain or<br />

pollution on it. Fig. 4 shows the total waste generation in (million tonnes)<br />

KATRA CITY:<br />

The small city <strong>of</strong> Katra is situated in the foot <strong>of</strong> the Trikuta hills in the state <strong>of</strong> Jammu and Kashmir. On these<br />

Trikuta hills is situated the holy temple <strong>of</strong> Vaishno Devi. Table 1shows the number <strong>of</strong> pilgrims visiting the<br />

shrine.<br />

Year<br />

<strong>20</strong>02 44.32<br />

<strong>20</strong>03 54<br />

<strong>20</strong>04 61<br />

<strong>20</strong>05 62.52<br />

<strong>20</strong>06 69.5<br />

<strong>20</strong>07 74.17<br />

<strong>20</strong>08 67.92<br />

<strong>20</strong>09 82.35<br />

<strong>20</strong>10 90.67<br />

<strong>20</strong>11 101.15<br />

No. <strong>of</strong> Pilgrims (In<br />

Lakhs)<br />

Table 1: Pilgrim statistics <strong>of</strong> Shri Mata Vaishno<br />

Devi from <strong>20</strong>02 to <strong>20</strong>11 (Courtesy: Shrine Board)<br />

This year till Aug. <strong>20</strong>12, no. <strong>of</strong> Pilgrims has crossed 73.67 lakh. The composition <strong>of</strong> MSW <strong>of</strong> Katra Town is<br />

shown in fig. 5.<br />

Fig. 5: Chart <strong>of</strong> MSW <strong>of</strong> Katra town<br />

Land area:<br />

MSW processing capacity<br />

Power generation capacity<br />

Water Requirement:<br />

Wastewater Generation ~<br />

Source <strong>of</strong> water:<br />

5.728 acres or 23180.22 sq.m<br />

1300 TPD<br />

10 MW<br />

471 m 3 /day<br />

172 m 3 /day<br />

Kondli sewage treatment plant<br />

243


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 2: Solid waste generation and power generation potential <strong>of</strong> Katra.(Courtesy: MSW Dep. Katra)<br />

Energy in Mega Joule<br />

MSW Per day available per day<br />

Katra Town 37.98 529.52<br />

Yatra Track 7.68 109.08<br />

Total 45.66 638.60<br />

Table 3: Projected solid waste generation and power generation potential<br />

Period Projected MSW Potential for Power<br />

Generation (TPD) Generation MW<br />

<strong>20</strong>12 215000 3650<br />

<strong>20</strong>17 304000 5<strong>20</strong>0<br />

The table no. 2 shows the solid waste and generation potential <strong>of</strong> Katra and table no. 3 shows the the projected<br />

figure <strong>of</strong> solid waste generation and power potential <strong>of</strong> Katra town for the next five year .<br />

The objective <strong>of</strong> the project is to create a sustainable metropolitan municipal solid waste management system<br />

that supports GHG emission reduction. The targets <strong>of</strong> the project are as follows:<br />

a. Reduction <strong>of</strong> MSW;<br />

b. Increase <strong>of</strong> value added refuse;<br />

c. Reduction <strong>of</strong> environmental and social problems at the<br />

disposal site;<br />

d. Utilisation <strong>of</strong> MSW to generate energy<br />

e. Improvement <strong>of</strong> MSW management services.<br />

Benefits <strong>of</strong> the Waste to Energy Project<br />

a. Reduction <strong>of</strong> environment pollution (in rivers, sea and ground caused by waste disposal and air<br />

pollution from open burning <strong>of</strong> waste).<br />

b. Overcome <strong>of</strong> social issues occurring from illegal waste disposal (open dumping).<br />

c. Conversion <strong>of</strong> non reusable waste into combustible gases for electricity generation, for better economic<br />

benefits.<br />

d. Utilization <strong>of</strong> municipal solid waste leading to<br />

reduction <strong>of</strong> the use <strong>of</strong> fossil fuel.<br />

e. Reduction <strong>of</strong> GHG emissions.<br />

f. Cleaner environment for better public health (odour,<br />

seeping <strong>of</strong> contaminated or polluted water, potential<br />

spreading <strong>of</strong> disease).<br />

g. Creation <strong>of</strong> job opportunities.<br />

Life-cycle-based assessments <strong>of</strong> the major environmental impacts (or sustainability indicators) <strong>of</strong> MSW have<br />

shown the positive benefits to be gained from MSW energy recovery.<br />

These gains are in the form <strong>of</strong>:<br />

a. Reduction <strong>of</strong> greenhouse gas emissions;<br />

b. Reduction <strong>of</strong> acid gas emissions;<br />

c. Reduction in depletion <strong>of</strong> natural resources;<br />

d. Reduction <strong>of</strong> impact on water (leaching); and<br />

e. Reduction <strong>of</strong> land contamination.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. Conclusions<br />

In view <strong>of</strong> the above and realizing the potential <strong>of</strong> energy recovery from waste, technological options for waste<br />

disposal and treatment have been recommended for Katra.<br />

The project will create a sustainable metropolitan municipal solid waste management system that supports GHG<br />

emission reduction and along with this generation <strong>of</strong> electricity by the waste will lead to another boon for the<br />

project.<br />

3. References<br />

[1] Municipal Solid Waste Disposal and Pollution Control <strong>Technology</strong> Policy established [<strong>20</strong>00] No. 1<strong>20</strong>.<br />

[2] LU Ying-Fang, Tian Jin-xin, SUN Xiang-Jun. Part <strong>of</strong> the National Urban Solid Waste Management Review.<br />

Construction Economics, <strong>20</strong>02, (5): 39 ~ 41.<br />

[3] Williams, P. (<strong>19</strong>98) Waste Treatment and Disposal. John Wiley and Sons, Chichester.<br />

[4] Maa vaishnodevi website<br />

[5] Ministry <strong>of</strong> renewable energy.<br />

245


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

PATH SYNTHESIS OF 4-BAR LINKAGES WITH JOINT<br />

CLEARANCES USING DE ALGORITHM<br />

Ruby Mishra 1* , T.K.Naskar 2 and Sanjib Acharya 2<br />

1 School <strong>of</strong> Mechanical Engineering, KIIT <strong>University</strong>, BBSR- 751 024, India<br />

2 Mechanical Engineering Department, Jadavpur <strong>University</strong>, Kolkata-700032, India<br />

1* rbm_mis@rediffmail.com<br />

Abstract<br />

This paper presents synthesis <strong>of</strong> linkages with joint clearances to generate a desired coupler curve. Link lengths<br />

are determined with an objective <strong>of</strong> minimizing error between desired curve and generated curve. Joint<br />

Clearances are treated as a virtual link. Deferential evaluation (DE) algorithm is used to find link parameters<br />

for minimizing error between desired and actual path due to clearances at joints connecting coupler and<br />

follower.<br />

Key words: Linkage synthesis, Joint clearance, Differential evaluation<br />

1. Introduction<br />

Linkages with revolute joints are widely used in machines to ensure their functions. Links exert various forces<br />

through joints to each other. Without considering clearance we assume the linkage is rigid joint but when<br />

clearance is assumed in joints, the resulting linkage is called flexible linkage. A number <strong>of</strong> works are reported<br />

in journals on flexible linkages and modeling <strong>of</strong> joint clearance. The initial framework for the study <strong>of</strong> planar<br />

flexible link mechanisms has been provided by Burns and Crossley [1] in their investigation <strong>of</strong> the structural<br />

permutations <strong>of</strong> flexible link 4-bar chains having revolute pairs. This led to the development <strong>of</strong> techniques for<br />

the dimensional synthesis <strong>of</strong> devices that satisfied specific motion requirements by undergoing large elastic<br />

deformations. Boronkay and Mei [2] analyzed linkages whose pivots were replaced by flexible joints.<br />

Dubowsky [3] investigated the effects <strong>of</strong> joint clearance in a slider crank mechanism considering impact model.<br />

T. Furuhashi, N. Morita and M. Matsuura [4-5] determined directions <strong>of</strong> joint clearances by assuming<br />

continuous contact in revolute joints with clearance and using Lagrange function. Mallik and Dhande [6]<br />

introduced a stochastic model <strong>of</strong> the four-bar, path-generating linkage with tolerance and clearance to analyze<br />

the mechanical error in the path <strong>of</strong> a coupler point. Tolerances and clearances were assumed to be random<br />

variables.<br />

Ting et al [7] presented an approach to identify position and direction errors due to the joint clearance <strong>of</strong><br />

linkages and manipulators. Joint clearance was modeled like a small link with length equals to one half <strong>of</strong> the<br />

clearance. A geometrical model was used in their method to assess the output position or direction variation, to<br />

predict the limit <strong>of</strong> position uncertainty and to determine the maximum clearance. Schwab et al [8] studied<br />

dynamic response <strong>of</strong> mechanisms and machines affected by clearance in revolute joint and a comparison was<br />

made between several continuous contact force models and an impact model. Tsai and Lai [9] performed<br />

position analysis <strong>of</strong> a planar 4-bar mechanism with joint clearance by using loop-closure equations. Clearance<br />

was treated as a virtual link in the work. Flores and Ambrosio et al [10] performed dynamic analysis <strong>of</strong><br />

mechanical systems considering realistic joint characteristics like joints with clearance and lubrication. The<br />

work analyzed contact impact forces <strong>of</strong> the kinematics and dynamic system. The joint clearance was modeled as<br />

a contact pair with dry contact as well as lubrication. For the lubricated case, the theory <strong>of</strong> hydrodynamic<br />

journal–bearings was used to compute the forces generated by lubrication action. Tsai and Lai [11] used<br />

equivalent kinematical pair in multi-loop linkage to model the motion freedoms obtained from joint clearances.<br />

In the paper GA approach was used to determine the direction <strong>of</strong> joint clearance relative to input link <strong>of</strong> a 4-bar<br />

linkage.<br />

In this paper we have designed the link lengths without and after considering clearances in the joints connecting<br />

input and output links with coupler and minimize the error between the designed curve and the actual curve. The<br />

effect <strong>of</strong> joint clearance is studied in connection with path generation by linkages. The joint clearance is<br />

considered as a mass less virtual link. An objective function is defined and parametric relations between input<br />

variable and direction <strong>of</strong> joint clearance are considered as the constraints for solving nonlinear differential<br />

equation by using differential evaluation.<br />

246


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. Theoretical analysis<br />

2.1. Vector loop analysis <strong>of</strong> 4R linkage<br />

Fig.1 shows the 4-bar linkage with vector loop. There are 10 independent variables, L1 , L2,<br />

L3<br />

, L4,<br />

L5<br />

, β , θ<br />

2,<br />

θ1,<br />

L0,<br />

L6<br />

.<br />

L<br />

Where 5<br />

and β L5<br />

are two parameters to locate the coupler point. the distance from a convenient reference<br />

point, and the angle that the line AP makes with the line <strong>of</strong> centre <strong>of</strong> the coupler AB.<br />

The loop closure equation is:<br />

L + L + L + L 0<br />

(1)<br />

1 2 3 4 =<br />

Using Euler equivalence Eq. (1) becomes:<br />

Fig.1. 4-bar Linkage: Vector Loop and Variables<br />

iθ1<br />

iθ<br />

2<br />

iθ<br />

3<br />

iθ<br />

4<br />

L e + L e + L e + L e 0<br />

(2)<br />

1 2<br />

3<br />

4 =<br />

The coordinates <strong>of</strong> coupler C, in the reference frame OXY, are,<br />

P X = L 2 cos θ 2 + AP cos ( θ 3 + β )<br />

(3)<br />

P Y<br />

= L<br />

2<br />

sin θ<br />

2<br />

+ AP sin ( θ<br />

3<br />

+ β )<br />

(4)<br />

Eqs. (3) and (4) are used in Eqs. (A1) and (A2) to develop the first part <strong>of</strong> the goal function.<br />

Fig.1.shows the variables <strong>of</strong> the 4R linkage.<br />

2.2. Optimization Techniques<br />

When the objective function is nonlinear and non-differentiable, direct search approaches are the methods <strong>of</strong><br />

choice. The best known <strong>of</strong> these are the algorithm by Nelder and Mead, genetic algorithms, by Hook and Jeeves,<br />

evolutionary algorithms. Here we have used evolutionary algorithm.<br />

Users generally require that a practical optimization technique should fulfill three requirements. First, the<br />

method should find the global minimum, regardless <strong>of</strong> the initial system parameter values. Second, convergence<br />

should be fast. Third, the program should have a minimum number <strong>of</strong> control parameters so that it will be easy<br />

to use. The optimization method presented here i.e. the DE possesses all the above mentioned properties.<br />

The main steps <strong>of</strong> DE algorithm are: Initialization, Evaluation, Repeat, Mutation, Recombination, Evaluation,<br />

Selection, (Until termination criteria are met).<br />

In DE an optimization task consisting <strong>of</strong> ‘D’ parameters can be represented by a ‘D’ dimensional vector; a<br />

population <strong>of</strong> ‘NP’ solution vectors is randomly created at the start; this population is successfully improved by<br />

applying mutation, crossover and selection operators.<br />

2.3. The Objective Function<br />

The objective function is the sum <strong>of</strong> two terms. The first part computes the position error (also called the<br />

structural error) as the sum <strong>of</strong> squares <strong>of</strong> the Euclidian distances between each desired points along the coupler<br />

247


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

curve i i<br />

( Px , Py ) that has to be traced by the mechanism and the corresponding generated points i i<br />

( Px , Py ) by the<br />

d<br />

d<br />

designed mechanism. The desired points are a set <strong>of</strong> target points along the coupler curve indicated by the<br />

designer and should be met by the coupler point <strong>of</strong> the mechanism and the generated curve is the curve that is<br />

actually obtained by the coupler point <strong>of</strong> the designed mechanism. For minimizing the error between desired and<br />

generated curves, the objective function is given by<br />

1<br />

Minimize F ( x)<br />

= ⎡<br />

N<br />

∑ ⎢⎣<br />

subject to h<br />

j<br />

( x)<br />

≤ 0, x ≤ x ≤ x ,<br />

where N = number <strong>of</strong> precision po int s<br />

l<br />

N<br />

i=<br />

1<br />

i i 2 i i<br />

( Px − Px ) + ( Py − Py )<br />

j<br />

d<br />

u<br />

g<br />

d<br />

2<br />

g<br />

⎤<br />

⎥⎦<br />

The inequality constraints ( h j<br />

( x)<br />

) consist <strong>of</strong> conditions <strong>of</strong> Grash<strong>of</strong>’s rule that specifies crank rocker situation.<br />

x l and x u are respectively the lower and upper bounds <strong>of</strong> the design variables. They consist <strong>of</strong> link lengths L i<br />

,<br />

i i<br />

( Px , Py ) and the structural angle, the angle that the line AP AB<br />

makes with the line <strong>of</strong> centre <strong>of</strong> the coupler<br />

d<br />

d<br />

to obtain the co-ordinates <strong>of</strong> the generated positions <strong>of</strong> the coupler point displacement analysis<br />

as seen in Fig. 1<br />

is essential.<br />

The successful application <strong>of</strong> the developed methodology for synthesis <strong>of</strong> mechanisms is shown through some<br />

case studies. All the data presented here are in a consistent set <strong>of</strong> units, i.e., all linear dimensions are in the unit<br />

<strong>of</strong> length and the angular dimensions are in degrees unless otherwise stated. For each case study an intermediate<br />

result and the final result are given. Finally, a summary <strong>of</strong> the results <strong>of</strong> all the cases indicating the values <strong>of</strong> the<br />

design variables obtained through DE is presented. The optimization algorithm is applied using MATLAB<br />

version 7.1. All the linkages shown in the following sections are obtained by using the design variables. Here<br />

the technique <strong>of</strong> geometric centroid <strong>of</strong> precision points (GCPP) [12] has been used to define the initial bounds <strong>of</strong><br />

the design variables. The GCPP is obtained by evaluating the mean coordinates X and Y<br />

cg<br />

cg (mass center<br />

position) <strong>of</strong> the desired precision points in X and Y directions respectively.<br />

2.4. Results from Computer Programming (DE)<br />

Input parameters<br />

Number <strong>of</strong> population: 250<br />

Maximum number <strong>of</strong> iteration: 1000<br />

Minimum value to reach: ( 1.95) ∗1.<br />

e − 0. 08<br />

lmax Link length ratio: = 8<br />

lmin<br />

0<br />

0<br />

Limits <strong>of</strong> transmission angle: µ min = 15 and µ max = 165<br />

Desired points<br />

x : 26 23 <strong>20</strong> 17 14<br />

d<br />

y : 16 16 16 16 16<br />

d<br />

Incremental crank angles corresponding to the first precision point:<br />

0 22 44 66 88<br />

Considering following design variables as L 1 = x1<br />

, L2<br />

= x2<br />

, L3<br />

= x3<br />

L4<br />

= x4<br />

, L5<br />

= x5<br />

, β = x6,<br />

θ2<br />

= x7<br />

, θ1<br />

= x8,<br />

L0<br />

= x9<br />

, L6<br />

= x10<br />

We have optimized.<br />

Limits <strong>of</strong> design variables ( x 1 to x 10 ) obtained from the GCPP technique:<br />

X min : 0 0 0 0 0 0 0 0 -41.0574 -45.0574<br />

X max : 61.0574 61.0574 61.0574 61.0574 61.0574 6.2832 6.2832 6.2832 81.0574 77.0574<br />

Shape <strong>of</strong> coupler is in Fig. 2 approximately straight line instead <strong>of</strong> triangular. After optimization the structural<br />

angle is 0.0305.<br />

g<br />

g<br />

(5)<br />

Table 1 shows the optimized values <strong>of</strong> variables where<br />

θ =inputvalue<br />

and we assume, θ = , L = L 0 .<br />

2<br />

1<br />

0<br />

0 6<br />

=<br />

248


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig.2. Design curve obtained by optimization without considering clearance.<br />

Table 1.Optimized value <strong>of</strong> variables<br />

Design variables Optimized value<br />

Without considering<br />

clearance<br />

L1(cm) 11.151457<br />

L2(cm) 5.7811281<br />

L3(cm) 14.227586<br />

L4(cm) 14.227529<br />

AP 28.455171<br />

β (degree) 0.030539<br />

e m Error<br />

0.00712<br />

Normalized(cm)<br />

3. Analysis <strong>of</strong> design curve: considering joint clearance<br />

In actual practice some clearances are in evitable in joints due to tolerances and defects due to manufacturing<br />

process adopted or wearing after a certain working period. In this study it is assumed that links are connected to<br />

each other by revolute joints with clearance. In the joint clearance, shown in Fig.3. r 2<br />

is defined as the difference<br />

between the radii <strong>of</strong> the pin and hole, r and r respectively. When the journal gives impact on the bearing<br />

B<br />

J<br />

wall, normal and tangential force occurs. Also, if the friction is negligible, the direction <strong>of</strong> joint clearance vector<br />

coincides with the direction <strong>of</strong> normal force at the contact point. When the continuous contact mode between<br />

journal and bearing at joint is considered, the clearance may be modeled as vector which is similar to mass less<br />

virtual link with length equal to joint clearance.<br />

The equivalent clearance (clearance vector) can be defined in the form,<br />

r2 = r B<br />

− r J<br />

(6)<br />

Similarly r 3 can be defined.<br />

Fig. 3. Equivalent clearance link<br />

3.1. Synthesis Of Four Bar Path Generator With Joint Clearance<br />

A four bar mechanism, as shown in Fig.4. is considered as an example to determine the effect <strong>of</strong> joint clearances<br />

between crank and coupler link and between coupler link and follower link on path generation. Here we ve also<br />

taken the coordinates ( X Y ) ( 0,0)<br />

and the input angle θ 0 , in a local coordinate system.<br />

0 , 0 =<br />

1 =<br />

249


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig. 4. 4-bar Linkages with clearance<br />

From the close loop vector relation<br />

L<br />

c<br />

c<br />

iθ1<br />

iθ2<br />

iθ3<br />

iθ4<br />

iγ<br />

2 iγ<br />

3<br />

1 e + L2e<br />

+ L3e<br />

+ L4e<br />

+ r2e<br />

+ r3<br />

e =<br />

Fig .5. 4-bar Linkage with clearance: vector loop<br />

By separating Eq. (7), into its real part and imaginary part and using trigonometric relations,<br />

joint clearance can be expressed as a function <strong>of</strong> θ and γ<br />

2 2 respectively:<br />

0<br />

⎛<br />

2 ⎞<br />

c −1⎜<br />

− B ± B − 4AC<br />

θ =<br />

⎟<br />

3 2 tan<br />

(8)<br />

⎜ 2A<br />

⎟<br />

⎝<br />

⎠<br />

c<br />

⎡ L<br />

⎤<br />

1<br />

− L2<br />

cosθ2<br />

− r2<br />

cosγ<br />

2<br />

− L3<br />

cosθ3<br />

− r3<br />

cosγ<br />

3<br />

⎢<br />

⎥<br />

⎣<br />

L4<br />

⎦<br />

c −1<br />

θ<br />

4<br />

= cos<br />

(9)<br />

(7)<br />

c c<br />

3 and θ 4<br />

θ with<br />

Where the superscript c denotes the value with clearance. A , B,<br />

C terms are given, with joint clearance<br />

respectively<br />

A = −( L1<br />

+ L3<br />

)( 2L2<br />

cosθ2<br />

+ 2r2<br />

cos γ 2 ) + 2r3<br />

cos γ 3<br />

+ 2L2r2<br />

cos( θ2<br />

− γ 2 ) + 2L2r3<br />

cos( θ2<br />

− γ 3) + 2r2r3<br />

cos( γ 2 − γ 3)<br />

2 2 2 2 2 2<br />

+ 2L1L<br />

3 + L1<br />

+ L2<br />

+ L3<br />

− L4<br />

+ r2<br />

+ r<br />

(10)<br />

3<br />

B = 4L<br />

( L sin θ + r sin γ + r γ )<br />

(11)<br />

2 2 2 2 3 3<br />

C = ( L3<br />

− L1<br />

) 2L2<br />

cosθ<br />

2 + 2r2<br />

cos γ 2 + 2r3<br />

cos γ 3 +<br />

2L2r2<br />

cos θ 2 − γ 2 + 2L2r3<br />

cos θ 2 − γ 3 + 2r2<br />

r3<br />

cos γ 2 − γ 3<br />

2<br />

1<br />

+ L<br />

+ L<br />

3 sin<br />

( ) ( ) ( )<br />

2<br />

2<br />

+ L<br />

2<br />

3<br />

− L<br />

2<br />

4<br />

2<br />

2<br />

+ r<br />

2<br />

3<br />

+ r<br />

− 2L<br />

L<br />

As shown in Fig.4, the position <strong>of</strong> the coupler point ( x y)<br />

clearance, respectively:<br />

c<br />

x<br />

c<br />

( θ ) + r cosγ<br />

+ A′<br />

P ( θ + β )<br />

P = L2 cos<br />

2 2 2<br />

cos<br />

3<br />

c<br />

c<br />

( θ ) + r sinγ<br />

+ A′<br />

P ( θ + β )<br />

Py<br />

= L2 sin 2 2 2 sin 3<br />

Where<br />

c<br />

x<br />

clearance.<br />

P ,<br />

c<br />

P denote the<br />

y<br />

X and Y<br />

1 3<br />

(12)<br />

P , relative to the crank pivot A<br />

1<br />

is given with joint<br />

(13)<br />

(14)<br />

coordinate values for the path <strong>of</strong> the coupler point in considering the joint<br />

In the kinematic analysis <strong>of</strong> the 4-bar mechanism with double joint clearance, it is necessary to determine the<br />

position <strong>of</strong> mass centre for moving links and then their corresponding velocities and accelerations. So in the<br />

case <strong>of</strong> joint clearance these positions are derived from the vector representation <strong>of</strong> the mechanism in Fig.5.<br />

250


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Due to motion transmission from crank link to follower, joint clearance between crank and coupler has<br />

important role on the path generation by coupler point P . If the crank pivot ( A 1)<br />

is taken as the reference point,<br />

the mass centre positions for moving links are given as follows.<br />

x c G 2 = A0<br />

G 2 cos θ 2<br />

(15)<br />

y c G 2 = A 0 G 2 sin θ 2<br />

(16)<br />

c<br />

c<br />

xG3 = L2<br />

cos θ<br />

2<br />

+ r2<br />

cosγ<br />

2<br />

+ AG3<br />

cos( θ3<br />

+ δ )<br />

(17)<br />

c<br />

( θ δ )<br />

3 = L2<br />

sinθ 2 + r2<br />

sinγ<br />

2 + AG3<br />

sin +<br />

c<br />

yG<br />

3<br />

c<br />

c<br />

c<br />

xG<br />

4<br />

= L2<br />

cosθ 2<br />

+ r2<br />

cosγ<br />

2<br />

+ L3<br />

cosθ<br />

3<br />

+ r3<br />

cosγ<br />

3<br />

+ BG4<br />

cosθ<br />

3<br />

c<br />

c<br />

c<br />

yG<br />

4 = L2<br />

sinθ 2 + r2<br />

sinγ<br />

2 + L3<br />

sinθ<br />

3 + r3<br />

sinγ<br />

3 + BG4<br />

sinθ<br />

3<br />

3.2. Result Considering Different Values <strong>of</strong> Joint Clearance<br />

In Figs. (6-17) we denote curve 1 as designed curve (optimized) without considering any clearance and curve 2<br />

as coupler curve before optimization after considering clearance.<br />

(18)<br />

(<strong>19</strong>)<br />

(<strong>20</strong>)<br />

for clearance γ = mm and γ 1<br />

2 0 3 =<br />

Fig .6. Designed curve and coupler curve<br />

Fig .7. Designed curve and coupler curve<br />

251


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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

for clearance γ = mm and γ 0<br />

2 1 3 =<br />

for clearance<br />

γ = mmandγ<br />

1mm<br />

2 1 3 =<br />

Fig.8. Designed curve and coupler curve<br />

for clearance γ = mmandγ<br />

0mm<br />

2<br />

2<br />

3<br />

=<br />

Fig.9. Designed curve and coupler curve<br />

for clearance γ<br />

2<br />

2<br />

3<br />

=<br />

= mm and γ 2 mm<br />

Fig.10. Designed curve and coupler curve<br />

These Figs. [6-10] Show that there are more gaps between curve 1 and curve 2. So optimization is required for<br />

reducing the gap.<br />

252


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Here optimization is done by Differential Evaluation method. And the results are<br />

In Figs. (11-<strong>20</strong>) curve 1 is designed curve (optimized) without considering any clearance, curve 2 is designed<br />

curve (optimized) after considering clearance and curve 3 is coupler curve before optimization considering<br />

clearance<br />

3.3. Path Errors For Joint Clearances Values<br />

The path errors obtained for different joint clearances values in the original (actual) and optimized mechanisms<br />

are shown in different figures. In figures it is shown, these errors for original (actual) mechanism are bigger than<br />

that <strong>of</strong> optimized mechanism. Here we have taken Curve 1 as desired curve, curve 2 as optimized curve and<br />

curve 3 as actual curve.<br />

Fig.11. Comparisons between curves (1, 2, 3)<br />

for clearance<br />

γ = mm and γ 1mm<br />

2 0 3 =<br />

Fig. 12. Path error in X direction and Y direction for clearance γ = mmand<br />

γ 1mm<br />

2<br />

0<br />

3<br />

=<br />

Fig.13. Comparisons between curves (1, 2, 3)<br />

253


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for clearance<br />

γ = mm and γ 0 mm<br />

2<br />

1<br />

3<br />

=<br />

for clearance γ = mm and γ 0 mm<br />

2<br />

1<br />

3<br />

=<br />

Fig. 14. Path error in X direction and Y direction<br />

Fig.15. Comparisons between curves (1, 2, 3)<br />

for clearance<br />

γ = mmand<br />

γ 1mm<br />

2<br />

1<br />

3<br />

=<br />

Fig.16. Path error in X direction and Y direction<br />

254


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for clearance<br />

γ = mm and γ 1mm<br />

2 1 3 =<br />

for clearance<br />

γ = mmand<br />

γ 0mm<br />

2 2 3 =<br />

Fig.17. Comparisons between curves (1, 2, 3)<br />

Fig.18. Path error in X direction and Y direction for clearance<br />

γ = mm and γ 0mm<br />

2 2 3 =<br />

for clearance<br />

Fig.<strong>19</strong>. Comparisons between curves (1, 2, 3)<br />

γ = mm and γ 2 mm<br />

2<br />

2<br />

3<br />

=<br />

Fig.<strong>20</strong>. Path error in X direction and Y direction for clearance γ = mmand<br />

γ 2 mm<br />

255<br />

2 2 3 =


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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3.4. Optimized Design Variables for Different Values <strong>of</strong> Joint Clearance<br />

The minimized error between desired curve and generated curve are shown in table for different clearance value.<br />

Table 2 .Optimized design variables for different values <strong>of</strong> joint clearance<br />

First clearance 0 mm 1 mm 2 mm 1 mm 2 mm<br />

Second clearance 1 mm 0 mm 0 mm 1 mm 2 mm<br />

L 1 (cm) 11.<strong>19</strong> 11.068640 10.985514 11.10<strong>20</strong>79 11.053802<br />

L 2 (cm) 5.7792 5.730<strong>19</strong>1 5.679<strong>19</strong>5 5.750582 5.7<strong>20</strong>761<br />

L 3 (cm) 14.315 14.085486 13.944055 14.034109 13.848833<br />

L 4 (cm) 14.375 14.170829 14.114999 14.181522 14.146543<br />

A'P (cm) 28.4606 28.415688 28.376284 28.396785 28.337841<br />

β (degree) 0.003 0.030539 0.059975 0.370321 0.721255<br />

Error (normalized)<br />

(cm)<br />

0.00323 0.0541 0.1082 0.0633 0.1266<br />

4. Conclusion<br />

In this study the main focus has been given to consider two joint clearances between crank and coupler link and<br />

between coupler link and follower link. We have shown the effect <strong>of</strong> joint clearances on path generation. Here<br />

the optimum link lengths are found out with an objective to minimize the error in the path generation<br />

considering the given joint clearances. It is observed from the result that after doing optimization we can reduce<br />

the error between the desired and optimized curve. These results can be seen as appropriate optimization<br />

technique for minimizing the actual error in the presence <strong>of</strong> clearances. The values <strong>of</strong> the clearances may vary<br />

due to precision to be maintained. Therefore optimum results are extracted for different set <strong>of</strong> values <strong>of</strong> the<br />

clearances to study the effect <strong>of</strong> joint clearances on the minimized error. From the results it is obtained that the<br />

error is minimum for the 1 st set. It is the designer’s option either to constrain the clearances for achieving<br />

targeted error minimization or to select optimum combination <strong>of</strong> clearances for a given constraints <strong>of</strong> clearances<br />

both <strong>of</strong> which can easily be done by using this optimization scheme.<br />

References<br />

[1] R.H. BURNS and F.R.E. CROSSLEY, Structural Permutations <strong>of</strong> Flexible Link Mechanisms, ASME<br />

Paper, 66-Mech-5.<br />

[2] T. G. BORONKAY and C. MEI, <strong>19</strong>70, Analysis and Design <strong>of</strong> Multiple Input Flexible Link Mechanisms,<br />

Journal <strong>of</strong> Mechanisms 5,29-40.<br />

[3] S. DUBOWSKY, <strong>19</strong>74, On predicting the dynamic effect <strong>of</strong> clearances in planar mechanisms, ASME<br />

Journal <strong>of</strong> Engineering for industry 93B, 317-323.<br />

[4] T. FURUHASHI, N. MORITA and M. MATSUURA, <strong>19</strong>78, Research on dynamics <strong>of</strong> four-bar linkage<br />

with clearances at turning pairs (1st Report, General theory <strong>of</strong> continuous contact model), Bulletin <strong>of</strong> the<br />

JSME 21, 518–523.<br />

[5] N. MORITA, T. FURUHASHI and M. MATSUURA, <strong>19</strong>78, Research on dynamics <strong>of</strong> four-bar linkage<br />

with clearances at turning pairs (2nd Report, Analysis <strong>of</strong> crank-level mechanism with clearance at joint <strong>of</strong><br />

crank and coupler using continuous contact model), Bulletin <strong>of</strong> the JSME 21,1284–1291.<br />

[6] A.K. MALLIK and S.G. DHANDE, <strong>19</strong>87, Analysis and synthesis <strong>of</strong> mechanical error in path-generating<br />

linkages using a stochastic approach, Mechanism and Machine Theory 22,115-123.<br />

[7] K.W. TING, J. ZHU and D. WATKINS, <strong>20</strong>00, The effects <strong>of</strong> joint clearance on position and orientation<br />

deviation <strong>of</strong> linkages and manipulators, Mechanism and Machine Theory 35, 391–401.<br />

[8] A.L. SCHWAB, J.P. MEIJAARD and P. MEIJERS, <strong>20</strong>02, A comparison <strong>of</strong> revolute joint clearance<br />

models in the dynamic analysis <strong>of</strong> rigid and elastic mechanical systems, Mechanism and Machine Theory<br />

37, 895–913.<br />

[9] M.J. TSAI and T.H. LAI, <strong>20</strong>04, Kinematic sensitivity analysis <strong>of</strong> linkage with joint clearance based on<br />

transmission quality, Mechanism and Machine Theory 39, 1189–1<strong>20</strong>6.<br />

[10] P. Flores, J. Ambrosio, J.C.P. Claro, H.M. Lankarani and C.S. Koshy, <strong>20</strong>06, A study on dynamics <strong>of</strong><br />

mechanical systems including joints with clearance and lubrication, Mechanism and Machine Theory 41,<br />

247–261.<br />

[11] M.J. TSAI and T.H. LAI ,<strong>20</strong>08, Accuracy analysis <strong>of</strong> a multi-loop linkage with joint clearances,<br />

Mechanism and Machine Theory 43, 1141–1157.<br />

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Appendix -A<br />

Separating into real and imaginary parts and putting θ 1 = 0<br />

L2 cosθ 2 + L3<br />

cosθ3<br />

+ L4<br />

cosθ4<br />

+ L1<br />

= 0<br />

(A.1) L<br />

2<br />

sin θ<br />

2<br />

+ L3<br />

sin θ<br />

3<br />

+ L4<br />

sin θ<br />

4<br />

= 0<br />

(A.2)<br />

Angles θ<br />

3<br />

and θ can be solved for input angle<br />

4<br />

2<br />

Four-bar from Freudenstein’s equation:<br />

K<br />

1<br />

cos θ<br />

4<br />

+ K<br />

2<br />

cos θ<br />

2<br />

+ K<br />

3<br />

= cos<br />

Where<br />

L1<br />

K<br />

1<br />

= − , K<br />

2<br />

L<br />

K<br />

4<br />

= −<br />

2<br />

L1<br />

, K<br />

5<br />

L<br />

2<br />

= −<br />

L1<br />

, K<br />

3<br />

L<br />

4<br />

L1<br />

= − , and K<br />

6<br />

L<br />

3<br />

( θ − θ )<br />

2<br />

2 2 2 2<br />

L3<br />

− L2<br />

− L4<br />

− L1<br />

=<br />

2L<br />

L<br />

2<br />

4<br />

4<br />

2<br />

3<br />

(A.3)<br />

2 2 2 2<br />

L4<br />

− L3<br />

− L2<br />

− L1<br />

=<br />

2L<br />

L<br />

θ and valid choice <strong>of</strong> vector lengths <strong>of</strong><br />

K<br />

4<br />

cos θ<br />

3<br />

+ K<br />

5<br />

cos θ<br />

2<br />

+ K<br />

6<br />

= cos<br />

( θ − θ )<br />

2<br />

3<br />

(A.4)<br />

The solution <strong>of</strong> the equation is,<br />

θ<br />

θ<br />

4 1<br />

3 1<br />

, 2<br />

, 2<br />

= 2 ta n&<br />

= 2 tan<br />

− 1<br />

⎛<br />

⎜ −<br />

⎜<br />

⎝<br />

− 1<br />

B ± B<br />

⎛<br />

⎜ − E ±<br />

⎜<br />

⎝<br />

2<br />

2 A<br />

E<br />

2 D<br />

− 4 AC<br />

2<br />

− 4 DF<br />

⎞<br />

⎟<br />

⎟<br />

⎠<br />

⎞<br />

⎟<br />

⎟<br />

⎠<br />

(A.5)<br />

Where<br />

A = K cosθ<br />

− K + K + cosθ<br />

, B= −2sinθ<br />

, C = K + K +<br />

2<br />

2<br />

2<br />

D=<br />

cosθ<br />

− K<br />

4<br />

1<br />

5<br />

3<br />

2<br />

2<br />

+ K cosθ<br />

+ K , E = −2sinθ<br />

, and F = K +<br />

6<br />

2<br />

2<br />

1<br />

3<br />

4<br />

cosθ2( K2<br />

−1)<br />

( K5<br />

−1) cosθ2<br />

+ K6<br />

257


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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

STOCHASTIC THERMAL BUCKLING RESPONSE OF LAMINATED<br />

COMPOSITE PLATE RESTING ON ELASTIC FOUNDATION BASED<br />

ON MICROMECHANICAL MODEL<br />

Rajiv Kumar 1 , Amit Sharma 2 and Rajesh Kumar 3<br />

1<br />

M.Tech , Deptt. Of Mech. Engg.,Murthal ,Haryana, India, rajiv.kumar13@gmail.com<br />

2 Asstt. Pr<strong>of</strong>essor, Deptt. Of Mech. Engg. DCRUST, Murthal, India, , mech_amit_sharma@yahoo.co.in<br />

3<br />

Pr<strong>of</strong>essor, Deptt. <strong>of</strong> Mech. Engg., DCRUST, Murthal, Haryana, India , rajeshtripathi63@gmail.com<br />

Abstract<br />

The present work investigates the thermally induced buckling response <strong>of</strong> elastically supported laminated composite<br />

plates with random system properties using stochastic finite element method. The properties such as material<br />

properties, thermal expansion coefficients and lamina thickness are modeled as basic random variables. A C 0<br />

nonlinear finite element method based on the higher order shear deformation plate theory using von Karman-type<br />

nonlinear strain displacement relations is used to discretize the laminate. A direct iterative method in conjunction<br />

with first order perturbation technique (FOPT) is outlined to solve the stochastic nonlinear generalized eigenvalue<br />

problems in thermal sense. Typical numerical results for second order statistics <strong>of</strong> thermal nonlinear buckling load<br />

<strong>of</strong> laminated composite plates are obtained for different support conditions, and temperature change. The numerical<br />

results for mean response are compared with the results available in the literature and for second order statistics<br />

with an independent Monte Carlo simulation.<br />

Keywords: Thermal Buckling; stochastic finite element; perturbation technique; boundary support.<br />

1. INTRODUCTION<br />

Laminated composite plates when subjected to temperature environments the thermal stresses are developed at the<br />

edges <strong>of</strong> the plates due to constraint thermal expansion coefficients. These thermal stresses induce thermal buckling<br />

loads which may have affected the structural behavior <strong>of</strong> the plates consequently result buckling <strong>of</strong> the plate.<br />

Therefore, it necessitates to understand the non linear buckling behavior <strong>of</strong> the composite plates induced by thermal<br />

loading. One <strong>of</strong> the aims <strong>of</strong> the designer is to control undesirable buckling that may eventually lead to the failure <strong>of</strong><br />

the structures due to fatigue and creep. Considerable investigations have been made in the past by researchers on the<br />

prediction <strong>of</strong> the nonlinear buckling response <strong>of</strong> conventional structures and composite structures in thermal<br />

environments based on deterministic analysis which is insufficient to predict the system behavior due to various<br />

system randomness as they only give the mean response and ignore accountability for the deviation caused by<br />

inherent randomness in the system properties. Notable among them are Liu and Huang (<strong>19</strong>96) and Lee and Lee<br />

(<strong>19</strong>97). Zhang and Ellingwood (<strong>19</strong>93) have evaluated the effect <strong>of</strong> random material field characteristics on the<br />

instability <strong>of</strong> a simply supported beam on elastic foundation and a frame using perturbation technique. A<br />

comprehensive summary <strong>of</strong> extensive literature is available on the response analysis <strong>of</strong> the structures with<br />

deterministic material properties to random excitations by Nigam and Narayanan (<strong>19</strong>94). Zhang et al. (<strong>19</strong>96) have<br />

investigated the stochastic perturbation method to vector-valued and matrix-valued function for response and<br />

reliability <strong>of</strong> uncertain structures. Some published literature is available on the analysis <strong>of</strong> the structures made <strong>of</strong><br />

metallic materials with random material properties. It is evident from the literature that the studies on the nonlinear<br />

thermal response buckling <strong>of</strong> laminated composite plates with random material properties are not dealt by the<br />

researcher to the best <strong>of</strong> author’s knowledge.<br />

2. FORMULATION<br />

Consider a rectangular laminated composite plate <strong>of</strong> length a, width b, and thickness h, which consists <strong>of</strong> N number <strong>of</strong><br />

orthotropic layers. All orthotropic layers <strong>of</strong> the composite plate are <strong>of</strong> uniform thickness. The mid plane <strong>of</strong> the plate<br />

considered as the reference plane. The thickness coordinates z <strong>of</strong> the top and bottom surfaces <strong>of</strong> any (k th ) layer are<br />

denoted by h (k+1) and h k , respectively. The fibers <strong>of</strong> k th layer are oriented at an angle θ k to the x-axis, supported at four<br />

edges defined in the (x, y, z) coordinate system with x- and y-axes located in the middle plane and its origin placed at<br />

the corner <strong>of</strong> the plate as shown in Fig. 1.<br />

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Fig 1<br />

2.1. Stress–strain relation<br />

The stress-strain relations <strong>of</strong> thermo-elasticity for the kth lamina oriented as an arbitrary angle with respect to the<br />

reference axis for an orthotropic layer under consideration <strong>of</strong> with stain in a plain stress state is given by Reddy<br />

(<strong>19</strong>96).<br />

{ σ} ⎡Q⎤<br />

{ ε}<br />

k<br />

= ⎣ ⎦<br />

k<br />

k<br />

Q Q Q<br />

0 0<br />

⎡<br />

⎤<br />

⎧σ 11 12 16<br />

x ⎫ ⎢<br />

⎥ ⎧ 1<br />

ε ⎫ ⎧ 1<br />

λ ⎫<br />

⎪<br />

σ<br />

⎪ ⎢Q 12 Q22 Q26<br />

0 0 ⎥ ⎪<br />

y<br />

ε<br />

⎪ ⎪<br />

2 1<br />

λ<br />

⎪<br />

⎪ ⎪ ⎢<br />

⎥<br />

⎪ ⎪ ⎪ ⎪<br />

⎨σ xy ⎬ = ⎢Q 16 Q26 Q66<br />

0 0 ⎥ ⎨ 6<br />

ε ⎬ −⎨ 12<br />

λ ⎬ δT<br />

(1)<br />

⎪σ<br />

⎪ ⎢<br />

⎥ ⎪<br />

yz 0 0 0 Q<br />

4<br />

0<br />

44 Q ε ⎪ ⎪ ⎪<br />

⎪ ⎪ ⎢<br />

45 ⎥ ⎪ ⎪ ⎪ ⎪<br />

⎪⎩ σxz<br />

⎪⎭ ⎢<br />

⎥ ⎪<br />

5<br />

ε ⎪ ⎪0⎪<br />

k<br />

k k<br />

0 0 0 Q45 Q ⎩ ⎭ ⎩ ⎭<br />

⎢⎣<br />

55 ⎥⎦<br />

k<br />

λ Qα Qα Qα ; λ Qα Qα Qα ; λ Qα Qα Qα<br />

= + + = + + = + + where, { Q } k<br />

where, 1 11 1 12 2 16 12 2 12 1 22 2 26 12 12 16 1 26 2 66 12<br />

, { σ} k<br />

and { ε } k<br />

are transformed stiffness<br />

matrix, stress and strain vectors <strong>of</strong> the kth lamina, respectively and α 1 , α 2 , are α 12 are the expansion coefficients along<br />

X, Y and Z directions which can be obtained from the thermal coefficients in the longitudinal (α l ) and transverse (α t )<br />

directions <strong>of</strong> the fibers using transformed matrix.<br />

2.2. Strain energy equations<br />

The strain energy <strong>of</strong> the plate is given by<br />

1 T<br />

U = { ε} [ σ ] dV<br />

2<br />

∫ (2)<br />

v<br />

Using Equations the strain energy (U) can be rewritten as<br />

259


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1 T 1 T<br />

U = { } { } { } { }{ }<br />

2∫<br />

ε ⎡<br />

l<br />

Q⎤<br />

A ⎣ ⎦<br />

εl dA+<br />

2∫<br />

εl Q ε<br />

A<br />

nl<br />

dA<br />

1 T 1 T<br />

+ { εnl } { Q}{ εl} dA { εnl } { Q}{ εnl<br />

} dA,<br />

2∫<br />

+<br />

A<br />

2∫A<br />

(3)<br />

Using linear strain displacement vector expressed in terms <strong>of</strong> thickness coordinate relations and mid-plain strain<br />

vector can be expressed as<br />

1 T 1 T<br />

U= { } { } [ ] [ 3]{ }{ } ,<br />

2<br />

∫A<br />

εl ⎡⎣ D⎤<br />

⎦ εl dA +<br />

2∫<br />

εl<br />

D A φ dA<br />

A<br />

(4)<br />

1 T T 1 T T<br />

+ { A} { φ} [ D4 ]{ εl<br />

} dA + { A} { φ} [ D5<br />

]{ A}{ φ}<br />

dA ,<br />

2∫A<br />

2∫A<br />

ε is defined as<br />

where [D], [D 3 ], [D 4 ] and [D 5 ] are the laminate stiffness matrices and mid plain strain vector { } l<br />

0 0 0 0 0 0 2 2 2 0 0 2 2<br />

{ l<br />

ε } ( 1<br />

ε ε2 ε6 k1 k2 k6 k1 k2 k6 ε4 ε5 k4 k5<br />

)<br />

T<br />

= (5)<br />

3. THE EQUATION OF MOTION AND ITS SOLUTION TECHNIQUE<br />

The governing equation for thermally induced nonlinear free vibration <strong>of</strong> the plate analysis can be derived using the<br />

Lagrange’s equation <strong>of</strong> motion.<br />

t2<br />

δ ∫ ( U −W − T ) dT = 0<br />

(6)<br />

t1<br />

Substituting Equations one obtains as in the form <strong>of</strong> non linear generalized eigen value problem as<br />

K q = λ M q<br />

(7)<br />

[ ]{ } [ ]{ }<br />

here, [ K ] = [ K ] + [ K ] − λ ⎡<br />

⎣K<br />

⎤<br />

⎦ with [ K ] = N ( q ) + N ( q )<br />

l nl T g<br />

⎡ 1 1 ⎤<br />

nl ⎢ 1 2<br />

2 3 ⎥<br />

⎣<br />

⎦<br />

2<br />

M and λ = ω are defined as global displacement vector, global linear, nonlinear and<br />

where { q } , [ K<br />

l ] , [ K<br />

nl ] , [ ]<br />

geometric stiffness matrices, global mass matrix and critical buckling temperature respectively.<br />

1 ( )<br />

N q and N ( )<br />

global nonlinear stiffness matrices which are linearly and quadratically dependent on the displacement vector,<br />

respectively.<br />

3.1 Solutions- perturbation technique<br />

Due to the result <strong>of</strong> randomness in basic input variables, all the quantities in Equation (15), i.e. [K], { }<br />

2<br />

q are<br />

q and λ are<br />

random as well. M. Based on this, the mean centered first order perturbation techniques in which all the system<br />

parameters are expanded in Taylor series is used to determine the stochastic characteristics <strong>of</strong> the nonlinear frequency<br />

<strong>of</strong> laminated composite plates.<br />

In general, without any loss <strong>of</strong> generality any arbitrary random variable can be expressed as the sum <strong>of</strong> its mean and<br />

the zero mean random part, denoted by superscripts ‘d’ and ‘r’, respectively<br />

d r d r d r<br />

K = K + K , λi = λ<br />

i<br />

+λi<br />

, qi = qi + qi<br />

,<br />

(8)<br />

where,<br />

d<br />

i<br />

2<br />

d<br />

i<br />

λ = ω , i=1, 2,….., p. The parameter p indicates the size <strong>of</strong> eigen problem.<br />

Using Taylor series and neglecting the higher order terms since the first order approximation is sufficient to yield<br />

results with desired accuracy having low variability as is the case in most <strong>of</strong> the sensitive applications Kleiber and<br />

Hein(<strong>19</strong>92). one obtains as<br />

Zeroth order perturbation Equation: ⎡ d d d d<br />

K ⎤ { qi<br />

} = λi<br />

[ M ]{ q<br />

⎣ ⎦<br />

i }<br />

(9)<br />

First order perturbation equation:<br />

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{ i } + K { i } λi [ ]{ i } + λi [ ]{ i }<br />

⎡ ⎤ ⎡ ⎤<br />

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d r r d r d d r<br />

⎣K ⎦ q ⎣ ⎦ q = M q M q<br />

(10)<br />

3.2 Micromechanical approach<br />

The material properties <strong>of</strong> the fiber composite at different temperature are evaluated using micromechanical model.<br />

Since the effect <strong>of</strong> temperature and moisture concentration is dominant in matrix material. The degradation <strong>of</strong> the<br />

fiber composite material properties is estimated by degrading the matrix property only.<br />

The elastic constants are obtained from the following equations Upadhyay et al. (<strong>20</strong>10).<br />

E = E V + F E V<br />

11 f 1 f m m m<br />

Fm Em V<br />

f<br />

E22<br />

= ( 1− V<br />

f ) Fm Em<br />

+<br />

⎛ Fm<br />

E<br />

1−<br />

Vf<br />

1−<br />

⎜<br />

⎝ E<br />

m<br />

f 2<br />

⎞<br />

⎟<br />

⎠<br />

(11)<br />

(12)<br />

Fm Gm V<br />

f<br />

G12<br />

= ( 1− V<br />

f ) Fm Gm<br />

+<br />

⎛ F G<br />

1−<br />

V ⎜1−<br />

⎞<br />

⎟<br />

m m<br />

f<br />

⎜ G ⎟<br />

⎝ f 12 ⎠ (13)<br />

ν = ν V + ν V<br />

12 f 12 f m m<br />

(14)<br />

where “V” is the volume fraction and subscripts “f” and “m” are used for fiber and matrix, respectively. The effect <strong>of</strong><br />

increased temperature on the coefficients <strong>of</strong> thermal expansion (α) is opposite from the corresponding effect on<br />

strength and stiffness.The matrix thermal property retention ratio is approximated as<br />

1<br />

Fh<br />

=<br />

Fm<br />

(15)<br />

Coefficients <strong>of</strong> thermal expansion are expressed as Upadhyay et al.(<strong>20</strong>10).<br />

E<br />

f 1V<br />

fα<br />

f 1<br />

+ Fm EmVm Fhα<br />

m<br />

α11<br />

=<br />

E V + F E V<br />

f 1 f m m m<br />

( 1 ) V ( 1 )<br />

α = + ν α + + ν V F α −ν α<br />

22 f 12 f f 2 m m h m 12 11<br />

(16)<br />

(17)<br />

The elastic constants are obtained from the following equations Shen, Hui-Shen.(<strong>20</strong>01).<br />

E11<br />

= VfEf + VmEm<br />

(18)<br />

2 Em 2 Ef<br />

Vf + υm − 2υ f υm<br />

1 Vf Vm Ef Em<br />

= + −VfVm<br />

(<strong>19</strong>)<br />

E Ef Em VfEf + VmEm<br />

22<br />

1 Vf Vm<br />

= + (<strong>20</strong>)<br />

G Ef Gm<br />

12<br />

υ12 = Vfυ f + Vmυ<br />

m<br />

(21)<br />

where “V” is the volume fraction and subscripts “f” and “m” are used for fiber and matrix, respectively. The effect <strong>of</strong><br />

increased temperature on the coefficients <strong>of</strong> thermal expansion (α) is opposite from the corresponding effect on<br />

strength and stiffness.Coefficients <strong>of</strong> thermal expansion are expressed as Shen.(<strong>20</strong>01).<br />

VfEf α f + VmEmα<br />

m<br />

α11<br />

=<br />

(22)<br />

VfEf + VmEm<br />

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α = (1 + υ f ) Vf α f + (1 + υm)<br />

Vmα m − υ α<br />

(23)<br />

22 12 11<br />

other constants are related as Shen.(<strong>20</strong>01).<br />

ρ = Vf ρ f + Vmρm<br />

(24)<br />

Vm + Vf = 1<br />

(25)<br />

3.3 Monte-Carlo Simulation<br />

In MCS approach, the samples for the random parameters are obtained by generating a set <strong>of</strong> random numbers <strong>of</strong><br />

given sample size to fit the desired mean and Standard deviation (SD). For present work, MATLAB inbuilt command<br />

is used for generating random numbers corresponding to mean values <strong>of</strong> the material property to be varied. The<br />

formula for Mean and SD <strong>of</strong> property x to be varied are as:<br />

x<br />

Mean = i = 1<br />

µ =<br />

n<br />

n<br />

∑<br />

i<br />

(26)<br />

Standard Deviation = (27)<br />

where i=1,2,3,…..n.<br />

The governing equation for thermal buckling <strong>of</strong> laminated composite plate can be derived using Variational principle<br />

Reddy (<strong>19</strong>81) which is generalization <strong>of</strong> the principle <strong>of</strong> virtual displacement. For the prebuckling analysis, the first<br />

variation <strong>of</strong> total potential energy Π = (Π 1 +Π 2 ) must be zero.<br />

T<br />

[ K ]{ q} ⎡F<br />

= ⎣<br />

⎤ ⎦<br />

(28)<br />

For the critical buckling state corresponding to the neutral equilibrium condition, the second variation <strong>of</strong> total<br />

potential energy (Π) must be zero. Following this conditions, ones obtains as standard eigenvalue problem<br />

[ K ]{ q} λ ⎡K ⎤<br />

g { q}<br />

= ⎣ ⎦<br />

(29)<br />

The Eq. 28 & 29 can be rewritten as<br />

[ K ] + λ ⎡K g<br />

⎤ = 0<br />

⎣ ⎦<br />

(30)<br />

Where [K],and [K g ] are the stiffness matrix and geometric stiffness matrix respectively<br />

4. RESULTS AND DISCUSSION<br />

In the present study, a procedure and a MATLAB code for performing stochastic analysis <strong>of</strong> the thermal buckling <strong>of</strong><br />

laminated composite plates has been developed. The direct iterative based stochastic finite element method<br />

(DISFEM) approach is outlined for the nonlinear response <strong>of</strong> the laminated composite plates subjected to temperature<br />

changes with random input variables through numerical examples. The approach has been validated by comparing the<br />

results with those available in literature and independent Monte Carlo Simulation with important sampling. A nine<br />

noded Lagrangian isoparametric element with 63 degrees <strong>of</strong> freedom (DOFs) for the present HSDT model has been<br />

used for discretizing the laminate. Based on convergence study, a (4×4) mesh has been used. Unless otherwise<br />

mentioned all the results reported in this paper have been obtained employing the full integration (3 × 3) rule.<br />

The influence <strong>of</strong> scattering in the system properties on the thermal nonlinear buckling referred as a nonlinear in the<br />

following text has been examined for the laminated composite plate with various temperature increments. The mean<br />

and standard deviation <strong>of</strong> the nonlinear buckling load are obtained considering the all random input variables.<br />

However, the results are only presented taking SD/mean <strong>of</strong> the system property equal to 0.10 Liu et al.(<strong>19</strong>96) as the<br />

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nature <strong>of</strong> the SD (Standard deviation) variation is linear and passing through the origin. Hence, the presented results<br />

would be sufficient to extrapolate the results for other SD/mean value keeping in mind the limitation <strong>of</strong> FOPT Liu et<br />

al.(<strong>19</strong>96). The basic random variables such as E 1 , E 2 , G 12 , G 13 , G 23 , υ 12 , α 1 , α 2 are sequenced and defined as appendix.<br />

b= E, b = E , b = G, b = G, b = G, b = ν , b = α, b = α,<br />

b = h<br />

1 11 2 22 3 12 4 13 5 23 6 12 7 1 8 2 9<br />

The following material properties are used for computation:<br />

d<br />

11<br />

40 d 22, d d 12 13<br />

0.6 d 22, d 23<br />

0.5 d 22, d<br />

d -6 0 -1 d -6 0 -1 d -6 0 -1 d<br />

9<br />

E = E G = G = E G = E ν12<br />

= 0.25, ρ = 1. αl = 1.14*10 C , αt = 11.4*10 C , α0 = 1*10 C , E22<br />

= 6.92*10 Pa .<br />

In the present study various combination <strong>of</strong> edge support conditions namely clamped (C) and simply supported (S)<br />

have been used for the investigation. The boundary conditions for the plate are as:<br />

All edges simply supported (SSSS):<br />

v= w= θ = ψ = 0, at x= 0, a; u = w= θ = ψ = 0at y = 0, bAll edges clamped (CCCC):<br />

y y x x<br />

u = v = w = ψ = ψ = θ = θ = 0, at x = 0, a and y = 0, b;<br />

x y x y<br />

Two opposite edges clamped and other two simply supported (CSCS):<br />

u = v = w = ψ = ψ = θ = θ = 0, at x = 0 and y = 0; v = w = θ = ψ = 0, at x = a u = w = θ = ψ = 0, at y = b<br />

x y x y<br />

y y x x<br />

4.1 Comparison results: mean and second-order statistics<br />

In order to verify the accuracy <strong>of</strong> the present finite element formulation in dimensionless nonlinear thermal buckling<br />

analysis <strong>of</strong> laminated composite angle-ply [0 0 /45 0 /45 0 /0 0 ] square plate with various aspect ratios and with uniform<br />

thermal loading condition having all edges simply supported is shown in Table 2(a) and 2(b), and compared with the<br />

results obtained by Liu and Huang (<strong>19</strong>96). Clearly, it is seen that the present finite element results obtained by HSDT<br />

are in good agreement with that obtained by Liu and Huang analysis using the first-order shear deformation plate<br />

theory. The maximum difference is about 2%.<br />

Due to unavailability <strong>of</strong> results concerning the buckling <strong>of</strong> composite plates subjected to thermal loading with<br />

randomness in system properties, the existing result concerning the random linear buckling <strong>of</strong> laminated composite<br />

plates in thermal environment has been validated by comparing the results obtained from present DISFEM approach<br />

with an independent MCS approach with various buckling load. It is assumed that one <strong>of</strong> the material property (i.e.,<br />

E 11 ) change at a time keeping other as a deterministic, with their mean values <strong>of</strong> the material properties. For the MCS<br />

approach, the samples are generated using Mat Lab to fit the desired mean and SD.<br />

Table 2(a), 2(b) examines the effect <strong>of</strong> temperature distribution variations (uniform, linearly, tent like and parabolic)<br />

with fiber volume fraction (Vf=0.6) and temperature changes (∆T=100C°, 0°C ) for random change in all material<br />

properties (bi) on the dimensionless<br />

Mean and coefficient <strong>of</strong> variation <strong>of</strong> buckling load on laminated composite plates having simply supported boundary<br />

conditions with temperature independent (TID) material properties. It can be observed that for the same fiber volume<br />

fraction and temperature change, the dimensionless mean buckling load <strong>of</strong> the plate is highest when plate has uniform<br />

constant temperature variation. It is noted that the coefficient <strong>of</strong> variation <strong>of</strong> buckling load is almost same for the<br />

plates subjected to uniform constant, linearly and tent like temperature variations but coefficient <strong>of</strong> variation <strong>of</strong><br />

buckling load on plate subjected to parabolic temperature distribution is highest<br />

5. CONCLUSION<br />

Table 1(a) Comparisons <strong>of</strong> buckling loads Px (KN) for perfect (±45 0 )2T laminated square plates (a/h=10) under sets<br />

<strong>of</strong> environmental conditions<br />

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∆T=0 Vf=0.5 Vf=0.6 Vf=0.7<br />

Present<br />

HSDT<br />

142.740 169.708 <strong>20</strong>3.014<br />

141.1574 171.2263 214.1426<br />

Table 1(b) Effects <strong>of</strong> individual input random variables b i , {(i =1 to 8) = 0.1} on the dimensionlised expected mean<br />

and coefficient <strong>of</strong> variation (SD/Mean) on the thermal buckling load N x (KN) for perfect angle ply (±45 0 2) T square<br />

plates resting on elastic foundations, (a/h=10), V f =0.6, T 0 =25 0 C , Simple Support (S2) under Environmental<br />

Conditions. The dimensionlised expected mean thermal buckling loads are given in brackets (KN). λ crl – Linear<br />

Random Winkler Foundation Pasternak Foundation<br />

Variables k1=100, k2=0 k1=100, k2=10<br />

(bi)<br />

Coefficient <strong>of</strong><br />

Coefficient <strong>of</strong><br />

variation(SD/ Mean), variation(SD/ Mean),<br />

∆T=0 ∆T=100 ∆T=0 ∆T=100<br />

E11(i=1) 0.0325<br />

(186.30<br />

0.0329<br />

(175.81)<br />

0.1360<br />

(276.72<br />

0.1364(<br />

260.59)<br />

E22(i=2) 0.0<strong>19</strong>0 0.0012 0.0127 7.6654e-4<br />

G12(i=3) 7.5753E 7.7052E-4 5.0894E 5.1768E-4<br />

G13(i=4) -4 0.0502 0.0501 0.0339 -4 0.0340<br />

G23(i=5) 0.0251 0.0251 0.0169 0.0170<br />

V12(i=6) 0.0028 2.0313E-4 0.00<strong>19</strong> 1.3594E-4<br />

ἀ1(i=7) 2.1394E 1.5255E-4 1.4403E 1.0291E-4<br />

ἀ2(i=8) -5 4.67<strong>19</strong>E 0.0021 -5 3.1453E 0.0014<br />

K1(i=9) -4 0.0048 0.0048 0.0032 -4 0.0032<br />

K2(i=10) 0 0 0.0327 0.0325<br />

Comparison <strong>of</strong> dimensionless mean buckling load with aspect ratios <strong>of</strong> a (0/45 0 /45 0 /0 0 ) laminated composite plates<br />

subjected to two sets <strong>of</strong> techniques to study the thermally induced geometrically linear response <strong>of</strong> laminated<br />

composite plate in the framework <strong>of</strong> higher order deformation theory with the von Karman sense. Thermal Increase<br />

the temperature results in decrease in linear mean buckling load <strong>of</strong> laminated plate for the same aspect ratio.<br />

However, dispersion <strong>of</strong> linear mean buckling load <strong>of</strong> the plate increases with increase the temperature.<br />

The SSSS plate is most sensitive, while CCCC plate is least sensitive against simultaneous change in all random input<br />

variables and thermal expansion coefficients. In contrast the mean values <strong>of</strong> SSSS and CCCC plate show the opposite<br />

effect.<br />

Table 2(a) The effects <strong>of</strong> environmental conditions and input random variables bi{i=1…8, 7-8, 9-10,1-10= 0.10} on<br />

the buckling <strong>of</strong> a angle ply (±45 0 2) T square laminated composite plate resting on Winkler (k1=100, k2=0) elastic<br />

foundation with plate thickness ratio (a/h=50), ,V f =0.6, T 0 =25 0 C, Simple Support(S2).<br />

Environmental<br />

Conditions.<br />

Wmax/h<br />

(KN)<br />

Winkler foundation (k1=100, k2=0)<br />

Coefficient <strong>of</strong> variation (SD/ Mean)<br />

bi<br />

(i=1- 8) (i=7.-8) (i=9-10) (i=1-10)<br />

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∆T=0 0 C, 4.9298 0.1<strong>20</strong>1 0.0036 0.0134 0.1<strong>20</strong>8<br />

∆T=100 0 C, 4.8528 0.1<strong>20</strong>0 0.0165 0.0129 0.1<strong>20</strong>7<br />

∆T=<strong>20</strong>0 0 C, 4.7742 0.1224 0.0272 0.0127 0.1230<br />

∆T=300 0 C, 4.7075 0.1252 0.0356 0.0127 0.1259<br />

Table 2(b)Effect <strong>of</strong> environmental conditions and input random variables bi{i=1…8, 7-8, 9-10,1-10= 0.10} on the<br />

buckling <strong>of</strong> a angle ply (±45 0 2) T square laminated composite plate resting on Pasternak (k1=100, k2=10) elastic<br />

foundation with ( a/h=50), ,V f =0.6, T 0 =25 0 C, Simple Support(S2).<br />

Environmental<br />

Conditions.<br />

Wmax/<br />

h<br />

(KN)<br />

Pasternak foundations (k1=100, k2=10)<br />

Coefficient <strong>of</strong> variation (SD/ Mean)<br />

bi<br />

(i=1- 8) (i=7.-8) (i=9-10) (i=1-10)<br />

∆T=0 0 C, 6.0523 0.1224 0.0029 0.0142 0.1232<br />

∆T=100 0 C 5.9537 0.1279 0.0134 0.0150 0.1288<br />

∆T=<strong>20</strong>0 0 C, 5.8525 0.1312 0.0222 0.0152 0.1321<br />

∆T=300 0 C, 5.7661 0.1340 0.0291 0.0152 0.1349<br />

6. Nomenclature<br />

Aij Bij, Laminate stiffness<br />

a, b : Plate length and breadth<br />

h<br />

Thickness <strong>of</strong> the plate<br />

Ef, Em : Elastic moduli <strong>of</strong> fiber and matrix<br />

Gf, Gm : Shear moduli <strong>of</strong> fiber and matrix<br />

vf, vm : Poisson’s ratio <strong>of</strong> fiber and matrix<br />

Vm, Vf : Volume fraction <strong>of</strong> fiber and matrix<br />

αf, αm : Coefficient <strong>of</strong> thermal expansion <strong>of</strong> fiber and matrix<br />

bi<br />

Basic random material properties<br />

E11, E22 : Longitudinal and Transverse elastic moduli<br />

G12,G13,G2 : Shear moduli<br />

3 Kl, Knl : Linear and Nonlinear stiffness matrix<br />

K1, K2 Normal and Shear stiffness <strong>of</strong> the foundation,<br />

Kg<br />

: Thermal geometric stiffness matrix<br />

M, m :<br />

:<br />

Mass and inertia matrices<br />

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ne, n : Number <strong>of</strong> elements, number <strong>of</strong> layers in the laminated plate<br />

Nx,Ny,Nxy In-plane thermal buckling loads<br />

nn<br />

: Number <strong>of</strong> nodes per element<br />

Ni<br />

: Shape function <strong>of</strong> ith node<br />

p<br />

:<br />

C ijkl<br />

Reduced elastic material constants<br />

f,{f}(e)<br />

:<br />

u, v, w<br />

:<br />

u u u , ,<br />

1, 2,<br />

3<br />

σ ij , ε ij<br />

ψ<br />

x<br />

, ψ<br />

y<br />

θ<br />

x<br />

, θ<br />

y<br />

, θ<br />

k<br />

ρ λ<br />

:<br />

:<br />

:<br />

Vector <strong>of</strong> unknown displacements, displacement vector <strong>of</strong><br />

either element<br />

Displacements <strong>of</strong> a point on the mid plane <strong>of</strong> plate<br />

Displacement <strong>of</strong> a point (x, y, z)<br />

Stress vector, Strain vector<br />

Rotations <strong>of</strong> normal to mid plane about the x and y axis<br />

Two slopes and angle <strong>of</strong> fiber orientation w.r.t x-axis for kth<br />

layer<br />

x, y, z<br />

Cartesian coordinates<br />

ρ, λ,<br />

var(.)<br />

: Mass density, eigenvalue, variance<br />

RVs : Random variables<br />

∆T<br />

: Difference in temperatures<br />

α1, α2 : Thermal expansion coefficients along x and y direction<br />

ne, n : Number <strong>of</strong> elements, number <strong>of</strong> layers in the laminated plate<br />

Nx,Ny,Nxy<br />

nn<br />

:<br />

Ni<br />

:<br />

p :<br />

C ijkl :<br />

f,{f}(e)<br />

:<br />

u, v, w<br />

:<br />

u1, u2,<br />

u<br />

3<br />

ρ, λ ,<br />

σ ij , ε ij<br />

ψ<br />

x<br />

, ψ<br />

y<br />

θ<br />

x<br />

, θ<br />

y<br />

, θ<br />

k<br />

:<br />

:<br />

:<br />

In-plane thermal buckling loads<br />

Number <strong>of</strong> nodes per element<br />

Shape function <strong>of</strong> ith node<br />

Reduced elastic material constants<br />

Vector <strong>of</strong> unknown displacements, displacement vector <strong>of</strong><br />

either element<br />

Displacements <strong>of</strong> a point on the mid plane <strong>of</strong> plate<br />

Displacement <strong>of</strong> a point (x, y, z)<br />

Stress vector, Strain vector<br />

Rotations <strong>of</strong> normal to mid plane about the x and y axis<br />

Two slopes and angle <strong>of</strong> fiber orientation w.r.t x-axis for kth<br />

layer<br />

x, y, z<br />

Cartesian coordinates<br />

ρ, λ,<br />

var(.)<br />

: Mass density, eigenvalue, variance<br />

RVs : Random variables<br />

∆T<br />

: Difference in temperatures<br />

α1, α2 : Thermal expansion coefficients along x and y direction<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

References<br />

[1] F.C.Liu and C.H.Huang.“Free vibration <strong>of</strong> composite laminated Plates subjected to temperature change”,<br />

omputers & Structures 60:1 (<strong>19</strong>96), 95-101.<br />

[2] J. N. Reddy, Mechanics <strong>of</strong> laminated composite plate theory and analysis, CRC Press, Florida, (<strong>19</strong>96).<br />

[3] J. Zhang and B. Ellingwood, “Effects <strong>of</strong> uncertain material properties on structural stability”, Journal <strong>of</strong><br />

Structural Engineering ASCE 121, (<strong>19</strong>93), 705-716.<br />

[4] Lee DM, Lee In (<strong>19</strong>97) Vibration behaviors <strong>of</strong> thermally postbuckled anisotropic plates using first-order shear<br />

deformable plate theory. Comput Struct 63(3):371–378.<br />

[5] M. Kleiber and T. D. Hien, “The Stochastic Finite lement Method”, John Wiley & Sons, USA, <strong>19</strong>92.<br />

[6] N. C. Nigam and S. Narayanan, Applications <strong>of</strong> random vibrations. Narosa, New Delhi, <strong>19</strong>94.<br />

[7] Pandey, Ramesh., Shukla, K. K. and Jain, Anuj. (<strong>20</strong>08). “Thermoelastic stability analysis <strong>of</strong> laminated composite<br />

[8] Shankara, C.A., N. G. R., Iyenger, “A C 0 element for the free vibration analysis <strong>of</strong> laminated composite plates”,<br />

Journal <strong>of</strong> Sound and Vibration <strong>19</strong>1: 5 (<strong>19</strong>96), 721-738.<br />

[9] Hui-Shen Shen.(<strong>20</strong>01). “Hygrothermal effects on the post buckling <strong>of</strong> shear deformable laminated plates”. Int J<br />

Mech Sci, (43), 1259-1281.<br />

[10] Upadhyay A.K, Pandey Ramesh, and Shukla K.K.(<strong>20</strong>10) Nonlinear flexural response <strong>of</strong> laminated composite<br />

plates under hygro-thermo-mechanical loading. Commun Nonlinear Sci Numer Simulat, 15, 2634–2650.<br />

[11] Y. Zhang, S. Chen, and Q. Lue, " Stochastic perturbation finite elements”, Computers & Structures 59: 3 (<strong>19</strong>96),<br />

425- 429.<br />

267


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

AN INTRODUCTION TO STRUCTURAL HEALTH MONITORING: A<br />

SMART SOLUTION<br />

Vikash Kumar 1 , Sanjeev Kumar 2 , Vikram Singh 3<br />

1 PhD Research Scholar, Department <strong>of</strong> Mech. Engg. <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad<br />

2,3 Associate Pr<strong>of</strong>essor, Department <strong>of</strong> Mech. Engg.,<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad<br />

1<br />

vidyarthig@gmail.com<br />

Abstract<br />

Structural health monitoring is an important safety factor in aviation that might benefit from advanced smart<br />

systems for damage sensing and signal processing. Current levels <strong>of</strong> structural safety and reliability do not<br />

present a particularly strong case for smart systems but cost considerations related to inspection and<br />

maintenance do. As an added benefit problems <strong>of</strong> poor accessibility and negative effects <strong>of</strong> human factors in<br />

inspection might be reduced. The implementation <strong>of</strong> such system requires development and demonstration by<br />

dedicated and qualified multidisciplinary teams, acceptance by aircraft designers, manufacturers and operators<br />

and approval by the authorities. Current European collaborative schemes and the associated funding in<br />

conjunction with an apparent interest among potential end users provide excellent prospects for the realisation<br />

<strong>of</strong> smart solutions.<br />

1. Introduction<br />

Structural health monitoring is an important safety factor in aviation that might benefit from advanced smart<br />

systems for damage sensing and signal processing. Current levels <strong>of</strong> structural safety and reliability do not<br />

present a particularly strong case for smart systems but cost considerations related to inspection and<br />

maintenance do. As an added benefit problems <strong>of</strong> poor accessibility and negative effects <strong>of</strong> human factors in<br />

inspection might be reduced. The implementation <strong>of</strong> such system requires development and demonstration by<br />

dedicated and qualified multidisciplinary teams, acceptance by aircraft designers, manufacturers and operators<br />

and approval by the authorities. Current European collaborative schemes and the associated funding in<br />

conjunction with an apparent interest among potential end users provide excellent prospects for the realisation <strong>of</strong><br />

smart solutions. [7]<br />

2. Structural health and usage monitoring: why<br />

Structural health is directly related to structural performance and in this respect it is a governing parameter with<br />

regard to safety <strong>of</strong> operation. This aspect <strong>of</strong> structural health is particularly relevant to transportation systems<br />

including their infrastructural elements and in this connection structural health monitoring is a safety issue. At<br />

the same time a change in structural health may affect structural performance to a degree that remedial actions<br />

become necessary. Structural repairs increase the cost <strong>of</strong> transportation in at least two ways. First, the design<br />

and implementation <strong>of</strong> repairs implies direct costs. Second, the execution <strong>of</strong> repairs generally requires the<br />

transportation system to be temporarily taken out <strong>of</strong> service and this induces indirect costs due to the loss <strong>of</strong><br />

production volume or as a result <strong>of</strong> leasing a substitute system. To reduce repair and maintenance cost one might<br />

attempt to repair at a very early stage <strong>of</strong> damage development to limit direct costs. Alternatively, it might be<br />

decided to postpone repair until the transportation system has to be taken out <strong>of</strong> service for scheduled major<br />

overhauls to reduce indirect costs. In this connection structural health monitoring becomes a cost issue. In case<br />

<strong>of</strong> the latter option (relying on the delay measure) it may be necessary to adapt operational usage to limit or even<br />

stop damage growth. If sufficient knowledge exists to relate damage rates to mission types this can be achieved<br />

by usage monitoring. [1]<br />

In general usage monitoring can be viewed as a valuable addition to structural health monitoring. Prescribed<br />

maintenance schedules are based on an estimated usage pattern. Knowledge <strong>of</strong> the actual utilization can be<br />

translated into a severity parameter that can be compared to the value corresponding to the estimated loading<br />

spectrum. In this manner prescribed inspection intervals and times between overhauls can be tuned to actual<br />

needs. [1]<br />

It is worthy to note that there are substantial differences in damage development and as a consequence in the<br />

manner structural health will deteriorate with time between metal and composite structure. Whereas in metallic<br />

components cracking is a gradual and predictable process with a high probability <strong>of</strong> occurrence the wear-out <strong>of</strong><br />

a composite component as a result after loading environment is much less pronounced but composites may<br />

suffer from discrete traumas due to accidental damage <strong>of</strong> a non-predictable random nature. The situation<br />

268


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

suggests that different health monitoring philosophies should be applied to the two families <strong>of</strong> structural<br />

components. [2]<br />

3. Structural health monitoring: how<br />

Structural health, or equivalently, the state <strong>of</strong> damage can be established either directly or indirectly. In the latter<br />

indirect approach structural performance or rather structural behaviour is measured and compared with the<br />

supposedly known global response characteristics <strong>of</strong> the undamaged structure. If the effect <strong>of</strong> certain damages<br />

on structural response characteristics is known this approach provides an indirect measure <strong>of</strong> damage and <strong>of</strong><br />

structural health. In a direct manner one checks for the damage type under consideration, like cracks, corrosion<br />

or delaminations, by applying an appropriate inspection technique. These techniques, based on physical<br />

phenomena, in fact sometimes amount to response measurements also but in this case they have a very local and<br />

direct character. The established inspection techniques vary from visual inspection by the naked eye to passing<br />

the structure through a fully automated inspection gantry.<br />

Obviously in both the direct and indirect approaches the sensitivity and the reliability <strong>of</strong> inspection are<br />

important quantitative performance measures. They are determined on the one hand by the laws <strong>of</strong> physics but<br />

on the other in practice also by the hardware and s<strong>of</strong>tware quality <strong>of</strong> the inspection equipment and last but not<br />

least by the equipment operator: the inspector. [8]<br />

In this connection human factors like the loss <strong>of</strong> alertness in case <strong>of</strong> rare occurrences <strong>of</strong> damage and inspector<br />

fatigue in case <strong>of</strong> long and tedious inspections are important reasons to consider a smarter solution to inspection<br />

as an element <strong>of</strong> structural health monitoring.<br />

4. Options for smart solutions<br />

It is for both sensitivity and reliability that the particular features provided by smart technologies are considered.<br />

Smart sensors could provide greater sensitivity provided that they are properly installed. This option is clearly<br />

related to specific inspections at precisely known critical locations that in addition may be poorly accessible. On<br />

the other hand, smart sensor systems with advanced data processing are relevant for inspecting larger areas for a<br />

variety <strong>of</strong> defects. If such systems function continuously the time between inspections is effectively zero and<br />

then a moderate sensitivity might suffice. [4]<br />

In a more general sense smart system design and smart interpretation and use <strong>of</strong> data generated by the systems<br />

are desirable features in any solution and in this context it is necessary to define what is meant here by smart<br />

solutions to structural health monitoring requirements: in the present paper smartness relates to either sensors for<br />

damage detection including their installation or to signal processing and presentation. [5]<br />

5. Is there a case for smart solutions in aircraft<br />

In the first chapter <strong>of</strong> this paper structural health monitoring was identified first <strong>of</strong> all as a safety issue. Certainly<br />

in air transport where structural failures may lead to fatal accidents the safety <strong>of</strong> operation is a prime<br />

consideration. Continuous research in the areas <strong>of</strong> fatigue and corrosion <strong>of</strong> metallic aircraft structure including<br />

inspection techniques (sometimes spurred and accelerated by dramatic accidents or incidents) has helped to<br />

achieve a very high level <strong>of</strong> structural reliability. Design for damage tolerance is now widely applied. It relies on<br />

a very pr<strong>of</strong>ound understanding <strong>of</strong> material behaviour, on a very accurate description <strong>of</strong> the loading environment<br />

(both external and internal) all <strong>of</strong> this in combination with advanced manufacturing techniques and, <strong>of</strong> course,<br />

proven and reliable inspection and maintenance procedures and in situations where brittle material behaviour or<br />

poor accessibility with regard to inspection are in the way <strong>of</strong> a damage tolerant design approach detailed<br />

numerical analysis supported by advanced testing has produced slow crack growth or safe life structure.<br />

Any interest for automated integrated inspection systems could then result only from a need for greater<br />

reliability <strong>of</strong> inspection: the damage tolerance chain is only as strong as its weakest link which probably is<br />

inspection. [3]<br />

It is thought that from a safety <strong>of</strong> flight position there is not a strong case yet for smarter solutions. Only in<br />

special situations an integrated sensor system may provide greater reliability than current methods. However, if<br />

in view <strong>of</strong> the rapidly growing air transport volume, expressed in billions <strong>of</strong> passenger miles flown, a significant<br />

reduction in structural failure rates is needed smart solutions may become more relevant as a safety issue.<br />

Another more important factor stimulating the development <strong>of</strong> smart systems, however, is the cost <strong>of</strong> inspection.<br />

[6]<br />

269


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

There is very little published data on the potential for cost reductions but the inspection efforts applied in current<br />

aircraft maintenance procedures are very considerable and moreover inspector training and motivation require<br />

continuous attention. It must be mentioned here that significant improvements have been achieved in traditional<br />

inspection equipment with regard to inspector friendliness and quantitative data presentation.<br />

A recent study on inspection requirements for a modern fighter aircraft (featuring both metal and composite<br />

structure) revealed that an estimated 40 percent plus can be saved on inspection time by utilizing smart<br />

monitoring systems. The situation at hand is illustrated in the table1 below. [4]<br />

Inspection<br />

Type<br />

Table 1: Comparision <strong>of</strong> Inspection<br />

Current<br />

Inspection type<br />

(% <strong>of</strong> total)<br />

270<br />

External<br />

Potential for<br />

smart systems<br />

Time<br />

Saved (%<br />

<strong>of</strong> Total)<br />

Flight Line 16 0.40 6.5<br />

Scheduled 31 0.45 14.0<br />

Unscheduled 16 0.10 1.5<br />

Service<br />

37 0.60 22<br />

Instruction<br />

100 44.0<br />

Another estimate derived for a fully automated impact sensing system for a composite structure, based on the<br />

use <strong>of</strong> integrated distributed piezo sensors in combination with advanced signal processing s<strong>of</strong>tware arrives at a<br />

50 percent saving on regular inspection time again for a fighter aircraft.<br />

Admittedly, these estimates are based on data derived from laboratory demonstrators. They provide a drive,<br />

however, for the development <strong>of</strong> full scale demonstrators <strong>of</strong> smart structural health monitoring systems. In fact a<br />

major programme, to be discussed in more detail further on, recently got underway on the basis <strong>of</strong> the<br />

assumption that up to <strong>20</strong> percent <strong>of</strong> current maintenance and inspection cost can be saved in civil and<br />

transportation by the use <strong>of</strong> integrated on-line damage monitoring systems.[7]<br />

So, the case for smart solutions to aircraft structural health monitoring requirements derives from cost<br />

considerations. The development <strong>of</strong> integrated automated damage sensing systems relies on different research<br />

disciplines and in addition it affects design and manufacture as well as operation and maintenance. As primary<br />

flight systems such as the airframe, landing gear or engines are involved the airworthiness authorities will have<br />

to be involved. Obviously, the development risks <strong>of</strong> smart systems are considerable and at the same time a broad<br />

acceptance among all parties involved is necessary to achieve implementation. These considerations have led, in<br />

Europe, to a number <strong>of</strong> initiatives aimed at setting up collaborative research and development projects.<br />

6. Conclusions<br />

Aircraft structural health monitoring is an essential element for continued safe operation. Current design<br />

capabilities and manufacturing and certification standards guarantee an extremely high level <strong>of</strong> structural<br />

reliability that can be maintained during the operational life <strong>of</strong> the aircraft provided that prescribed inspections<br />

are carried out, that data are processed and that remedial actions are taken when necessary. As a consequence,<br />

safety requirements do not contribute a strong case for advanced, smart, structural health monitoring systems<br />

with the possible exception <strong>of</strong> the requirement to limit the negative effects <strong>of</strong> human factors on inspection<br />

reliability.<br />

Both the direct costs <strong>of</strong> carrying out preventive inspections and the indirect costs associated with interrupted<br />

service, however, provide a strong stimulus for cost reduction programs. In this respect integrated damage<br />

sensing systems, advanced signal processing and maintenance oriented data presentation constitute smart<br />

solutions to inspection requirements that may reduce the cost <strong>of</strong> manpower for inspections and maintenance and<br />

at the same time increase reliability and enhance data presentation.<br />

Aircraft manufactures and operators have indicated that they would like to see more integrated automated<br />

inspection systems provided that they do <strong>of</strong>fer a cost benefit and possibly are more reliable when compared to<br />

current inspection methods. They should not interfere with other flight systems and preferably be<br />

communicative to maintenance personnel. The authorities will accept such smart systems as long as they do not<br />

adversely affect current safety levels.


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Current international programs for the development and demonstration <strong>of</strong> integrated damage sensing systems for<br />

aircraft structural health monitoring in Europe provide the opportunity to achieve a breakthrough for existing<br />

technology towards actual application. The broad participation representing all the different key expertise<br />

needed, the obvious interest among the potential end user community and the financial support by international<br />

bodies are important assets in the current efforts to demonstrate and exploit smart health monitoring systems.<br />

References:<br />

[1] BOLLER, C. and BUDERATH, M., <strong>20</strong>07, Fatigue in aero structures—where structural health monitoring<br />

can contribute to a complex subject, Phil. Trans. R. Soc. A 365, 561–587.<br />

[2] BROWNJOHN, J. M. W., <strong>20</strong>07, Structural health monitoring <strong>of</strong> civil infrastructure, Phil. Trans. R. Soc.<br />

A 365, 589–622.<br />

[3] DOEBLING, S. W., FARRAR, C. R., PRIME, M. B. and SHEVITZ D. W., <strong>19</strong>96, Damage identification<br />

and health monitoring <strong>of</strong> structural and mechanical systems from changes in their vibration<br />

characteristics: A literature review, Los Alamos National Laboratory report LA-13070-MS.<br />

[4] FARRAR, C. R., DOEBLING, S. W. and NIX, D. A., <strong>20</strong>01, Vibration-based structural damage<br />

identification, Phil. Trans. R. Soc. A 359, 131–149.<br />

[5] FARRAR, C. R. et al., <strong>20</strong>03, Damage prognosis: current status and future needs, Los Alamos National<br />

Laboratory report LA-14051-MS.<br />

[6] FARRAR, C. R. And LIEVEN, N. A. J., <strong>20</strong>07, Damage prognosis: the future <strong>of</strong> structural health<br />

monitoring, Phil. Trans. R. Soc. A 365, 623–632.<br />

[7] FASSOIS, S. D. & SAKELLARIOU, J. S., <strong>20</strong>07, Time series methods for fault detection and<br />

identification in vibrating structures, Phil. Trans. R. Soc. A 365, 411–448.<br />

[8] FRISWELL, M. I., <strong>20</strong>07, Damage identification using inverse methods, Phil. Trans. R. Soc. A 365, 393–<br />

410.<br />

[9] HAYTON, P., UTETE, S., KING, D., KING, S., ANUZIS, P. and TARASSENKO, L., <strong>20</strong>07, Static and<br />

dynamic novelty detection methods for jet engine health monitoring, Phil. Trans. R. Soc. A 365, 493–<br />

514.<br />

[10] LYNCH, J. P., <strong>20</strong>07, An overview <strong>of</strong> wireless structural health monitoring for civil structures. Phil.<br />

Trans. R. Soc. A 365, 345–372.<br />

271


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

PREDICTING WIND TURBINE DESIGN PARAMETER USING<br />

ACTUATOR DISK THEORY AS A ROTATIONAL BASIS<br />

Hari Pal Dhariwal 1 , Barun Kumar Roy 2 , Bhupender Yadav 3<br />

1 Research Scholar, Singhania <strong>University</strong> Rajasthan<br />

2 Director Om Institute <strong>of</strong> <strong>Technology</strong> and Management, Hisar<br />

3 Assistant Pr<strong>of</strong>essor, <strong>YMCA</strong>UST Faridabad<br />

1 hpdhariwal@gmail.com , +9<strong>19</strong>813509678 2 barunrai_hbti@rediffmail.com , +9<strong>19</strong>992722903<br />

Abstract<br />

Wind energy is present and future demand <strong>of</strong> our society. Wind energy is affected by various parameters. Wind<br />

energy can be better abstracted only with a better technology. By assuming certain assumptions Actuator Disk<br />

Theory provides some technical data for designing wind turbine parameters.<br />

Keywords: ADT- Actuator Disk Theory, HAWT- Horizontal Axis Wind Turbines.<br />

1. Introduction<br />

Land and water areas absorb and release different amount <strong>of</strong> heat received from the sun. As warm air rises,<br />

cooler air rushes in to take its place, causing local winds. The wind turns the blades <strong>of</strong> a windmill-like machine.<br />

The rotating blades turn the shaft to which they are attached. The turning shaft typically can either power a pump<br />

or turn a generator, which produces electricity Most wind machines have blades attached to a horizontal shaft.<br />

This shaft transmits power through a series <strong>of</strong> gears, which provide power to a water pump or electric generator.<br />

These are called horizontal axis wind turbines.<br />

2. Problem Statement<br />

In order to obtain rotational basis , maximum power from the wind is captured. As there are certain parameters<br />

that affects the efficiency <strong>of</strong> the wind turbine. Our problem is to find how much power we can abstract.<br />

3. Method<br />

The Actuator Disk Theory (ADT) and the Betz Limit: A simple model, generally attributed to Betz (<strong>19</strong>26) can be<br />

used to determine the power from an ideal turbine rotor, the thrust <strong>of</strong> the wind on the ideal rotor and the effect <strong>of</strong><br />

the rotor operation on the local wind field. The simplest aerodynamic model <strong>of</strong> a HAWT is known as ‘actuator<br />

disk model’ in which the rotor becomes a homogenous disk that removes energy from the wind. Actuator disk<br />

theory is based on a linear momentum theory developed over 100 years ago to predict the performance <strong>of</strong> ship<br />

propeller.<br />

The theory <strong>of</strong> the ideal actuator disk is based on the following assumptions:<br />

• Homogenous, Incompressible, steady state fluid flow<br />

• No frictional drag<br />

• The pressure increment or thrust per unit area is constant over the disk<br />

• The rotational component <strong>of</strong> the velocity in the slipstream is zero. Thus the actuator disk is an ideal<br />

mechanism which imparts momentum to the fluid in the axial direction only<br />

• There is continuity <strong>of</strong> velocity through the disk<br />

• An infinite number <strong>of</strong> blades<br />

A complete physical representation <strong>of</strong> this actuator disk may be obtained by considering a close pair <strong>of</strong> tandem<br />

propellers or turbine blades rotating in opposite direction and so designed that the element <strong>of</strong> torque at any radial<br />

distance from the axis has the same value for each blade in order that there shall be no rotational motion in the<br />

slipstream; also each turbine actual blade must be replaced with its small number <strong>of</strong> blades by another <strong>of</strong> the<br />

same diameter having a very large number <strong>of</strong> very narrow equal frictionless blades, the solidity at any radius<br />

being the same as for the actual turbine and finally to have the blade angles suitably chosen to give a uniform<br />

distribution <strong>of</strong> thrust over the whole disk.<br />

The analysis <strong>of</strong> the actuator disk theory assumes a control volume, in which the control volume boundaries are<br />

the surface <strong>of</strong> a stream tube and two cross sections <strong>of</strong> the stream tube as shown in Figure 1.<br />

272


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig. 1 Flow through a wind turbine under ideal condition represented by a non- rotating actuator disc<br />

The only flow is across the ends <strong>of</strong> the streamtube. The turbine is represented by a uniform “actuator disk” which<br />

creates a discontinuity <strong>of</strong> pressure in the streamtube <strong>of</strong> air flowing through it. Note also that this analysis is not<br />

limited to any particular type <strong>of</strong> wind turbine.<br />

From the assumption that the continuity <strong>of</strong> velocity through the disk exists;<br />

(1)<br />

For steady state flow, air mass flow rate through the disk can be written as;<br />

m= ρAUR (2)<br />

Applying the conservation <strong>of</strong> linear momentum to the control volume enclosing the whole system, the net force<br />

can be found on the contents <strong>of</strong> the control volume. That force is equal and opposite to the thrust, T which is the<br />

force <strong>of</strong> the wind on the wind turbine. Hence from the conservation <strong>of</strong> linear momentum for a one-dimensional,<br />

incompressible, time-invariant flow the thrust is equal and opposite to the change in momentum <strong>of</strong> air stream;<br />

(3)<br />

No work is done on either side <strong>of</strong> the turbine rotor. Thus the Bernoulli function can be used in the two control<br />

volumes on either side <strong>of</strong> the actuator disk. Between the free-stream and upwind side <strong>of</strong> the rotor (from section 1<br />

to 2 in Figure 1) and between the downwind side <strong>of</strong> the rotor and far wake (from section 3 to 4 in Figure 1)<br />

respectively;<br />

(4)<br />

(5)<br />

The thrust can also be expressed as the net sum forces on each side <strong>of</strong> the actuator disk;<br />

T = Ap′ (6)<br />

Where<br />

′ <br />

By using equations (3.4) and (3.5), the pressure decrease, p′ can be found as;<br />

′ <br />

) (7)<br />

And by substituting equation (7) into equation (6) ;<br />

<br />

) (8)<br />

By equating the thrust values from equation (3) in which substituting equation (2) and equation (8) , the velocity<br />

at the rotor plane can be found as;<br />

<br />

(9)<br />

<br />

273


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Thus, the wind velocity at the rotor plane, using this simple model, is the average <strong>of</strong> the upstream and<br />

downstream wind speeds.<br />

If an axial induction factor (or the retardation factor), `a` is defined as the fractional decrease in the wind velocity<br />

between the free stream and the rotor plane, then<br />

<br />

<br />

(10)<br />

1 (11)<br />

1 2 (12)<br />

The power output, P is equal to the thrust times the velocity at the rotor plane;<br />

P= T (13)<br />

<br />

) (14)<br />

Using equation 3.8,<br />

Cp= 4a(1−a)² (15)<br />

The maximum Cp is determined by taking the derivative <strong>of</strong> equation (15) with respect to `a` and setting it equal<br />

to zero yields;<br />

(Cp )max = 16/27 = 0.5926<br />

When a = 1/3<br />

This result indicates that if an ideal rotor were designed and operated such that the wind speeds at the rotor were<br />

2/3 <strong>of</strong> the free stream wind speed, then it would be operating at the point <strong>of</strong> maximum power production. This is<br />

known as the Betz limit.<br />

4. Conclusion<br />

ADT provides a rational basis for illustrating that the flow velocity at the rotor should be different from the freestream<br />

velocity. The Betz limit (Cp)max = 0.593 shows the maximum theoretically possible rotor power<br />

coefficient that can be attained from a wind turbine. In practice the rotation <strong>of</strong> wake behind the rotor and finite<br />

number <strong>of</strong> blades with associated tip losses, effects lead to a decrease in the maximum achievable power<br />

coefficient.<br />

References<br />

1. Burton, T., Sharpe, D., Jenkins, N. &Bossanyi, E. (<strong>20</strong>01), Wind Energy Handbook, JohnWiley and Sons<br />

Ltd.<br />

2. Clausen, P. D., and Wood, D. H., “Research and Development Issues for Small Wind Turbines,”<br />

Renewable Energy, Vol. 16, Issues. 1-4, <strong>19</strong>99, pp. 922-927.<br />

3. DhariwalHariPal “ Wind Turbine Design a Feasibility Study and Scope <strong>of</strong> Improvement” Soch-Masthnath<br />

Journal <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong> India, vol.5,pp-6-10.<br />

4. Hansen, A.C., and Butterfield, C.P., “Aerodynamics <strong>of</strong> Horizontal Axis Wind Turbines,” Annual Review<br />

<strong>of</strong> Fluid Mechanics, Vol 25, March <strong>19</strong>93, pp. 115-149<br />

5. Huyer, S.A., Simms, D. and Robinson, M.C., “Unsteady aerodynamics associated with a horizontal-axis<br />

wind turbine,” AIAA Journal, Vol. 34, No. 7, July <strong>19</strong>96, pp. 1410-14<strong>19</strong>.<br />

6. WE Handbook- 2- Aerodynamics and Loads .<br />

274


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

SHAPE OPTIMIZATION TO UTILIZE PRESSURE DIFFERENCE AT<br />

FRONT AND REAR OF THE BODY<br />

Amit Chauhan 1* , Nadish Saini 2 , Shivam 3 , Udit Dureja 4 and Narender Panwar 5<br />

1,2,3,4,5 Department <strong>of</strong> Mechanical Engineering, UIET, Panjab <strong>University</strong>, Chandigarh-160014, India<br />

E-mail: drchauhan98@gmail.com, nadishsaini@yahoo.co.in , maitreya.shivam@gmail.com,<br />

uditdrj99@gmail.com and naren_panwar@yahoo.co.in<br />

1* Corresponding author: drchauhan98@gmail.com, Mob. +91-9463703366<br />

Abstract<br />

In present work, analysis has been carried out to optimize the shape <strong>of</strong> converging passage to utilize pressure<br />

difference at front and rear <strong>of</strong> the body using ANSYS (version 12) s<strong>of</strong>tware by incorporating a nozzle like<br />

passage in the design <strong>of</strong> the body. It has also been observed that elliptical cross-section provides a more<br />

coherent flow field whereas rectangular and circular provides a higher maximum out velocity, however an<br />

elliptical cross section. A new feasible design has been introduced which is applicable to the rockets. The<br />

enhancement would generate more thrust and in addition it would also stabilize the motion <strong>of</strong> rocket by<br />

pacifying eddies due to flow separation.<br />

Keywords: Pressure drag, thrust, elliptical cross-section, converging passage.<br />

1. Introduction<br />

Because <strong>of</strong> boundary layer separation phenomena, when a body moves relative to a fluid it experiences a<br />

pressure drag. To elucidate, a body with a cylindrical cross section gets its flow separated at the ends <strong>of</strong><br />

diameter perpendicular to low resulting in the formation <strong>of</strong> wake region. This wake region experiences eddies,<br />

the intensity <strong>of</strong> which increases with the increase <strong>of</strong> Reynolds’s number. These eddies result in huge losses.<br />

Also the wake region formed is a site <strong>of</strong> low pressure. The pressure at the front <strong>of</strong> cylinder is quite high as<br />

compared to this wake region, as a result there exists a pressure difference at front and rear face <strong>of</strong> the cylinder,<br />

or <strong>of</strong> any body for that matter. Owing to this pressure difference, the body experiences a drag known as pressure<br />

or form drag and the body must do some work to overcome this pressure drag. If the air from the front and sides<br />

<strong>of</strong> a body is channeled and connected through a nozzle to the rear <strong>of</strong> body into the wake region where pressure<br />

is low, the pressure drag could be converted, which was earlier detrimental to the motion <strong>of</strong> the body, into<br />

kinetic energy <strong>of</strong> the out coming fluid. Owing to the Impulse Momentum theorem, the same principle which<br />

governs rocket propulsion, useful thrust can be generated. The equation governing the exit velocity <strong>of</strong> nozzle if<br />

the inlet velocity is zero is given as [1]:<br />

Where, = Exhaust velocity at nozzle exit, m/s; = absolute temperature <strong>of</strong> inlet gas (K); = Universal gas<br />

law constant = 8314.5 J/(kmol·K); = the gas molecular mass, kg/kmol; = c p / c v = isentropic expansion<br />

factor; c p = specific heat <strong>of</strong> the gas at constant pressure; c v = specific heat <strong>of</strong> the gas at constant volume;<br />

= absolute pressure <strong>of</strong> exhaust gas at nozzle exit, Pa; = absolute pressure <strong>of</strong> inlet gas, Pa.<br />

Computational Fluid Dynamics (CFD), in one or another form, is based on the fundamental governing equations<br />

<strong>of</strong> fluid dynamics- the continuity, momentum, and energy equations. The fundamental basis <strong>of</strong> almost all CFD<br />

problems is the Navier–Stokes equations, which define any single-phase fluid flow. The continuity and<br />

momentum equations are given as [2]:-<br />

(1)<br />

Where, is fluid density, is time, and is the flow velocity vector field.<br />

(3)<br />

(4)<br />

275


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Where, is the flow velocity, is the fluid density, is the pressure, is the (deviatoric) stress tensor, and<br />

represents body forces (per unit volume) acting on the fluid and is the del operator. This is the statement <strong>of</strong><br />

conservation <strong>of</strong> momentum in a fluid and it is an application <strong>of</strong> Newton's second law to a continuum; in fact this<br />

equation is applicable to any non-relativistic continuum and is known as the Cauchy momentum equation. The<br />

idea conceptualized here has been framed keeping in view the research <strong>of</strong> Jason et al. [4] which demonstrates<br />

the influence <strong>of</strong> geometry simplification <strong>of</strong> a vehicle model to perform simulations. Further, Nadish et al. [5]<br />

has analyzed the general aerodynamic body with and without the converging passage, and has obtained positive<br />

results at both sonic velocity and near sonic velocity in terms <strong>of</strong> thrust generation which is evident from the<br />

increased velocity at the outlet section. Based on the literature survey, here, an attempt has been made to<br />

compare circular, elliptical, and rectangular cross section for the converging passage.<br />

2. Methodology<br />

Anybody that moves relative to a fluid has to spend considerable amount <strong>of</strong> energy to overcome pressure drag.<br />

This project intends to utilize this pressure drag to provide a thrust to a body. It is based on a manifestation <strong>of</strong><br />

the basic law <strong>of</strong> conservation <strong>of</strong> energy- changing pressure energy into kinetic energy. It will use the otherwise<br />

detrimental pressure drag to the advantage <strong>of</strong> a moving body by providing an extra thrust without affecting fuel<br />

consumption. This would revolutionize the aerodynamic modeling. The concept which this project intends to<br />

introduce has been proved by analyzing a simplified general body in air flow. The results <strong>of</strong> this project can be<br />

used as a benchmark for more complicated designs. A general aerodynamic body has been analyzed using the<br />

ANSYS (FLUENT) s<strong>of</strong>tware. The s<strong>of</strong>tware <strong>of</strong>fers two models Large Eddy Simulation (LES) and Detached<br />

Eddy Simulation (DES), which can be implemented in the project. Both models depict real flows. The model<br />

used in this project is DES [3]. This model attempts to treat near-wall regions in a Reynolds Averaged Navier<br />

Stokes (RANS)-like manner, and treat the rest <strong>of</strong> the flow in an LES-like manner. The model was originally<br />

formulated by replacing the distance function in the Spalart-Allmaras (S-A) model with a modified distance<br />

function given as:<br />

Where, is a constant and is the largest dimension <strong>of</strong> the grid cell in question. This modified distance<br />

function causes the model to behave as a RANS model in regions close to walls, and in a Smagorinsky-like<br />

manner away from the walls. The DES approach may be used with any turbulence model that has an<br />

appropriately defined turbulence length scale (distance in the S-A model) and is a sufficiently localized model.<br />

The parameters used in this project are: realizable K –epsilon with delayed DES; the model constants are :<br />

0.61, C2-Epsilon: 1.9, Turbulent Kinetic Energy (TKE) Prandtl Number: 1, Turbulent Dissipation Rate (TDR)<br />

Prandtl Number: 1.2, the boundary conditions are stationary wall with a specified shear stress <strong>of</strong> 290Pa (Xcomponent),<br />

turbulence intensity <strong>of</strong> 10% and hydraulic diameter <strong>of</strong> 4m, the direction <strong>of</strong> backflow is normal to<br />

boundary with radial equilibrium pressure distribution, the materials used are air as fluid and aluminium as the<br />

solid body.<br />

3. Results and Discussion<br />

3.1 Analysis <strong>of</strong> General Model<br />

The figure 3.1 illustrates the general model selected for analysis. The figure shows a converging passage<br />

incorporated in the design. The cuboid in the figure shows the flow field and the body carved out <strong>of</strong> flow field is<br />

distinctly visible. The blue section in the figure shows inlet section i.e. the section through which air enters<br />

perpendicular to the surface. The front face <strong>of</strong> the model is the symmetry plane.<br />

(5)<br />

276


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Converging passage<br />

Inlet section<br />

Fig. 3.1:General body under analysis-converging passage Blue section shows inlet section<br />

Fig 3.2: Velocity distribution in the flow field (circular cross section)-side view<br />

Fig 3.3: Velocity distribution in the flow field (circular cross section)-rear view<br />

277


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig 3.4: Velocity distribution in the flow field (elliptical cross-section)-side view<br />

Fig 3.5: Velocity distribution in the flow field (elliptical cross-section)-rear view<br />

Fig 3.6: Velocity distribution in the flow field (rectangular cross section) - side view<br />

All three cross sections have the same inlet and outlet area. The inlet area being 817.2 square units and the<br />

outlet area being 426.2 square units. The velocity for the rectangular cross section comes out to be highest equal<br />

to 1.014* 10^3 m/s followed by circular and then elliptical. However, the velocity distribution for the<br />

rectangular and circular pr<strong>of</strong>ile is not uniform and velocity is highest only at the periphery. In contrast, the<br />

velocity distribution for the elliptical pr<strong>of</strong>ile is more uniformly distributed at the rear cross section. This can be<br />

attributed to the fact that the passage in case <strong>of</strong> elliptical section is more constricted than the other two for any<br />

cross section <strong>of</strong> the same area. Thus it can be easily imagined that the polyhedrons used to generate mesh in<br />

case <strong>of</strong> elliptical are more in number and finer than rectangular or circular which leads to a uniform velocity.<br />

278


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3.2: The proposed model<br />

Fig 3.7: The green region represents the converging passage within the aerodynamic body<br />

Fig 3.8: Velocity distribution in the flow field for the proposed model - side view<br />

Fig 3.9 Velocity distribution in the flow field for the proposed model - front view<br />

The model applies to rockets, introducing an enhancement attached to the body <strong>of</strong> a rocket which incorporates<br />

the passage. It is essential that the enhancement has a larger cross section area as compared to the body <strong>of</strong> the<br />

rocket so that the inlet section faces the fluid flow directly. The enhancement would generate more thrust than it<br />

produces extra pressure drag. In addition it would also stabilize the motion <strong>of</strong> rocket by pacifying the eddies due<br />

to flow separation. Passages <strong>of</strong> different cross sections can be introduced.<br />

279


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Thrust per unit mass flow rate = V 2 – V 1 = (9.966+002) – (3.32e+002) = 6.644e+002 N Kg -1 s = 664.4 N Kg -1 s<br />

Fig 3.10: Pressure distribution in the proposed model (sectional view)<br />

Fig 3.11: Pressure distribution in the proposed model (side view)<br />

Pressure difference between the front and rear faces would result into form or pressure drag which is detrimental<br />

to the model.<br />

Approximate pressure difference =2.094e+004-(-2.4<strong>19</strong>e+005) Pa =2.513e+005 Pa<br />

4. Conclusion<br />

Just by bringing about certain changes in the design <strong>of</strong> the body and channelling the ambient air to pass through<br />

the body in a certain way it was possible to create an additional thrust to the body without affecting the fuel<br />

consumption. After the converging passage was introduced the pressure difference was utilized to make the air<br />

exit the converging passage at high velocity, which being coherent in nature also helped to straighten out the<br />

eddies that were being formed in the wake region. In rockets channelling ambient air from the front and sides<br />

will also increase the mass flow rate <strong>of</strong> the exhaust gases: If these designs <strong>of</strong> converging passages are<br />

introduced into the body <strong>of</strong> a rocket such that the passage would channel the ambient air into the exhaust <strong>of</strong> the<br />

rocket, from where all the exhaust gasses <strong>of</strong> rocket propulsion exit the rocket, not only it would create an<br />

additional thrust for the rocket (because <strong>of</strong> the increased kinetic energy) but it would also increase the mass flow<br />

rate <strong>of</strong> the exhaust gasses which would in turn further increase the thrust for the rocket according to impulse<br />

momentum theorem. The analysis has been performed on a general aerodynamic body, its practical<br />

implementation is still a difficult task because <strong>of</strong> the complex design problems related to the real bodies.<br />

Moreover, if a method is devised to vary the outlet cross-section with the help <strong>of</strong> PID controllers, thrust<br />

generation can be optimized for different speeds. It has been established by the above result that circular and<br />

rectangular section provides a higher maximum out velocity, however an elliptical cross-section provides a<br />

more coherent flow field. Structurally, a circular section is easy to carve out and most symmetrical thus must be<br />

preferred. The structure can have any cross-section suiting to the particular application.<br />

280


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

References<br />

[1] http://en.wikipedia.org/wiki/De_Laval_nozzle (Dated: 12/11/<strong>20</strong>11)<br />

[2] JOHN D. ANDERSON JR.,<strong>19</strong>95, Computational Fluid Dynamics- The Basics with Applications,<br />

Tata McGraw Hill Publishers.<br />

[3] http://en.wikipedia.org/wiki/Large_eddy_simulation (Dated 12/11/<strong>20</strong>11)<br />

[4] JASON M. ORTEGA, TIM DUNN, ROSE MCCALLEN, AND KAMBIZ SALARI, <strong>20</strong>02,<br />

Computational Simulation <strong>of</strong> a Heavy Vehicle Trailer Wake, Preprint UCRL-JC-152549, submitted to<br />

the United Engineering Foundation, Aerodynamics <strong>of</strong> Heavy Vehicles: Trucks, Buses, and Trains<br />

Conference, Monterey, CA,<br />

[5] NADISH SAINI, SHIVAM MAITREYA, UDIT DUREJA AND AMIT CHAUHAN,<strong>20</strong>12,<br />

Aerodynamic Pressure Drag utilization to Impart Thrust to the body, International Conference on Fluid<br />

Dynamics and Thermodynamics Technologies (FDTT <strong>20</strong>12) IPCSIT,.33, IACSIT Press, Singapore.<br />

281


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

INVESTIGATIONS OF THE VARIATION OF BUSH TEMPERATURE<br />

OF AN OFFSET-HALVES JOURNAL BEARING PROFILE<br />

Amit Chauhan<br />

Department <strong>of</strong> Mechanical Engineering, UIET, Panjab <strong>University</strong>, Chandigarh-160014, India,<br />

E-mail: drchauhan98@gmail.com, Mob. +91-9463703366<br />

Abstract<br />

The analysis <strong>of</strong> <strong>of</strong>fset-halves journal bearing has been carried out to find out the rise in bush temperature by<br />

evaluating the oil-film temperature using parabolic temperature pr<strong>of</strong>ile approximation technique. It has been<br />

observed that the bush temperature increases with increase in speed and the same trend observed in both upper<br />

and lower lobes <strong>of</strong> the bearing. During simulation, the bush temperature observed to be <strong>of</strong> increasing nature<br />

with increase in eccentricity ratio in lower lobe whereas <strong>of</strong> little decreasing nature with increase in eccentricity<br />

ratio in upper lobe <strong>of</strong> the bearing. Hence, it can be concluded that rise in bush temperature is considerable and<br />

comparable. Therefore, it should be taken into consideration while designing <strong>of</strong>fset-halves journal bearing.<br />

Keywords: Offset-halves bearing, bush temperature, and Parabolic Temperature Pr<strong>of</strong>ile Approximation.<br />

1. Introduction<br />

Hydrodynamic journal bearings find an extensive use in high speed rotating machinery. Under the normal<br />

operating conditions, these bearings usually experiences a considerable variation in bush and oil-film<br />

temperature due to viscous heat dissipation. This change in temperature significantly affects the bearing<br />

performance as lubricant viscosity is a strong function <strong>of</strong> temperature and, hence, leads to failure <strong>of</strong> the bearing.<br />

Thus, computation <strong>of</strong> oil-film and bush temperature is <strong>of</strong> great importance to predict bearing performance<br />

parameters. The non-conventional journal bearings, like lobed bearings and tilting pad bearings have a common<br />

feature that these bearings operate with more than one active oil film which accounts for superior stiffness and<br />

damping characteristics <strong>of</strong> these bearings as compared to the conventional circular bearings. The <strong>of</strong>fset-halves<br />

journal bearing is commonly used as a lobed bearing in which two lobes are obtained by orthogonally displacing<br />

the two halves <strong>of</strong> a cylindrical bearing (Fig. 1) and frequently used in gear boxes connecting turbine and<br />

generator in power generation industries.<br />

Fig. 1 Schematic diagram <strong>of</strong> <strong>of</strong>fset-halves journal bearing<br />

Offset-halves journal bearings show stiffness and damping properties which permit light loads at high rotational<br />

speeds [1]. The importance <strong>of</strong> thermal effects in hydrodynamic journal bearings has been long recognized, but<br />

very limited study about thermal effects in lobed bearing especially <strong>of</strong>fset-halves bearing has been reported in<br />

282


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

literature whereas it is difficult to find publications reporting the bush temperature in the <strong>of</strong>fset-halves journal<br />

bearing. However, here few research works closely related to the bearing under study have been listed. Chauhan<br />

et al. [2] has carried out a comparative study for rise in oil temperatures, thermal pressures and load capacity for<br />

three different commercially available grade oils have been carried out. The authors have reported that with<br />

increase in speed, oil temperature, thermal pressure and load carrying capacity rises for all grade oils under<br />

study. Also, Chauhan et al. [3] has analyzed thermal performance <strong>of</strong> elliptical and <strong>of</strong>fset- halves bearings by<br />

solving energy equation while assuming parabolic temperature pr<strong>of</strong>ile approximation across the fluid film.<br />

Authors have been found that <strong>of</strong>fset-halves journal bearing runs cooler with minimum power loss and good load<br />

capacity. An attempt was made by Suganami and Sezri [4] to formulate a thermohydrodynamic model <strong>of</strong> film<br />

lubrication which is valid in both laminar and superlaminar flow regimes. The authors stated that energy<br />

equation retains heat conduction in direction <strong>of</strong> sliding motion, and is applicable even at large eccentricities.<br />

Boncompain et al. [5] have presented a general thermohydrodynamic theory. The authors have solved<br />

generalized Reynolds equation, energy equation in film and heat transfer equation in bush and shaft<br />

simultaneously. Indulekha et al. [6] have solved three dimensional momentum and continuity equations and<br />

three dimensional energy equations to obtain pressure, velocity and temperature field in the fluid <strong>of</strong> a<br />

hydrodynamic circular journal bearing using finite element method. Authors have computed attitude angle, end<br />

leakage and power loss, for a wide range <strong>of</strong> eccentricity ratios.<br />

Hussain et al. [7] have predicted temperature distribution in non-circular journal bearings (namely two-lobe,<br />

elliptical and orthogonally displaced). The work is based on a two-dimensional treatment following Mc<br />

Callion’s approach (an approach in which Reynolds and energy equations in oil film are decoupled by<br />

neglecting all pressure terms in energy equation). Sehgal et al. [8] have presented a comparative theoretical<br />

analysis <strong>of</strong> three types <strong>of</strong> hydrodynamic journal bearing configurations namely, circular, axial groove, and<br />

<strong>of</strong>fset-halves. It has been observed by authors that the <strong>of</strong>fset bearing runs cooler than an equivalent circular<br />

bearing with axial grooves. A computer-aided design <strong>of</strong> hydrodynamic journal bearing is provided considering<br />

thermal effects by Singh and Majumdar [9]. In this design, Reynolds equation has been solved simultaneously<br />

along with energy equation and heat conduction equations in bush and shaft to obtain steady-state solution and a<br />

data bank is generated that consists <strong>of</strong> load, friction factor and flow rate for different L/D and eccentricity ratios.<br />

Sharma and Pandey [10] have carried out a thermohydrodynamic lubrication analysis <strong>of</strong> infinitely wide slider<br />

bearing assuming parabolic and Legendre polynomial temperature pr<strong>of</strong>ile across film thickness. Author<br />

observed that temperature approximation across film thickness by Legendre Polynomial yields more accurate<br />

results in comparison to Parabolic Temperature Pr<strong>of</strong>ile approximation.<br />

Evaluation <strong>of</strong> bush temperature has been carried out using Parabolic Temperature Pr<strong>of</strong>ile Approximation<br />

(PTPA) in the fluid film <strong>of</strong> an <strong>of</strong>fset-halves journal bearing for the Mak Multigrade oil. Mak Multigrade oil is<br />

recommended for use in heavy duty commercial vehicles, light commercial vehicles and multi-utility vehicles<br />

fitted with high speed naturally aspirated or turbo charged diesel engines operating at low speed and high torque<br />

conditions [2].<br />

2. Governing Equations<br />

Reynolds equation<br />

For steady-state and incompressible flow, Reynolds equation is [7]:<br />

3<br />

3<br />

∂ ⎛ h ∂p<br />

⎞ ∂ ⎛ h ∂p<br />

⎞ ∂h<br />

= U<br />

x<br />

⎜<br />

x<br />

⎟ +<br />

z<br />

⎜<br />

z<br />

⎟ 6<br />

∂ ⎝ µ ∂ ⎠ ∂ ⎝ µ ∂ ⎠ ∂x<br />

(1)<br />

This equation is then set into finite differences by using central difference technique. The variation <strong>of</strong> viscosity<br />

with temperature and pressure has been simulated using following relation:<br />

αP−γ<br />

( T −T 0 )<br />

µ µ<br />

(2)<br />

=<br />

ref<br />

e<br />

Energy Equation<br />

The energy equation for steady-state and incompressible flow is given as [10]:<br />

283


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2<br />

2<br />

⎛ ∂ T ∂ T ⎞ ∂ ⎛ ∂ T ⎞ ⎡⎛<br />

∂ u ⎞ ⎛ ∂ w ⎞ ⎤<br />

ρ C P ⎜ u + w ⎟ = ⎜ K ⎟ + µ ⎢⎜<br />

⎟ + ⎜ ⎟ ⎥<br />

(3)<br />

⎝ ∂ x ∂ z ⎠ ∂ y ⎝ ∂ y ⎠ ⎢⎣<br />

⎝ ∂ y ⎠ ⎝ ∂ y ⎠ ⎥⎦<br />

The term on left hand side in above equation represents energy transfer due to convection, whereas first term on<br />

right hand side represents energy transfer due to conduction and second term on right hand side represents<br />

energy transfer due to dissipation. The variation <strong>of</strong> temperature across film thickness in equation (3) is<br />

approximated by parabolic temperature pr<strong>of</strong>ile for faster computation <strong>of</strong> temperatures [10]. The temperature<br />

pr<strong>of</strong>ile across film thickness is represented by a second order polynomial as:<br />

T a +<br />

= (4)<br />

2<br />

1<br />

+ a2<br />

y a3<br />

y<br />

In order to evaluate constants appearing in eqn. (4), following boundary conditions are used: At<br />

at<br />

y = h, T = T ,<br />

U<br />

T<br />

m<br />

=<br />

1<br />

h<br />

h<br />

∫<br />

0<br />

Tdy<br />

Thus, temperature pr<strong>of</strong>ile expression (written in eqn. (4)) takes the following form:<br />

2<br />

y = , T = T<br />

0 ,<br />

⎛ y ⎞<br />

⎛ y ⎞<br />

T = T − ( 4T<br />

+ 2T<br />

− 6T<br />

) ⎜ ⎟ + ( 3T<br />

+ 3T<br />

− 6T<br />

) ⎜ ⎟ (5)<br />

L L U m<br />

L U m<br />

⎝ h ⎠<br />

⎝ h ⎠<br />

Where, T<br />

L<br />

, T<br />

U<br />

, and T<br />

m<br />

represent temperatures <strong>of</strong> lower bounding surface, upper bounding surface, and mean<br />

temperature across film respectively.<br />

Substitution <strong>of</strong> ‘u’, ‘w’, and ‘T’ expressions (Eqns. (4), (5), and (6)) into energy equation (3) and subsequently<br />

integrating energy equation across film thickness from limit ‘0’ to ‘h’ yields following form <strong>of</strong> energy equation.<br />

L<br />

6T<br />

⎛<br />

⎜<br />

⎝<br />

L<br />

∂T<br />

∂z<br />

+ 6T<br />

L<br />

U<br />

∂TU<br />

+<br />

∂z<br />

− 12T<br />

4<br />

h ⎡⎛<br />

∂P<br />

⎞<br />

+ ⎢⎜<br />

⎟<br />

12 Kµ<br />

⎢⎣<br />

⎝ ∂x<br />

⎠<br />

∂T<br />

− 12<br />

∂z<br />

2<br />

m<br />

+<br />

4<br />

ρC<br />

P<br />

h ∂P<br />

−<br />

1<strong>20</strong> Kµ<br />

∂x<br />

⎛<br />

⎜<br />

⎝<br />

m<br />

⎞ ρC<br />

⎟ −<br />

⎠<br />

∂P<br />

∂z<br />

2<br />

⎞<br />

⎟<br />

⎠<br />

P<br />

h<br />

⎤ µ<br />

⎥ +<br />

⎥⎦<br />

⎛<br />

⎜<br />

⎝<br />

2<br />

∂T<br />

∂x<br />

2<br />

( u + u ) ∂T<br />

ρC<br />

h ( u − u )<br />

2 K<br />

∂TU<br />

+<br />

∂x<br />

( u − u )<br />

U<br />

L<br />

L<br />

K<br />

L<br />

U<br />

2<br />

∂T<br />

− 12<br />

∂x<br />

m<br />

∂x<br />

= 0<br />

−<br />

m<br />

⎞<br />

⎟<br />

⎠<br />

P<br />

4<br />

ρC<br />

P<br />

h ∂P<br />

−<br />

1<strong>20</strong> Kµ<br />

∂z<br />

U<br />

12 K<br />

L<br />

⎛<br />

⎜<br />

⎝<br />

∂T<br />

U<br />

∂x<br />

−<br />

∂T<br />

∂x<br />

L<br />

⎞<br />

⎟<br />

⎠<br />

(6)<br />

The temperature in bush is determined by using the Laplace equation within the bearing material as given below<br />

[11]:<br />

∂<br />

T<br />

2<br />

b<br />

2<br />

∂x<br />

∂ T<br />

+<br />

∂y<br />

2<br />

b<br />

2<br />

∂ T<br />

+<br />

∂z<br />

2<br />

b<br />

2<br />

= 0<br />

(In Cartesian coordinate) (7)<br />

∂<br />

T<br />

2<br />

b<br />

2<br />

∂r<br />

1 ∂T<br />

+<br />

r ∂r<br />

b<br />

1<br />

+<br />

2<br />

r<br />

2<br />

∂ T<br />

2<br />

∂θ<br />

∂ T<br />

+<br />

∂y<br />

2<br />

b<br />

2<br />

= 0<br />

(In cylindrical coordinate) (8)<br />

In these equations, r stands for bush radius, and T<br />

b<br />

stands for bush temperature. The equation (8) is then set<br />

into finite differences by using central difference technique.<br />

The film thickness (h) equations for <strong>of</strong>fset-halves journal bearing are given as [8]:<br />

⎡⎛ 1+<br />

δ ⎞ ⎛1−<br />

δ ⎞<br />

= c m ⎢⎜<br />

⎟ + ⎜ ⎟cosθ<br />

− ε sin θ<br />

⎣⎝<br />

2δ<br />

⎠ ⎝ 2δ<br />

⎠<br />

⎤<br />

( φ − ) ⎥⎦<br />

h (0


⎡⎛ 1+<br />

δ ⎞ ⎛1−<br />

δ ⎞<br />

= c m ⎢⎜<br />

⎟ − ⎜ ⎟cosθ<br />

− ε sin θ<br />

⎣⎝<br />

2δ<br />

⎠ ⎝ 2δ<br />

⎠<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

⎤<br />

( φ − ) ⎥⎦<br />

h (180


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

For temperature:<br />

|<br />

( Ti<br />

, j<br />

) − (<br />

,<br />

)<br />

1 ∑T<br />

n<br />

i j<br />

| ( ∑Ti<br />

, j<br />

) |<br />

∑ −<br />

n<br />

n<br />

|<br />

≤ 0.0001<br />

(12)<br />

Where, n represents number <strong>of</strong> iterations.<br />

4. Results and Discussion<br />

Input parameters and properties <strong>of</strong> oil used in computer simulations are given in Table 1. From computer<br />

simulation, variation <strong>of</strong> bush temperature with speed and eccentricity ratio has been obtained and is discussed as<br />

follows:<br />

1. Fig. 2 shows the variation <strong>of</strong> bush temperature along the central plane <strong>of</strong> the bearing with speeds. It has been<br />

observed that the bush temperature increases with increase in speed and the same trend observed in both lobes<br />

<strong>of</strong> the <strong>of</strong>fset-halves journal bearing. Further, the rise in bush temperature is considerable and comparable with<br />

the rise in oil-film temperature obtained for same operating conditions [2].<br />

2. The variation <strong>of</strong> bush temperature with eccentricity ratio has been presented in Fig. 3. The figure shows that<br />

the bush temperature increases with increase in eccentricity ratio in lower lobe whereas a little decrease in bush<br />

temperature with increase in eccentricity ratio observed in upper lobe <strong>of</strong> the <strong>of</strong>fset-halves journal bearing.<br />

Outer diameter <strong>of</strong> bearing, OD<br />

Inner diameter <strong>of</strong> bearing, ID<br />

Length, l<br />

Radial Clearance, C<br />

Minimum Clearance,<br />

C<br />

m<br />

Oil inlet temperature, T 0<br />

Ambient Temperature, Ta<br />

Viscosity, µ<br />

Table 1: Input parameters<br />

85mm<br />

65mm<br />

65mm<br />

500 µ m<br />

<strong>20</strong>0 µ m<br />

33 0 C<br />

30 0 C<br />

0.<strong>20</strong>0Pas<br />

Density <strong>of</strong> oil, ρ 885Kg/m 3<br />

Barus viscosity-pressure index, α<br />

2.3e-8<br />

Temperature viscosity- coefficient, γ 0.034<br />

Thermal conductivity <strong>of</strong> bush,<br />

Coefficient <strong>of</strong> thermal expansion <strong>of</strong> bush,<br />

K 0.22W / m Deg. C<br />

bush<br />

h<br />

bush 75e-6<br />

−1<br />

K<br />

286


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig. 2 Variation <strong>of</strong> bush temperature along central plane <strong>of</strong> <strong>of</strong>fset-halves bearing with speed at<br />

eccentricity ratio=0.7<br />

Fig. 3 Variation <strong>of</strong> bush temperature along central plane <strong>of</strong> <strong>of</strong>fset-halves bearing with eccentricity<br />

ratio at speed=5000rpm<br />

5. Conclusion<br />

The bush temperature for the <strong>of</strong>fset-halves journal bearing has been obtained by evaluating the oil-film<br />

temperature using parabolic temperature pr<strong>of</strong>ile approximation technique. It has been observed during the<br />

analysis that a considerable amount <strong>of</strong> heat flows through the bearing material in addition o the flow <strong>of</strong> heat<br />

with the lubricating oil used for hydrodynamic action. Further, it can be seen from the discussion that the<br />

eccentricity ratio and speed <strong>of</strong> journal influences the amount <strong>of</strong> temperature rise in bush material. Hence, it can<br />

be concluded that care <strong>of</strong> bush temperature parameter should be taken into consideration while designing such<br />

kind <strong>of</strong> journal bearing pr<strong>of</strong>iles.<br />

287


6. Nomenclature<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

e<br />

Eccentricity, m<br />

O B<br />

Bearing centre<br />

O j<br />

Journal centre<br />

O L<br />

Lower-lobe centre<br />

O U<br />

Upper-lobe centre<br />

P<br />

Film pressure, Pa<br />

R<br />

Journal radius, mm<br />

r<br />

Bush radius, mm<br />

T<br />

Lubricating film temperature, 0 C<br />

U<br />

Relative velocity between journal and bearing surface, m/s<br />

u, w Velocity components in X- and Z-directions, m/s<br />

Velocity <strong>of</strong> lower bounding surface, m/s<br />

u<br />

u<br />

θ<br />

L<br />

U<br />

ω<br />

φ<br />

ε<br />

Velocity <strong>of</strong> upper bounding surface, m/s<br />

Angle measured from horizontal split axis in direction <strong>of</strong> rotation<br />

Angular velocity <strong>of</strong> shaft, rad/s<br />

Attitude angle<br />

Eccentricity Ratio<br />

References<br />

1. CHAUHAN, AMIT AND SEHGAL, RAKESH,<strong>20</strong>08, An experimental investigation <strong>of</strong> the variation <strong>of</strong> oil<br />

temperatures in <strong>of</strong>fset-halves journal bearing pr<strong>of</strong>ile using different oils, Indian Journal <strong>of</strong> Tribology, 3 (2),<br />

27-41.<br />

2. CHAUHAN A, SEHGAL R, AND SHARMA RK.,<strong>20</strong>11, A study <strong>of</strong> thermal effects in <strong>of</strong>fset-halves journal<br />

bearing pr<strong>of</strong>ile using different grade oils, Lubrication <strong>Science</strong>, 23, 233-248.<br />

3. CHAUHAN A, SEHGAL R, AND SHARMA RK.,<strong>20</strong>11,Investigations on the Thermal Effects in Non-<br />

Circular Journal Bearings, Tribology International, 44, 1765-1773.<br />

4. SUGANAMI, T. AND SEZRI, A. Z., <strong>19</strong>79, A Thermohydrodynamic analysis <strong>of</strong> journal bearings, Journal <strong>of</strong><br />

Lubrication <strong>Technology</strong>, 101, 21-27.<br />

5. BONCOMPAIN, R. FILLON, M. AND FRENE, J.,<strong>19</strong>86, Analysis <strong>of</strong> thermal effects in hydrodynamic<br />

bearings, Journal <strong>of</strong> Tribology, 108, 2<strong>19</strong>-224.<br />

6. INDULEKHA, T. P., JOY, M. L. AND PRABHAKARAN NAIR, K., <strong>19</strong>94, Fluid flow and thermal analysis<br />

<strong>of</strong> a circular journal bearing, Warme-und st<strong>of</strong>fubertragung, 29, 367-371.<br />

7. HUSSAIN, A., MISTRY, BISWAS, S. K. AND ATHRE, K.,<strong>19</strong>96, Thermal analysis <strong>of</strong> Non-circular<br />

bearing, Transactions <strong>of</strong> ASME, 118, 246-254.<br />

8. SEHGAL, R., SWAMY, K. N. S., ATHRE, K. AND BISWAS, S., <strong>20</strong>00, A comparative study <strong>of</strong> the<br />

thermal behaviour <strong>of</strong> circular and non-circular journal bearings, Lubrication <strong>Science</strong>, 12 (4), 329-344.<br />

9. SINGH, D. S. AND MAJUMDAR, B. C., <strong>20</strong>05, Computer-aided design <strong>of</strong> hydrodynamic journal bearings<br />

considering thermal effects, Proc. IMechE, Part J: J. Engineering Tribology, 2<strong>19</strong>, 133-143.<br />

10. SHARMA, R. K. AND PANDEY, R. K., <strong>20</strong>07, Effects <strong>of</strong> the temperature pr<strong>of</strong>ile approximations across the<br />

film thickness in Thermohydrodynamic analysis <strong>of</strong> Lubricating films”, Indian Journal <strong>of</strong> Tribology, 2 (1),<br />

27-37.<br />

11. HORI Y., <strong>20</strong>06, Hydrodynamic lubrication”, Springer-Verlag Tokyo, <strong>20</strong>06.<br />

288


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

NAVIGATION CONTROL AND LOCALIZATION OF MOBILE<br />

ROBOT<br />

Meghana S 1 and Dr. D.N Drakshayani 2<br />

1,2 Department <strong>of</strong> Mechanical Engineering, Sir M Visvesvaraya Institute <strong>of</strong> <strong>Technology</strong>, Bengaluru<br />

1 Corresponding author: megha87_s@yahoo.co.in<br />

Abstract<br />

This paper presents an experimental study on localization and navigation control based on vision system. The<br />

system is designed for a robot navigating in an indoor environment with a single web camera. A colour image<br />

segmentation method based on RGB (Red, Green, and Blue) colour information <strong>of</strong> the colour image is applied<br />

for the recognition <strong>of</strong> position and orientation <strong>of</strong> a small mobile robot. First, the lower and higher threshold<br />

values <strong>of</strong> RGB are determined for the sample colours. The colour image segmentation and processing is<br />

performed using MATLAB tool. The localization and navigation control <strong>of</strong> the robots are efficiently and<br />

accurately established by knowing the intensity <strong>of</strong> each extracted colour region. Experimental results <strong>of</strong> the<br />

colour image segmentation or threshold segmentation method applied to the recognition <strong>of</strong> an object are<br />

studied. This work proposes the navigation control <strong>of</strong> a mobile robot with inexpensive hardware.<br />

1. Introduction<br />

Autonomous mobile robots need the capability to explore, navigate and localize themselves in dynamic or<br />

unknown environments in order to suit the wide range <strong>of</strong> industrial applications. In the past two decades, a<br />

number <strong>of</strong> different approaches have been proposed to develop flexible and efficient navigation systems for<br />

manufacturing industry, based on different sensor technologies such as odometry, Inertial Navigation, Landmark<br />

Navigation, laser scanners, inertial sensors, sonar and vision [1] etc.<br />

Localization and navigation are the fundamental problems <strong>of</strong> mobile robots. In the past, a variety <strong>of</strong> approaches<br />

for mobile robot localization has been developed. They mainly differ in the techniques used to represent the<br />

belief <strong>of</strong> the robot about its current position and according to the type <strong>of</strong> sensor information that is used for<br />

localization [2]. The basic requirements for the autonomous navigation <strong>of</strong> a mobile robot are environmental<br />

recognition, path planning, driving control, and location estimation/correction capabilities [3], [4]. The location<br />

estimation and correction capabilities are practically indispensable for the autonomous mobile robot to execute<br />

the given tasks efficiently. There are two general methods for the estimation <strong>of</strong> location: 1) using deadreckoning<br />

sensors attached at the wheels and body to add the displacement to the initial position data and 2)<br />

using a camera, ultrasonic, laser, radar and/or infrared sensors to recognize and locate beacons. The former<br />

scheme, though cheap and easy to implement, is subject to the aggregate error that may result in inaccurate<br />

position data. The latter scheme has become very popular recently, as it can provide precise location data<br />

instantaneously. However, there are many factors involved in obtaining accurate location information while the<br />

mobile robot is moving [5]. To get reliable and precise location data, sensor fusion techniques [6], [7] have also<br />

been developed.<br />

When a charge-coupled device (CCD) camera is utilized under good illumination conditions, certain patterns or<br />

shapes <strong>of</strong> objects are also effective for determining the location [8], [9]. Cameras are excellent sensors in robotic<br />

systems. However, a camera being extreme sensitive to illumination variation restricts its capability. The image<br />

sensor <strong>of</strong> a camera has extremely high sensitivity to varying light illumination. The image sensor in a camera<br />

usually results in inconsistent colour data due to little illumination variation because <strong>of</strong> fixed aperture. Lighting<br />

is one <strong>of</strong> the most important considerations for any vision application. Varying intensity <strong>of</strong> light source surely<br />

makes captured image data different. Without the right type <strong>of</strong> lighting, the application will not be successful<br />

[10]. Most researchers [11], [12] focus on the indoor navigation <strong>of</strong> a mobile robot in a well-structured<br />

environment. In other words, beacons, doors, and corridor edges are utilized to estimate the current location <strong>of</strong><br />

the mobile robot.Hence in this work, the localization system based on the Infrared sensors and vision based<br />

system has been developed. It works on relative positioning technique promising with better performance and at<br />

low cost. Even though using a vision sensor or combination <strong>of</strong> vision sensor and infrared sensors can provide<br />

plenty <strong>of</strong> information about the environment, extraction <strong>of</strong> visual features for positioning is not easy.<br />

Localization is done by the identification <strong>of</strong> colours with the predefined information <strong>of</strong> their intensity for the<br />

given environment. During its operation, the robot uses its Infrared sensors to scan obstacles present in its<br />

surrounding.<br />

289


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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. Methodology<br />

The system requirements for the whole setup are; a general purpose computer with configurations which can<br />

support image processing tools like MATLAB and a web camera for capturing the image. Automation <strong>of</strong><br />

mechanical setup is driven by two stepper motors and controlled by microcontroller. In particular a computer<br />

regulates all the tasks involved in the system. The mechanical unit consisting <strong>of</strong> DC motors, IR sensors and<br />

driver circuits are used to achieve absolute localization <strong>of</strong> mobile robot and navigation control. Fig. 1 shows<br />

generic representation <strong>of</strong> mobile robot system. The detection <strong>of</strong> obstacle in the environment is done using IR<br />

technique. Information is sent to the computer through the serial port using a microcontroller computer<br />

interface. The camera captures the image <strong>of</strong> the obstacle and it is given for processing. The processing <strong>of</strong> the<br />

image is done by the algorithm using MATLAB. If the image possessed is <strong>of</strong> target colour then the signals from<br />

the microcontroller controls the mechanical unit. The input to the microcontroller is through serial interface by<br />

computer. The serial input to the microcontroller decides the behavior <strong>of</strong> the mechanical part to navigate in a<br />

particular direction and to locate itself properly.<br />

Fig.1 Generic representation <strong>of</strong> mobile robot system<br />

3. Block Diagram<br />

The biggest challenge <strong>of</strong> autonomous robot is to make the visual system to adapt to changes in the visual field<br />

environment. Robot relay on colour information for image segmentation to accomplish the goals have been<br />

identified. The block diagram <strong>of</strong> the project is as shown in Fig.2 The IR detector circuit is connected to<br />

microcontroller which detects the presence <strong>of</strong> obstacle. Microcontroller sends a signal serially to MATLAB to<br />

capture image. Computer CPU regulates and process the image captured by the web camera installed within the<br />

mechanical setup.<br />

Image<br />

acquisition<br />

system<br />

Localization /<br />

navigation control<br />

Object detection<br />

system<br />

Microcontroller<br />

RS232<br />

Computer<br />

Fig.2 Block diagram <strong>of</strong> autonomous robot system<br />

290


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The captured image is then processed by the computer. Accordingly serial data is sent from MATLAB to<br />

microcontroller. The movement <strong>of</strong> the mechanical setup is driven by DC motors. The circuit changes the<br />

potential across the DC motor thus changing the direction <strong>of</strong> the motion <strong>of</strong> the setup.<br />

4. Object Colour Detection Algorithm Based On Image Processing<br />

Several colours are as shown in Fig.3 mapped into their locations in the RGB (red, green, blue) cube, or colour<br />

space. Full intensity red, having zero green or blue components, also is positioned at a corner <strong>of</strong> the cube at<br />

location (255, 0, 0).Similarly blue, green are at (0,0,255) and (0,255,0) respectively.<br />

Fig. 3 The RGB colour cube<br />

Grayscale color space more commonly is used in color image processing. Change from RGB to grayscale is<br />

equivalent to do decoupling. Saturation is represented by threshold value. But saturation is different for different<br />

colour. The greater saturation is the more pure color.<br />

In this work initially, the target object’s color information is converted grayscale values <strong>of</strong> color model for<br />

image processing in MATLAB. Secondly set lower bound to filter out the variegated colours. The purpose <strong>of</strong><br />

the segmentation is to find the pixel, which may belong to the target colour. As the recognition algorithm is<br />

without change <strong>of</strong> illumination conditions, the pixel must belong to the target object. With the change <strong>of</strong><br />

illumination there is change in pixel which requires the change in lower bound <strong>of</strong> threshold. The following Fig.<br />

4 represents the algorithm. Object colour recognition helps in navigation control and localization.<br />

291


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig. 4 Object Detection Algorithm<br />

5. Analysis Of Colour Detection Influenced By Varying Light Illumination<br />

Precise determination <strong>of</strong> the location <strong>of</strong> a mobile robot is a fundamental requirement in controlling the mobile<br />

robot. In a planar motion, localization requires information about a robot’s position and orientation. As shown in<br />

Fig. 5, two infrared sensors mounted in front. Hence it helps in obstacle detection coming in between the path.<br />

Both Fig. 5 and 6 shows different views <strong>of</strong> robot.<br />

The designed lighting consists <strong>of</strong> two situations; minimum light intensity <strong>of</strong> room environment and higher light<br />

intensity <strong>of</strong> sunshine environment. With the change <strong>of</strong> illumination there is change in pixel values <strong>of</strong> images.<br />

292


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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig.5 Top view <strong>of</strong> mobile robot<br />

Fig.6 Front view <strong>of</strong> mobile robot<br />

For capturing images webcamera used is <strong>of</strong> low resolution with 640x480 pixels. Robot is designed to function<br />

according to the type <strong>of</strong> detected colour. Totally three colours are used. System design is such that each colour<br />

attains different functionality. Red, green, blue are used to stop, turn robot towards left and turn right<br />

respectively. Therefore, the values <strong>of</strong> RGB components <strong>of</strong> the images <strong>of</strong> objects are influenced by minimum<br />

light intensity. The minimum light intensity can be easily expressed by colored pictures like Fig. 7. Figs. 7 (a)-<br />

(c) shows the red, blue, green colours as in (a), (b) and (c) respectively.<br />

(a) (b) (c)<br />

Fig. 7 Images captured at minimum light intensity<br />

Since the sensor used is camera, digital signal obtained as a result <strong>of</strong> processed image varies depending on the<br />

light intensity <strong>of</strong> surrounding environment was observed. The higher light intensity can be easily expressed by<br />

colored pictures like Fig. 8. Figs. 8 (a)-(c) shows the red, blue, green colours as in (a), (b) and (c) respectively.<br />

293


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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

(a) (b) (c)<br />

Fig. 8 Image captured at higher light intensity<br />

Using algorithm proposed in this paper, the experimental results in different illumination conditions are shown<br />

in Fig. 7 and Fig.8. The test results are as given below in Table 1.<br />

Sl. No. Colour Minimum light<br />

intensity(Threshold )<br />

Table 1. Test results<br />

Higher light<br />

intensity(Threshold )<br />

Action taken<br />

By robot<br />

1 Red Any Value less than 225 Any Value less than 255 Localization<br />

2 Blue Below 150 Below 175 Turn towards<br />

Right<br />

3 Green Below 100 Below 125 Turn towards light<br />

As per Table 1, the threshold values are more for higher light intensity when compared to that <strong>of</strong> minimum light<br />

intensity environmental conditions. According to overall results, higher the light intensity higher values <strong>of</strong><br />

threshold can be obtained.<br />

6. Conclusion<br />

In connection with the demand <strong>of</strong> the robot application, this work proposes colour image detection method for<br />

target object recognition. Using colour image segmentation algorithm in MATLAB to find target object is a<br />

slow process. From the tests it’s recognized that estimation accuracy depends on object colour detection. The<br />

effectiveness <strong>of</strong> this algorithm was verified through real experiments. Autonomous robot localization and<br />

functionality depends on the image processing <strong>of</strong> data taken by the camera. Data can be greatly affected by light<br />

energy received from the environment. It can be concluded from the test results; light illumination problem can<br />

be overcome by adjusting the threshold value and improve the robustness and adaptability <strong>of</strong> the system. Realtime<br />

image processing and camera calibration are future research work needed to improve the estimation<br />

accuracy for the mobile robot.<br />

References<br />

[1] J. BORENSTEIN, H.R. EVERETT, L. FENG, AND D. WEHE, Mobile Robot Positioning & Sensors and<br />

Techniques, Invited paper for the Journal <strong>of</strong> Robotic Systems, Special Issue on Mobile Robots. 14(4),. 231<br />

– 249.<br />

[2] SOOYONG LEE AND JAE-BOK SONG, <strong>20</strong>05, Mobile Robot Localization using Range Sensors :<br />

Consecutive Scanning and Cooperative Scanning“, International Journal <strong>of</strong> Control, Automation, and<br />

Systems, 3(1), 1-14, March <strong>20</strong>05<br />

[3] R. A. BROOKS, <strong>19</strong>86, A robust layered control system for a mobile robot, IEEE J. Robot. Automat., vol.<br />

RA-2, 14–23.<br />

[4] Y. NAKAMURA, <strong>19</strong>91, Advanced Robotics: Redundancy and Optimization. Reading, MA: Addison-<br />

Wesley,<br />

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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[5] R. SIM AND G. DUDEK,<strong>19</strong>99, Learning visual landmarks for pose estimation, in Proc. <strong>19</strong>99 IEEE Int.<br />

Conf. Robotics and Automation, <strong>19</strong>72–<strong>19</strong>78.<br />

[6] N. Ayache and O. D. Faugeras,<strong>19</strong>89,Maintaining representations <strong>of</strong> the environment <strong>of</strong> a mobile robot,<br />

IEEE Trans. Robot. Automat.,. 5 804–8<strong>19</strong>.<br />

[7] H. ZHOU AND S. SAKANE, <strong>20</strong>01, Sensor planning for mobile robot localization based on probabilistic<br />

inference using Bayesian network,” in Proc. 4 th IEEE Int. Symp. Assembly and Task Planning, 7–12.<br />

[8] S. SEGVIC AND S. RIBARIC, <strong>20</strong>01, Determining the absolute orientation in a corridor using projective<br />

geometry and active vision,” IEEE Trans. Ind. Electron., 48,. 696–710.<br />

[9] N. STROBEL, S. SPORS, AND R. RABENSTEIN, <strong>20</strong>01, Joint audio-video object localization and<br />

tracking,” IEEE Signal Processing Mag., 18, pp. 22–31.<br />

[10] KUO-YANG TU,<strong>20</strong>09, Analysis <strong>of</strong> Camera’s Images Influenced by Varying Light Illumination for Design<br />

<strong>of</strong> Colour Segmentation, Journal <strong>of</strong> Information <strong>Science</strong> And Engineering 25, 1885-1899.<br />

[11] H. CHOSET AND K. NAGATANI,<strong>20</strong>01, Topological simultaneous localization and mapping (SLAM):<br />

Toward exact localization without explicit localization, IEEE Trans. Robot. Automat., 17, 125–137.<br />

[12] P. HOPPERNOT AND E. COLLE, <strong>20</strong>01, Localization and control <strong>of</strong> a rehabilitation mobile robot by close<br />

human-machine cooperation,” IEEE Trans. Neural Syst. Rehab. Eng., 9, 181–<strong>19</strong>0.<br />

295


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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

FUZZY CONTROL OF SEMI-ACTIVE QUARTER CAR SUSPENSION<br />

SYSTEM WITH MR DAMPER<br />

Devdutt 1 , Dr. M.L. Aggarwal 2<br />

1 Research Scholar, <strong>YMCA</strong>UST, Faridabad<br />

2 Pr<strong>of</strong>essor, <strong>YMCA</strong>UST, Faridabad<br />

1 Email: devdutt.fet@mriu.edu.in<br />

Abstract<br />

In present paper effectiveness <strong>of</strong> fuzzy controller in semi-active quarter car suspension system having magnetorheological<br />

(MR) damper is studied. For experimental work, cyclic excitation is applied to an MR damper<br />

prototype using MTS machine to generate Force- Displacement and Force-Velocity curves. A fuzzy controller is<br />

designed, working on the feedback data, based on measurable sprung mass velocity and suspension velocity.<br />

Finally, a quarter vehicle semi-active suspension model having MR damper is considered for comparative<br />

analysis <strong>of</strong> simulation work under various road excitations to evaluate the performance <strong>of</strong> semi-active<br />

suspension system with fuzzy controller compared to passive suspension system.<br />

Keywords: Quarter car model, semi-active suspension, MR Damper, Fuzzy logic controller<br />

Introduction<br />

In today’s competitive industrial environment & customer’s high requirements related to ride comfort, vehicle<br />

safety and road handling ability, automotive manufacturers are struggling hard to produce high quality vehicles<br />

to meet customer’s expectations. Since vehicles having passive suspension system completely relies on the<br />

working <strong>of</strong> non-controllable conventional components such as springs and dampers to control vehicle road input<br />

vibrations during traveling. A good automotive suspension system needs to control the sprung mass movement<br />

together with acceleration and generate minimum suspension deflection to keep tires in contact with the uneven<br />

road surface. Hard spring and damper can provide better road holding ability to vehicle but passenger ride<br />

comfort experience gets worse. Thus, these two conflicting requirements related to ride comfort and road holding<br />

ability need to be controlled by the optimum design <strong>of</strong> concerned elements. Advanced technology related to<br />

semi-active and active suspension systems is playing crucial role to fulfill the above said demands. Comparative<br />

results related to supplied energy and working frequency range <strong>of</strong> the actuators for the three types <strong>of</strong> suspension<br />

systems is shown in Fig. 1 as per [1].<br />

Fig.1: Comparison between passive, adaptive, semi-active and active systems.<br />

These advanced suspension systems fulfill the requirements up to maximum level by preventing the road induced<br />

disturbances to affect the passenger’s ride comfort as well as provide smooth riding and good drive experience.<br />

Thus, this latest technology related to vehicle suspension systems has attracted the industries and researchers in<br />

the last few decades for commercial and scientific reasons. Practically, active suspension system is assembled<br />

with sensors and actuators, maximizing its working performance but real world application <strong>of</strong> this concept is<br />

restricted or limited due to expensive components and large power requirements. On the other hand, semi-active<br />

suspension systems are attractive choice for industries due to less expensiveness and can provide comparable or<br />

desired performance in place <strong>of</strong> active suspension related technology.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Semi-active suspension system performance is dependent on the controllability <strong>of</strong> smart part known as<br />

magnetorhelogical (MR) or electro-rheological (ER) dampers. Magneto-rheological (MR) dampers provide a<br />

base for promising future related to vibration control <strong>of</strong> semi-active suspension systems. Power requirement by<br />

this controllable MR damper is low while response is quick to provide output results is a few milliseconds. The<br />

alignment behavior <strong>of</strong> magnetizable suspended particles is related to the application <strong>of</strong> electric current to MR<br />

damper [Fig. 2].<br />

Fig. 2: Illustration <strong>of</strong> MR Fluid Activation behavior:<br />

(a) Without Magnetic Field (b) Initial stage during Magnetic Field application (c) Fully developed stage<br />

Latest technological developments in the field <strong>of</strong> MR fluids have forced the automotive manufactures to choose<br />

the concerned fluid compared to electro-rheological fluid for the application in MR dampers [2-4]. Several<br />

attractive characteristics <strong>of</strong> MR damper which make them suitable for semi-active suspension system are quick<br />

response to the applied controllable magnetic field, compact size and reliability i.e. can act as a fail safe device in<br />

form <strong>of</strong> passive damper in case <strong>of</strong> power failure.<br />

Many researchers have presented the data related to the useful and effective performance <strong>of</strong> MR damper<br />

assembled in semi-active suspension system [5-7]. Duym studied the physical model <strong>of</strong> a shock absorber related<br />

to the automotive dynamic simulation [8]. Guclu presented his study results about the dynamic property <strong>of</strong> a<br />

vehicle model by considering effect <strong>of</strong> dry friction on the dampers [9]. Choi et al. studied the practical<br />

applicability <strong>of</strong> a cylindrical MR damper using hardware-in-loop simulation method [10].Nguyen et al. used<br />

finite element analysis technique to study an optimal design <strong>of</strong> a MR damper [11].<br />

2. Mathematical Modeling <strong>of</strong> Quarter Car Model<br />

In present study, a simple quarter-car suspension model with two-degree-<strong>of</strong>-freedom (2DOF) system<br />

representing one-fourth mass <strong>of</strong> car body, suspension parts and single tyre with wheel is analyzed (Fig. 3) by<br />

considering vertical movement but neglecting pitching and rolling motion <strong>of</strong> mentioned system. It shows an<br />

unsprung mass, indicating the quarter body mass <strong>of</strong> car, the lower unsprung mass and the wheel mass.<br />

Fig.3: Semi-active Quarter car suspension model<br />

The equations <strong>of</strong> vertical direction motion for the quarter car suspension system i.e. sprung mass (quarter car<br />

body mass) and unsprung mass (suspension parts) can be represented by applying Newton’s second law <strong>of</strong><br />

motion with the help <strong>of</strong> following mathematical equations:<br />

297


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

where z s and z u represents the vertical displacement <strong>of</strong> the sprung and unsprung mass respectively whereas z r is<br />

road displacement i.e. road pr<strong>of</strong>ile variation input and F MR is the controllable damping force generated by MR<br />

damper.<br />

Let z = [ z s z u ] T . Then Eq. (1) can be presented in matrix form as :<br />

where<br />

Let<br />

. Then Eq. (2) can be written in state space as:<br />

where<br />

Table 1: Quarter Car Model Parameters with Values<br />

Parameter Symbol Value<br />

Sprung Mass m s 425 Kg<br />

Unsprung Mass m u 60 Kg<br />

Spring Stiffness k s 60 kN/m<br />

Wheel Stiffness k t 181 kN/m<br />

Damper C 0 1000 N.s/m<br />

3. MR Damper experimental work and results<br />

MR damper’s cylindrical tube is filled with controllable magnetorheological fluid having randomly suspended<br />

micron-sized particles. Under the influence <strong>of</strong> externally applied magnetic field these particles shows<br />

polarization effect leading to the formation <strong>of</strong> chain like structures which changes the fluid behavior from<br />

viscous state to semi-solid state in a few milliseconds. MR damper shows highly non-linear effect related to the<br />

damping force with the variation and application <strong>of</strong> applied current. This sudden change in damper force<br />

generation characteristics is due to alignment <strong>of</strong> micron-sized magnetizable particles in the form <strong>of</strong> chain like<br />

structures perpendicular to the fluid flow as soon as the current is applied.<br />

Fig. 4 MR damper cross-sectional view<br />

298


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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The damping force generated by MR damper can be obtained using mathematical formulations as follows [12-<br />

13] :<br />

Where Ap represents working area <strong>of</strong> the piston, η is the viscosity <strong>of</strong> MR fluid in the absence <strong>of</strong> magnetic field,<br />

is the length <strong>of</strong> each damping duct, R 2 is the inner radius <strong>of</strong> the circular cylindrical orifice, R 1 is the outer<br />

radius <strong>of</strong> the orifice.<br />

The applied current is to be set within certain allowable range for safe working and generation <strong>of</strong> damping force<br />

within acceptable limits for MR damper. Fig. 5 shows the measurement results <strong>of</strong> force-displacement (f-d) and<br />

force-velocity (f-v) relation when the test conditions are: 1Hz sinusoidal excitation and amplitude <strong>of</strong> 4 mm under<br />

the influence <strong>of</strong> supplied current range between 0 to 0.75 A.<br />

Fig. 5: Experimental results <strong>of</strong> MR damper:<br />

(a) Damping force vs. time; (b) Damping force vs. piston displacement; (c) Damping force vs. velocity<br />

Due to its attractive characteristics related to the application in automotive field, MR dampers are top choice but<br />

their inherent nonlinear hysteretic nature and nonlinear dynamic uncertainty make it typical for the developer or<br />

control engineer to select a proper control algorithm for the application in automotive suspension system. To<br />

analyze and compare the behavior as well as performance characteristics <strong>of</strong> MR dampers, many models have<br />

been considered. These include the neural network model proposed by Chang and Roschke [14-15], polynomial<br />

model [16], fuzzy model [17] and other methods [18-<strong>20</strong>]. Therefore, development <strong>of</strong> effective model <strong>of</strong> MR<br />

damper is needed for working with nonlinear behaviour and inverse calculation <strong>of</strong> control current when damping<br />

force is known. The selected polynomial model in present study was put forward by Choi et al. [21], which<br />

provides an easy, reliable and effective method to use the experimental data, obtained by testing MR damper.<br />

299


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4. Fuzzy Logic control system for quarter-car model<br />

In present research work, the aim is to provide maximum ride comfort to riders by minimizing the vibration<br />

magnitude <strong>of</strong> passenger seat and automotive structure as far as possible by selecting and implementing the<br />

suitable control system. Fuzzy logic is based on the fuzzy set theory put forward by Lotfi Zadeh [22-23] which<br />

emerged as a powerful and popular tool for engineers & scientists for use in nonlinear dynamic systems through<br />

implementation <strong>of</strong> human knowledge and practical experience. In present case the main objective <strong>of</strong> FLC design<br />

is to achieve desired control performance related to suspension movement for the changing road and load<br />

disturbances.<br />

There are four main components <strong>of</strong> a FLC making it to work as per expert’s knowledge or designer’s process<br />

requirements:<br />

1. Fuzzification interface changes or modifies the input data from crisp or numerical values into fuzzy values for<br />

interpretation and comparison in next processing.<br />

2. Rule base contains the knowledge in the form <strong>of</strong> If-Then rules related to achieving or providing the desired or<br />

best system performance.<br />

3. Inference Engine selects the best control rule for the application to control the plant activities at the current<br />

time.<br />

4. Defuzzification interface converts the fuzzy results decided by the inference engine into real mathematical<br />

values and supplies to the plant.<br />

Fig. 6: Application <strong>of</strong> FLC controller in Quarter car model.<br />

In present work Mamdani method is selected in fuzzy inference system whereas “max-min” inference method is<br />

selected as aggregation operator, being mostly used and simplest method. For defuzzification stage, “centroid”<br />

method is employed where “center <strong>of</strong> mass” <strong>of</strong> the output generates a numerical value i.e. transformation <strong>of</strong><br />

linguistic variables to crisp values.<br />

The two input to the selected fuzzy logic controller are sprung mass velocity and the suspension velocity<br />

(velocity difference between sprung and unsprung mass) while the controller output is the damping value (C ) <strong>of</strong><br />

the semi-active MR damper.<br />

Fig. 7: Number <strong>of</strong> Inputs and Output for designing Fuzzy Inference System for FLC<br />

300


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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The labels used for linguistic variables are mentioned as: NL (Negative Large), NM (Negative Medium), NS<br />

(Negative Small), ZE (Zero), PS (Positive Small), PM (Positive Medium) and PL (Positive Large). Implemented<br />

fuzzy control rules are presented in Fig. 8 to achieve maximum passenger ride comfort including driving safety<br />

and vehicle handling.<br />

Fig. 8: Fuzzy Logic control rules<br />

Fig. 9: Fuzzy membership functions<br />

5. Simulation Work<br />

Practically, road surface pr<strong>of</strong>ile is uneven i.e. varies from place to place having bumps and holes. When a vehicle<br />

passes through such type <strong>of</strong> roads, the excitation input generates vibrations in the whole vehicle body.<br />

Effectiveness and proper choice <strong>of</strong> controller system depends upon suspension system behavior on the input<br />

parameters <strong>of</strong> a real road condition. In present case, vehicle suspension effectiveness is studied by considering<br />

the simple functions such as step function, sine wave function, cosine wave function and random excitations for<br />

simulation purpose as the input disturbances from the road surface. In every case the vehicle forward velocity is<br />

assumed to be constant.<br />

Case 1: Step Input<br />

In second case, the step input excites the dynamics <strong>of</strong> the quarter car suspension model as the vehicle hitting it on<br />

the real road conditions like bump input. The amplitude for the present step input case is having initial value <strong>of</strong><br />

zero and a final value <strong>of</strong> 10 cm.<br />

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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Case 2: Bump Input<br />

In first case, the road disturbance is considered in the form <strong>of</strong> bump represented by the following equation:<br />

where ‘a’ denotes the amplitude <strong>of</strong> the bump.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

6. Conclusion<br />

In present study, effectiveness <strong>of</strong> MR damper as well as fuzzy controller in semi-active suspension system was<br />

investigated. The experimental results related to force-displacement and force-velocity curves indicate the<br />

variation <strong>of</strong> damping force with change in magnitude <strong>of</strong> supplied current. Simulation results, taking quarter car<br />

model into consideration demonstrates that the performance <strong>of</strong> selected controller in semi-active suspension<br />

system is better in handling acceleration and displacement <strong>of</strong> sprung mass under various road conditions<br />

compared to passive suspension system. Thus, MR damper and Fuzzy controller presents a suitable choice for<br />

use in suspension system to attain better results in terms <strong>of</strong> passenger ride comfort and vehicle handling.<br />

References<br />

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2. J.D.Carlson, and K.D. Weiss, A growing attraction to magnetic fluids, J. Machine Design, 66(15), (<strong>19</strong>94)<br />

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3. J.D. Carlson, and M.J. Chrzan, Magnetorheological Fluid Dampers, U.S. Patent 5277281, <strong>19</strong>94.<br />

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9. Guclu, R.: Fuzzy control <strong>of</strong> seat vibrations <strong>of</strong> a non-linear full vehicle model. Nonlinear Dyn. 40, 21-34<br />

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16. S.B. Choi, S.K. Lee, Y.P. Park, A hysteresis model for the field-dependent damping force <strong>of</strong> a<br />

magnetorheological damper, Journal <strong>of</strong> Sound and Vibration 245 (2) (<strong>20</strong>01) 375–383.<br />

17. K.C.Schurter, P.N. Roschke, Fuzzy modeling <strong>of</strong> a magnetorheological damper using ANFIS, in:<br />

Proceedings <strong>of</strong> the IEEE International Conference on Fuzzy Systems, <strong>20</strong>00, pp. 122–127.<br />

18. Ahmadian, M., Simon, D.E.: An analytical and experimental evaluation <strong>of</strong> magneto rheological<br />

suspensions for heavy trucks. Veh. Syst. Dyn. 37, 38–49 (<strong>20</strong>02)<br />

<strong>19</strong>. Ahmadian, M., Vahdati, N.: Transient dynamics <strong>of</strong> semiactive suspensions with hybrid control. J. Intell.<br />

Mater. Syst. Struct. 17(2), 145–153 (<strong>20</strong>06)<br />

<strong>20</strong>. Wang, E.R., Ma, X.Q., Rakheja, S., Su, C.Y.: Semi-active control <strong>of</strong> vehicle vibration with MR-dampers.<br />

In: Proceedings <strong>of</strong> the 42nd IEEE Conference on Decision and Control, Maui, HI, December (<strong>20</strong>03)<br />

21. Choi, S.B., Lee, H.S., Park, Y.P.: H-infinity control performance <strong>of</strong> a full-vehicle suspension featuring<br />

magnetorheological dampers. Veh. Syst. Dyn. 38(5), 341–360 (<strong>20</strong>02).<br />

22. Zadeh L.A.: Fuzzy sets. Information and Control. <strong>19</strong>65. 8: pp.338–353.<br />

23. Zadeh L.A.: Fuzzy logic and its application to approximate reasoning. Information Processing 74, Proc.<br />

IFIP Congr. <strong>19</strong>74 (3), pp. 591–594.<br />

304


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

STRESS DISTRIBUTION ANALYSIS OF A ROTATING HYPER<br />

ELASTIC VANE WITH THE FINITE ELEMENT METHOD<br />

Pratik D Upadhyay 1 ,Akshay J Patel 2<br />

1 B.Tech Mechanical Engineering, SASTRA <strong>University</strong>, Tamil Nadu, India, Email: upadhyay.pratik24@gmail.com<br />

2 Sr. Development Engineer, Xylem Water Solutions, Gujarat, India, Email:akshay.patel@xyleminc.com<br />

Abstract<br />

Improving the Impeller life is one <strong>of</strong> the most significant steps in improving the sustainability <strong>of</strong> the Flexible Impeller Pump.<br />

For the same purpose it is necessary to know the stress distribution on the impeller vane at specific conditions when<br />

failure is most likely to occur. Also it is necessary to identify the specific locations <strong>of</strong> failure on the vane. This process is<br />

difficult to carry out by hand calculation or by experimentation due the hyper elastic nature <strong>of</strong> the impeller<br />

material and also due to the high running speed <strong>of</strong> the pump. This paper proposes a solution to the above problem by<br />

simplification <strong>of</strong> the impeller geometry and subsequent discretization <strong>of</strong> the equations involved in vane deformation<br />

using the finite element method. This approach gives us stress distributions and points <strong>of</strong> expected failure over the entire<br />

vane geometry at instant when the pump starts. The points <strong>of</strong> failure are then experimentally verified.<br />

1. Introduction<br />

The flexible impeller pump is a relatively unknown product used primarily in the food processing and marine industries.<br />

This pump has a polymer impeller which is deformed during rotation by an internal cam pr<strong>of</strong>ile. The pump uses the change in<br />

impeller shape during deformation to get the pumping action and cause transport <strong>of</strong> fluids. The constantly improving<br />

industrial technology has created newer applications for these types <strong>of</strong> pumps which require longer pump sustainability<br />

and lower current consumptions. It is obvious that the impeller characteristics such as deformation, material<br />

stiffness and the speed <strong>of</strong> rotation control the life <strong>of</strong> impeller as well as the current consumption. Thus to improve the<br />

impeller life it is necessary to first have an in-depth understanding <strong>of</strong> the stress distributions over the impeller. Furthermore it<br />

is necessary to identify the instants <strong>of</strong> time during the running <strong>of</strong> the pump when the stress is highest and failure is most likely.<br />

One way to do it would be to use experimental methods to test the pump for failure <strong>of</strong> impeller in various conditions.<br />

However this is a lengthy and expensive procedure without prior knowledge <strong>of</strong> expected failure times or points <strong>of</strong> failure<br />

extensive testing would be required and the results might still be inconclusive. Also this problem does not lend itself easily to<br />

hand calculations due to the complex nature <strong>of</strong> the geometry and the multiple forces involved. Thus the best<br />

possible solution is to carry out a finite element analysis to find out the stress distributions and the expected locations <strong>of</strong><br />

failure and then verify this data experimentally.<br />

PROBLEM DESCRIPTION<br />

Fig 1. Actual Impeller Geometry<br />

The above shown geometry is the actual shape <strong>of</strong> the impeller; this impeller rotates at 2800 rpm, and the vane<br />

deformation takes place by contact with a stationary cam pr<strong>of</strong>ile inside the pump bore. Figure 2 and Figure 3<br />

together illustrate the pump construction and situation during operation <strong>of</strong> the pump.<br />

305


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig 2a. Pump assembly, parts 1, 4, 6 are in contact with the impeller and contribute to friction<br />

Fig 2b .Front view <strong>of</strong> pump bore<br />

The condition <strong>of</strong> maximum stress is explained below:<br />

i. The maximum stresses experienced are during the time when the pump runs dry.<br />

ii. The current draw is maximum at the start <strong>of</strong> the pump. This data is noted from prior performance tests<br />

carried out on the pump. The impeller will have to overcome static friction from 3 different surfaces when it<br />

is tending to move.<br />

iii. When the impeller starts from rest the inertia resistance will be the greatest.<br />

Thus from above observations it can be inferred that to find the maximum stress levels the pump should be simulated<br />

in a run dry condition. The run dry condition is most closely simulated during the instant that the pump is about to<br />

start running (i.e. there is no fluid in the pump yet and the impeller is tending to move)<br />

From the above observations we infer the following boundary conditions and constraints. Boundary Conditions and<br />

Forces Applied:<br />

i. Impeller is stationary<br />

ii. The tip <strong>of</strong> the vane is in contact with the cam surface, back wall <strong>of</strong> the body, and the face <strong>of</strong> the end cover.<br />

iii. Motor torque <strong>of</strong> 549 N mm calculated by power ratings <strong>of</strong> the impeller<br />

306


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

FORMULATION OF THE MATERIAL MODEL:<br />

Table 1 Material property data for polyurethane<br />

The material to be used for this case is Polyurethane (PU) foam. Polyurethane shows Hyper elastic Behavior in the<br />

temperature range <strong>of</strong> <strong>20</strong>°C - 30°C, we have the material data as shown in table. 1 and thus a simple neo-hookean<br />

formulation involving two coefficients will be used<br />

The [1] 1 neo-hookean constitutive law (eq. 7) is derived by the use <strong>of</strong> strain energy conservation equation .The<br />

summary <strong>of</strong> governing equations written above for the material model is stated as follows:<br />

i. The shape <strong>of</strong> the solid in its unloaded condition (this will be taken as the stress free reference<br />

configuration) (Eq. 1)<br />

ii. A body force distribution b acting on the solid(Eq. 5)<br />

iii. Boundary conditions, specifying displacements on a portion (Eq. 6)<br />

iv. The material constants , for the Neo-Hookean constitutive law.<br />

v. The mass density <strong>of</strong> the solid in its reference configuration<br />

1 [1] Bower A.F. “Applied Solid Mechanics”<br />

307


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The coefficients , are found by using the young’s modulus (E) and Poisson ratio (ν) in the equations below :<br />

These equations are discretized using a suitable scheme and then a convenient numerical method may be used to<br />

solve these equations.<br />

DEVELOPMENT OF THE MODEL<br />

Fig 3 Simplified Vane Geometry<br />

The simplification is carried out as follows:<br />

i. The vanes are symmetrically placed about all the three axes and thus the deformation <strong>of</strong> each vane will be similar<br />

at a given point inside the pump bore.<br />

ii. Further, the material is isotropic.<br />

iii. The above observations are sufficient to simplify the geometry by considering only one vane.<br />

iv. Also unnecessary rounds, embossing etc are removed for better meshing.<br />

Thus to find the maximum stress distributions over the whole impeller we have to analyze the motions <strong>of</strong> a single<br />

vane at the instant when motion starts.<br />

The significant point to be kept in mind is that the vane is just tending to move, thus the friction at contact surfaces is<br />

static. To model contact, infinite friction is used.<br />

The loads are as follows:<br />

i. A moment load <strong>of</strong> 549 mm-N at center <strong>of</strong> the impeller calculated using the motor torque data and the<br />

impeller radius.<br />

ii. Pressure loading on vane sides to simulate pressure differential.<br />

iii. Vane tip, base <strong>of</strong> vane and one face <strong>of</strong> the vane are constrained to simulate friction<br />

The s<strong>of</strong>tware used is Pro/Mechanica and the geometry is built in Pro/E wildfire5.0.The maximum element size is<br />

1mm and thus about 5 million quad elements are formed. The simulation is run on a 4 core 8GB RAM system and<br />

takes about 48hrs to complete.<br />

308


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

RESULTS AND INTERPRETATION<br />

Fig 4 various loads and constraints applied to the simplified geometry<br />

Fig 5 Failure index at different locations on the vane.<br />

Fig 5. indicates the failure index over the whole geometry. The failure index indicates the likelihood <strong>of</strong> failure at<br />

different locations on the vane. The higher failure probability regions are indicated in red.<br />

309


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

These regions are at the joint <strong>of</strong> the vane and the impeller hub and approximately at 1/3 length along the vane tip. It<br />

may also be noted that other areas <strong>of</strong> the vane, such as the vane face are relatively unaffected and thus do not<br />

fracture.<br />

This analysis is verified in dry run simulations where impeller vanes are known to break from the above two regions<br />

only<br />

Fig 6 displacement <strong>of</strong> vane with undisplaced position overlay<br />

Fig 6 indicates the relative displacement magnitude w.r.t the original position over the whole geometry. It is seen that<br />

the impeller vane first starts moving from one face because <strong>of</strong> unequal friction coefficients.<br />

Fig 7 indicates the stress distribution over the whole geometry. A higher stress at a point indicates a higher chance <strong>of</strong><br />

failure at that point. The .higher stress regions are indicated in red and yellow<br />

These regions are at the joint <strong>of</strong> the vane and the impeller hub, along the impeller face and approximately at 1/3<br />

length along the vane tip. A possible cause <strong>of</strong> this high stress may be the frictional forces as well torsion effect <strong>of</strong> the<br />

moment load from the motor.<br />

This analysis is verified in dry run simulations where impeller vanes are known to break from the above two regions<br />

only.<br />

310


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig 7 Von Mises stress on the vane<br />

CONCLUSIONS AND FUTURE SCOPE<br />

i. This analysis has helped us identify the weak points in the vane design and thus adequate stress relieving<br />

measures may be incorporated into the design for a better sustainability.<br />

ii.<br />

iii.<br />

iv.<br />

A relation between the stress and the current consumption may be found by experimentation and further<br />

analysis, thus allowing for a better pump design.<br />

Further analysis may be carried out to determine the effect <strong>of</strong> forces during rotation.<br />

The above analysis if carried out will allow us to take into consideration fatigue and cyclic loading thus<br />

allowing us to predict the life <strong>of</strong> the impeller accurately<br />

311


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

STUDY OF UNCOILING IN SUSPENSION SPRINGS ITS EFFECTS<br />

Kushal A Jolapara 1* , Adhip Puttaraj 2 , Abhishek Chatterjee 3<br />

1* Kushal A Jolapara, B.E (Mech). Production Manager, KushalPolycoats, Bangalore. PH: +91 9900780037. E-<br />

mail: bollerophon@gmail.com<br />

2 AdhipPuttaraj, B.E (Mech) Administrator, Manasa Hospital, Bangalore. PH: +91 98867<strong>20</strong>987. E-mail: adhipputtaraj@gmail.com<br />

3 AbhishekChatterjee, B.E (Mech), Project Co-ordinator, CBRE Pvt Ltd, Bangalore, PH: +91 8095813521 E-<br />

mail: abhishek.chatterjee23@gmail.com<br />

Abstract<br />

The uncoiling effect is evident when motion <strong>of</strong> one end <strong>of</strong> the spring is completely constrained and the other end<br />

is allowed to rotate freely during compression.The free rotation results in a change in spring attributes like rate<br />

<strong>of</strong> the spring and stresses generated within the spring. This has an obvious impact on the working and life <strong>of</strong> the<br />

spring. This paper showcases the work in a project, carried out to determine the extent <strong>of</strong> variation in load rates<br />

between helical suspension springs operating under both the cases (coiling restricted and coiling unrestricted).<br />

The experimental and FEM data showed a variation in the load rate as well as rotational movement in the end<br />

coil. Based on the study, it was concluded that, firstly, there is a definite change in spring performance under the<br />

two conditions. Secondly, during the design process and failure analysis, uncoiling is not considered. Lastly,<br />

testing processes need to be standardized as certain load machines have a rotating bottom table to allow<br />

uncoiling and some do not, resulting in different readings in a test for the same spring in different machines.<br />

Keywords—Uncoiling effect, helical suspension springs, static loading, load, deflection, shear stress, uncoiling<br />

angle.<br />

1. INTRODUCTION<br />

Sixteenth century wagons and carriages tried to solve the problem <strong>of</strong> feeling every bump on the road by slinging<br />

the carriage body from leather straps attached to four posts <strong>of</strong> a chassis that looked like an upturned table. Because<br />

the carriage body was suspended from the chassis, the system became to be known as a “suspension”. This<br />

term is still used to describe the mechanisms built for this purpose. The slung body suspension was not a true<br />

spring system but it did enable the body and wheels <strong>of</strong> the carriage to move independently. By the time powered<br />

vehicles hit the road, more efficient spring systems were developed so that passengers could experience a smooth<br />

ride. The suspension system is a setup that supports the weight, absorbs and dampens shock and helps maintain<br />

tire contact with the road.<br />

FIG. 1 SUSPENSION STRUT<br />

A spring is a member used to convert and store mechanical energy, i.e.; Kinetic energy to Potential energy and<br />

vice versa. Theworking <strong>of</strong> a spring is based on the elastic properties <strong>of</strong> the material used[1, 2]. This means that<br />

within the elastic limit, a material will try to withstand any change in its shape and dimensions and try to regain<br />

its original shape. There are stresses created within the body <strong>of</strong> the object which tends to counter act the force<br />

causing deformation. The manner in which a helical spring structure behaves under forces acting on it is also<br />

complex. When a compressive force (compression load) is applied on helical springs, they undergo plastic deformation<br />

and store the energy. This deformation is a decrease in the pitch distance and hence the length <strong>of</strong> the<br />

spring.<br />

312


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Most commonly used suspension springs are the open coil helical springs [3] (Fig. 1). They <strong>of</strong>fer resistance to<br />

compressive force. Round wire is the material is commonly used to make the springs. This is because it is readily<br />

available and adaptable to standard manufacturing methods. Square, rectangular or special shaped wires are used<br />

in some cases. When the diameter <strong>of</strong> the spring is constant throughout, it is called straight helical. There are<br />

types where the diameter <strong>of</strong> the spring varies. These are tapered or conical springs.<br />

2. THE UNCOILING PHENOMENON<br />

In the design <strong>of</strong> helical compression springs, the coiling/uncoiling <strong>of</strong> active coils during compression <strong>of</strong> the<br />

spring is not accounted for [4, 5, 6]. Although this concept forms the basis for the function <strong>of</strong> torsional springs, it<br />

is ignored during the design <strong>of</strong> helical compression springs. The uncoiling effect is evident when motion <strong>of</strong> one<br />

end <strong>of</strong> the spring is completely constrained and the other end is allowed to rotate freely during compression. This<br />

also results in torsional forces on supporting structures <strong>of</strong> the spring. The free rotation results in a change in<br />

spring attributes like rate <strong>of</strong> the spring and stresses generated within the spring.This has an obvious impact on the<br />

working and life <strong>of</strong> the spring.<br />

FIG. 2 UNCOILING ANGLE θ<br />

Green line: Position <strong>of</strong> free end with rotation constrained<br />

Pink line: Position <strong>of</strong> free end without constraintment<br />

This paper showcases the work in a project [7], carried out to determine the extent <strong>of</strong> variation in load rates between<br />

helical suspension springs operating under both the cases (coiling restricted and coiling unrestricted). The<br />

work involved FEM analysis and experimental testing on springs, carried out at a leading spring manufacturer’s<br />

premises. A fixture was designed and built to allow and measure the extent <strong>of</strong> uncoiling in springs. The experimental<br />

and FEM data showed a variation in the load rate as well as rotational movement in the end coil. Uncoiling<br />

angles ranging between 10º ~ 14º and load variation <strong>of</strong> up to 10% were noted at same compression height<br />

experimentally.<br />

When a compressive force (compression load) is applied on helical springs, they undergo plastic deformation and<br />

store the energy. This deformation is a decrease in the pitch distance and hence the length <strong>of</strong> the spring. It also<br />

causes a little observed angular movement <strong>of</strong> the coils around the axis <strong>of</strong> the spring or uncoiling <strong>of</strong> the helix (Fig.<br />

2). In automobiles, this effect is given a free reign by providing a thrust bearing at one <strong>of</strong> the ends to allow free<br />

rotation <strong>of</strong> the spring end [8].<br />

By comparing the same suspension spring under different conditions – uncoiling restricted and uncoiling unrestricted,<br />

it was determined that uncoiling has a significant effect on the functioning <strong>of</strong> the spring.<br />

Currently, manufacturers ignore this effect while designing the spring and testing it. The project work has been to<br />

determine:<br />

• The variation in load between free and restricted springs<br />

• The variation in stresses produced<br />

• The extent to which the end coil turns during free uncoiling compression<br />

Five different springs were chosen. Experimental analysis was done on all 5 springs. And FEM analysis was<br />

done on one spring. The experimental analysis was carried on a Larson testing machine. The FEM analysis was<br />

carried out on s<strong>of</strong>tware called NASTRAN. The 3D modeling was done on SOLID WORKS <strong>20</strong>06.<br />

313


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

FIG. 3 DESIGN SOFTWARE MATH PAGE<br />

3 SUSPENSION SPRING DESIGN<br />

Manufacture <strong>of</strong> an automobile suspension springs involves a high level <strong>of</strong> designing and testing [9, 10]. This is<br />

needed because the spring is a critical component in the working <strong>of</strong> an automobile and its failure can be disastrous.<br />

The spring is a member which has to undergo constant load as well as fatigue loading. Hence it is essential<br />

to be certain about the performance <strong>of</strong> the spring before manufacturing it on a large scale. With advances in testing<br />

machines and s<strong>of</strong>tware tools like 3D drawing packages (SOLID WORKS <strong>20</strong>06) and FEM analysis packages<br />

(ABACUS, NASTRAN), spring design has become more precise, reliable and accurate. The design process followed<br />

at Stumpp, Schuele&Somappa Pvt. Ltd. is at par with international standards [11]. The steps involved are<br />

as follows:<br />

1. Initially the customer drawings for the suspension setup are studied. Data such as inner diameter, length,<br />

outer diameter, no. <strong>of</strong> fatigue cycles, bump load and height, unladen load and height etc. are collected from<br />

the customer.<br />

2. This collected data is input into the SSS design tool kit. SSS tool kit is s<strong>of</strong>tware built specifically for springs.<br />

The data is entered in the MATH page (Fig. 3) and unknown parameters are filled in using standard or approximate<br />

values. This generates a Load vs. Deflection graph which is based on the customer requirement.<br />

Wire diameter is calculated.<br />

314


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3. Then the data is entered into the testing s<strong>of</strong>tware and one-dimensional results are acquired. The tests involve<br />

load conditions at Full Bump, Laden (Fig. 4), Unladen, Rebound and Solid height. The calculations are<br />

solved and stored as a file known as a iterate.<br />

4. The iterate is imported to the tool kit again. And the Load vs. Deflection graph <strong>of</strong> the designed spring is<br />

plotted. This graph should meet with the customer requirement graph. It is seen whether the spring satisfies<br />

the safety conditions for a safe design.<br />

5. Along with the Load vs. Deflection graph, we get the axis and gap information from which we get the coordinates<br />

<strong>of</strong> the spring. These co-ordinates are entered into SOLID WORKS <strong>20</strong>06, 3D designing s<strong>of</strong>tware,<br />

to create a 3D model <strong>of</strong> the spring.<br />

FIG. 4 SPRING PARAMETERS AT LADEN CONDITION<br />

6. After completion, this model is sent for 3D FEM analysis to a company called Wave Axis. There the analysis<br />

is done to see the stresses acting on the spring along with the deformation undergone in 3D and results<br />

are sent back to Stumpp, Schuele&Somappa Pvt. Ltd. where the results are checked.<br />

7. Upon approval, the production designs are made and sent to the production department to manufacture samples.<br />

8. These samples are put through rigorous tests which include Fatigue testing and Static load testing. If the<br />

spring passes, the customer is given all the details.<br />

9. After receiving the go ahead from the customer and making any changes requested by the customer, the<br />

spring is put into production.<br />

4 STUDY METHODOLOGY<br />

4.1 FEM Analysis<br />

FEM is done for 3-dimensional models to analyse it in a more detailed manner [11, 12]. Firstly the entire model<br />

is discretised into small elements and later it as meshed into the actual model. FEM uses a complex system <strong>of</strong><br />

points called nodes which make a grid called a mesh. This mesh is programmed to contain material and structural<br />

properties which define how the structure will react to different loading conditions. Nodes are assigned at a certain<br />

density throughout the material depending on the anticipated stress levels <strong>of</strong> a particular area. Steps involved<br />

in FEM analysis-<br />

315


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

FIG. 5 FULL BUMP HEIGHT COMPRESSION STRESS<br />

(WITH UNCOILING RESTRICTED)<br />

1. Creating the 3-dimensional model in SOLID WORKS <strong>20</strong>06 using co-ordinates <strong>of</strong> the spring acquired from<br />

Math page.<br />

2. Meshing <strong>of</strong> the model using Hyper Mesh.<br />

3. FEM analysis using NASTRAN.<br />

4. Generation <strong>of</strong> stress distribution, load reaction and rotational displacement under different loading conditions<br />

(Fig. 5)<br />

5. Capturing a video <strong>of</strong> the analysis.<br />

6. Analysis and experimental verification <strong>of</strong> the data.<br />

4.2 Experimental Testing<br />

The Larson testing machine (Fig. 6) in Stumpp, Schuele&Somappa Pvt. Ltd is computerized .It is used to test the<br />

behavior <strong>of</strong> springs under the application <strong>of</strong> compressive loads. The Larson testing machine has two test beds at<br />

the top and the bottom. The top test bed is supported by four columns .It has the computer on the right side. The<br />

entire machine has a protective casing to ensure a dust free environment which is perfect for testing conditions.<br />

Periodic calibration is done to ensure the accuracy <strong>of</strong> the machine. The specifications <strong>of</strong> the Larson testing machine<br />

are as follows-<br />

FIG. 6 LARSEN TESTING MACHINE<br />

316


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

1. Compression range-635mm<br />

2. Extension range-533mm<br />

3. Platform diameter-305mm(equipped with three load cells for maximum <strong>of</strong>f centre load capacity)<br />

4. Operating system-MS Windows XP<br />

5. S<strong>of</strong>tware-FLASH Pro Spring<br />

6. Load cell capacity-1361 kg, 3000lb<br />

7. Power-240VAC, 50Hz<br />

8. Emergency stop button is provided in case <strong>of</strong> overloading<br />

9. Least count <strong>of</strong> the machine is 1 N<br />

4.3 Experimental testing procedure<br />

The operation <strong>of</strong> the Larson testing machine is as follows-<br />

1. As the machine is powered on an automatic self check takes place to ensure that the machine is working<br />

properly.<br />

2. The top and the bottom surfaces touch and thus zero calibration is automatically done so that the machine<br />

knows the exact location <strong>of</strong> the top surface.<br />

3. The end seats are fixed on both the top and bottom surfaces <strong>of</strong> the testing machine.<br />

4. The spring is now placed on the bottom end seat and the top end seat is made to just come in contact with<br />

the top part <strong>of</strong> the spring.<br />

5. The shackle height is calculated and the total <strong>of</strong>fset height is fed into the computer.<br />

6. Now the load is gradually applied on the spring and values are directly read <strong>of</strong>f the screen.<br />

7. The spring height is decreased in steps <strong>of</strong> 25mm and the loads values are taken.<br />

8. When the shackle is placed on the machine along with the load readings the turn in Degrees is also noted<br />

down from the laminated circular scale on the shackle.<br />

4.4 Shackle Design<br />

Under normal testing conditions in the Larson testing machine, the coiling and uncoiling motion <strong>of</strong> a compression<br />

spring is restricted. The end seats which are used under normal testing conditions fits snugly into the end<br />

coil pr<strong>of</strong>ile. The top plate and the bottom test bed <strong>of</strong> the machine are fixed, thus preventing the uncoiling <strong>of</strong> the<br />

spring. To allow the coiling and uncoiling motion we have designed a shackle [7]. It also measures the degree to<br />

which the spring coils and uncoils under normal compressive load. The shackle has been designed with a thrust<br />

bearing. The thrust bearing takes the load on the spring but allows free rotation along the axis <strong>of</strong> the spring. The<br />

shackle consists <strong>of</strong> a base plate, the thrust bearing and a top plate. The bottom plate is fixed to the bottom test<br />

bed <strong>of</strong> the Larson testing machine with the help <strong>of</strong> a bolt made to specification. The thrust bearing itself is made<br />

up <strong>of</strong> two hardened steel circular plates, both <strong>of</strong> which have grooves to account for the ball bearings which are in<br />

the middle <strong>of</strong> the two circular plates. The two circular plates <strong>of</strong> the thrust bearing rotate because <strong>of</strong> the ball bearings.<br />

The bottom circular plate <strong>of</strong> the thrust bearing is press fitted onto the base plate <strong>of</strong> the shackle and the top circular<br />

plate <strong>of</strong> the thrust bearing is press fitted onto the top plate <strong>of</strong> the shackle. A laminated circular measuring<br />

scale is fixed onto the base plate <strong>of</strong> the shackle which measures the degree <strong>of</strong> rotation <strong>of</strong> the compression spring<br />

being tested in Degrees. The top plate <strong>of</strong> the shackle has a pointer attached to it. When the bottom end <strong>of</strong> the<br />

spring rotates the top plate <strong>of</strong> the shackle also rotates and the pointer gives the reading on the circular scale. The<br />

top and bottom plates <strong>of</strong> the shackle are made <strong>of</strong> mild steel. The top and the bottom plates <strong>of</strong> the shackle have<br />

holes with M<strong>20</strong> screw threads which fit firmly into the top and bottom test beds <strong>of</strong> the Larson testing machine.<br />

The set up <strong>of</strong> the shackle is as follows-<br />

1. The bottom plate <strong>of</strong> the shackle along with the laminated circular scale are placed on the bottom test bed <strong>of</strong><br />

the Larson testing machine and is bolted using M<strong>20</strong> bolt to make sure that it is fixed firmly.<br />

2. The ball bearing ring is then placed on top <strong>of</strong> the bottom circular plate <strong>of</strong> the thrust bearing. Oil is then applied<br />

to ensure smooth rotation.<br />

3. Now the top circular plate <strong>of</strong> the thrust bearing which is press fitted onto the top part <strong>of</strong> the shackle is put on<br />

top <strong>of</strong> the ball bearing ring. The top part <strong>of</strong> the shackle also has a pointer attached to it.<br />

317


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

FIG. 7 SHACKLE PLACED DURING TESTING<br />

4. The pointer is made to coincide with the zero <strong>of</strong> the laminated circular scale.<br />

5. The end seat is then placed on top <strong>of</strong> the shackle and is bolted firmly using a M<strong>20</strong> nut.<br />

6. The notch in the end seat is then aligned with the pointer.<br />

7. The spring is then placed on top <strong>of</strong> the entire shackle arrangement and is ready to be tested in the Larson<br />

testing machine.<br />

5 RESULT<br />

5.1 FEM analysis results<br />

FEM analysis was carried out using NASTRAN. The 3D model was created on SOLID WORKS <strong>20</strong>06 and the<br />

model was meshed and imported into NASTRAN. This FEM analysis is for SPRING-1. Fig. 8 shows the data<br />

presented in a tabular form. Keeping the deflection as constant between the two conditions, a variation <strong>of</strong> 0.4%<br />

was seen in load, 0.35 % in shear stress and 10º angular rotation <strong>of</strong> the free end [7].<br />

5.2 Experimental test results<br />

Experimental results (Table 1) for the 5 springs tested showed a much higher variation in load: upto 9% in one<br />

spring. Angular rotation <strong>of</strong> upto 15º was observed. Graphs (Fig. 9 & 10) were plotted with the available data to<br />

compare the performance <strong>of</strong> the spring under the two different conditions as well as to further analyse the behavior<br />

<strong>of</strong> uncoiling, which seemed more or less linear [7].<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

TABLE 1. SHOWING FEM ANALYSIS RESULTS FOR SPRING -1<br />

SL<br />

NO.<br />

SPECIFICA-<br />

TION<br />

HEIGHT<br />

(mm)<br />

UNCOILING UNRESTRICTED<br />

LOAD (N)<br />

SHEAR<br />

STRESS<br />

(N/mm2)<br />

TURN (Rad)<br />

UNCOILING RE-<br />

STRICTED<br />

LOAD<br />

(N)<br />

SHEAR<br />

STRESS<br />

(N/mm2)<br />

LOAD %<br />

DIFF (N)<br />

SHEAR<br />

STRESS %<br />

DIFF (N/mm2)<br />

1 REBOUND 285 366.859 99.528 0.018 368.37 99.881<br />

2 UNLADEN 225 1325.697 359.659 0.066 1331.154 360.932<br />

3 FULL BUMP 130 3597.724 976.057 0.179 3611.683 979.511<br />

0.41187486<br />

2<br />

0.41163252<br />

2<br />

0.38799529<br />

9<br />

0.354674062<br />

0.353946377<br />

0.353872776<br />

FIG. 9 LOAD vs DEFLECTION GRAPH<br />

7. CONCLUSION<br />

Based on the work, it is established that there is a clear difference between the two cases <strong>of</strong> spring loading under<br />

static conditions. The load, load rates and stress values are higher for restricted uncoiling springs compared to<br />

unrestricted uncoiling. Both the experimental and FEM analysis results support this claim [7]. The inference is:<br />

1. Failure <strong>of</strong> the bearing in the suspension strut results in increased load on the spring, which increases the<br />

chances <strong>of</strong> failure. We also found that the bearing failure is not considered during spring failure analysis.<br />

2. Some testing machines at the facility had a turning test bed already placed on a bearing, while others did not.<br />

Thus, standardization <strong>of</strong> these testing machines will result in more accurate results on all the machines.<br />

3. During the course <strong>of</strong> the project, a shackle was designed that can be mounted on the Larson testing machine<br />

and the uncoiling in any compression spring can be measured.<br />

3<strong>19</strong>


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

FIG. 10 LOAD vs DEFLECTION GRAPH<br />

The parameters <strong>of</strong> the spring can be varied individually and a detailed study can be made on this phenomenon.<br />

The result will be an improvement in the spring design process where theoretical values will be closer to the actual<br />

values depending on the spring working conditions. The parameters that should be varied for a better understanding<br />

<strong>of</strong> this phenomenon are:<br />

1. Material <strong>of</strong> the spring<br />

2. Wire diameter<br />

3. Spring diameter<br />

4. Number <strong>of</strong> active turns<br />

5. Spring end type<br />

The scope <strong>of</strong> future work would be:<br />

1. Arriving at a formula for the uncoiling <strong>of</strong> the helical spring<br />

2. Determining whether a bearing should be used for a particular spring application<br />

3. Determination <strong>of</strong> exact stress values and load values based on restricted or unrestricted uncoiling <strong>of</strong> the<br />

spring<br />

4. Determination <strong>of</strong> torsional stresses on the support structure<br />

TABLE 2. SHOWING EXPERIMENTAL RESULTS FOR ALL 5 SPRINGS<br />

SL<br />

NO.<br />

SPRING<br />

NAME<br />

1 SPRING-1<br />

2 SPRING-2<br />

3 SPRING-3<br />

4 SPRING-4<br />

5 SPRING-5<br />

SPRING<br />

TYPE<br />

STRAIGHT<br />

HELICAL<br />

STRAIGHT<br />

HELICAL<br />

(MULTI<br />

RATE)<br />

STRAIGHT<br />

HELICAL<br />

DOUBLE PIG<br />

TAIL<br />

DOUBLE PIG<br />

TAIL<br />

MANUFAC-<br />

TURING<br />

PROCESS<br />

COLD<br />

COILED<br />

COLD<br />

COILED<br />

HOT COILED<br />

COLD<br />

COILED<br />

HOT COILED<br />

APPLICATION<br />

REAR SUSPEN-<br />

SION<br />

FRONT SUS-<br />

PENSION<br />

FRONT SUS-<br />

PENSION<br />

FRONT SUS-<br />

PENSION<br />

REAR SUSPEN-<br />

SION<br />

UNCOIL-<br />

ING RE-<br />

STRICTED<br />

MAX<br />

LOAD (N)<br />

UNCOIL<br />

COIL-<br />

ING<br />

TURN (˚)<br />

UNCOILING<br />

UNRE-<br />

STRICTED<br />

MAX LOAD<br />

(N)<br />

%<br />

DIFFE-<br />

FE-<br />

RENC<br />

E<br />

4540 15.5 4130 9.0308<br />

2486 11 2362 4.9879<br />

4510 14.5 4155 7.87<br />

6035 14.5 5525 8.4507<br />

5455 11.5 5135 5.8662<br />

ACKNOWLEDGEMENT<br />

The authors wish to thank Mr. J. SharanaBasavaraja (Senior Lecturer, Dept <strong>of</strong> Mechanical Engineering,<br />

B.M.S.C.E.),<br />

Mr. Deepak Hiremath (R&D Dept, Stumpp, Schuele and SomappaPvt Ltd.) & Mr. Prakash (Wave Axis Pvt.<br />

Ltd.). Without their guidance and support, the research would not have been possible.<br />

3<strong>20</strong>


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

REFERENCES<br />

[1] Machine Design - Robert L. Norton, Pearson Education Asia<br />

[2] Design <strong>of</strong> Machine Elements - V.B. Bhandari, Tata McGraw Hill<br />

[3] Suspension Spring Design Manual - Trainee Handbook, Stumpp, Schuele&Somappa Pvt. Ltd.<br />

[4] Design Data Hand Book- K. Mahadevan and Balaveera Reddy, CBS Publication<br />

[5] Design Data Hand Book - K. Lingaiah, McGraw Hill<br />

[6] Design <strong>of</strong> Helical Compression Springs - Course material, Institute <strong>of</strong> Spring <strong>Technology</strong>, UK<br />

[7] Study <strong>of</strong> uncoiling in suspension springs and its effect - Kushal A Jolapara, AdhipPuttaraj, AbhishekChatterjee<br />

(Visvesvaraya Technological <strong>University</strong>, Final project report)<br />

[8] Suspension Coil Spring and Rubber Insulators: Towards a Methodology <strong>of</strong> Global Design - Michel Langa<br />

and AbderrahmanOuakka<br />

[9] A Textbook <strong>of</strong> Machine Design – Dr. RajendraKarwa, LP Publishers<br />

[10] Design Study for MSIL YV4 250309 - Deepak Hiremath, R&D paper, Stumpp, Schuele&Somappa Pvt. Ltd.<br />

[11] Manufacturing Process Flowchart - Production department, Stumpp, Schuele&Somappa Pvt. Ltd<br />

[12] Internet<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

FACTORS AFFECTING THE AUTOMATIC RAIN SENSING WIPER<br />

SYSTEM<br />

Rahul Sindhwani 1 , Vasdev Malhotra 2<br />

1 Research Scholar, <strong>YMCA</strong>UST, Faridabad<br />

2 Asst. Pr<strong>of</strong>. Deptt. <strong>of</strong> Mechanical Engg., <strong>YMCA</strong>UST, FBD.<br />

1 rahul.sindhwani<strong>20</strong>06@gmail.com<br />

ABSTRACT<br />

The modern age <strong>of</strong> automation is broadly defined as replacement <strong>of</strong> manual efforts by mechanical power in all<br />

degree <strong>of</strong> automation. While using traditional wiper system, it requires driver’s constant attention in setting the<br />

wiper on or <strong>of</strong>f. Despite this, automatic rain-sensing wiper systems are relatively uncommon in modern vehicles for<br />

a number <strong>of</strong> reasons [3]. They are <strong>of</strong>ten too expensive, too unsightly, or too unreliable to be desired in new<br />

automobiles. This paper elaborates the factors <strong>of</strong> the automatic rain sensing wiper system.<br />

Keywords: Automatic, Sensor, Mechanism.<br />

1. INTRODUCTION<br />

With drivers exposed to an ever increasing number <strong>of</strong> distractions, automatic rain-sensing wiper systems become an<br />

even more appealing feature, as they work to minimize the time the driver must take his/her hands <strong>of</strong>f the wheel [5].<br />

These systems detect droplets <strong>of</strong> rain on the windshield and automatically turn on. A rain sensing wiper consists <strong>of</strong> a<br />

sensor circuit incorporated with mechanical system for automatic wiping <strong>of</strong> raindrops during rainfall, thus providing<br />

complete degree <strong>of</strong> automation [2]. Both rain-sensor and intermittent wipers are significant milestones that<br />

incorporate the windshield wiper as part <strong>of</strong> an overall design system. These systems were developed with the end<br />

user in mind and were not last-minute considerations [4]. Efficiency <strong>of</strong> rain sensing wiper system depends on the<br />

different factors.<br />

2. FACTORS AFFECTING THE RAIN SENSING WIPER SYSTEM<br />

2.1. Conveniences<br />

To dispense with troublesome wiper operation needed when rainfall conditions change or when driving conditions<br />

change, including the car speed and entry or exit from tunnels [1].<br />

2.2. Comfort<br />

To operate the wiper with response to changing rainfall and driving conditions, thus keeping the driver’s windshield<br />

clear.<br />

2.3. Installation<br />

The system is easy to install. In the installation process we add one sensor system on the front glass. When sensor<br />

detect water drop late then wiper system is operating. If the installation in not do in proper manner then it may be<br />

not work in right manner [4].<br />

2.4. Failsafe function<br />

It is assured that the wiper operates at 6-second intervals when the drop detection function is disabled because the<br />

sensor is completely blocked by dust, snow, or other matter stuck to the sensor[3].<br />

2.5. System Design<br />

The battery supplies the power to the sensor as well as rain operated motor. Wiper motor is automatically on during<br />

the time <strong>of</strong> rainfall. The senor is fixed in the vehicle glass. The conductive (Touch) sensor is used in this project. It<br />

senses the rainfall and gives control signal to the control unit [6]. The wiper sweeps the windshield with the help <strong>of</strong><br />

a 4-bar linkage using a simple inversion. The motion <strong>of</strong> wiper is based on double crank mechanism whose working<br />

322


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

is quite similar to coupling rod <strong>of</strong> locomotive. The control unit activates the wiper motor automatically. This<br />

operation is called “Automatic rain operated wiper”.<br />

The control unit activates the wiper motor automatically. This operation is called “Automatic rain operated wiper”.<br />

• As the raindrop falls on touch sensor, it activates a timer which is supplied power through a battery.<br />

• It then activates the relay circuit which gets on or <strong>of</strong>f w.r.t. falling <strong>of</strong> raindrops.<br />

• Relay circuit then activates D.C. motor which is connected to a linkage mechanism which is further<br />

connected to the wipers.<br />

2.6. SENSORS<br />

Passive sensors detect the reflected or emitted electro-magnetic radiation from natural sources, while active sensors<br />

detect reflected responses from objects which are irradiated from artificially generated energy sources, such as radar<br />

[5]. Each is divided further in to non-scanning and scanning systems. A sensor classified as a combination <strong>of</strong><br />

passive, non-scanning and non-imaging method is a type <strong>of</strong> pr<strong>of</strong>ile recorder, for example a microwave radiometer<br />

[6]. A sensor classified as passive, non-scanning and imaging method, is a camera, such as an aerial survey camera<br />

or a space camera, for example on board the Russian Cosmos satellite. Sensors classified as a combination <strong>of</strong><br />

passive, scanning and imaging are classified further into image plane scanning sensors, such as TV cameras and<br />

solid state scanners, and object plane scanning sensors, such as multi-spectral scanners (optical-mechanical scanner)<br />

and scanning microwave radiometers.<br />

A pair <strong>of</strong> outer conducting members on the outside <strong>of</strong> a windshield is separated by a long common insulating<br />

border defining a border resistance in parallel with a first capacitance. Each <strong>of</strong> the outer conducting members is<br />

capacitive coupled through a layer <strong>of</strong> the windshield to an inner conducting member to form coupling capacitances<br />

in series with the combination <strong>of</strong> the border resistance and first capacitance. The preceding elements form a timing<br />

circuit for an oscillator, the timing circuit having an equivalent capacitance varying with border resistance. When the<br />

water droplets bridge the border <strong>of</strong> outer conducting members, the border resistance decreases from infinity to<br />

change the equivalent capacitance <strong>of</strong> the timing circuit and thus the frequency <strong>of</strong> the oscillator circuit; and this<br />

change is detected to modify wiper operation.<br />

3. CONCLUSION<br />

The rain sensing technology has provided automation over manual wiper control. This techno- logy is not new to<br />

India and needs to be implemented to avoid road accidents and for driver’s comfort. The technology is cheap and<br />

uses simple design and principles and is much reliable as well. The technology meets with some advantages and has<br />

some limitations as well. Steps are being undertaken by various companies to provide complete automation in rain<br />

sensing technology such as automatic speed control <strong>of</strong> wipers with voice activation. We have to develop an<br />

automatic wiper control system which is improved version <strong>of</strong> intermittent wiper system. This wiper system reduces<br />

cumbersome wiper operation and improves driver’s level comfort. It will give a new dimension <strong>of</strong> comfort and aid<br />

to the drivers who work at night and traffic prone areas where they already have to concentrate on brakes and clutch.<br />

The removal <strong>of</strong> controlling the wipers during rain will provide them much ease and help them concentrate on the<br />

basic ABC (accelerator, brake and clutch) <strong>of</strong> driving. This system features high accuracy and, high sensitivity. This<br />

paper conclude the factor which affecting the efficiency <strong>of</strong> automatic rain sensing wiper system.<br />

REFERENCES<br />

[1] Abhishek Shukla, Rohan Dwivedi, “Design and Implementation <strong>of</strong> Vision System Aid in Windscreen Assembly”<br />

International Journal <strong>of</strong> Computer Applications,, Vol. 7, No.12, <strong>20</strong>10 pp 82-86,.<br />

[2] Bosch.R , "CAM Specification 2.0" International journal <strong>of</strong> Automation & Control, , Vol. 2, No. 3, <strong>19</strong>91 pp 123- 128.<br />

[3] Sarkis, J. and Talluri, S., “Automatic wiper controller using optical sensor”, Journal <strong>of</strong> design process, Vol 38, No. 1, ,<br />

Winter <strong>20</strong>02, pp. 18-28.<br />

[4] Smeltzer, L.R and Carr, A.S.., “Windshield Wiper System with Rain Detector”, European Journal <strong>of</strong> Sensors Detecting<br />

system Management, Vol 5, , <strong>19</strong>99, pp. 43-51.<br />

[5] Verma, R. and Pullman, M.E., “An analysis <strong>of</strong> the wiper selection process”, International Journal <strong>of</strong> Design & Automation,<br />

Vol 26, No. 6, <strong>19</strong>98, pp. 739-750,.<br />

[6] Yazgac, T and Barbarosoglu, G., “An application <strong>of</strong> the analytic designing process <strong>of</strong> the wiper system”, Production and<br />

Designing Management Journal, Vol 38, No. 1, , First Quarter <strong>19</strong>99 pp. 14-21.<br />

323


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

FAILURE ANALYSIS AND COUNTER MEASURE OF CAPACITOR<br />

LEADS USED IN AUTOMOTIVE PCBS<br />

Santosh kumar Joshi 1 , Dr. D. N. Shivappa 2 , Venkatesh Madhyastha 3<br />

1 PG Student, e-mail: skjoshi.au@gmail.com<br />

2 Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, Sir M Visvesvaraya Institute <strong>of</strong> <strong>Technology</strong><br />

Bangalore 562157, India, e-mail: shivappadn@gmail.com<br />

3 Advanced Analysis Engg, Delphi Technical Center India, Bangalore-560066<br />

e-mail: Venkatesh.madhyastha@delphi.com<br />

Abstract<br />

Leaded Electronic components such as capacitors, resistors, and inductors used in automotive PCBs are prone<br />

to failure due to vibration loads. To predict failure, experimental failure analysis <strong>of</strong> capacitor carried out and<br />

suitable lead wire radius was identified through simulation. Experimental failure analysis <strong>of</strong> capacitor is made<br />

by considering two different types <strong>of</strong> capacitors. Finite element models for the two capacitors are built and the<br />

accuracy <strong>of</strong> the models is checked by comparing the results <strong>of</strong> deterministic vibration analysis with experimental<br />

capacitor analysis made using vibration shaker. Verified and most accurate FE model was selected and<br />

simulated to quantify the reliability <strong>of</strong> capacitor by identifying the most significant parameter that affects the life<br />

<strong>of</strong> the capacitor. Sinusoidal vibration pr<strong>of</strong>ile is selected to input vibration load. Monte Carlo Simulation<br />

Technique <strong>of</strong> probabilistic design is selected for the simulation. Results <strong>of</strong> analysis show that; Lead length and<br />

lead radius are identified as important factors influencing the natural frequency <strong>of</strong> vibration. Lead radius is<br />

identified as significant factor for capacitor leads failure. Best size <strong>of</strong> capacitor lead radius is 0.5 mm +0.1 mm<br />

with <strong>20</strong>% failure probability, which is acceptable to the company.<br />

Keywords: Leads, Capacitor, PCB, Monte Carlo Simulation, Fatigue, Failure Probability.<br />

1. Introduction<br />

Printed circuit board (PCB) is housed with number <strong>of</strong> components such as capacitors, resistors and inductors<br />

which are fixed to PCB using copper wire leads. These leaded components are the building blocks <strong>of</strong> any<br />

electronic equipment. These are usually attached to PCBs with the use <strong>of</strong> solder and these are available in a large<br />

variety <strong>of</strong> types, sizes, and materials. PCBs made with these components are extensively used in automotive<br />

vehicles, where vibration loads are significant.<br />

When a printed circuit board is deflected during exposure to vibration, the magnitude <strong>of</strong> the stresses produced<br />

depends on the deflected shape <strong>of</strong> the circuit board. This deflection is strongly dependent upon the boundary<br />

conditions imposed in constraining the board and is most severe during resonance.<br />

However, during vibration in an axis perpendicular to the plane <strong>of</strong> the printed circuit board the circuit board<br />

bends back and forth so bending stresses are developed in the electrical lead wires <strong>of</strong> the components which<br />

fasten the components to the PCB’s. If the stress levels are high enough and the number <strong>of</strong> fatigue cycles is great<br />

enough then fatigue failures can be expected in the solder joints and/or lead wires <strong>of</strong> the electronic components.<br />

Probabilistic approach can be used in this type <strong>of</strong> situations when the relationship between things and the<br />

phenomenon is not known with certainty. In real life, all input parameters are subjected to scatter and each<br />

component needs to be assessed to quantify the reliability, by identifying the most significant parameter that<br />

affects its life cycle.<br />

2. Literature Review<br />

According to Steinberg [1], many <strong>of</strong> the electronic failures are mechanical in nature; many <strong>of</strong> these mechanical<br />

failures occur in the component lead wires and solder joints. In electronic packages, fatigue problem is<br />

commonly observed in solder joints, bond wires, and lead wires etc. Fatigue life or failure <strong>of</strong> electronic<br />

components can be related to the stresses developed due to dynamic displacements by them during vibration [2].<br />

Stress-life approach for fatigue life estimation is suitable where the applied load is primarily within the elastic<br />

range <strong>of</strong> material [3]. Unknown variables encountered in problems particularly displacement in this context are<br />

infinite in the continuum. The finite element procedure reduces such unknowns to a finite number hence makes<br />

the problem easier [4].<br />

Probabilistic design is an analysis technique for assessing the effect <strong>of</strong> uncertain input parameters and<br />

assumption model. Probabilistic approach can be used in situations when the relationship between things and the<br />

324


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

phenomenon is not known with certainty. In real life, all input parameters are subjected to scatter and each<br />

component needs to be assessed to quantify the reliability, by identifying the most significant parameter that<br />

affects its life cycle. The Monte Carlo Simulation method is the most common and traditional method for a<br />

probabilistic analysis. It is a numerical experimentation technique to obtain the statistics <strong>of</strong> the output variables<br />

<strong>of</strong> function, given the statistics <strong>of</strong> input variables. This method allows to simulate how virtual components<br />

behave the way they are built. Each simulation loop represents one manufactured component subjected to a<br />

particular set <strong>of</strong> loads and boundary conditions [5].<br />

3. Capacitor Failure Analysis<br />

Failure <strong>of</strong> leaded capacitors on PCBs <strong>of</strong> automotive electronic equipment’s takes place due to vibrations in the<br />

vehicles. It is difficult to make the real time study <strong>of</strong> breakage <strong>of</strong> capacitor leads during running <strong>of</strong> vehicles. In<br />

order to carry out the failure studies, company had developed vibration shaker to create the vibration similar to<br />

that takes place in vehicles. On these vibration shaker PCBs with leaded capacitor were mounted and tests were<br />

carried for two different types <strong>of</strong> capacitors. Schematic views <strong>of</strong> capacitor <strong>of</strong> both the types are shown in Fig.1<br />

and Fig. 2. The difference between the two types is that the capacitor used in the case 1 has larger size and mass<br />

compare to the capacitor <strong>of</strong> case 2.<br />

Fig. 1 Capacitor Case 1<br />

Fig. 2 Capacitor Case 2<br />

The experimental set up shown in Fig.3 mainly consist <strong>of</strong><br />

(i) Electro dynamic shaker (DEV- 001, 50 kg-f)<br />

(ii) Fixture for mounting PCB attached to bracket.<br />

(iii) PC with Vibration controller s<strong>of</strong>tware for exciting the shaker at desired input vibration pr<strong>of</strong>ile.<br />

(iv) Failure detecting circuit for detecting failure <strong>of</strong> component.<br />

1–Vibration Shaker, 2–Signal conditioning PC, 3–Failure detector<br />

Fig. 3 Experimental setup required for the analysis<br />

In the test, initially the resonant frequency <strong>of</strong> the capacitor was searched using the resonance search module <strong>of</strong><br />

the vibration control s<strong>of</strong>tware. Sine sweep at an input acceleration level <strong>of</strong> 2.33 G and at the rate <strong>of</strong> 0.5<br />

octave/min was used to determine the resonant frequencies. The term G is the ratio <strong>of</strong> ‘acceleration’ applied to<br />

the ‘acceleration due to gravity’. To get the peak responses <strong>of</strong> the capacitor under vibration, behavior <strong>of</strong><br />

325


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

capacitor within the frequency range <strong>of</strong> +3 from resonant frequency is observed. When any <strong>of</strong> the lead-wire or<br />

solder joint fails, the LED provided on the failure detecting circuit will go <strong>of</strong>f and the failure time is recorded.<br />

Case1, capacitor failed near leads after <strong>19</strong>.8 minutes. Similarly in the case2 also, capacitor failed near leads but<br />

after 4.2 minutes. It is required to understand the influence <strong>of</strong> each parameter on the vibration performance <strong>of</strong> the<br />

capacitor to minimize the failure.<br />

4. Building FE Model for Capacitor<br />

The finite element model <strong>of</strong> the capacitor consists <strong>of</strong> two leads and a capacitor body with circular cross sections.<br />

Leads are designed so that their centers fall in same plane. First a solid circular area is created with radius equal<br />

to capacitor radius, and then another two circles are created with radius equal to the lead radius on the same<br />

plane <strong>of</strong> circle created initially. The two circles are created in such a way that the center distance between both<br />

the circle is 7.5 mm in case 1 and 5 mm in case 2. Now these two circles are subtracted in the larger circle using<br />

Boolean operation, retaining their area for meshing. And these circles are meshed freely with the suitable<br />

element size. These meshed areas are extruded to a required length. The larger circle indicating the cross<br />

sectional area <strong>of</strong> the capacitor extruded to the capacitor height. Two smaller circles indicating the cross sections<br />

<strong>of</strong> leads are extruded to the lead length in the direction opposite to that extruded for capacitor body. The volume<br />

so generated is meshed automatically, this completes the generation <strong>of</strong> the finite element model. Fig.4 shows the<br />

FE model <strong>of</strong> capacitor. PLANE42 and SOLID 45 elements were used for modeling. To achieve the accuracy<br />

element refinement was done. All the nodes were given zero displacement where leads are soldered to PCB.<br />

Fig. 4 Capacitor FE Model<br />

4.1 Verification <strong>of</strong> FE Model<br />

The verification <strong>of</strong> component level FE Model to the reality is checked for both the cases by comparing their<br />

outcome with the outcome <strong>of</strong> system level experimental analysis. Finite element vibration analysis is carried out<br />

at the component level under the same input loading conditions as that <strong>of</strong> the system level cases.<br />

Initially resonant frequency is determined and then sinusoidal vibration analysis is carried out to extract bending<br />

stress at the leads. Fatigue life in minutes is estimated based on this stress. Output comparison <strong>of</strong> the<br />

Experimental and FE Analysis is given in the Table 1.<br />

Table 1 Output Comparisons <strong>of</strong> Experimental and FE Analysis<br />

Input Parameter<br />

Mean<br />

Value<br />

Standard<br />

Deviation<br />

Distribution<br />

Type<br />

Lead length, mm 1.2 0.4 Normal<br />

Lead radius, mm 0.3 0.1 Normal<br />

Capacitor length, mm 21 2.6 Normal<br />

Capacitor radius, mm 6.25 2.5 Normal<br />

Capacitor mass, gm 3.24 0.50 Normal<br />

Table 2 Typical Values <strong>of</strong> Input Parameters for simulation<br />

326


OUTPUT<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Expt.<br />

Results<br />

CASE – I<br />

FEA<br />

Results<br />

Expt.<br />

Results<br />

CASE – II<br />

FEA<br />

Results<br />

Natural Frequency (Hz) 266 264.6 237 237.76<br />

Life (in Minutes) <strong>19</strong>.8 <strong>19</strong>.96 4.2 4.47<br />

It has been concluded that the FE Models are accurate and represents the reality. Parameter Life matches<br />

accurately in both the cases but natural frequency <strong>of</strong> the capacitor was found matching more accurately in case2<br />

as compare to the case1. Hence case2 was selected for the simulation analysis.<br />

5. Simulation Analysis and Identification <strong>of</strong> Counter Measure<br />

Verified FE model is simulated using Monte Carlo simulation Technique <strong>of</strong> probabilistic design. Significant<br />

factor influencing the life <strong>of</strong> capacitor and counter measure is identified. For the simulation <strong>of</strong> capacitor a<br />

program was written using the suitable commands known as macro, program details are available in Appendix A<br />

for description about the complete macro, which includes finite element modeling and vibration analysis with<br />

fatigue life calculator. This macro is iteratively executed in ANSYS/PDS for probabilistic analysis. Geometrical<br />

parameters like lead length, lead diameter, capacitor mass and height are considered as random input variables.<br />

Normal distribution is taken for all these variables as fewer input variables are there [6]. Typical values for these<br />

input parameters are listed in the Table 2. Resonant frequency and life <strong>of</strong> the capacitor are considered as random<br />

output variables.<br />

5.1 Monte Carlo Simulation<br />

The Monte Carlo Simulation method is the most common and traditional method for a probabilistic analysis. It is<br />

a numerical experimentation technique to obtain the statistics <strong>of</strong> the output variables <strong>of</strong> function, given the<br />

statistics <strong>of</strong> input variables.<br />

This method allows to simulate how virtual components behave the way they are built. Each simulation loop<br />

represents one manufactured component subjected to a particular set <strong>of</strong> loads and boundary conditions [7].<br />

For Monte Carlo simulations there are two approaches, namely ‘Direct Sampling method’ and ‘Latin Hypercube<br />

Sampling method’. As Latin Hypercube Sampling method requires fewer simulation loops than the Direct<br />

Sampling method to deliver the same results with the same accuracy this method was selected for simulation<br />

study.<br />

For simulation analysis it is necessary to provide fatigue life <strong>of</strong> capacitor lead, this is required to determine the<br />

input parameter influencing the failure <strong>of</strong> capacitor. Following section describes how the fatigue life calculated.<br />

5.2 Fatigue Life Calculator<br />

In the present context the approximate fatigue life <strong>of</strong> the lead wire is obtained using the log-log S-N fatigue<br />

curve for the copper lead wire shown in Fig.5. This curve includes a stress concentration factor <strong>of</strong> 2.0, to account<br />

for cuts.<br />

Fig. 5 S-N Log-Log Fatigue Curve for Copper Wire<br />

The fatigue damage relation [1] given below is used to find the number <strong>of</strong> stress cycles required to produce a<br />

fatigue failure, as well as the expected fatigue life.<br />

327


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

= (1)<br />

Where, N= 1000 stress cycles to fail at 310.275 N/mm2, (copper reference point)<br />

S2= 310.275 N/mm2 (stress reference point)<br />

b = 6.4 (reference slope <strong>of</strong> fatigue curve for copper lead wire with k= 2)<br />

S1 = wire stress from the analysis<br />

N1 = No <strong>of</strong> cycles before the failure <strong>of</strong> wire and is given by the equation;<br />

N1 =N2 (2)<br />

Wire life in hours = (3)<br />

The equations 2 and 3 will be directly included in the macro with constant values N2, S2, and b for copper lead<br />

wire. The stress S1 will be obtained from vibration analysis and used to calculate the number <strong>of</strong> cycles to failure.<br />

These N1 and natural frequency (Fn) will be utilized automatically to calculate life in minutes.<br />

6. Results and Discussion<br />

Simulation is carried for the capacitor with copper leads under 2.33 G vibrations loading by running a coded<br />

program generally called macro in suitable analysis tool. To estimate failure probability, fatigue life calculator<br />

was incorporated in the program. In this section detailed discussion <strong>of</strong> the results obtained from the simulation<br />

are made with suitable graphs.<br />

6.1 Sensitivity Analysis<br />

Sensitivity plots are important in order to improve the design as more reliable and better quality product, or to<br />

save money while maintaining the reliability or quality <strong>of</strong> product. It is possible to draw sensitivity plot for any<br />

random output parameter <strong>of</strong> a component. In this case natural frequency and life are the two important output<br />

parameters. Sensitivity plots for the Natural Frequency and Life <strong>of</strong> component are shown in Fig.6 and Fig.7<br />

respectively. It consists <strong>of</strong> both bar chart and pie chart. Sensitivities are ranked so the random input variable<br />

having the highest sensitivity appears first. From the sensitivity plot for natural frequency it can be concluded<br />

that natural frequency <strong>of</strong> the capacitor is more sensitive to lead length, lead radius. Similarly sensitivity plot for<br />

life (number <strong>of</strong> minutes to failure) clearly represents that lead radius is directly proportional to failure <strong>of</strong><br />

component, and hence lead radius is the most significant parameter for the failure <strong>of</strong> capacitor.<br />

Fig. 6 Sensitivity Plot for Natural Frequency<br />

328


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig. 7 Sensitivity Plot for Life<br />

6.2 Identifying Optimum Diameter <strong>of</strong> Capacitor Lead<br />

From the sensitivity analysis it has been concluded that life <strong>of</strong> capacitor is completely dependent on the radius <strong>of</strong><br />

leads with direct proportion. So in order to reduce the failure probability <strong>of</strong> capacitor, lead radius needs to be<br />

increased. Hence to identify the optimum size <strong>of</strong> the capacitor leads number <strong>of</strong> iterations <strong>of</strong> FE model simulation<br />

were carried out by varying the radius <strong>of</strong> the lead. Cumulative distribution curve for capacitor life is used to<br />

obtain the optimum size <strong>of</strong> capacitor lead radius. This curve gives the failure probability <strong>of</strong> capacitor at a<br />

particular lead radius. X-axis represents the number <strong>of</strong> minutes to fail and Y- axis represents the probability <strong>of</strong><br />

failure. Graph consists <strong>of</strong> three curves representing failure probability. Lower and upper curves quantify the<br />

accuracy <strong>of</strong> probability results; center curve gives the probability (P) <strong>of</strong> life. Complement to this reliability is the<br />

probability <strong>of</strong> failure, i.e. 1-P. It is the probability that the life exceeds the limit [8]. Optimized lead diameter is<br />

one for which the failure probability is smaller. Details <strong>of</strong> FE model simulation iterations are given below;<br />

Iteration 1: Simulation was carried out with lead radius <strong>of</strong> 0.3 mm + 0.1 mm, for expected life <strong>of</strong> 8 hours (480<br />

minutes). Cumulative distribution plot <strong>of</strong> capacitor life in minutes for iteration 1 is shown in Fig.8.<br />

From the graph it can be observed that there is about 95% failure probability <strong>of</strong> component, which is<br />

unacceptable.<br />

Fig. 8 Cumulative Distribution Plot <strong>of</strong> Life for Iteration1<br />

Iteration 2: In this iteration lead radius was increased to 0.45 mm + 0.1 mm, simulation carried out with<br />

increased lead radius, for expected life <strong>of</strong> 8 hours (480 minutes). Cumulative distribution plot <strong>of</strong> capacitor life in<br />

minutes for iteration 2 is shown in Fig.9. From the graph it can be observed that there is about 65% failure<br />

probability <strong>of</strong> component, which is also unacceptable.<br />

329


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig. 9 Cumulative Distribution Plot <strong>of</strong> Life for Iteration 2<br />

Iteration 3: Further radius was increased to 0.5 mm+0.1 mm lead radius and simulation carried out third time.<br />

Figure10 shows Cumulative distribution plot <strong>of</strong> capacitor life in minutes for iteration 3. It was observed that the<br />

failure probability is about <strong>20</strong>% for the capacitor. Again it is possible to increase the lead radius till the 0%<br />

failure probability <strong>of</strong> capacitor, but the company won’t prefer further increase in lead radius as it may result in<br />

shear failure <strong>of</strong> lead due to increased cross sectional area <strong>of</strong> leads. Therefore 0.5 mm+0.1 mm lead radius is<br />

considered as the suitable and acceptable lead radius for the capacitor.<br />

Fig.10 Cumulative Distribution Plot <strong>of</strong> Life for Iteration3<br />

7. Conclusion<br />

System level experiments for the two cases <strong>of</strong> capacitor gave the significant information which was useful for<br />

building a FE model for detailed analysis <strong>of</strong> leaded capacitor failure.<br />

Finite element models for the typical capacitor configuration were built for both case 1 and 2. The accuracy <strong>of</strong><br />

FE models were verified by comparing the results <strong>of</strong> FE model analysis with system level case studies and it was<br />

found that the FE Models were accurate and represents the reality.<br />

Out <strong>of</strong> two cases, FE model developed for the case 2 is more accurate compared to the case 1 and hence this<br />

model was used for the simulation analysis. From the analysis it was concluded that;<br />

• Lead length and radius <strong>of</strong> capacitor are found to be significant parameters for natural frequency.<br />

• Lead radius is the only significant input parameter which has influence on the failure <strong>of</strong> the capacitor leads.<br />

• Best size <strong>of</strong> capacitor lead radius is 0.5 mm+0.1 mm which has <strong>20</strong>% probability <strong>of</strong> failure, which is<br />

acceptable to the company.<br />

Further this probabilistic design approach can be adopted for other similar PCB mounted components and system<br />

level product evaluation as it provides a wealth <strong>of</strong> information that cannot be discovered otherwise.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Acknowledgement<br />

We take this opportunity to give a sincere gratitude to DELPHI TCI, for giving an opportunity to carry out the<br />

work. We thank all the people <strong>of</strong> Delphi TCI who have supported and helped me directly or indirectly to carry<br />

out this work. Special thanks to Mr. Sangmesh Honnapurmath, EGM – Mechanical Engineering Department,<br />

Delphi TCI, Bangalore.<br />

References<br />

[1] `DAVE S. STEINBERG ASSOCIATES, <strong>20</strong>00, Vibration Analysis <strong>of</strong> Electronic Equipment’s, Third edition,<br />

Wiley-Interscience Publication.<br />

[2] SANJAY SINGH CHAUHAN, SANGMESH. H AND ARVIND KRISHNA, Effect <strong>of</strong> Mounting Structure<br />

Vibration on the Performance <strong>of</strong> Through-Hole Capacitors, Delphi Electronics & Safety.<br />

[3] ESIN, A., <strong>19</strong>81, Properties <strong>of</strong> Materials for Mechanical Design, Middle East Technical <strong>University</strong>,<br />

Gaziantep.<br />

[4] CHANDRUPATLA, <strong>19</strong>98, Finite Element Methods”, McGraw Hill Publication.<br />

[5] J.D. BOOKER, <strong>20</strong>01, “Designing Capable and Reliable Products, <strong>University</strong> <strong>of</strong> Bristol, UK Butterworth<br />

Heinemann.<br />

[6] DAVE S. STEINBERG, <strong>19</strong>88, Preventing Thermal Cycling and Vibration Failures in Electronic<br />

Equipment, presented at the 9th Annual IEEE Dayton Chapter Symposium.<br />

[7] WILLIAM Q. MEEKER, <strong>19</strong>98, Statistical Methods for Probabilistic Design”, Department <strong>of</strong> Statistics<br />

and Center for Nondestructive Evaluation Iowa State <strong>University</strong> Ames, IA 50011, Spring Research<br />

Conference, New Mexico.<br />

[8] DR. STEFAN REH, DR. PAUL LETHBRIDGE, DALE OSTERGAARD, Quality-Based Design with<br />

Probabilistic Method, Volume 2, Number 2, ANSYS Solutions.<br />

Appendix A<br />

Macro for the Monte Carlo Simulation <strong>of</strong> Probabilistic Design<br />

/PREP7<br />

!******* DEFINING THE VARIABLES******<br />

!* ask, caprad, enter the radius <strong>of</strong> capacitor, 6.25<br />

caprad=6.25<br />

!* ask, caplen, enter the length <strong>of</strong> capacitor, 21<br />

caplen=21<br />

!* ask, leadrad, enter the radius <strong>of</strong> lead, 0.3<br />

Leadrad =0.3<br />

!* ask, leadlen, enter the length <strong>of</strong> lead, 1.2<br />

leadlen=1.2<br />

!* ask, capm, Enter capacitor mass in grams, 3.24<br />

capm = 3.24<br />

pi=3.1416<br />

v=pi*(caprad**2)*caplen !Formula for capacitor volume<br />

densc=1e-6*capm/v !Formula for capacitor Density<br />

!****** DEFINING THE ELEMENT TYPE ******<br />

ET,1,PLANE42<br />

ET,2,SOLID45<br />

!****** DEFINING THE MATERIAL PROPERTIES<br />

!*Youngs modulus (EX), Density (DENSC), and Poissons ratio (PRXY)<br />

!* Material NO.1,Alluminium<br />

MP,EX,1,2.8e5<br />

MP,DENS,1,DENSC<br />

MP,PRXY,1,0.3<br />

!* Material NO.2,Copper<br />

MP,EX,2,1.17e5<br />

MP,DENS,2,8.9e-9<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

MP,PRXY,2,0.3<br />

!****** FINITE ELEMENT MODELING ******<br />

cyl4,0,0,caprad<br />

cyl4,(-0.4*caprad),0,leadrad<br />

cyl4,(0.4*caprad),0,leadrad<br />

ASEL,,,,2,3<br />

cm, leads, area<br />

allsel<br />

asba,1,leads,,dele,keep<br />

ASEL,S, , , 2<br />

ASEL,A, , , 3<br />

CM, leadarea, AREA<br />

amesh,leadarea<br />

allsel,all<br />

ASEL,S, , , 4<br />

CM,caparea,AREA<br />

amesh,caparea<br />

allsel,all<br />

type,2<br />

mat,1<br />

esize,,14<br />

vext,all,,,,,caplen<br />

allsel<br />

TYPE,2<br />

MAT,2<br />

esize,,(leadlen*4)<br />

vext,2,3,,,,-leadlen<br />

Allsel<br />

!****** APPLYING BOUNDRY CONDITIONS ******<br />

NSEL,S,LOC,Z,-leadlen<br />

CM,bcnodes,NODE<br />

d,all,all<br />

ALLSEL,ALL<br />

!* Setting the analysis peferances<br />

KEYW,PR_SET,1<br />

KEYW,PR_STRUC,1<br />

/COM, Structural<br />

/SOL<br />

!****** MODAL ANALYSIS ******<br />

ANTYPE,2<br />

MODOPT,LANB,1 !selecting the analysis option<br />

EQSLV,SPAR<br />

MXPAND,1, , ,yes<br />

/STATUS,SOLU<br />

SOLVE<br />

/post1<br />

*get,frq1,mode,1,freq<br />

! RESPONSE TO 2.3G SINE SWEEP / HARMONIC ANALYSIS<br />

/Prep7<br />

Acel, ,23000<br />

/solu<br />

antype, harmonic<br />

! 2.3 G along Y-axis<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

hropt, msup<br />

harfrq,(frq1-3),(frq1+3)<br />

hrout,<strong>of</strong>f,on<br />

nsubst,500<br />

zeeta=1/(4*sqrt(frq1))<br />

dmprat,(4.13*zeeta)<br />

lvscale,1<br />

kbc,1<br />

solve<br />

/solu<br />

expass,on<br />

expsol,,,frq1,yes<br />

hrexp,all<br />

solve<br />

fini<br />

!**********************************************<br />

/POST1<br />

SET,1,LAST,1,1<br />

!<br />

! Get the displacement at the lead end<br />

!<br />

NSEL,S,LOC,Z,caplen<br />

nsort,u,y<br />

*GET,MAXDISP,SORT,0,MAX<br />

!<br />

NSEL,S,LOC,z,-leadlen<br />

NSORT,S,z<br />

*GET,bendstrs,SORT,0,MAX<br />

!***FATIGUE LIFE CALCULATION***<br />

!N1S1**b=N2S2**b S-N Curve equation<br />

!N1=Actual number <strong>of</strong> fatigue cycles to fail<br />

!s1=bending stress <strong>of</strong> beam<br />

!FOR COPPER<br />

!N2=10**3<br />

!s2=310.26N/mm2<br />

!b=6.4 fatigue exponent for copper<br />

N1 = (8.8521e18)/(bendstrs**6.4)<br />

!Life=LIFE OF BEAM<br />

Life = N1/ (FRQ1*60)<br />

FINISH<br />

*************************************************<br />

### PROBABILISTIC DESIGN ANALYSIS###<br />

*************************************************<br />

/PDS<br />

! INPUT RANDOM VARIABLES<br />

PDANL,capacitor.mac !Probabilistic design analysis type<br />

PDVAR,caprad,GAUS,6.25,2.5 !Probabilistic design variables<br />

PDVAR,caplen,GAUS,21,2.6<br />

PDVAR,leadrad,GAUS,0.3,0.1<br />

PDVAR,leadlen,GAUS,1.2,0.4<br />

PDVAR,capm,GAUS,3.24,.50<br />

! OUTPUT RANDOM VARIABLES<br />

PDVAR,FRQ1,RESP<br />

PDVAR,LIFE,RESP<br />

PDMETH,MCS,LHS !Probabilistic design method, Monte Carlo Simulation<br />

PDLHS,30,1<br />

PDEXE,CAPACITOR,SER !Execute the probabilistic design<br />

####FINISH###<br />

333


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

ANALYSIS OF BRAKE SPONGY DEFECT IN PASSENGER VEHICLE<br />

AND DEVELOPING THE COUNTER MEASURES – QI CASE STUDY<br />

M. Chethan 1 , Dr D N Shivappa 2 ,Santosh S Navada 3<br />

1 PG Student, e-mail: chethaninbangalore@yahoo.co.in<br />

2 Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, Sir M. Visvesvaraya Institute <strong>of</strong> <strong>Technology</strong>Bangalore,<br />

e-mail: shivappadn@gmail.com<br />

3 Deputy Manager, Assembly Department, Production Division, Toyota Kirloskar Motor Pvt Ltd, Bidadi, India<br />

(e-mail: santhya@ toyota-kirloskar.co.in)<br />

Abstract<br />

Quality improvement case study to identify causes for brake spongy defect and to develop counter measures was<br />

carried out at Toyota Kirloskar Motor, Bidadi. Brake spongy is a s<strong>of</strong>t feeling <strong>of</strong> brake pedal which occurs when<br />

there is more brake pedal free play. To find causes<strong>of</strong> the brake spongy problem, a comprehensive root cause<br />

analysis using 5-Why methodology was adopted. Analyses identified that there were as many as 11 important<br />

causes for brake spongy defect in Toyota Innova vehicles, and details <strong>of</strong> these causes are; tightening defect,<br />

more clearance between brake pad and rotor, more clearance between brake shoe and brake drum, brake and<br />

clutch pedals in low position before filling the brake fluid, improper clamping <strong>of</strong> gun seal packings to the<br />

reservoir, damage in gun seal packings <strong>of</strong> brake fluid filling gun, presence <strong>of</strong> moisture or dust in the brake<br />

tube,improper clamping <strong>of</strong> pressure seal clamp between gun to hose joint,blockage <strong>of</strong> vacuum filter,presence <strong>of</strong><br />

moisture in brake fluid and bad brake hose material. Paper discusses the sources <strong>of</strong> these causes<br />

andidentification <strong>of</strong> counter measures.<br />

Keywords:Brake system, Brake fluid, Brake spongy<br />

Abbreviations<br />

W d Work done on brake pedal<br />

F bp Force output <strong>of</strong> the brake pedal assembly<br />

F d Force applied to the brake pedal pad by the driver<br />

P MC Hydraulic pressure generated by the master cylinder<br />

D MC Diameter <strong>of</strong> master cylinder hydraulic piston<br />

A MC Effective area <strong>of</strong> the master cylinder hydraulic piston<br />

F cal Mechanical force generated by the caliper piston<br />

D cal Diameter <strong>of</strong> the caliper hydraulic piston found<br />

A cal Effective area <strong>of</strong> the caliper hydraulic piston<br />

P cal Hydraulic pressure transmitted to the caliper piston<br />

L 1 Distance Fulcrum to master cylinder pushrod attachment<br />

L 2 Distance Fulcrum to Brake pedal pad<br />

ABS Antilock braking system<br />

F wc Mechanical force generated by the wheel cylinder piston<br />

D wc Diameter <strong>of</strong> the wheel cylinder hydraulic piston<br />

A wc Effective area <strong>of</strong> the wheel cylinder piston.<br />

P wc Hydraulic pressure transmitted to the wheel cylinder piston<br />

W wc Work done on wheel cylinder piston to move Brake shoe<br />

Work done on caliper piston to move Brake pad<br />

W cal<br />

1. Brake Spongy<br />

Brake spongy is the s<strong>of</strong>t feeling <strong>of</strong> brake pedal, that means brake pedal travel before any action takes place in<br />

brake system. It should be between 1 to 3 mm, if brake pedal free play is greater than 3 mm it causes brake<br />

spongy. Brake spongy is related to forces in braking system, brake system components, brake fluid filling<br />

equipment, which are briefly discussed here under.<br />

1.1 Forces in Braking System<br />

The braking force applied and pressure developed inside brake system is determined by Pascal's law which states<br />

that "pressure exerted any where in a confined incompressible fluid is transmitted equally in all directions<br />

throughout the fluid such that the pressure ratio remains the same"[1]. From basic physics, the kinetic energy <strong>of</strong> a<br />

body in motion is defined as:Kinetic Energy = ½mv 2 , m is mass and v is velocity <strong>of</strong> the vehicle.Brake pedal<br />

334


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

exists to multiply the force exerted by the driver’s foot, the force increase will be equal to the driver’s applied<br />

force multiplied by the lever ratio <strong>of</strong> the brake pedal assembly, F b =F d ×(L 2 /L 1 ).<br />

Master cylinder translate the force from the brake pedal assembly into hydraulic fluid pressure. The pressure<br />

generated by the master cylinder will be P MC =F bp /A MC<br />

Caliper translate the hydraulic fluid pressure from the pipes and hoses into a linear mechanical force. The onesided<br />

linear mechanical force generated by the caliper will be F cal =P cal xA cal and P MC =P cal<br />

1.2 Brake System Components<br />

It consist <strong>of</strong> Brake booster, Master cylinder, Disc Brakes, Drum Brakes. The working <strong>of</strong> these components <strong>of</strong><br />

brake system are explained hereunder.<br />

Brake Booster: The typical brake booster shown in Fig. 1; the basic principle <strong>of</strong> the brake booster is pressure<br />

differential, when vacuum is applied to both sides <strong>of</strong> the diaphragm piston it is pushed to the right by the spring<br />

and remains there. When the brake pedal is pressed it causes the plunger to move inside brake booster and<br />

atmospheric air is allowed into variable pressure chamber. Due to the difference in pressure the piston starts to<br />

compress the spring and moves to the left. This causes the piston rod to move the piston <strong>of</strong> the master cylinder<br />

and generating hydraulic pressure.<br />

Fig. 1 Brake Booster<br />

Master Cylinder: The typical master cylinder is shown in Fig. 2; when the brake pedal is de-pressed, the primary<br />

piston moves to the left. As the primary piston is pushed fartherit builds hydraulic pressure inside the master<br />

cylinder which is transmitted to the wheel cylinders <strong>of</strong> the rear brake. The same hydraulic pressure is applied to<br />

the secondary piston, and hydraulic pressure in the primary chamber moves the secondary piston to the left, after<br />

the compensating port <strong>of</strong> the secondary chamber is closed, hydraulic pressure builds and is transmitted to the<br />

brake caliper <strong>of</strong> front brake.<br />

Fig. 2 Master Cylinder with Reservoir<br />

Drum Brakes: It consist <strong>of</strong> wheel cylinder, brake shoes shown in Fig. 3; When the hydraulic pressure builds<br />

inside the master cylinder, it is transmitted to the wheel cylinder and in turn it pushes piston on each end <strong>of</strong> the<br />

335


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

wheel cylinder outward, this in turn pushes the brake shoes against the brake drum, Braking force is generated by<br />

friction between the brake shoes and the lining <strong>of</strong> brake drum.<br />

Fig. 3 Drum Brake<br />

Disc Brakes: The disc brake assembly consists <strong>of</strong> rotor that rotates with the wheel, Caliper assembly, brake pad<br />

that is mounted to the caliper assembly shown in Fig. 4. When the hydraulic pressure builds inside the master<br />

cylinder, it is transmitted to the brake caliper and in turn it pushes the brake pad to contact the disc.<br />

Fig. 4 Disc Brake<br />

1.3 Brake Fluid Filling Equipment<br />

The brake fluid filling equipment is consist <strong>of</strong> De-aerated tank, Cushioning tank, De-gasifier, Drain salvage tank,<br />

Vacuum tank shown in Fig. 5. Brake fluid equipment has a optical fiber sensor which is placed inside the brake<br />

fluid barrel and it sense the level <strong>of</strong> brake fluid then indicate the pump to supply brake fluid to the de-aerated<br />

tank. De-aerated tank has a provision for de-gasifier where the sprayed brake fluid is collected and condensed<br />

then it is passed to the de-aerated tank. Brake fluid from de-aerated tank is passed to the cushioning tank where it<br />

is stored before sending it to the reservoir <strong>of</strong> vehicle. The following are the functions <strong>of</strong> brake fluid filling<br />

equipment:<br />

Pre-vacuuming: Vacuum pump creates 9.9x10 2 pa vacuum pressure within 10 seconds when the gun is clamped<br />

to the reservoir <strong>of</strong> the vehicle.<br />

Vacuuming: It is the continued process <strong>of</strong> the Pre-vacuuming where in vacuum pressure from 9.9x10 2 pa to<br />

2.1x10 2 pa is created within 70 seconds.<br />

Filling: Filling is done after the vacuum pressure is set to required level inside the reservoir <strong>of</strong> the vehicle, then<br />

the pressure regulator valve develops the 2x10 5 pa pressure inside the cushioning tank that forces the brake fluid<br />

inside the cushioning tank to fill brake fluid inside the reservoirand filling takes place in 28 seconds.<br />

336


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Leveling: In this process the vacuum <strong>of</strong> 2.4x10 2 pa is created inside the drain salvage tank by the vacuum pump<br />

for 10 seconds it removes the excess brake fluid from the reservoir and send it to drain salvage tank.<br />

Blow: After leveling process, the gun has to be unclamped from reservoir. It is not easy to unclamp the gun as it<br />

causes damage to reservoir due to vacuum pressure, for this purpose vacuum pressure has to be removed. The<br />

pressure regulator valve supply the pressure <strong>of</strong> 2 bar within 10 seconds to overcome vacuum pressure.<br />

1.4 Types Of Error In Brake Fluid Filling Equipment<br />

Types <strong>of</strong> Error in brake fluid filling equipment are given in the Table 1. Out <strong>of</strong> these errors only the Vacuum and<br />

Pre-vacuum error causes low or no brake fluid filling condition. Only these errors are considered for further<br />

investigation and analysis.<br />

Table 1 Types <strong>of</strong> Error in Brake Fluid Filling Equipment<br />

Types <strong>of</strong><br />

defects<br />

Contribution<br />

<strong>of</strong> error in<br />

percentage<br />

Machine Condition<br />

Vacuum error 47.06% Low brake fluid filled<br />

Pre Vacuum<br />

error<br />

<strong>19</strong>.85% No brake fluid filled<br />

Other 14.71%<br />

ABS fault &<br />

ABS actuator<br />

error<br />

10.29%<br />

Filling fault 8.09%<br />

Not concern about<br />

brake fluid<br />

Not concern about<br />

brake fluid<br />

No brake fluid filled or<br />

Low brake fluid filled<br />

2. Identification <strong>of</strong> Causes and Developing Counter Measures for Brake Spongy<br />

Detail investigative study was carried out to identify the causes <strong>of</strong> brake spongy, these causes were clasified<br />

under four categories such as Man, Machine, Materials and Methods. Fig.6 gives details <strong>of</strong> all possible causes<br />

identified under different categories responsible for brake spongy defect.<br />

Fig. 5 Brake Fluid Filling Equipment<br />

337


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

For each cause the 5 why analysis is used to explore the cause and effect relationships underlying a particular<br />

problem and developing the counter measures. The primary goal <strong>of</strong> 5 why analysis technique is to determine the<br />

root cause <strong>of</strong> a brake spongy defect by asking question why for 5 times and find the answers for these questions<br />

which will be helpful in developing counter measures. Due to space limitations 5 why analysis and identification<br />

<strong>of</strong> countermeasures for the cuases due to ‘Man’ are explained in the paper.<br />

Fig. 6 Cause and Effect Diagram for Brake Spongy<br />

2.1 Five Why Analysis – Brake Spongy Defect due to Man<br />

It explains how the brake spongy defect occur from worker during assembling the brake system components<br />

using 5 Why Analysis, Accordingly 5 why possible questions were identified as given below.<br />

(i) Why – there is improper tightening <strong>of</strong> Brake tube<br />

The tightening defects in brake tube causes due to improper apply <strong>of</strong> torque, cross thread and poor seating <strong>of</strong><br />

double flare, which are described hereunder.<br />

Torque: the torque should be in correct range while tightening brake tube if the worker applied torque is less then<br />

there will be gap between the double flare and tubing seat shown in Fig. 7, due to this there will be leakage <strong>of</strong><br />

vacuum pressure which causes pre-vacuum error. Torque should be between 9.5 Nm to 22.5 Nm and target value<br />

is 16 Nm.<br />

Fig. 7 Brake Tube<br />

338


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Cross thread: while tightening brake tube if the worker tilts the flare nut this causes cross thread, due to this<br />

there will be leakage <strong>of</strong> vacuum pressure and causes pre-vacuum error.<br />

Poor seating: while tightening brake tubeif the worker does not place the double flare <strong>of</strong> brake tube to seat<br />

properly on tubing seat, there will be gap between the double flare and tubing seat due to this there will be<br />

leakage <strong>of</strong> vacuum pressure which causes pre-vacuum error.<br />

After detail analysis and observation <strong>of</strong> workers doing the assembly <strong>of</strong> brake tube it is identified that “tightening<br />

defect” is one <strong>of</strong> the sources or causes <strong>of</strong> brake spongy defect.<br />

(ii) Why – More clearance between Brake Pad and Rotor occurs<br />

During assembling front disc brake the worker adjust the clearance between brake pad and rotor through the<br />

caliper. Due to improper alignment <strong>of</strong> caliper by the worker it causes more clearance between the brake pad and<br />

rotor. A sample data shown in Table 2 shows that out <strong>of</strong> 10 vehicles randomly inspected for clearance between<br />

brake pad and rotor it is found that in vehicles the clearance is more in many vehicles. This results in more<br />

distance for the brake pad to touch the rotor. Because <strong>of</strong> this more brake force is required for brake pad to touch<br />

the rotor. If the brake pad does not touch the rotor it causes brake pedal free play more than 3 mm due to this<br />

brake spongy occurs.<br />

While observing workers assembling the front disc brake it is identified that “more clearance between Brake Pad<br />

and Rotor” is one <strong>of</strong> the sources or causes <strong>of</strong> brake spongy defect.<br />

Table 2 Clearance between Brake Pad and Rotor<br />

Brake pad and rotor<br />

clearance in mm<br />

LH ABS RH ABS<br />

0.4 0.3<br />

0.3 0.7<br />

0.5 0.6<br />

> 0.8 > 0.8<br />

0.1 0.5<br />

0.2 0.4<br />

> 0.8 > 0.8<br />

> 0.8 > 0.8<br />

0.4 0.3<br />

0.4 0.1<br />

(iii) Why – more clearance between Brake Shoe and Brake Drum occurs<br />

During assembling rear brake drum the worker adjust the clearance between brake shoe and brake drum. Due to<br />

improper alignment <strong>of</strong> brake shoe and brake drum by the worker it causes more clearance between the brake<br />

shoe and brake drum. This results in more distance for the brake shoe to touch the brake drum so more brake<br />

force is required forbrake shoe to touch the brake drum. If the brake shoe does not touch the brake drum it causes<br />

brake pedal free play is more than 3mm due to this brake spongy occurs.<br />

Analysis and observation <strong>of</strong> workers assembling the rear brake drum it is identified that “more clearance between<br />

Brake Shoe and Brake Drum” is also one <strong>of</strong> the source or cause <strong>of</strong> brake spongy defect.<br />

(iv) Why – Brake pedal or Clutch pedal is in low position before filling Brake fluid<br />

Due to negligence <strong>of</strong> worker, the brake pedal or clutch pedal is kept in low position. In turn this result in low<br />

brake fluid filled in brake system components.<br />

(a) Brake pedal is in low position before filling Brake fluid<br />

When the brake pedal is in upper position, the plunger remains in same position inside the brake booster this<br />

causes push rod <strong>of</strong> brake booster to remain in same position. In turn push rod <strong>of</strong> brake booster does not move the<br />

primary piston, due to this both primary inlet port and primary compensating port remains in open position. It<br />

339


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

causes the secondary piston remains in same position, due to this both secondary inlet port and secondary<br />

compensating remains in open position. During vacuuming process, it creates vacuum pressure in all brake<br />

components since both primary and secondary compensating port is in open position and in turn brake fluid is<br />

filled to all brake components.<br />

Due to negligence <strong>of</strong> worker, the brake pedal is kept in low position. It causes the plunger to move inside brake<br />

booster. In turn it pushes the push rod <strong>of</strong> brake booster and push rod <strong>of</strong> brake booster moves primary piston<br />

inside the master cylinder, due to this primary inlet port is in open position and primary compensating port is in<br />

closed position. In turn primary piston moves secondary piston causing only secondary inlet port to open and<br />

secondary compensating port to close. During vacuuming process, the vacuum pressure is not created inside the<br />

rear wheel cylinder and front disc brake since the both primary and secondary compensating port is in closed<br />

position and due to this brake fluid is not filled to rear wheel cylinder and front disc brake.<br />

(b) Clutch pedal is in low position before filling Brake fluid<br />

The brake fluid reservoir is connected to clutch master cylinder (CMC) through a hose. When the clutch pedal is<br />

in upper position, the push rod remains in same position. In turn push rod does not move the piston inside the<br />

CMC, due to this both inlet port andcompensating port remains in open position. During vacuuming process, it<br />

creates vacuum pressure in all components since compensating port is in open position and in turn brake fluid is<br />

filled to all components.<br />

Due to negligence <strong>of</strong> worker, the clutch pedal is kept in low position. It causes the push rod to move inside<br />

CMC. In turn push rod moves piston inside the CMC, due to this inlet port is in open position and compensating<br />

port is in closed position. During vacuuming process, the vacuum pressure is not created inside the clutch tube<br />

and release cylinder since the compensating port is in closed position and in turn brake fluid is not filled to clutch<br />

tube and release cylinder.<br />

With the above discussion it is found that “Brake pedal is in low position before filling Brake fluid” and “Clutch<br />

pedal is in low position before filling Brake fluid” are also likely sources <strong>of</strong> brake spongy defect.<br />

(v) Why – gun seal packings <strong>of</strong> brake fluid filling gun is not clamped properly<br />

Gun seal packing A and gun seal packing B shown in Fig. 8 is used for sealing brake fluid reservoir so that<br />

vacuum pressure does not leak while creating vacuum, if worker handling brake fluid filling gun does not clamp<br />

it properly to the brake fluid reservoir then leakage <strong>of</strong> vacuum pressure occurs, in turn this leads to pre-vacuum<br />

error.<br />

It is found that “Improperly clamped gun seal packings <strong>of</strong> brake fluid filling gun” causes pre – vacuum error that<br />

leads to brake spongy defect.<br />

Fig. 8 Brake Fluid Filling Gun Seal Packings<br />

2.2 Indentification <strong>of</strong> Counter Measures<br />

As mentioned earlier details <strong>of</strong> 5 – why analysis and identification <strong>of</strong> counter measures related causes <strong>of</strong> ‘Man’<br />

is explained in the paper. Accordingly counter measures identified for causes due to ‘Man’ are explained here<br />

below.<br />

(i) Tightening defect <strong>of</strong> Brake Tube<br />

Tightening defect causes the leakages <strong>of</strong> vacuum pressure, due to this pre–vacuum erroroccurs. This happens<br />

when the vacuum pressure <strong>of</strong> 9.9x10 2 pa created by vacuum pump does not remain same for 10 seconds.<br />

Pressure sensor measures drop <strong>of</strong> vacuum pressure, the drop <strong>of</strong> vacuum pressure indicates there is a leakage <strong>of</strong><br />

340


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

vacuum pressure.As discussed in 5 - why analysis presented in section 2.1 tightening defect <strong>of</strong> Brake tube occurs<br />

due to improper apply <strong>of</strong> torque, cross thread and poor seating <strong>of</strong> double flare assembly. As a counter measure to<br />

overcome, this problem it is recommended that after the assembly <strong>of</strong> Brake Tube a quality inspector is employed<br />

for double check whether torque <strong>of</strong> different component mentioned in the Table 3 is achieved by the worker,<br />

Torque should be between 9.5 Nm to 22.5 Nm and target is 16 Nm so the double check is done by using Autotorque<br />

tool and is set to the lower limit 9.5 Nm, if the component moved while tightening it indicates that it is not<br />

tightened properly.<br />

Table 3 Torque for Different Parts<br />

Joint Name<br />

Targe<br />

t in<br />

Nm<br />

Range in<br />

Nm<br />

Rear brake tube no.3 to ABS<br />

side 16 9.5 to 22.5<br />

Front brake tube no.5 to ABS<br />

side 16 9.5 to 22.5<br />

Front brake tube no.3 to ABS<br />

side 16 9.5 to 22.5<br />

Front brake tube no.2 to ABS<br />

side 16 9.5 to 22.5<br />

Rear brake tube no.1 to ABS<br />

side 16 9.5 to 22.5<br />

Rear brake tube no.1 to BMC<br />

side 16 9.5 to 22.5<br />

Front brake tube no.1 to<br />

3way 16 9.5 to 22.5<br />

Front brake tube no.2 to<br />

3way 16 9.5 to 22.5<br />

Clutch tube to CMC side 16 9.5 to 22.5<br />

Clutch tube to Accumulator<br />

bottom 16 9.5 to 22.5<br />

Clutch tube to Accumulator<br />

LH side 16 9.5 to 22.5<br />

Front brake tube no.1 to<br />

BMC side 16 9.5 to 22.5<br />

Front brake tube no.7 to 3<br />

way 16 9.5 to 22.5<br />

(ii) More clearance between Brake Pad and Rotor<br />

As per the company standard, brake pedal free play should not exceed 3 mm. In order to limit the Brake pedal<br />

free play at 3mm it is required to find out optimum clearance between brake pad and rotor. Following procedure<br />

is used to calculate the optimum clearance.<br />

Calculation <strong>of</strong> Clearance required between Brake pad and Rotor for Brake pedal free play upto 3 mm.<br />

When the force applied to the brake pedal pad by the driver (F d ) the output force <strong>of</strong> brake pedal assembly (F bp )<br />

increases and will be equal to the driver applied force multiplied by the lever ratio <strong>of</strong> brake pedal assembly<br />

shown in Fig. 9.<br />

341


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig. 9 Brake Pedal<br />

Work done on the brake pedal (W d ) = Force applied to the brake pedal pad by the driver (Fd) x Displacement <strong>of</strong><br />

brake pedal<br />

movedI<br />

W d = Xx3 = 3X N-mm<br />

F bp = (F d ) x (L 2 )/L 1 = (X) x (435)/142<br />

F bp = X x 3.0634<br />

F bp = 3.0634 X N<br />

Output force <strong>of</strong> brake pedal assembly act on the master cylinder hydraulic piston.<br />

Pressure = force/area<br />

P MC = F bp /A MC<br />

Master cylinder<br />

D MC = 25.4 mm<br />

A MC = (π/4) x (D MC ) 2 = (π/4) x (25.4) 2 = 506.7075 mm 2<br />

P MC =F bp / A MC = (3.0634 X) / (506.7075) = (6.0457 x 10 -3 X) N / mm 2<br />

By the Pascal law, fluid pressure remains same<br />

P MC =P cal = P wc = (6.0457 x 10 -3 X) N/mm 2<br />

In front disc brake<br />

P cal = (6.0457 x 10 -3 X) N/mm 2<br />

P cal = F cal x A cal<br />

D cal = 45.4 mm<br />

A cal = (π / 4) x (D cal ) 2 = (π / 4) x (45.4) 2 = 1618.8313 mm 2<br />

F cal =P cal x A cal = (6.0457x10 -3 X) x 1618.8313 = (9.7842X) N<br />

W cal = F cal x Distance the brake pad moved<br />

W cal = (9.7842X) x Distance the brake pad<br />

moved II<br />

342


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Comparing equation I and equation II<br />

3X = (9.7842 X) x Distance the brake pad moved<br />

Distance the brake pad moved = 0.3066 mm<br />

Counter measure: The clearance between brake pad and rotor should be lesser than 0.3066 mm for brake pedal<br />

free play <strong>of</strong> 3mm.<br />

(iii) More clearance between Brake shoe and Brake drum<br />

As per the company standard, brake pedal free play should not exceed 3 mm. In order to limit the Brake pedal<br />

free play at 3 mm it is required to find out optimum clearance between brake shoe and Brake drum. Following<br />

procedure is used to calculate the optimum clearance.<br />

Similarly, Calculation <strong>of</strong> Clearance required between Brake shoe and Brake drum for Brake pedal free play upto<br />

3 mm.<br />

W d = F d x displacement <strong>of</strong> brake pedal = X x 3 = 3X N-mm<br />

P MC =P cal = P wc = (6.0457 x 10 -3 X) N/mm 2<br />

In rear brake drum<br />

P wc = F wc / A wc<br />

P wc = (6.0457 x 10 -3 X) N/mm 2<br />

d wc = 22.22 mm<br />

A wc = (π /4) x (d wc ) 2 = (π/4) x (22.22) 2 = 380.1327 mm 2<br />

F wc =P wc x A wc = (6.0457 x 10 -3 X) x 380.1327 = (2.2982 X) N<br />

W wc = F wc x Distance the brake shoe moved<br />

W wc = (2.2982 X) x Distance the brake shoemoved<br />

Comparing equation I and equation II<br />

3X = (2.2982 X) x Distance the brake shoe moved<br />

Distance the brake shoe moved = 1.3055 mm<br />

Counter measure: Clearance between brake shoe and brake drum should be lesser than 1.3055 mm for brake<br />

pedal free play <strong>of</strong> 3 mm.<br />

(iv) Brake pedal and Clutch pedal is in low position before filling Brake fluid<br />

While assembling the compounds inside the vehicle, the worker carries the tray which consists <strong>of</strong> the<br />

components that is to be assembled. Due to the negligence, if the worker places the components tray on the brake<br />

pedal or clutch pedal it pushes brake pedal or clutch pedal to low position before filling brake fluid. This leads to<br />

less quantity <strong>of</strong> brake fluid filled to reservoir. To avoid such mistakes <strong>of</strong> workers at Final 1 line <strong>of</strong> assembly line<br />

as to be educated not to place the tray on the brake pedal and also make sure it is in correct position.<br />

(v) Improperly clamped gun seal packings <strong>of</strong> brake fluid filling gun<br />

If the worker improperly clamps gun seal packings <strong>of</strong> brake fluid filling gun it results in leakage <strong>of</strong> vacuum<br />

pressure which causes pre- vacuum error. Hence the workers are to be trained to place the gun seal packings<br />

appropriately clamp to the reservoir.<br />

343


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Similarly Counter measures for causes due to Machine, Method and Material are identified which are given<br />

below.<br />

2.3 Causes due to Machine<br />

Cause:Damage in gun seal packings <strong>of</strong> brake fluid filling gun<br />

Counter Measure:If there is damage in gun seal packings <strong>of</strong> brake fluid filling gun, it leads to leakage <strong>of</strong> vacuum<br />

pressure and this also causes pre-vacuum error. In this case if pre - vacuum error occurs, it is difficult to identify<br />

for what reason it happened. To identify this problem the mock model <strong>of</strong> reservoir is made by closing the three<br />

ports excluding to port and top port is used for placing brake fluid filling gun to check whether vacuum pressure<br />

drops or not after developing vacuum pressure inside the mock reservoir. If the pressure sensor detects the drop<br />

in vacuum pressure this indicates there is a problem in gun seal packings and it as to be replaced.<br />

Cause: Improper clamping <strong>of</strong> pressure seal clamp between Gun to hose joint<br />

Counter Measure:Pressure seal clamp is used for joining the gun and hose shown in Fig. 10.Due to improper<br />

clamping <strong>of</strong> pressure seal clamp between gun to hose joint, which results in leakage <strong>of</strong> vacuum pressure between<br />

gun to hose joint, due to this pre- vacuum error.<br />

Pressure seal clamp should be clamped properly between gun to hose joint and also check once in a day whether<br />

the leakage <strong>of</strong> pressure vacuum occurs.<br />

Cause:Blockage <strong>of</strong> Vacuum filter<br />

Fig. 10 Pressure Seal Clamp, Gun, Hose<br />

Counter measure:Vacuum filter in the vacuum hoses is mounted in-line on the vacuum hose.Accumulation <strong>of</strong><br />

dust particles inside the vacuum filter causes blockage <strong>of</strong> vacuum filter. During vacuuming, if the Vacuum filter<br />

is blocked this causes vacuum pressure to block so the vacuuming is not done to brake system components which<br />

results in vacuum error.Vacuum filter has to be checked daily and if there is accumulation <strong>of</strong> dust, clean it.<br />

Vacuum filter should be cleaned once in a week by using distilled water and dried before placing it back.<br />

2.4 Causes due to Method<br />

Cause: Presence <strong>of</strong> moisture or dust in the Brake tube<br />

Counte Measue: During vacuuming, if moisture or dust is present in the brake tube it causes the blockage <strong>of</strong><br />

brake tube, due to this blockage vacuuming is not achieved in farther component and which results in vacuum<br />

error. To overcome this problem after removing the cover <strong>of</strong> brake tube, air gun used to blow2 bar pressure<br />

inside the brake tube to remove dust or moisture present in it and end cap is place on the both end <strong>of</strong> brake tube.<br />

Cause: Presence <strong>of</strong> moisture in Brake fluid<br />

Counter measure:If the moisture is present inside the brake fluid, it decreases the boiling point <strong>of</strong> fluid and<br />

results in the vaporization at lower temperature which causes brake spongy.Vapor lock point equipment is used<br />

for detecting the boiling point <strong>of</strong> brake fluid and from boiling point we can detect the moisture content. Boiling<br />

point <strong>of</strong> brake fluid should be determined whenever the brake fluid barrel is changed.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2.5 Causes due to Material<br />

Cause: Bad Brake hose material<br />

Counter measure:During vacuuming, if brake hose material has defect like crack or hole it causes leakage <strong>of</strong><br />

vacuum pressure, this results in pre-vacuum error. Due to defective brake hose material it also causes inflate <strong>of</strong><br />

brake hose at higher pressure. When brake pedal applied this causes expansion <strong>of</strong> brake hose and results in<br />

accumulation <strong>of</strong> brake fluid inside the brake hose. Due to accumulation <strong>of</strong> brake fluid it damages the brake hose<br />

resulting crack on brake hose, this leads to leakage <strong>of</strong> brake fluid.<br />

Calculation for determining maximum pressure developed in brake system<br />

Considering maximum Mass applied on brake pedal = 100 Kg<br />

F d = Mass applied on brake pedal x Acceleration<br />

F d = 100 x 9.80665 = 980.66 Kg-m/s 2 = 980.66 N<br />

Approximating braking force (F d ) to 1000 N<br />

F bp = (F d )x(L 2 ) / L 1 = (1000)x(435)/142 = 1000 x 3.0634<br />

F bp = 3063.4 N<br />

D MC = 25.4 mm<br />

A MC = (π/4) x (D MC ) 2 = (π/4) x (25.4) 2 = 506.7075 mm 2<br />

P MC =F bp /A MC = (3063.4)/(506.7075) = 6.0457 N/mm 2<br />

By the Pascal law, fluid pressure remains same<br />

P MC =Pcal=Pwc= 6.0457 N/mm 2<br />

The maximum pressure developed in the Brake system is 6.0457 N/mm 2<br />

Counter measure: Brake hose should have to with stand and do not inflate at pressure 6.0457 N/mm 2 .<br />

3. Conclusion<br />

A comprehensive root cause analysis using 5 - Why methodology to find the causes and reasons for brake<br />

spongy defect resulted in identifing suitable counter measures for this problem.Out <strong>of</strong> <strong>20</strong> suspected causes for<br />

brake spongy defect 11 causes are identified as potential sources <strong>of</strong> this problem. The list <strong>of</strong> these 11 caurces and<br />

corresponding counter measures is given below.<br />

(i) Tightening defect: Torque range for tightening brake tube is standardized and worker is employed to check<br />

whether the torque for tightening different component is achieved.<br />

(ii) More clearance between Brake pad and Rotor: This clearance is to be ≤ 0.3066 mm.<br />

(iii) More clearance between Brake shoe and Brake drum: This should be ≤ 1.3055 mm<br />

(iv) Brake and Clutch pedals in low position: The team member is educated not to press the brake pedal and<br />

clutch pedal by putting the components tray in pedals and ensure that the pedals are in correct position<br />

before filling the brake fluid.<br />

(v) Improper clamping <strong>of</strong> gun seal packings: Workers are to be trained to place the gun seal packings properly<br />

and appropriately clamp to the reservoir.<br />

(vi) Damage in gun seal packings <strong>of</strong> brake fluid filling gun: Mock model <strong>of</strong> reservoir is developed to check the<br />

pre-vacuum error.<br />

(vii) Improper clamping <strong>of</strong> pressure seal clamp between gun to hose joint: Pressure seal clamp should be<br />

clamped properly between gun to hose joint, and also pressure seal clamp should be checked once in a day<br />

whether the leakage <strong>of</strong> pressure vacuum occurs.<br />

(viii) Blockage <strong>of</strong> Vacuum filter: Vacuum filter has to be checked daily and if there is accumulation <strong>of</strong> dust,<br />

clean it. Vacuum filter should be cleaned once in a week by using distilled water and dried before placing it<br />

back.<br />

345


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

(ix) Presence <strong>of</strong> moisture or dust in the Brake tube: Air gun is used to blow 2 bar pressure inside the brake tube<br />

to remove dust or moisture and end cap is place on the both end <strong>of</strong> brake tube.<br />

(x) Presence <strong>of</strong> moisture in Brake fluid: Vapor lock point equipment is used for detecting the boiling point <strong>of</strong><br />

brake fluid.<br />

(xi) Bad Brake hose material: Brake hose should not inflate at pressure less than 6.0457 N/mm 2 .<br />

Reference<br />

[1] JAMES WALKER, <strong>20</strong>05, The Physics <strong>of</strong> Braking Systems, copy right <strong>of</strong> Stop Tech LLC, United States, 1-8.<br />

346


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

VIRTUAL REALITY IN DESIGN: USER TRAINING AND<br />

EVALUATION<br />

Harish Pungotra<br />

Beant College <strong>of</strong> Engineering and <strong>Technology</strong>, Gurdaspur, India<br />

Email: pungotra@gmail.com<br />

Abstract<br />

Virtual Reality (VR) has emerged as a realistic option in a number <strong>of</strong> applications, the range and number <strong>of</strong><br />

which are increasing annually. It is also being considered as the new future interface for allowing humans to<br />

communicate with computers. This is crucial, when designers and industrial engineers are involved in design<br />

activity with the help <strong>of</strong> computers. Modern computer-aided design (CAD) systems and s<strong>of</strong>tware tools have<br />

played a significant role in improving the efficiency <strong>of</strong> the overall product design process. However, the impact<br />

<strong>of</strong> these technologies is largely restricted to the detailed modeling and engineering analysis. At the early stages<br />

<strong>of</strong> product design the specifications and constraints are not been fully established. The industrial designers and<br />

engineers need the freedom to change and modify the product configuration. They also need to investigate the<br />

mechanical behavior for a wide range <strong>of</strong> alternative solutions. Recent advancements in high-speed computer<br />

hardware and VR technology provide opportunities to carry on design, evaluation and user training before a<br />

project is launched. This paper presents evaluation <strong>of</strong> the concept design and user training in VR environment.<br />

A unique design and simulation is used to illustrate and discusses the role that virtual reality in design,<br />

evaluation and user training.<br />

Keywords-virtual concept design, virtual reality, modeling and simulation, evaluation, user training, deformable<br />

object, B-spline surface.<br />

1. Introduction<br />

Industrial designers and engineers continue to seek new tools to artistically modify product concepts. Several case<br />

studies[1-3] have emphasized the need for a viable VR-based conceptual design tool. The studies have concluded<br />

that the human-computer interface and related s<strong>of</strong>tware tools for interacting with the virtual models must be<br />

intuitive to the user. Recent advancements in high-speed, multi-core computer hardware and virtual reality (VR)<br />

technology provide opportunities to link the more fluid processes <strong>of</strong> creative conceptual design with the rigidly<br />

defined tasks <strong>of</strong> product detailing and engineering analysis.<br />

The concept design process needs creativity and freedom to innovate and explore alternative solutions [4]. During<br />

the concept generation phase a rough idea, which can come from the background research or from a previous<br />

design, is expanded into several solution alternatives. Physical product design and production may require major<br />

investments and can lead to significant financial implications in the event <strong>of</strong> a solution not meeting design<br />

requirements or specifications. However, these risks can be managed by developing and testing new solutions at<br />

the concept stage. The product concepts can be evaluated depending on the design considerations and identified<br />

customer needs.<br />

Figure 1. Haptic Interaction With A Virtual Model Through A Haptic Device At The Univerity Of Western<br />

Ontario, London, Canada.<br />

347


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 1 shows the user interacting with a virtual model through a haptic device. The haptic sense is usually<br />

divided into two main distinct sensory modalities. The first sense is the kinaesthetic sense (motion and force<br />

sensing), which includes perception <strong>of</strong> muscular effort. The second sense is the tactile sense, which provides<br />

coetaneous information, related to contact between the skin <strong>of</strong> the human body and the external environment<br />

(pressure, vibration, temperature etc.). These sensory interactions enable the user to perceive physical properties<br />

such as rigidity <strong>of</strong> the model and the surface characteristics <strong>of</strong> model (roughness etc.).<br />

The evaluation <strong>of</strong> the design is required to make a decision on whether to discontinue the concept, further iterate<br />

the concept, or start utilising the concept. Similarly, the end users can be involved to gauge the customer<br />

satisfaction for the given concept. Another goal may be to evaluate the design from a human factors perspective.<br />

The VR allows an industrial designer to sculpt and validate the concept design. A group <strong>of</strong> users can also evaluate<br />

the concept in VR environment.<br />

Virtual reality environment can provide real-time interaction with virtual world through several communication<br />

methodologies. These include visual (preferably stereoscopic display), tactile (force feedback) and audio (stereo<br />

sound) feedback. Virtual reality environment is used to provide a far more natural environment to the user than<br />

that is possible by workstations. This is especially suitable for free form shape design. An industrial designer or<br />

engineer can explore all conceivable options without the constraints imposed by commercial CAD/CAM<br />

environments. However VR faces many issues in efficient use <strong>of</strong> the virtual reality environment. Firstly, the realtime<br />

rendering <strong>of</strong> the complex word during simulation requires very large computations which are still not<br />

feasible, particularly on desktop computers. The speed with which the computer processing speed is increasing,<br />

will make is possible in future.<br />

The second issue is in the implementation <strong>of</strong> collision detection algorithms. Collision detection, while interacting<br />

with large, complex and deformable models can be very tricky. Many techniques are being used to develop<br />

efficient collision detection algorithms. The third issue is <strong>of</strong> providing physical properties to the virtual models<br />

created in virtual reality. To simulate the behavior <strong>of</strong> a real object, the simulation must include object properties<br />

such as rigidity, strength, mass, friction, surface texture, and heat transfer. Adding these physical characteristics to<br />

virtual objects require powerful computing hardware and efficient algorithms. This issue is <strong>of</strong> more importance<br />

when we need to evaluate the product at the concept stage.<br />

However, virtual reality development is a fast growing area in computer graphics and engineering. Already, it is<br />

being used for training for laparoscopic surgery and games. This paper discusses the process <strong>of</strong> evaluation and<br />

user training during the concept design in the virtual reality environment.<br />

1.1. Previous Work<br />

Virtual reality environment allows a user to use his/her sense <strong>of</strong> touch while interacting with a virtual model using<br />

haptic devices. A user interacts with a virtual model by feeding and receiving information through tactile<br />

sensation.<br />

Different types <strong>of</strong> surfaces are used to represent virtual objects. The most common approach is to use implicit<br />

geometry techniques to represent clay-like objects used by Bloomenthal and Shoemaker [5] and Witkin et al. [6].<br />

Knopf and Sangole [7] investigated the Self Organization Feature Map (SOFM) as the starting point for haptic<br />

interaction. The SOFM technique has also been extended for many applications. These include, geometric and<br />

visual exploration <strong>of</strong> numerical data [8] and surface fitting [9]. Raviv and Elber [10] used a set <strong>of</strong> uniform<br />

trivariate B-spline functions to represent virtual objects. On the other hand, Pungotra[11] used B-spline surfaces<br />

to model objects in virtual reality environment for easy exchange with existing CAD s<strong>of</strong>tware. Alternative data<br />

structure to represent virtual sculpting has also be proposed such as, voxel-based system [12], and B-spline<br />

surfaces [13].<br />

Initially, the product models were created in existing 3D CAD systems and then translated into a VR<br />

environment. These VR-enhanced 3D visualization techniques were used in Virtual Design II [14], and ISAAC<br />

[15]. Such systems only permit designers to visualize and analyze CAD objects in a 3D virtual environment. A<br />

VR-based CAD modeling environment that allows rapid shape creation by using a bi-modal, voice, and hand<br />

tracking interface is the COnceptual VIRtual Design System (COVIRDS)[16, 17]. Mouse/keyboard interface is<br />

replaced with voice recognition and 3D interaction devices and allows parametric and free form design modes. In<br />

addition to COVIRDS, there are many VR-based design systems. These include 3DM [18], CUP [<strong>19</strong>],<br />

DesignSpace [<strong>20</strong>], CDS [21], Loughborough <strong>University</strong> Conceptual Interactive Design (LUCID)and 3-Draw<br />

[22]. LUCID [3, 23] integrated VR-based Human-Computer Interfaces into the design process. These models<br />

348


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

work very efficiently within their domain. However, the limitation on the size <strong>of</strong> the virtual model and its<br />

complexity limits the scope <strong>of</strong> these systems. A time lag sets in when complex, highly deformable and large sized<br />

virtual models are encountered and real-time interaction may not be possible.There are more research groups [24-<br />

26] using virtual reality for concept design. The virtual concept design tools are in high demand in industry.<br />

1.2. VR Based Design Process<br />

The virtual reality based design process is based on the interaction <strong>of</strong> the user with the virtual model through a<br />

haptic device. There are three distinct processes that need to be performed to carry out the interaction. To<br />

visualize the virtual model and the tool, a ‘haptic rendering system’ is used. The ‘collision detection system’<br />

calculates the relative position <strong>of</strong> the model and the tool at any instance in time. As soon as the haptic tool starts<br />

interacting with the tool, this information about the position <strong>of</strong> contact and the extent <strong>of</strong> penetration is provided<br />

by the collision detection system. Based the information provided by the collision detection algorithm, the<br />

‘physics-based system’ determines the deformation <strong>of</strong> the model(s) and the resultant reactive forces to be fed<br />

back to the user. Figure 2 shows the schematic representation <strong>of</strong> a general virtual reality-based design process.<br />

Figure 2. Schematic Representation Of A Vr-Based Design Process.<br />

1.3. Collision Detection<br />

Collision detection is used in virtual assembly, simulation-based concept design, evaluation <strong>of</strong> design, motion<br />

planning, medical training, virtual reality based games and animation. Collision detection is computationally<br />

intensive and is considered a bottleneck in these applications. A collision detection system automatically reports a<br />

geometric contact between the haptic tool and a virtual object. It calculates when a contact is about to occur or<br />

has actually occurred. There are many collision detection algorithms available in literature. Jimenez [27] surveyed<br />

various collision detection algorithms. It focused on how the model representation leads to different collision<br />

detection algorithms. On the other hand, Lin and Gottschalk [28] presented a survey on the state <strong>of</strong> the art in<br />

collision detection between models represented by smooth surfaces. Pungotra et al [29] proposed an algorithm<br />

that uses B-spline based models and rigid as well as deformable tool. This algorithm uses best <strong>of</strong> parametric<br />

representation <strong>of</strong> surface and efficiency <strong>of</strong> triangle-triangle intersection test.<br />

1.4.Physics Based Deformation Modelling<br />

The deformation <strong>of</strong> the model can be simulated by a geometric- or physics-based system. Geometric techniques,<br />

though efficient, do not yield accurate results which may be required for the evaluation <strong>of</strong> the model. Physicsbased<br />

techniques, on the other hand, yield accurate results. However, the computational cost is large for such<br />

techniques. A mass spring damper system, consisting <strong>of</strong> a set <strong>of</strong> particles (nodes) connected through a network <strong>of</strong><br />

springs and dampers can provide reasonable accuracy and speed for real time interaction. Pungotra et al [30]<br />

proposed the representation <strong>of</strong> B-spline surfaces in terms <strong>of</strong> blending matrices. This facilitated integration <strong>of</strong><br />

collision detection with the mass spring system. The virtual object is modeled as a collection <strong>of</strong> point masses<br />

connected by springs and dampers in a lattice structure. In general, the spring forces are assumed to be linear.<br />

However, nonlinear springs can also be used to model objects which exhibit inelastic behaviour. Such a system<br />

contains a mass ρ, a spring with spring constant K that serves to restore the mass to a neutral position, and a<br />

damping element which opposes the motion <strong>of</strong> the vibratory response with a force proportional to the velocity <strong>of</strong><br />

the system. The constant <strong>of</strong> proportionality, also known as damping constant, is denoted by D. Different<br />

combinations <strong>of</strong> linear springs and damper can be used to model deformable objects. Voigt model is the most<br />

349


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

commonly used combination <strong>of</strong> spring and damper and has been used in this thesis. Figure 3 shows a mass spring<br />

damper system with two mass nodes i and j.<br />

Figure 3. Voigt model <strong>of</strong> mass spring damper system.<br />

The volumetric self-organizing feature map (VSOFM) [31] is a viable framework for modeling realistic objects<br />

that dynamically change shape with time. Figure 4 shows the flowchart for the mass spring mesh generation and<br />

its integration with the collision detection algorithm.<br />

Figure 4. Flow Chart For Mass Spring Mesh Generation And Its Integration With Collision Detection<br />

Algorithm.<br />

The blending matrices are used to generate spars sparse point cloud on the B-spline surfaces so that it encloses the<br />

3D lattice <strong>of</strong> the deformable VSOFM. The VSOFM model used should have the required number <strong>of</strong> nodes<br />

attached through springs and dampers. The lattice is allowed to expand to the point cloud. The deformable<br />

VSOFM geometrically transforms into the B-spline surface model shape while maintaining the relative<br />

connection <strong>of</strong> neighboring nodes in the mesh.<br />

The surface nodes are connected to the neighboring surface nodes as well as the interior nodes that lie directly<br />

below. This way, the algorithm assigns exterior nodes <strong>of</strong> the mass spring damper mesh to the points generated on<br />

the B-spline surface [26]. The model generated in such a way, can be given any material properties by changing<br />

the stiffness <strong>of</strong> the spring and the damping coefficients based on experimental data. Collision detection algorithm<br />

determines the region where tool is interacting with the model. This information is used to transfer the haptic<br />

forces to the model. This information is used by the mass spring system to generate the response <strong>of</strong> the model to<br />

the applied forces.<br />

2.VR Based Design<br />

The concept design process needs creativity and freedom to innovate and explore alternative solutions [4]. Based<br />

on research or a previous design, a rough idea is created. This rough idea is then expanded into several alternative<br />

350


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

solutions. However, selection <strong>of</strong> a wrong idea can cost a lot in terms <strong>of</strong> time and investment. Hence, it is<br />

imperative that the ideas are evaluated in terms <strong>of</strong> customer needs and other design considerations at the concept<br />

stage so as to avoid time and cost overruns. Real-time interaction with a product model during interactive<br />

development provides a quick insight into the overall performance <strong>of</strong> the proposed solution.<br />

Consider the design <strong>of</strong> spoons that are used in every household. These designs presume that the intended users<br />

can efficiently work with their hands and fingers. However, many persons are the patients suffering from<br />

rheumatoid arthritis. Rheumatoid arthritis is a chronic inflammatory disorder that most typically affects the small<br />

joints in hands and feet [32]. Eating is one <strong>of</strong> basic tasks that can be impaired by rheumatoid arthritis. These<br />

patients may not be able to use the spoons that are commercially available. Virtual reality can allow an industrial<br />

designer to imitate a rheumatoid arthritis patient.<br />

Figure 5(a-b) shows natural way <strong>of</strong> fetching and eating food. Figure 5(c) shows the hand <strong>of</strong> a patient suffering<br />

from rheumatoid arthritis. This limits the movement <strong>of</strong> fingers and wrist. It is generally accepted that a user<br />

would hold a spoon in particular way and turn wrist to eat as shown in Figure 5(a-b).<br />

(a) (b) (c)<br />

Figure 5. Generally accepted motions (a) Holding a spoon and (b) Rotating wrist while eating (c) Rheumatoid<br />

arthritis restricts movements <strong>of</strong> fingers and wrist, modified picture from [33].<br />

However, this may not be possible for different set <strong>of</strong> users. These can be rheumatoid arthritis patients, children,<br />

and aged people. Due to a weak grip (children and aged people) or restricted motion (rheumatoid arthritis<br />

patients), it possible that a user cannot put the food properly in the spoon or can get the food in the spoon, but<br />

cannot turn his/her wrist enough to bring it to mouth without spilling it. Using the VR environment, the spoon<br />

was redesigned to accommodate the lack <strong>of</strong> wrist movement [34] as shown in Figure 6.<br />

(a) (b) (c)<br />

Figure 6. Investigation Of Different Shapes Of A Spoon To Accommodate Impaired Hand Movements. The<br />

Original Design Is Shown In (A) And Design Modifications Are Presented In (B) And (c).<br />

Figure 6(a) shows the initial design and Figure 6(b-c) show different variations <strong>of</strong> the design. The designs shown<br />

in Figure 6(c-d) provide better grip for different sets <strong>of</strong> users. These grips can be further modified to suit grip <strong>of</strong><br />

the user. Using this design, the user does not have to rotate his/her wrist. However, due to the bend, the user will<br />

experience a torque. Thus it is imperative that the spoon be evaluated before finalizing the design.<br />

2.1. Evaluation Of The Design<br />

Again, considering the group <strong>of</strong> users affected by rheumatoid arthritis, aged people, and children, it will be vital<br />

to know if these users can eat with the spoon without spilling the food. The spoon designed in VR environment,<br />

as shown in Figure 6, can be evaluated for it performance, that is if the spoon can be used to eat food without<br />

spilling. The insight gained in the simulation, can be used to further modify the design.<br />

351


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

A B-spline surface patch having 8×8 control points net was used to represent food (jelly) for interaction with the<br />

spoon to mimic eating with a spoon [34]. A 12×12×12 mass spring damper mesh was used to incorporate material<br />

properties <strong>of</strong> jelly to this model, as discussed in Section II. Figure 7 shows the results <strong>of</strong> the interaction <strong>of</strong> the<br />

jelly with the spoon [35]. The spoon was tilted at different degrees to know, what should be the optimal<br />

inclination <strong>of</strong> the bowl part <strong>of</strong> the spoon with its handle.<br />

(a) Jelly flowing<br />

due to its own<br />

weight<br />

(b) Jelly does not<br />

spill out <strong>of</strong> spoon,<br />

when bowl is tilted<br />

by 10 o .<br />

(c) Jelly spills<br />

out <strong>of</strong> spoon,<br />

when bowl is<br />

tilted by <strong>20</strong> o .<br />

Figure 7. Simulation Of Food (Jelly) In A Spoon (A) Spoon Without Tilting (B) When The Bowl Is Tilted By<br />

Ten Degree. (C) When The Bowl Is Tilted By Twenty Degree.<br />

Due to its own weight, jelly started flowing downwards as shown in Figure 7(a). This means that if this design is<br />

used, the user cannot eat jelly by using this size without spilling it. It is clear that the jelly is spilling from the<br />

front portion <strong>of</strong> the spoon bowl. At this point, an industrial designer can start modifying the design in such a way<br />

that the jelly does not get spilled. If the bowl is tilted about 10 degree in the backward (clockwise for the spoon<br />

shown, when seen from the handle side along the handle) direction. Figure 7(b) shows the jelly put in a spoon<br />

with tilted bowl. This time it does not spill out <strong>of</strong> the spoon and it spreads in the spoon evenly. This shows that<br />

there was improvement in the design. The bowl was tilted by <strong>20</strong> degree to see if it further improves the design.<br />

However, as shown in Figure 7(c), the jelly started flowing from the back part <strong>of</strong> the spoon. This means that by<br />

tilting the bowl by twenty degrees, the design deteriorated rather than improving its functionality. Thus, by using<br />

the VR environment, the spoon can be evaluated and modified at the concept state, thereby reducing the lead-time<br />

and cost <strong>of</strong> design.<br />

2.2.User Training<br />

Even when a product design for a given user segment is ready, the users may require training to benefit from the<br />

unique features <strong>of</strong> the design. Even when a variety <strong>of</strong> shapes is available for a spoon, adaptations needed for<br />

eating may still be overwhelming for patients suffering from rheumatoid arthritis or aged people having weak<br />

grips. An occupational therapist can help train these people. However, this would require that products are readily<br />

available in the market. In the absence <strong>of</strong> a suitable product, it might be difficult for an occupational therapist to<br />

train this user segment. Virtual reality environment can be used to efficiently train these users. At the same time,<br />

an industrial designer can have better understanding <strong>of</strong> the difficulties <strong>of</strong> the user group. This can help the<br />

industrial designer to come up with better design after receiving valuable inputs from the users.<br />

A major challenge for patients <strong>of</strong> rheumatoid arthritis or aged people is to eat food with a spoon without spilling<br />

it. There are primarily two reasons for spilling food from the spoon; tilting <strong>of</strong> spoon and shaking <strong>of</strong> hands while<br />

eating with a spoon. Virtual reality environment can provide various scenarios in which a user can interact with<br />

spoon while eating food. A variety <strong>of</strong> spoons developed during the interactive design phase can be used to<br />

determine the best fit for the user. In the simulation study, different scenarios were considered, which included<br />

different angle <strong>of</strong> tilt for the spoon and shaking <strong>of</strong> hands. Acceleration was imparted to spoon to simulate shaking<br />

<strong>of</strong> hands. When the spoon gets tilted, jelly may start spilling out <strong>of</strong> the spoon. A larger tilt will increase the rate <strong>of</strong><br />

spilling <strong>of</strong> jelly. However, by practicing with the virtual spoon, a user can be trained to eat without spilling food.<br />

Figure 8(a) shows the interaction <strong>of</strong> spoon and food to simulate a user tilting his/her spoon while eating food.<br />

Different angle <strong>of</strong> tilt were considered which resulted in spilling <strong>of</strong> jelly by different magnitudes. Figure 8(b)<br />

shows spilling <strong>of</strong> jelly when the spoon was tilted by ten degrees. The spilling <strong>of</strong> jelly increased with increased<br />

angle <strong>of</strong> tilt as shown by Figure 8(b-c). Figure 8(d-f) show the side view <strong>of</strong> the spoon and jelly.<br />

352


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

(a) Jelly on spoon<br />

(b) Jelly spills out<br />

<strong>of</strong> spoon when<br />

spoon is tilted by<br />

10 degrees<br />

(c) Jelly spills out<br />

<strong>of</strong> spoon when<br />

spoon is tilted by<br />

<strong>20</strong> degrees<br />

(d) Side view <strong>of</strong> the<br />

jelly on spoon<br />

(e) Side view <strong>of</strong> the<br />

spilling jelly<br />

Figure 8. Simulation Of Food (Jelly) In A Spoon When The Spoon Is Tilted By Different Degrees.<br />

The spilling <strong>of</strong> spoon gets aggravated when the tilting <strong>of</strong> spoon is accompanied by the shaking <strong>of</strong> hands while<br />

eating with a spoon. By incorporating the acceleration to the spoon and eventually to the food, both the tilting <strong>of</strong><br />

spoon as well as shaking <strong>of</strong> hands can be simulated. Figure 9 shows the simulation.<br />

(f) Side view <strong>of</strong> the<br />

spilling jelly<br />

(a) Jelly spills out <strong>of</strong> spoon when<br />

spoon is tilted by 30 degrees and<br />

the user's hand is shaking in the<br />

same direction<br />

(b) Jelly spills out <strong>of</strong> spoon when<br />

spoon is tilted by 30 degrees and<br />

the user's hand is shaking in the<br />

transverse direction<br />

(c) Jelly spills out <strong>of</strong> spoon when<br />

spoon is tilted by 30 degrees<br />

sideways and the user's hand is<br />

shaking in the same direction<br />

(d) Side view <strong>of</strong> the spilling jelly (e) Side view <strong>of</strong> the spilling jelly (f) Side view <strong>of</strong> the spilling jelly<br />

Figure 9. Simulation Of Food (Jelly) In A Spoon When The Spoon Is Tilted By Different Degrees And The Hand<br />

Of The User Is Shaking.<br />

If the user tilts the spoon (anti-clockwise rotation <strong>of</strong> the spoon when seen from the side <strong>of</strong> the handle <strong>of</strong> the<br />

spoon) and his/her hands are shaking in the same direction, the jelly will experience force due to its own weight<br />

as well as due to the inertial forces. Figure 9(a and d) show the result <strong>of</strong> simulation. It is clear from the figure that<br />

shaking <strong>of</strong> hand exacerbates the slipping <strong>of</strong> jelly from the spoon. However, when the shaking <strong>of</strong> hands happened<br />

in the transverse direction, the jelly slipped to lesser extent as shown in Figure 9(b and e).In the same way, when<br />

the tilting and the shaking <strong>of</strong> hand happens in transverse direction (along the major axis <strong>of</strong> the handle <strong>of</strong> the<br />

spoon), the jelly slips and starts falling down from the side. This is shown in Figure 9(c and f). At this point if an<br />

industrial designer concludes that the user cannot eat without the tiling and shaking <strong>of</strong> hands, the spoon design<br />

can be reviewed. Some modification such as raising one side <strong>of</strong> the spoon bowl or tilting the bowl part <strong>of</strong> the<br />

spoon in the other direction can be carried out at this stage.<br />

353


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3. Conclusion<br />

In this paper, the role that virtual reality can play in the design, particularly in the evaluation and user training was<br />

introduced. Product designers and engineers require various tools that help them to quickly modify the shape,<br />

style, size and functionality <strong>of</strong> a product. VR technology allows the designer to intuitively create and manipulate<br />

the shape <strong>of</strong> complex freeform CAD models. The mass spring damper system introduced in this paper can be<br />

used to incorporate any material properties in the virtual objects. The simulation studies can be used to<br />

interactively design an optimal solution. The proposed methodology allows a designer to evaluate the design and<br />

incorporate any changes that can enhance the functionality <strong>of</strong> the design. The VR environment can also be used<br />

for user training. This can enhance the acceptability <strong>of</strong> the product when it is launched in the market. At the same<br />

time, several users who are suffering from disabilities can be provided training in virtual reality environment.<br />

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environment using B-spline blending matrices, 21 st IASTED Int. Conference on Modeling and Simulation<br />

(MS <strong>20</strong>10), Banff, Alberta, Canada, <strong>20</strong>10, 281-288.<br />

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Niagara Falls, Canada.<br />

355


SLAB WIDTH MEASUREMENT TECHNIQUE USING MANIPULATOR<br />

IN PLATE ROLLING MILL OF BHILAI STEEL PLANT(SAIL)<br />

Anand S. Srivastava 1 , Krishna K. Saxena 2<br />

1 Graduate Student, Department <strong>of</strong> Mechanical Engineering, B.I.E.T. Jhansi (U.P.)<br />

2 Graduate Student, Department <strong>of</strong> Mechanical Engineering, B.I.E.T. Jhansi (U.P.)<br />

krishnasxn@gmail.com, +91_9557417310<br />

Abstract<br />

Manipulators are used for proper alignment <strong>of</strong> slabs and plates before rolling passes begin. Width is a very<br />

important parameter in rolling <strong>of</strong> the plate, so a precise and reliable method should be introduced to measure the<br />

width <strong>of</strong> the plate. The manipulators can be used for the measurement <strong>of</strong> the width with the help <strong>of</strong> a rack and<br />

pinion arrangement and an encoder-decoderin the existing layout <strong>of</strong> the plate mill <strong>of</strong> Bhilai Steel Plant using hydraulic manipulator. A program in C language<br />

has also been developed for design <strong>of</strong> manipulator pinion or assistance in design process for the same.The thermal<br />

In this paper, a method is suggested for the slab width measurement<br />

analysis using Solid works s<strong>of</strong>tware has been carried for the manipulator jaw so as to avoid any dimensional<br />

distortion <strong>of</strong> jaw due to high temperature <strong>of</strong> slab. This also ensures reliable measurement.<br />

Keywords: Manipulator, rack and pinion, slab.<br />

NomenclatureP=pitch <strong>of</strong> rack, T= Teeth advanced by rack.<br />

1. Introduction<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The function <strong>of</strong> the manipulator is to align the incoming heated slab (1<strong>20</strong>0 0 C) [1] in order to make the slab to be<br />

perfect perpendicular to the rolling axis and to make zero <strong>of</strong>fset between slab and rolling axis. The manipulator<br />

(Fig 2.) is very essential mechanism in the plate mill since it is used 3000 times a day [2]. In plate mill,<br />

measurement <strong>of</strong> width <strong>of</strong> the slab is a critical process because <strong>of</strong> high temperature <strong>of</strong> slab. This is done manually<br />

using a holder arrangement with digital display. There are many problems associated with the manual arrangement<br />

<strong>of</strong> width measurement: (1). The manual measurement process is not a reliable process due to chances <strong>of</strong> inaccuracy<br />

(2). Due to high temperature <strong>of</strong> slab the measurement is associated with safety issue.<br />

In order to enhance the productivity <strong>of</strong> plate mill, width act as a major parameter. Since condition <strong>of</strong> plain strain is<br />

applicable to the rolling process, therefore very small widening is observed in rolling. So, to produce the plate<br />

conforming the dispatch width as per order, measurement should be done in an accurate manner. In order to attain<br />

the normal width, a proper gap between roll has to be given.The measurement <strong>of</strong> width is done by the linear motion<br />

<strong>of</strong> ram or jaws. In other words the gap between the jaws <strong>of</strong> manipulator (while aligning the slab) is a measurement<br />

<strong>of</strong> width <strong>of</strong> the slab. The method focuses on the measurement <strong>of</strong> rotary motion (Fig 1.). . Hence the linear motion<br />

<strong>of</strong> the ram has to be converted to rotary motion. The conversion <strong>of</strong> linear motion <strong>of</strong> the ram to rotary motion is to be<br />

carried out without any slippage. The basic design processes that have to be carried out are: (1). To attain the<br />

positive drive. (2). To select a suitable device.<br />

Figure 1 BASIC SCHEME OF WIDTH MEASUREMENT<br />

356


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. Mathematical formulation<br />

Figure 2 MECHANISM OF MANIPULATORS<br />

The pitch and number <strong>of</strong> teeth are the parameters <strong>of</strong> rack and pinion which is to be fitted to manipulator which can<br />

be used for the measurement <strong>of</strong> slab width. For this purpose, the pitch <strong>of</strong> rack and pinion on both left and right<br />

manipulators is taken to be same.<br />

Figure 3 IDLE POSITION OF MANIPULATOR<br />

The position when there is no slab between the jaws is diagrammatically shown in Fig 3. When slab come in<br />

between the jaws <strong>of</strong> manipulator, the left and right jaws start advancing towards the slab for zero <strong>of</strong>fset between<br />

slab axis and rolling axis. In this process both jaw touches the edge <strong>of</strong> heated slab as shown in Fig 4.<br />

SLAB WIDTH (W) = D-(advancement made by both jaw)……………………………….1.1<br />

W= (2×pitch×No. <strong>of</strong> teeth advanced by rack)…………………………..1.2<br />

The multiplying factor <strong>of</strong> 2 in equation 1.2 accounts for the symmetry <strong>of</strong> rack on both sides <strong>of</strong> ram.<br />

The final equation becomes:<br />

W= D - (2×P×T)<br />

3. Design for pinion <strong>of</strong> manipulator<br />

Material: Cast Iron, Pressure angle: <strong>20</strong> 0 full depth involute.<br />

The basic design for the pinion [4] to be used in the manipulators is demonstrated with the help <strong>of</strong> C program [3].<br />

The flowchart is represented in this paper.<br />

357


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4. Thermal analysis <strong>of</strong> manipulator jaw<br />

The thermal study [5] <strong>of</strong> manipulator jaw was carried on SolidWorks s<strong>of</strong>tware which ensured that no distortion<br />

could take place in the manipulator jaw while holding the slab. This also ensured the reliability <strong>of</strong> measurement.<br />

Figure 4 SLAB HOLDING POSITION OF THE MANIPULATOR<br />

TABLE 1: Material Properties<br />

Model Reference Properties Components<br />

Name:<br />

AISI 1035 Steel (SS)<br />

Model type: Linear Elastic<br />

Isotropic<br />

SolidBody<br />

Thermal<br />

conductivity:<br />

Specific heat:<br />

Mass density:<br />

52 W/(m.K)<br />

486 J/(kg.K)<br />

7850 kg/m^3<br />

358


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Mesh Model<br />

TABLE 2: Mesh Information<br />

Mesh type<br />

Solid Mesh<br />

Mesher Used:<br />

Curvature based mesh<br />

Jacobian points<br />

4 Points<br />

Maximum element size<br />

107.721 mm<br />

Minimum element size<br />

107.721 mm<br />

Mesh Quality<br />

High<br />

Total Nodes 16046<br />

Total Elements 10503<br />

Load name Load Image Load Details<br />

Entities:<br />

Temperature:<br />

1 face(s)<br />

1300 Celsius<br />

Temperature-1<br />

The results <strong>of</strong> simulation study are displayed in fig 5.<br />

359


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 5 THERMAL STUDY OF MANIPULATOR JAW [5]<br />

5. Conclusion<br />

Advantages to plate mill <strong>of</strong> Bhilai steel Plant with this method include reliability in measurement risk free<br />

measurement and wastage <strong>of</strong> material due to trimming loss is reduced.<br />

Since economy is a major factor in manufacturing process reducing the trimming losses the cost per plate will be<br />

reduced. Also the productivity will also increase. There are no safety issues in this suggested system. Temperature<br />

<strong>of</strong> slab also doesn’t distorts the dimensions <strong>of</strong> jaw, hence method suggested above is reliable.<br />

6. References<br />

[1]. Gateway-An Introductory Guide to Bhilai Steel Plant, Edition <strong>20</strong>09, Editor - ManasShukla, DGM (HRD),<br />

Bhilai steel Plant.<br />

[2]. Bhilai Steel Plant- intranet website (retrieved during 18-06-<strong>20</strong>12 to 10-07-<strong>20</strong>12)<br />

[3]. Computer concepts and programming in C by E. Balaguruswamy, Tata Mcgraw Hill publications.<br />

[4]. Design <strong>of</strong> machine elements by V.B. Bhandari, Tata McGraw hill publications.<br />

[5]. SolidWorks <strong>20</strong>11 Premium x64 Edition.<br />

360


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

FEM ANALYSIS OF COPPER USING EQUAL CHANNEL ANGULAR<br />

PRESSING<br />

Neeraj Saraswat 1, a , Rahul Jain 2, b , Rajnish Saxena 3, c<br />

1 Dayalbagh Education Institute, Agra-282110 INDIA<br />

2 Faculty <strong>of</strong> Engineering & <strong>Technology</strong>, Agra College, Agra-28<strong>20</strong>10, INDIA<br />

3 Manav Rachana International <strong>University</strong>, Faridabad, INDIA<br />

a neeraj7946@gmail.com, b rahuljain6@gmail.com<br />

Abstract<br />

The Severe Plastic Deformation (SPD) is an effective approach for producing bulk nanostructured material.<br />

Equal Channel Angular pressing (ECAP) processes provide an efficient procedure for achieving ultra fine<br />

grained material with excellent mechanical properties. The objective is to achieve high and homogeneous<br />

deformation in the work piece. In this work an optimized design <strong>of</strong> the channel die is presented which improves<br />

deformations obtained in materials using standard dies. This is a very useful process which can help in the<br />

reuse <strong>of</strong> bulk materials. It can convert the used bulk material to Ultra fine grained material. Ultra-fine<br />

grained materials exhibit superior mechanical properties such as high strength and ductility. In this work,<br />

three dimension finite element <strong>of</strong> ECAP process was carried out for Billet Material Copper with channel angle<br />

<strong>of</strong> 1<strong>20</strong> o for Strain harding Copper using Forge <strong>20</strong>07 s<strong>of</strong>tware. The Simulation results clearly depict the<br />

Evolution <strong>of</strong> Strain on body <strong>of</strong> work piece. The FE simulation greatly help to design the experimental condition<br />

to produce good material die for forging. The process parameter <strong>of</strong> ECAP influences the effect on properties <strong>of</strong><br />

material. In the present study FEM modeling <strong>of</strong> ECAP process using Copper for 10 mm round billet is attempt<br />

the effect <strong>of</strong> various process viz. channel intersection () angle, friction at die billet and punch velocity are<br />

studied. The FE simulations greatly help to design the experimental condition to produce good quality products<br />

in manufacturing industries.<br />

Keywords: Severe Plastic Deformation (SPD), ECAP, Ultra-fine grained Materials, FE Simulation<br />

1. Introduction<br />

The grain size <strong>of</strong> polycrystalline materials plays a critical role in determining the mechanical behaviour <strong>of</strong> the<br />

material. At low temperatures the strength increases with decreasing grain size through the Hall-Petch relationship<br />

[HA51, PE53].<br />

FORMULA<br />

Where σ y is the yield stress, σ o is a materials constant for the starting stress for dislocation movement (or the<br />

resistance <strong>of</strong> the lattice to dislocation motion), k y is the strengthening coefficient (a constant unique to each<br />

material), and d is the average grain diameter. At high temperatures, when diffusion becomes important, the material<br />

flows more rapidly when the grain size is reduced [LA93]. Thermo-mechanical processing is generally used<br />

in industrial operations to achieve a range <strong>of</strong> acceptable grain sizes for different applications but the smallest grain<br />

sizes attained in this way are typically <strong>of</strong> the order <strong>of</strong> a few micrometers. Two different types <strong>of</strong> processing technique<br />

have been developed in attempts to achieve exceptionally small grain sizes in the sub micrometer and nanometer<br />

range[ IWA96]. There are two types <strong>of</strong> approaches are used for grain refinement.<br />

2. Severe Plastic Deformation (SPD)<br />

Severe plastic deformation (SPD) is a generic term describing a group <strong>of</strong> metal-working techniques involving<br />

very large strains which are imposed without introducing any significant changes in the overall dimensions <strong>of</strong><br />

the specimen or work-piece. A further defining feature <strong>of</strong> SPD techniques is that the preservation <strong>of</strong> shape is<br />

achieved due to special tool geometries which prevent the free flow <strong>of</strong> material and thereby produce a<br />

significant hydrostatic pressure. The presence <strong>of</strong> a high hydrostatic pressure, in combination with large shear<br />

strains, is essential for producing high densities <strong>of</strong> crystal lattice defects, particularly dislocations, which can<br />

result in a significant refining <strong>of</strong> the grains. As the dimensions <strong>of</strong> the work-piece practically do not change in an<br />

SPD operation, the process may be applied repeatedly to impose exceptionally high strains. Optimization <strong>of</strong><br />

routes and regimes <strong>of</strong> SPD can eventually introduce an extremely fine microstructure into the processed material<br />

which will extend, reasonably homogeneously, throughout the bulk.<br />

361


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3. Equal-Channel Angular Pressing (ECAP)<br />

Equal channel angular pressing (ECAP) was invented by Segal in <strong>19</strong>77 in Russia. This technique involves<br />

pressing a billet through a die with the billet constrained within a channel which is bent through an abrupt<br />

angle within the die [FUR01]. Although the principles <strong>of</strong> ECAP processing were first introduced<br />

approximately twenty-five years ago, it is only very recently that the ECAP procedure has been applied to<br />

the processing <strong>of</strong> single crystals.<br />

4. Principles <strong>of</strong> Equal Channel Angular Pressing<br />

The basic principle <strong>of</strong> the ECAP process is to press a sample through a die having two intersecting channels,<br />

where the two channels have identical cross-sections so that the cross-section <strong>of</strong> the sample experiences no<br />

change during pressing. A specially-designed die is used in ECAP and two internal angles Φ and Ψ are defined<br />

as the curvature associated with the two channels where Φ corresponds to the angle between the two intersecting<br />

channels and Ψ is the angle at the outer arc <strong>of</strong> curvature <strong>of</strong> the two intersecting channels as shown in figure.1.<br />

Figure 1<br />

5. Finite Element Simulation<br />

Finite Element (FE) Simulation results for Copper materials<br />

1 Billet = Circular in cross section (10*100)<br />

2 Billet Material = Copper<br />

3 Lower die = Square in cross section<br />

4 Upper die = Circular in cross section<br />

5 Ψ = 0<br />

6 Φ = 1<strong>20</strong><br />

7 N = Single pass<br />

8 Friction = High<br />

9 Thermal Exchange = Adiabatic<br />

10 Temperature = <strong>20</strong> (Constant)<br />

11 Press = Hydraulic<br />

12 Velocity = 1 mm/s<br />

5.1 Equivalent Strain generated in Equal Channel Angular Pressing (ECAP)<br />

We can see value <strong>of</strong> equivalent strain is 1.4.<br />

Figure 2<br />

362


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5.2 Temperature distribution in Equal Channel Angular Pressing (ECAP)<br />

We can see that value <strong>of</strong> temperature distribution in ECAP process is 406 o C.<br />

Figure 3<br />

5.3 Pressure generated in Equal Channel Angular Pressing (ECAP)<br />

As shown in figure, Pressure generated in ECAP process is 48.49 MPA.<br />

Figure 4<br />

5.4 Force required for passing the Billet in Equal Channel Angular Pressing<br />

Graph-1<br />

As shown in graph, force required for passing the billet in ECAP is 15.47 Tones.<br />

363


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

6. Result<br />

Force(Tones) Equivalent Strain Pressure(MPa) Temperature( o C)<br />

15.47 1.4 48.49 406<br />

7. Conclusion<br />

1. Among all the SPD techniques, ECAP is the most developed and can so far produce the largest bulk Nano<br />

structured materials. However, ECAP is a discontinuous technique, which makes it a labour-intensive and<br />

relatively expensive process.<br />

2. In ECAP, it is possible very large deformation strain can be obtained after repeated passes without<br />

changing the shape <strong>of</strong> billets. Very uniform and homogeneous deformation can be applicable throughout<br />

the cross section <strong>of</strong> the Billet. In ECAP because input billet and end billet both have same cross section. so<br />

same lower die can be use for multiple times for the sake <strong>of</strong> larger strain generation.<br />

3. Single crystalline and polycrystalline both types <strong>of</strong> metal can be treated with ECAP Can be conducted at<br />

room temperature.<br />

4. ECAP processed UFG alloys have significantly enhanced properties<br />

5. Result obtained from FEM simulation is very useful for designing <strong>of</strong> Die.<br />

6. ECAP Process is useful for industrial application .it can be use in mass production.<br />

References<br />

1) E.O HALL, <strong>19</strong>51, Effect <strong>of</strong> deformation mode on the strength <strong>of</strong> deformation process, Material <strong>Science</strong><br />

Forum, 53-57, B64, HA51<br />

2) N.J.PETCH, <strong>19</strong>53, cleavage strength <strong>of</strong> polycrystals, journal <strong>of</strong> iron and steel institute 174, 25-28. PE53<br />

3) T.G.LANGDON, <strong>19</strong>93,Solute and Dispersed combined effects on mechanical properties <strong>of</strong> ultrafine<br />

grained Al alloy produced by friction stir processing” page no 410-411, Material science engineering.<br />

LA93<br />

4) IWAHASHI, Y., WANG, J., HORITA, Z., NEMOTO, M. AND LANGDON, T.G., <strong>19</strong>96, Principle <strong>of</strong><br />

Equal-Channel Angular Pressing for the Processing <strong>of</strong> Ultra-Fine Grained Materials, Scripta Materialia,<br />

35, 143-146. IWA96<br />

5) BIRRINGER, R., GLEITER, H., H. P. KLEIN, MARQUARDT, P., <strong>19</strong>84, Nanocrystalline materials: an<br />

approach to a novel solid structure with gas-like disorder, Physics letters, 102 A, 365- 369. BIR84<br />

6) ERB, U., <strong>19</strong>95, Electrodeposited nanocrystals: Synthesis, properties and industrial applications”,<br />

Nanostructured Materials, 6(5-8), 533-538. ER95<br />

7) Koch C. C. and Cho, Y. S., <strong>19</strong>92 “Nanocrystals by High Energy Ball Milling, Nanostructured Materials,<br />

1, <strong>20</strong>7–212. KO92<br />

8) KOCH, C.C.,<strong>20</strong>03, Top-down synthesis <strong>of</strong> nanostructured materials: Mechanical and thermal processing<br />

methods, Review <strong>of</strong> Advance Material <strong>Science</strong>, 5, 91–99. CC03<br />

9) FURUKAWA, M., HORITA, Z., NEMOTO, M. AND LANGDON, T.G., <strong>20</strong>02, The Use <strong>of</strong> Severe Plastic<br />

Deformation for Micro structural Control, Materials <strong>Science</strong> and Engineering, 324 A, 82-89. FU02<br />

10) IWAHASHI, Y., HORITA, Z., NEMOTO, M. AND LANGDON, T.G.,<strong>19</strong>98, The Process <strong>of</strong> Grain<br />

Refinement in Equal-Channel Angular Pressing, Acta Materialia, 46, 3317-3331.<br />

11) LANGDON, T.G., FURUKAWA, Z., NEMOTO, M. AND M., HORITA,<strong>20</strong>00, Refining Grain Size<br />

through Severe Plastic Deformation, Journal <strong>of</strong> Materials <strong>Science</strong>, 52(4), 30-33. HOR98<br />

12) ROSOCHOWSKI A., OLEJNIK L., RICHERT M.,<strong>20</strong>04,Metal forming technology for producing bulk<br />

nanostructured metals, Journal <strong>of</strong> Steel and Related Materials - Steel GRIPS, 2, Suppl. Metal Forming, 35-<br />

44. ROS04<br />

13) SEGAL, V.M.<strong>20</strong>02, Severe Plastic deformation :simple shear versus pure shear, Material science and<br />

Engineering (A), 2.,331-344. S02<br />

14) LANGDON,T.G,<strong>20</strong>10, The impact <strong>of</strong> Bulk Nanostructured Materials in Modern Reasearch, Rev.Adv.<br />

Mater. Sci. Res 25,11-15. LA10<br />

15) VALIEV,R.Z.,LANGDON,T.G,<strong>20</strong>11, Achieving Exceptional Grain Refinement through Severe Plastic<br />

Deformation: New Approches for Improving the process <strong>Technology</strong>, Metallurgical and Material<br />

transaction A,42,2942-2951. LA11<br />

364


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

SOLAR ELECTRIC VEHICLE: A SUSTAINABLE MODE OF<br />

TRANSPORT<br />

Team Solaris 1 , Dr. Samsher Gautam 2<br />

1<br />

Team Solaris: Mohd Bilal, Parth Desai, Prateek Jain, Sagar Biyani, Shashank Tayal, Vaibhav Arora<br />

Delhi Technological <strong>University</strong>, New Delhi<br />

Abstract<br />

The Solar Electric Vehicle, popularly known as SEV, is an important innovation to meet the future demands <strong>of</strong><br />

sustainable modes <strong>of</strong> transport. The present study investigates the need for development <strong>of</strong> SEV, and the strategy<br />

<strong>of</strong> the Solar Electric Vehicle development at Delhi Technological <strong>University</strong> over the years. The competition<br />

race strategy that is based on the maximization <strong>of</strong> the operational efficiency <strong>of</strong> the batteries to 90% is also<br />

discussed. The flow <strong>of</strong> energy in Avenir, the latest version <strong>of</strong> the DTU-SEV is also presented. Further, the design<br />

parameters <strong>of</strong> the chassis used in Avenir have been discussed, and stress analysis <strong>of</strong> the same on SolidWorks<br />

<strong>20</strong>10 is done to reflect the feasibility <strong>of</strong> the design on the basis <strong>of</strong> factor <strong>of</strong> safety, calculated to be 2.3 or higher.<br />

Keywords: Solar Car, Solar Electric Vehicle, SEV, Renewable Energy, Sustainable modes <strong>of</strong> transport, Solar<br />

photovoltaic cells, MPPT<br />

1. Introduction<br />

The automotive industry currently relies on non-renewable sources <strong>of</strong> energy like petroleum oil. At the current<br />

rate <strong>of</strong> consumption, these conventional sources <strong>of</strong> energy may be exhausted in the near future. In addition,<br />

consumption <strong>of</strong> petroleum and other non-renewable sources <strong>of</strong> energy by the automotive industry contributes<br />

highly to the ever increasing pollution levels, that has deleterious effects on biodiversity. Consequently, there<br />

have been innovations that utilize cleaner and sustainable sources <strong>of</strong> energy, especially in the automotive<br />

industry, and extensive research is being carried out in this field. In this regard, solar energy is <strong>of</strong> particular<br />

interest as it can be utilized very efficiently as a substitute for fuel in the automotive as well as other engineering<br />

sectors. The amalgamation <strong>of</strong> the automotive and the solar energy sector gave rise to the development <strong>of</strong> Solar<br />

Electric Vehicles, popularly known as SEVs, which derive the input energy from the Sun. The solar energy<br />

obtained from the sun, transformed into electrical energy by the cells, placed on the surface <strong>of</strong> the vehicle,<br />

charges the batteries. The power from the battery pack drives the motor and eventually powers the shafts, thus<br />

transforming the electrical energy to mechanical energy. With the efficiency <strong>of</strong> commercially available Solar<br />

Cells increasing to around 30% [1] , highly efficient solar electric vehicles have been developed in countries across<br />

the globe to fully utilise the solar energy. India especially has a huge potential in this field as the solar intensity is<br />

high at all times <strong>of</strong> the year. Hence, Solar Electric Vehicles hold immense significance in India in near future<br />

because <strong>of</strong> the abundant solar energy available.<br />

In India, an initiative in the field <strong>of</strong> development <strong>of</strong> SEV was first taken by the faculty and students <strong>of</strong> Delhi<br />

Technological <strong>University</strong>. The first vehicle under the project SOLARIS was presented in <strong>20</strong>07. Thereafter, two<br />

other vehicles with modifications and alterations in the design have been engendered, viz. Rogue in <strong>20</strong>08 and<br />

Avenir in <strong>20</strong>11.Rogue participated in the <strong>20</strong>08 South African Solar Challenge while Avenir participated in the<br />

World Solar Challenge in Australia in October <strong>20</strong>11. There have been improvements in design and structure <strong>of</strong><br />

the vehicle with each new version and the project continues to serve its aim <strong>of</strong> providing an alternative to fuel in<br />

the automotive industry in future. The fourth vehicle is under development, with an objective to culminate into a<br />

commercial Solar Electric Vehicle, ready to compete with the cars available in the market, running on fuel or<br />

gas. This paper is an overview <strong>of</strong> the development made by Delhi Technological <strong>University</strong> students in the SEV<br />

over the years. The structure, components and efficiency <strong>of</strong> the three models have been compared based on data<br />

obtained from testing and that collected at the competitions. A strategy <strong>of</strong> maximizing the battery life was<br />

followed at the <strong>20</strong>11 World Solar Challenge. The paper showcases the race strategy in detail. Also, the energy<br />

management systems including design <strong>of</strong> vehicle, analysis <strong>of</strong> race data are discussed in detail.<br />

2. Comparative study <strong>of</strong> Rogue (<strong>20</strong>08) and Avenir (<strong>20</strong>11)<br />

The electrical and mechanical components as well as the design <strong>of</strong> the two versions <strong>of</strong> the Solar Electric Vehicle-<br />

Rogue(’08) and Avenir(’11) differ in type, configuration, and efficiency. Technical modifications were made to<br />

improve efficiency, durability and to satisfy the event regulations <strong>of</strong> World Solar Challenge, which are different<br />

from those in South African Solar Challenge. The differences in the geographical conditions <strong>of</strong> Australia and<br />

365


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

South Africa were also considered while making the changes to the previous model. A detailed comparison is<br />

made in the following sections.<br />

2.1 Electrical System<br />

2.1.1 Rogue<br />

The battery pack consisting 8 number <strong>of</strong> Lead acid batteries (pure lead tin type) each <strong>of</strong> 12V, 42 Ah rating<br />

connected in series was used in Rogue(’08). Each battery weighed 13 kg, thus giving a total weight <strong>of</strong> 104 kg.<br />

Solar panels <strong>of</strong> monocrystalline PM84 series by MoserBaer, with efficiency <strong>of</strong> 16% and rated voltage and<br />

current as 0.6V and 5.5A respectively, were employed. Eight panels with 36 cells each were used on top <strong>of</strong> the<br />

vehicle giving a total output power <strong>of</strong> 674 watts.<br />

2.1.2 Avenir<br />

4 batteries <strong>of</strong> conventional lead acid type with a configuration <strong>of</strong> 12V, 33 Ah were used in order to make the<br />

battery pack with 48V rated voltage. Each battery with a weight <strong>of</strong> <strong>20</strong>kg made a total weight <strong>of</strong> 80 kg <strong>of</strong> the<br />

battery pack, thus decreasing the total weight <strong>of</strong> the vehicle. Solar panels <strong>of</strong> polycrystalline cells I6MU series by<br />

IndoSolar with an efficiency <strong>of</strong> 16.66% and rated voltage and current as 0.6V and 7.7A respectively were used.<br />

It had a rated power <strong>of</strong> 4 watts. Four panels <strong>of</strong> 60 cells each were used on top <strong>of</strong> the vehicle giving a total power<br />

<strong>of</strong> 960 Watts. The frame was also eliminated from the panels and a rubber coating was used to absorb the shocks<br />

on edges and corners, thus reducing the weight <strong>of</strong> the panels. A brushless DC hub motor was used instead <strong>of</strong> a<br />

separately excited motor connected through chain transmission thus reducing the losses.<br />

2.2 Mechanical Systems<br />

2.2.1 Rogue<br />

The chassis <strong>of</strong> the SEV was made <strong>of</strong> Aluminium 6063 alloy extrudes after stress analysis on ProE s<strong>of</strong>tware. The<br />

analysis showed that the chassis could bear 1.5 times the normal estimated weight <strong>of</strong> the car. The total weight <strong>of</strong><br />

the chassis was measured to be around 54kg.Front suspension <strong>of</strong> MacPherson strut type had been used, with a<br />

trailing arm suspension on the rear. Single reduction chain and sprocket type system with gear reduction ratio <strong>of</strong><br />

6.5:1 transmitted the power from the motor to the rear wheel.<br />

2.2.2 Avenir<br />

The chassis made <strong>of</strong> HINDALCO-aluminium 63400 alloy weighed around 50kg. Stress analysis <strong>of</strong> the chassis<br />

on SolidWorks <strong>20</strong>10 revealed that a total load equal to 2.3 times the estimated weight <strong>of</strong> the car could be borne<br />

by the chassis. Double A-Arm type suspension was used on the front as it provides better control. The<br />

suspension was designed so that it improved the ride quality and reduced tire wear considerably.<br />

Fig.1. Energy Flow Diagram <strong>of</strong> Avenir-<strong>20</strong>11<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3. Energy Flow in the SEV<br />

The power which drives the SEV is obtained from the batteries which are in turn charged by the solar energy<br />

obtained from the solar cells arranged on the surface <strong>of</strong> the vehicle. The power from the battery pack drives the<br />

motor and eventually powers the shafts, and hence transforming the electrical energy to mechanical energy. The<br />

flow <strong>of</strong> energy in the <strong>20</strong>11 version <strong>of</strong> the SEV is shown in Fig.1.<br />

3.1 Solar Energy<br />

The area covered by the cells on the surface was 6 m 2 complying with the regulations <strong>of</strong> the World Solar<br />

Challenge [2] . The amount <strong>of</strong> electrical power generated by the cells from solar energy depends on various factors<br />

like the weather conditions, solar isolation at a particular location, time <strong>of</strong> day and the angle <strong>of</strong> placing the solar<br />

cells on the surface. The efficiency <strong>of</strong> the polycrystalline silicon solar cells used was 16.66%and the efficiency <strong>of</strong><br />

a single module 13%, as tested in the lab [3] . Taking into account the above mentioned facts and factors, the<br />

overall power generated by the cells over a 6 m 2 area can be calculated as:<br />

P s = I .A .η (1)<br />

I = intensity <strong>of</strong> sunlight per unit area= 1000 W/m 2 (assuming clear sky during day) [6]<br />

A = Surface area covered by cells = 6 m 2<br />

η = overall efficiency <strong>of</strong> the module = 13%<br />

We get the value <strong>of</strong> power from solar cells at clear sky P s = 780 Watts<br />

The cut <strong>of</strong>f voltage <strong>of</strong> a single cell is 0.5V and so a total voltage <strong>of</strong> 60V is obtained as 1<strong>20</strong> cells are arranged in<br />

series. Considering this constraint, a 48V lead acid battery pack was used. The power from the solar cells charges<br />

the battery every moment until it is charged to its maximum capacity and battery voltage is maintained at 48V by<br />

the charge controller. In the mobile state <strong>of</strong> the car, the power from the batteries is continuously used by the<br />

motor and hence it gets discharged.<br />

3.2 Mechanical Power<br />

The force required at any moment for driving the SEV, assuming constant velocity is equal to the aerodynamic<br />

drag and the rolling frictional force acting on the car. Motorcycle tires <strong>of</strong> the SEV were <strong>of</strong> dimensions 100/80<br />

R17 and had a rolling resistance co-efficient <strong>of</strong> 0.02 [4] . The drag coefficient C d for a particular aer<strong>of</strong>oil pr<strong>of</strong>ile can<br />

be calculated using empirical formulae provided in the literature, and was evaluated to be 0.147 [1] . Hence, the<br />

power required at any moment can be calculated as follows:<br />

P m = P a + P r (2)<br />

P a = Aerodynamic loss = 1/2 .ρ .C d .A . v 3<br />

Where ρ = air density = 1.44 kg/m 3<br />

C d = co efficient <strong>of</strong> drag = 0.146 [6]<br />

v = velocity <strong>of</strong> car<br />

A = Frontal area <strong>of</strong> car = 1 m 2<br />

P r = Rolling resistance = µNv<br />

where µ= co-efficient <strong>of</strong> rolling friction= 0.02 [4] ; N = Normal Reaction on the tires =500 kgf<br />

3.3 Battery Efficiency<br />

The batteries used in an SEV should be robust, reliable and electrically isolated from the chassis <strong>of</strong> the car in<br />

order to prevent any catastrophe. Lead Acid batteries are the most conventional option and four 12V, 33 Ah<br />

batteries connected in series make a 48V, 33Ah battery pack. The efficiency <strong>of</strong> a battery can be defined as the<br />

ratio <strong>of</strong> the energy used in charging the battery to the energy supplied (in this case, by the solar cells). The<br />

efficiency <strong>of</strong> a battery increases with the decrease in charge. As mentioned by the manufacturers, the efficiency<br />

<strong>of</strong> the battery is minimum(about 60%) when it is more than 80% charged is maximum (about 90%) when it is<br />

less than 50% charged.<br />

4. Race Strategy for Competitions<br />

Considering the variations in the efficiency <strong>of</strong> the battery, the speed and the time during which the car should be<br />

run was strategized in order to get the optimal usage <strong>of</strong> batteries and charge them at maximum efficiency for the<br />

longest time possible during the race. For this reason, the usage <strong>of</strong> batteries was divided into 3 different sections<br />

on the basis <strong>of</strong> the amount <strong>of</strong> charge in the batteries:<br />

• Fully charged to 80% - at 60% charging efficiency<br />

• 80% to 50% - at 75% efficiency (assuming average efficiency)<br />

• 50% to <strong>20</strong>% - at 90% efficiency<br />

367


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The energy equation for any section mentioned above can be given as:<br />

(P m - P s ) t = D s (3)<br />

D s = battery discharge<br />

T = time<br />

On substituting the values <strong>of</strong> velocity <strong>of</strong> the car, the amount <strong>of</strong> time in any particular section <strong>of</strong> battery discharge<br />

can be obtained. Hence, on substituting the values <strong>of</strong> speeds from 25 to 60 kph on increments <strong>of</strong> 5 kph, the<br />

corresponding time and hence the distance that could be travelled is obtained. The mechanical power required to<br />

propel the car different velocities is listed in Table 1.<br />

Table 1. Power consumption at different speeds<br />

Sr. No. Velocity(kph) P a (Watts) P r (watts) P m (watts)<br />

1 60 405.72 1631.28 <strong>20</strong>37.00<br />

2 55 312.68 1497.32 1810.00<br />

3 50 235.00 1361.00 1596.00<br />

4 40 1<strong>20</strong>.42 1088.58 1<strong>20</strong>9.00<br />

5 30 51.00 816.00 867.00<br />

6 25 30.00 686.00 716.00<br />

The corresponding mechanical power for the velocities from 60 to 25 kph is obtained. Using these values, the<br />

time (using equation (3)) and hence the distance that could be travelled for two different sections are calculated.<br />

The observations are as follows:<br />

Table 2. Distance covered by the SEV at different battery charge percentage<br />

Battery discharge<br />

Battery discharge<br />

Sr.<br />

V(kph)<br />

80%-50%<br />

50%-<strong>20</strong>%<br />

No.<br />

Time(min) Distance(km) Time(min) Distance(km)<br />

1 60 <strong>19</strong>.00 <strong>19</strong>.00 21.00 21.00<br />

2 55 23.00 21.00 25.73 23.60<br />

3 50 28.<strong>20</strong> 23.50 31.89 26.87<br />

4 40 45.69 30.46 56.<strong>20</strong> 37.49<br />

5 30 101.10 50.55 172.80 86.40<br />

The efficiency <strong>of</strong> the battery is least(60%) while the battery discharges up to 80% <strong>of</strong> its capacity. Hence, for this<br />

range the car is driven at its maximum speed, i.e. is 60 kph in order to cover maximum distance in least possible<br />

time. For the battery capacity range <strong>of</strong> 80%-50%, maximum distance is covered at a speed <strong>of</strong> 30 kph, but the<br />

time taken is much higher than that at 40 kph, as inferred from Table 2. While the time taken for discharge at 50<br />

kph is lesser, there is a considerable loss <strong>of</strong> distance that can be covered. Hence, 40 kph is the optimum speed to<br />

drive at in this range. Also, for the battery discharge <strong>of</strong> 50%-<strong>20</strong>%, where the efficiency <strong>of</strong> the battery is about<br />

90%, the car is driven at 30 kph, thus covering maximum distance and allowing the battery to be operated at the<br />

highest efficiency.<br />

5.Chassis Design<br />

Chassis is the main frame <strong>of</strong> the vehicle that provides strength and rigidity to the vehicle and houses the driver,<br />

thus providing protection. Other components like batteries and electronic system are mounted to the chassis.<br />

Table 3. Weight <strong>of</strong> the Components <strong>of</strong> the SEV<br />

Component <strong>of</strong> the SEV<br />

Weight(kg)<br />

Chassis 50<br />

Upper Body and Solar Panels 142<br />

Lower Body 41<br />

Batteries 82<br />

Motor 15<br />

MPPT 4<br />

Wheels and other mechanical systems 40<br />

Driver Weight 90<br />

368


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Total 464<br />

Thus, it is imperative to calculate the amount and type <strong>of</strong> load exerted by these components on the chassis.<br />

Hence, the weight <strong>of</strong> the components was measured accurately, and is listed in Table 3.<br />

5.1 Design considerations<br />

Chassis must have high torsional rigidity, and must be able to withstand bump and droop forces, and support the<br />

passenger and body loads. In case <strong>of</strong> overturning, the roll cage must be strong enough to protect the driver. It is<br />

difficult to conduct real life experiments to determine the torsional rigidity and stiffness <strong>of</strong> the chassis. Hence, a<br />

model <strong>of</strong> the chassis was developed on SolidWorks <strong>20</strong>10, and stress analysis was done for various load cases.<br />

The resultant stresses were then compared with the yielding stresses <strong>of</strong> HINDALCO Aluminium 63400 <strong>of</strong> which<br />

the chassis was originally fabricated.<br />

5.2 Design implementation<br />

To increase the rigidity <strong>of</strong> the structure a combination <strong>of</strong> The Pratt Truss and The Warren truss was used in 3<br />

dimensions, leading to a Space-frame type chassis. For proper stress distribution and to provide support to the<br />

solar panels, the top rear <strong>of</strong> the chassis had an additional Warren Truss as shown in Fig.2. The mounting points<br />

<strong>of</strong> suspension and the driver’s seat were strengthened in a similar manner. Extrudes <strong>of</strong> HINDALCO Aluminium<br />

63400 alloy <strong>of</strong> 14 gauge and 1inch outer diameter were used. The alloy has an elastic modulus equal to 69GPa,<br />

Poisson’s ratio 0.33 and yield strength <strong>of</strong> 80MPa [5] .<br />

Fig.2.Chassis design <strong>of</strong> Avenir SEV showing load carrying family <strong>of</strong> members<br />

5.3 Static Structural Analysis <strong>of</strong> Chassis<br />

The stress analysis <strong>of</strong> chassis was done on SolidWorks <strong>20</strong>10. Geometry <strong>of</strong> the chassis design was created using<br />

SolidWorks GUI as per the design considerations mentioned above. Proper weldments were provided at the<br />

joints <strong>of</strong> the 3 dimensional structures to simulate the actual fabricated chassis. The structure was meshed using<br />

the Beam element, and load was applied on different members as listed in Table 4. The model was then solved<br />

for Von Misses stress distribution using Direct Sparse Solver. The report <strong>of</strong> the analysis was generated by<br />

SolidWorks <strong>20</strong>10. In the present analysis, the distribution <strong>of</strong> stress and the factor <strong>of</strong> safety for various members<br />

<strong>of</strong> the structure are studied.<br />

369


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 4. Type and Distribution <strong>of</strong> load for static analysis<br />

Load<br />

No.<br />

Load type<br />

Corresponding<br />

Member<br />

Family No.<br />

Load<br />

value(N)<br />

Distribution<br />

1. Weight <strong>of</strong> Solar Panels<br />

and Upper Body<br />

1 1400 Universally<br />

Distributed<br />

2. Battery weight 2 800 Universally<br />

Distributed<br />

3. Driver’s weight 3 900 Universally<br />

Distributed<br />

4. Lower Body Weight 4 400 Universally<br />

Distributed<br />

Total 3500<br />

Load Direction<br />

Vertically Downward<br />

Vertically Downward<br />

Vertically Downward<br />

Vertically Downward<br />

6. Results &Discussions<br />

The stress analysis results are conducted to study the strength and stiffness <strong>of</strong> the chassis. The maximum and<br />

minimum values <strong>of</strong> Von Misses stress in different members are observed for the worst case analysis. Fig. 3<br />

depicts the distribution <strong>of</strong> load across various members as well as the variation <strong>of</strong> Von Misses stress. It is<br />

observed that the maximum value <strong>of</strong> stress generated for any member is 39.104 MPa, which is much lower than<br />

the yield stress (80MPa) <strong>of</strong> HINDALCO Aluminium 63400. Further the factor <strong>of</strong> safety is also computed and its<br />

minimum value is found to be 2.5 as shown in Fig.4. Thus, the analysis shows that the structure is safe in static<br />

load conditions.<br />

Fig.3. Von Misses Stress distribution in structural members<br />

370


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig.4. Factor <strong>of</strong> Safety (FOS) <strong>of</strong> the Structural Members<br />

7. Conclusions<br />

Three versions <strong>of</strong> the Solar Electric Vehicle have been developed at Delhi Technological <strong>University</strong> since <strong>20</strong>07.<br />

A steady improvement in the technical design <strong>of</strong> the SEV has been made, as shown in the comparative study.<br />

Analysis <strong>of</strong> the data, collected during the race at the World Solar Challenge, shows that the car operated in the<br />

high efficiency range <strong>of</strong> the batteries, thereby increasing the life <strong>of</strong> the batteries. The race strategy as hereby<br />

proposed allowed the team to obtain a high efficiency <strong>of</strong> the system, as well as in maximising the distance<br />

travelled in minimum possible time. Appraising the data in table 2, the speeds at which the car should be driven<br />

for optimum usage <strong>of</strong> the battery are finalized as 60, 40 and 30 kph for the three discharge periods with<br />

corresponding efficiencies <strong>of</strong> 60%, 75% and 90% respectively. Moreover, the analysis <strong>of</strong> the chassis shows that<br />

the minimum factor <strong>of</strong> safety for any member is 2.3, which is an optimum value for static loading in case <strong>of</strong><br />

ductile materials. Hence, the chassis structure is safe. The chassis design and optimum utilisation <strong>of</strong> energy by<br />

the proposed method can be applied to develop a highly efficient Solar Electric Vehicle. The development <strong>of</strong> the<br />

SEVand successful participation at various international competitions viz. South African Solar Challenge in<br />

<strong>20</strong>08 and The World Solar Challenge in <strong>20</strong>11 underlines the feasibility <strong>of</strong> a cost effective and efficient Solar<br />

Electric Vehicle that can meet the demands <strong>of</strong> the automotive industry for a sustainable source <strong>of</strong> energy.<br />

References<br />

[1] http://azurspace.de/index.phpmm=97<br />

[2] http://www.worldsolarchallenge.org/files/13_regulations_for_<strong>20</strong>13_world_solar_challenge_release_copy_1-<br />

1.pdf<br />

[3] http://www.indosolar.co.in/product.html - product range<br />

[4] Cossalter, Vittore (<strong>20</strong>06). Motorcycle Dynamics (Second Edition ed.).Lulu.com. pp. 37–72.ISBN 978-1-<br />

4303-0861-4.<br />

[5] www.hindalco.com/businesses/pdfs/specification_extrusion.pdf<br />

[6] Carroll, Douglas R. (<strong>20</strong>03). The winning solar car: A design guide for solar race car teams. SAE<br />

International. ISBN 978-0-7680-1131-9.<br />

371


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Deflection and stress Analysis <strong>of</strong> Brake Disc using Finite Element Method<br />

Atul sharma 1 and M.L. Aggarwal 2<br />

1 Sr. Instructor, Machine shop, <strong>YMCA</strong>UST, Faridabad-121006,India.<br />

E-mail: atulfbd@rediffmail.com<br />

2 Pr<strong>of</strong>essor. Mech. Engg. Deptt, <strong>YMCA</strong>UST, Faridabad-121006,India.<br />

aggarwalmlal@rediffmail.com<br />

Abstract<br />

Disc brake are <strong>of</strong>ten used in automobile transmission system to stop moving machine. Due to space constraint<br />

and performance requirement, disc brakes have fluctuating load characteristics, resulting in local stress and<br />

deflections. Friction temperature in brake disc can cause material carbonization and debonding. This research<br />

paper explains the design and finite element analysis (FEA) model <strong>of</strong> brake disc by which deflections in X, Y, Z<br />

direction and Von mises stress can be calculated by applying boundry conditions. The FEA outcomes are<br />

correlated with experimental data. A good agreement, with 5% discrepancy in the experimental data during the<br />

first engagement is obtained. The developed method improves the understanding <strong>of</strong> the structural failure, modal<br />

prediction, operating conditions, and reduces product development time and cost.<br />

1. Introduction<br />

The disc brake is a device for slowing or stopping the rotation <strong>of</strong> a wheel while it is in motion. To stop the<br />

wheel, friction material in the form <strong>of</strong> brake pads is forced against both sides <strong>of</strong> the disc. The metallurgical<br />

properties <strong>of</strong> a rotor determine its strength, noise, wear and braking characteristics. Joe Y.G. cha [1] explained<br />

Analysis <strong>of</strong> disc brake instability due to friction induced vibration. M.Bayat[2] explained the effect <strong>of</strong> ceramic in<br />

combination <strong>of</strong> functionally graded rotating disc and the friction-induced vibration with a constant friction<br />

coefficient. Utz von wagner[3] explained Influence <strong>of</strong> dynamic brake pad properties on automotive disc brake<br />

squeal. A linear, lumped, and distributed parameter model to represent the floating caliper disc brake system. For<br />

actual geometric approximation, the disc is modeled as a hat-disc shape structure by the finite element method.<br />

Computer Aided Engineering is Computer Aided technology for supporting engineers in tasks such as analysis,<br />

simulation, design, manufacture, planning, diagnosis and repair. Computer Aided Analysis (CAA) is a technique<br />

by which approximate solution <strong>of</strong> a numerical problem can carry out. ANSYS is known as the standard in the<br />

field <strong>of</strong> Computer Aided Engineering. Finite Element method (FEM) simulates a physical part or assembly’s<br />

behavior by dividing the geometry <strong>of</strong> the part into a number <strong>of</strong> elements <strong>of</strong> standard shapes, applying loads and<br />

constraints, then calculating deflection and stresses.<br />

The stress and deflections is pointed out as essential parameter by most <strong>of</strong> the researchers in the case <strong>of</strong> brake<br />

disc and advanced s<strong>of</strong>twares are available for doing the analysis.<br />

Experimentally testing the brake disc takes lot <strong>of</strong> time. The objective <strong>of</strong> present work is to reduce brake disc<br />

testing time using computer model.<br />

2. Experimentation<br />

Computer aided engineering analysis <strong>of</strong> brake disk is a process in which two dimensional drawing is prepared on<br />

Autocad followed by solid modeling and then finite element analysis by meshing. The meshed model divided<br />

into the element list assigned with material properties. Boundry conditions are applied on model and deflections<br />

in X,Y,Z directions along with von Mises stresses are calculated. The procedure for static analysis consists <strong>of</strong><br />

these main steps Building the model, Obtaining the solution, Reviewing the results.<br />

.<br />

372


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig.1 Development Process<br />

Fig.2 Meshing properties <strong>of</strong> CAD model<br />

Fig.3 Meshing<br />

Fig.4 partial view meshing<br />

Fig. 5 Closer view meshing<br />

Fig. 6 Colour element plot after mesh<br />

373


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig.7 Element numbers and colours<br />

Fig.8 Element definition<br />

Fig.9 Element listing<br />

Fig.10 Material properties <strong>of</strong> disc AISI 1005<br />

Fig.11 Applying boundary condition<br />

Fig.12 Deflection - X<br />

374


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig.13 Deflection - Y<br />

Fig.14 Deflection - Z<br />

Fig.15 Von mises stress<br />

3. Results and Discussions<br />

Table 1 After applying boundry conditions following are the outcomes:-<br />

Parameter Experiment result FEA result<br />

Load 180 Kg 180 Kg<br />

Deflection-X 0.121E -03 0.115E -03<br />

Deflection - Y 0.312E -04 0.303E -04<br />

Deflection - Z 0.118E -03 0.1<strong>20</strong>E -03<br />

Von Mises stress 22 14.964<br />

Factor <strong>of</strong> Safety:-<br />

F.O.S=Ultimate Stress / Working Stress<br />

Maximium Ultimate Stress =299N/mm 2<br />

Working Stress =14.694N/mm 2<br />

i.e F.O.S=299/14.694<br />

=<strong>20</strong>.34<br />

After test results load is 180 Kg which includes passenger, load, weight transferred to front wheel. As shown in<br />

the table the experimental results are near to the results obtained in the FEA analysis.<br />

4. Conclusions<br />

The Deflection is found low ie .0001 ie approximately 0. and the working stress on new model is 14.694<br />

N/mm 2 which is less than test result <strong>of</strong> 21-22 N/mm 2 <strong>of</strong> existing model. The model is safe under the practical<br />

loading condition and our factor <strong>of</strong> safety is <strong>20</strong>.34.The present work can be utilised for fast analysis <strong>of</strong> brake<br />

disc to check stress and deflection.<br />

375


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

References<br />

1. Joe Y.G., cha,Analysis <strong>of</strong> disc brake instability due to friction induced vibration,International <strong>of</strong> automotive<br />

technology,Vol 9,No 2,PP 169-171.<br />

2. M.Bayat, The effect <strong>of</strong> ceramic in combination <strong>of</strong> functionally graded rotating disc,Internatinal journal <strong>of</strong><br />

computational method,Vol 9,No 2,<strong>20</strong>12,22 pages.<br />

3. Utz von wagner,Influence <strong>of</strong> dynamic brake pad properties on automotive disc brake squeal,PAMM,Vol<br />

11,Issue 1,Paper 345-346,Dec <strong>20</strong>11.<br />

4. Guillance fritz,investigation <strong>of</strong> the relationaship between damping and mode coupling patterns in case <strong>of</strong><br />

brake squeal,Journal <strong>of</strong> sound and vibration,vol 307,issue 3-5,Nov <strong>20</strong>07 PP 591-609.<br />

5. Adzhiev,V.,Kartasheva,E.,Konii,T.,Pasko A,Schmitt,B., Cellular Functional Modelling <strong>of</strong> Hetrogeneous<br />

Objects,Proceedings <strong>of</strong> Seventh ACM Symposium on Solid Modelling <strong>of</strong> Hetrogeneous<br />

Objects,Proceedings <strong>of</strong> Seventh ACM Symposium on Solid Modeling,<strong>20</strong>02,Page 129-170.<br />

6. Gursoz,EL.,Choi,Y and Prinz F.B. <strong>19</strong>90 “Vertex based representation <strong>of</strong> Boundaries”,Geometric for Product<br />

Engineering,North Holland,Pg 107-130<br />

376


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

TO ELIMINATE BIG END OVER SIZE REJECTION BY SIZING PLUG<br />

GAUGE ON CONNECTING ROD HONING MACHINE: A CASE<br />

STUDY<br />

Aditya Singh 1 and Rajeev Saha 2*<br />

1 Manager, Hero Honda, Dharuhera, Haryana, India.<br />

2 Asst. Pr<strong>of</strong>., Department <strong>of</strong> Mechanical Engg., <strong>YMCA</strong> UST, Faridabad<br />

2* Email: rajeevsaha@ymcaust.ac.in<br />

Abstract<br />

Connecting Rod or conrod used in a reciprocating piston engine connects the piston to the crank or crankshaft.<br />

Together with the crank, they form a simple mechanism that converts linear motion into rotating motion. It was<br />

observed that rejection rate <strong>of</strong> connecting rod being used in a two-wheeler industry was high. Identifying the<br />

root cause <strong>of</strong> rejection and finding a solution to reduce or rather eliminate the rejection <strong>of</strong> connecting rod has<br />

been dealt with in this case study.<br />

Keywords: Connecting Rod, Reciprocating Engine, Crankshaft.<br />

1. Introduction<br />

Connecting rod is an important part <strong>of</strong> a two wheeler which converts linear motion <strong>of</strong> piston into rotating motion<br />

<strong>of</strong> crank. As such it undergoes stringent checks <strong>of</strong> quality to ensure its proper functioning during actual<br />

workload. The connecting rod machining process is shown in Fig 1.<br />

Fig 1. Machining process <strong>of</strong> Connecting Rod<br />

Mukai and Komatsu (<strong>19</strong>89) developed a method for manufacturing <strong>of</strong> conrod and got it patented. A new<br />

technology known as the fracture splitting technology was developed in the beginning <strong>of</strong> the <strong>19</strong>90s for<br />

manufacturing conrods as described in Shuqin et al (<strong>20</strong>01) and Gu et al (<strong>20</strong>05).<br />

Fig 2. Actual photograph <strong>of</strong> a Connecting Rod<br />

377


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig 2 shows the actual photograph <strong>of</strong> a connecting rod. The past data <strong>of</strong> percentage <strong>of</strong> rejected conrod during<br />

different machining processes for a six month period has been shown in Fig 3.<br />

e<br />

g<br />

a<br />

%<br />

1.5<br />

1.3<br />

1.1<br />

0.9<br />

0.7<br />

0.5<br />

0.3<br />

0.1<br />

- 0.1<br />

1.01%<br />

0.<strong>19</strong><br />

0.25<br />

0.57 0.48<br />

0 0<br />

0.16<br />

1.31%<br />

1.15%<br />

0.25<br />

0.17<br />

0.75% 0.81% 0.26 0.33<br />

0.1<br />

0.11 0.11<br />

0.16<br />

0.44 0.72 0.73 0.36 0.55<br />

0 0<br />

MAR APR MAY JUN JUL AUG AVG.<br />

TOTAL 1.01 0.75 0.81 1.15 1.31 0.86 0.98<br />

OTHERS 0.<strong>19</strong> 0.11 0.1 0.17 0.25 0.24 0.18<br />

FINE BORING 0.25 0.16 0.11 0.26 0.33 0.13 0.2<br />

HONING 0.57 0.48 0.44 0.72 0.73 0.36 0.55<br />

DDG 0 0 0.16 0 0 0.13 0.06<br />

Fig 3. Percentage rejection <strong>of</strong> connecting rod<br />

0.86% 0.98%<br />

0.13 0.06<br />

To identify the root cause <strong>of</strong> conrod rejection, it was necessary to collect data <strong>of</strong> its manufacturing process. As<br />

we see in Fig 3, 55% <strong>of</strong> data rejection was at Honing process. For the same period <strong>of</strong> six months Honing process<br />

data was collected for analysis as shown in Fig 4.<br />

0.24<br />

0.13<br />

0.18<br />

0.2<br />

L<br />

O<br />

T<br />

S<br />

I<br />

Z<br />

E<br />

1000<br />

800<br />

600<br />

400<br />

<strong>20</strong>0<br />

0<br />

66%<br />

658<br />

Sizing P lug<br />

Rough<br />

87%<br />

<strong>20</strong>6<br />

Sizing Plug<br />

Semi F inish<br />

94% 98% 100%<br />

69<br />

36 23<br />

Ledge Setting setting Taper<br />

100%<br />

90%<br />

80%<br />

70%<br />

60%<br />

50%<br />

40%<br />

30%<br />

<strong>20</strong>%<br />

10%<br />

0%<br />

Fig 4. Rejection Contribution by different process during Honing<br />

As it is clearly visible from Fig 4, 87% <strong>of</strong> rejection could be attributed to processes <strong>of</strong> sizing plug rough and<br />

sizing plug semi finish. Data on quantity <strong>of</strong> rejected conrod during study period for the above said processes<br />

were collected as shown in Fig 5.<br />

378


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

<strong>20</strong>0<br />

187<br />

150<br />

ṡ<br />

o100<br />

N<br />

50<br />

164<br />

32<br />

132<br />

144 140<br />

40 38<br />

104 102<br />

44<br />

143<br />

125<br />

28<br />

97<br />

104<br />

24<br />

80<br />

0<br />

March April May June July August<br />

Total 164 144 140 187 125 104<br />

Semi<br />

finish<br />

32 40 38 44 28 24<br />

Rough 132 104 102 143 97 80<br />

Fig 5. Rejection due to Sizing Plug Gauge<br />

2. Problem Analysis<br />

To identify the root cause <strong>of</strong> problem, following steps were performed.<br />

Step 1: Machine Checking and Analysis: Machine Operators were first checked for their skill level and health for<br />

both shift A and B. The results were OK. Then Machine input for air pressure and hydraulic pressure were<br />

checked and found OK. Finally component fixtures and machine table were checked and also found to be within<br />

required limits.<br />

Step 2: Plate Assembly and Limit Switch Bracket were checked. It was found that there was certain play in<br />

sizing plug holder during plate assembly while in case <strong>of</strong> limit switch assembly there was difficulty in setting it<br />

correctly.<br />

Problem Observed<br />

1. Play in sizing plug holder<br />

2. Gap in Plug & Plate<br />

3. Perpendicularity not OK<br />

Fig 6. Plate Assembly model showing the problems observed<br />

Fig 6 shows the plate assembly model along with the problems observed. Inspection <strong>of</strong> plate assembly and its<br />

parts helped in detection <strong>of</strong> errors causing rejection <strong>of</strong> conrods. Fig 7 shows the inspection process and errors<br />

encountered therein.<br />

379


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig 7. Inspection <strong>of</strong> Plate Assembly & its Parts<br />

Problem Observed<br />

1. Fixed design.<br />

2. Difficult to adjust height.<br />

Fig 8. Limit Switch Working model showing problem observed<br />

The problems observed in Limit Switch working has been envisaged in Fig 8.<br />

3. Ideas for Solution<br />

IDEA No 1: New Plate with Bearing was designed as shown in Fig 9. This new design eliminated the problem <strong>of</strong><br />

wear.<br />

Fig 9. Design <strong>of</strong> new plate to eliminate wear problem<br />

IDEA No 2: New Plug Holder with Taper was designed as shown in Fig 10. This design eliminated the need <strong>of</strong><br />

having two separate plug for rough and semi-finish machining process. It also helped in reducing plug inventory<br />

by eliminating the existing diameter size variation problem.<br />

380


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig 10. Design <strong>of</strong> new plug holder with taper<br />

IDEA No 3: Limit Switch Bracket was modified as shown in Fig 11. This modification provided flexibility to Set<br />

limit switch position which ultimately resulted in common Rough & Semi finish Plug holder.<br />

Before<br />

After<br />

Fig 11. Limit Switch Bracket, Before and After modification<br />

4. Results<br />

Implementation <strong>of</strong> the three ideas suggested above helped in reducing the conrod rejection due to honing<br />

processes. Further implications <strong>of</strong> this study may be summarized as<br />

a) Less rejection.<br />

b) Setting time reduced<br />

c) Better quality<br />

d) Minimum variation in size<br />

e) Flexibility in fixture setting<br />

The complete plate assembly model due to implementation <strong>of</strong> above three ideas has been shown in Fig 12.<br />

381


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig 12. Plate Complete Assembly<br />

The tangible benefit due to implementation <strong>of</strong> above modification is saving <strong>of</strong> Rs. 103689.00 per year.<br />

Table 1A. Before implementing the modifications<br />

Data / Year Quantity Cost / Comp. Amount<br />

Rejection 1728 50.96 88059.00<br />

Sizing plug Gauge 18 1225 2<strong>20</strong>50.00<br />

Plate used 4 600 2400.00<br />

Bearing 6<strong>20</strong>6. 0 0 0.00<br />

Limit switch 2 510 10<strong>20</strong>.00<br />

Total 113529.00<br />

Table 1B. After implementing the modifications<br />

Data / Year Quantity Cost / Comp. Amount<br />

Rejection 0 50.96 0.00<br />

New Sizing plug Gauge 4 1545 6180.00<br />

Plate used 2 700 1400.00<br />

Bearing 6<strong>20</strong>6. 2 390 780.00<br />

382


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Limit switch 2 740 1480.00<br />

Total 9840.00<br />

Saving 113529.00 – 9840 = 103689.00<br />

5. Conclusion<br />

Analysis <strong>of</strong> the rejection problem <strong>of</strong> the connecting rod successfully led to the detection <strong>of</strong> the root causes <strong>of</strong> its<br />

rejection. Since Honing process contributed approximately 55% rejection on an average, it was naturally chosen<br />

to go through the Honing process in detail for identification <strong>of</strong> root causes. Collection <strong>of</strong> data during each step <strong>of</strong><br />

Honing process helped in identification and hence elimination <strong>of</strong> the root causes <strong>of</strong> rejection.<br />

References<br />

Gu, Z. and Yang, S. and Ku, S. and Zhao, Y. and Dai, X., "Fracture splitting technology <strong>of</strong> automobile engine<br />

connecting rod", The International Journal <strong>of</strong> Advanced Manufacturing <strong>Technology</strong>, volume 25, number 9, 883-<br />

887, <strong>20</strong>05<br />

Mukai, M. and Komatsu, K., “Method for producing connecting rod <strong>of</strong> reciprocating motion system”, US Patent<br />

No. 4,802,269 dated Feb. 7, <strong>19</strong>89<br />

Shuqing, K. and Wenming, J. and Zhengwei, G. and Shenhua, Y., "The New <strong>Technology</strong> and Developing Trend<br />

<strong>of</strong> IC Engine Connecting Rod Manufacturing", Chinese Internal Combustion Engine Engineering, volume 1,<br />

<strong>20</strong>01<br />

383


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

DESIGN OF IIR BAND PASS FILTER USING TIME DOMAIN<br />

APPROACH<br />

Ruchika Singh 1 ,Munish Vashisht 2<br />

1 Research Scholar, Deptt. <strong>of</strong> Electrical & Electronics Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>,<br />

Faridabad<br />

2 Associate Pr<strong>of</strong>essor, Deptt. <strong>of</strong> Electrical & Electronics Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> &<br />

<strong>Technology</strong>, Faridabad<br />

Corresponding Author: 1 helloruchi09@yahoo.com munish276@yahoo.com<br />

Abstract<br />

Filter design is the process <strong>of</strong> designing a filter (in the sense in which the term is used in signal processing,<br />

statistics, and applied mathematics), <strong>of</strong>ten a linear shift-invariant filter, that satisfies a set <strong>of</strong> requirements,<br />

some <strong>of</strong> which are contradictory. The purpose is to find a realization <strong>of</strong> the filter that meets each <strong>of</strong> the<br />

requirements to a sufficient degree to make it useful. The filter design process can be described as an<br />

optimization problem where each requirement contributes with a term to an error function which should be<br />

minimized. Certain parts <strong>of</strong> the design process can be automated, but normally an experienced electrical<br />

engineer is needed to get a good result.This paper deals with the design and implementation <strong>of</strong> IIR filter for<br />

wireless communication <strong>of</strong> a occupied channel. When a user <strong>of</strong> mobile occupies a channel, it assigns a range<br />

<strong>of</strong> frequencies for the same channel. For this purpose, we have designed a IIR filter to select a particular<br />

frequency range assigned to a particular channel. In our design, we have designed the appropriate type <strong>of</strong> band<br />

pass filter to implement this operation.<br />

Key words: IIR filter, Wireless communication, Band pass filter.<br />

1. Introduction<br />

IIR filters are digital filters with infinite impulse response. Unlike FIR filters, they have the feedback (a<br />

recursive part <strong>of</strong> a filter) and are known as recursive digital filters therefore. For this reason IIR filters have<br />

much better frequency response than FIR filters <strong>of</strong> the same order. Unlike FIR filters, their phase characteristic<br />

is not linear which can cause a problem to the systems which need phase linearity. For this reason, it is not<br />

preferable to use IIR filters in digital signal processing when the phase is <strong>of</strong> the essence.<br />

Otherwise, when the linear phase characteristic is not important, the use <strong>of</strong> IIR filters is an excellent solution.<br />

There is one problem known as a potential instability that is typical <strong>of</strong> IIR filters only. FIR filters do not have<br />

such a problem as they do not have the feedback. For this reason, it is always necessary to check after the design<br />

process whether the resulting IIR filter is stable or not.<br />

IIR filters can be designed using different methods. One <strong>of</strong> the most commonly used is via the reference analog<br />

prototype filter. This method is the best for designing all standard types <strong>of</strong> filters such as low-pass, high-pass,<br />

band-pass and band-stop filters. FIR filters can have linear phase characteristic, which is not typical <strong>of</strong> IIR<br />

filters. When it is necessary to have linear phase characteristic, FIR filters are the only available solution. In<br />

other cases when linear phase characteristic is not necessary, such as speech signal processing, FIR filters are<br />

not good solution. IIR filters should be used instead. The resulting filter order is considerably lower for the same<br />

frequency response.<br />

The ability to communicate with people on the move has evolved remarkably. People throughout the world have<br />

enthusiastically adopted the new wireless communication methods and services. For past few years, the mobile<br />

radio communication industries have grown by orders <strong>of</strong> magnitude, fueled by digital and RF circuit fabrication<br />

improvements, new large scale circuit integration, and other miniaturization technologies which makes portable<br />

radio equipment smaller, cheaper and more reliable. Digital switching techniques have facilitated the large-scale<br />

deployment <strong>of</strong> affordable and easy to use radio communication network [7].<br />

Recursive digital filters have been recognized as a very efficient and powerful implementation <strong>of</strong> many signalprocessing<br />

applications. While the problem <strong>of</strong> choosing the coefficients <strong>of</strong> a nonrecursive digital filter to<br />

approximate a specified magnitude characteristic has been thoroughly explored, the corresponding problem for<br />

recursive digital filter remains open. Design procedures for recursive digital filters generally deal only with the<br />

384


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

piecewise constant case, and involve transformations <strong>of</strong> well known continuous time filter designs, such as the<br />

Butterworth or Chebyshev.<br />

Digital filters are very important in signal processing because they allow distortion-free transmittion <strong>of</strong><br />

waveforms. The ease in realizability <strong>of</strong> the linear-phase characteristics is one <strong>of</strong> the main advantages <strong>of</strong> FIR<br />

filter over IIR filter. However, FIR filter has the drawback <strong>of</strong> the higher order than IIR filters having same<br />

magnitude characteristics. In many filter design problems, it is required to satisfy the linear-phase characteristics<br />

in the pass-band with a filter <strong>of</strong> the lowest possible order [5]. IIR digital filters can meet filter specifications<br />

more efficiently than FIR filter. Unfortunately, existing techniques for designing IIR filters are either restrictive<br />

or have undesirable characteristics.<br />

A number <strong>of</strong> methods have been proposed for the design <strong>of</strong> an IIR filter that approximates an arbitrary complexvalued<br />

frequency response. Such methods have been observed to exhibit undesirable properties. This is to be<br />

expected, because the development <strong>of</strong> such methods is inherently difficult due to the nonlinearity and<br />

complexity <strong>of</strong> the IIR filter design problem [4].<br />

2. Design Requirements<br />

Typical requirements which are considered in the design process are:<br />

• The filter should have a specific frequency response<br />

• The filter should have a specific phase shift or group delay<br />

• The filter should have a specific impulse response<br />

• The filter should be causal<br />

• The filter should be stable<br />

• The filter should be localized<br />

• The computational complexity <strong>of</strong> the filter should be low<br />

• The filter should be implemented in particular hardware or s<strong>of</strong>tware<br />

3. IIR Filter Design<br />

The IIR filter design using bilinear transformation can be split into several steps:<br />

1. Defining filter specification;<br />

2. Specifying analog prototype filter;<br />

3. Computing the filter order required for a given set <strong>of</strong> specifications and specified analog prototype filter;<br />

4. Computing the transfer function <strong>of</strong> reference analog prototype filter;<br />

5. Conversion into analog filter via scaling;<br />

6. Conversion into digital filter via bilinear transformation;<br />

7. If the obtained filter doesn’t satisfy the given specifications or if it is possible to decrease the filter order,<br />

then it is necessary to do it. The filter order can be increased or decreased according to needs and after<br />

that steps 4, 5 and 6 are repeated as many times as needed.<br />

The final objective <strong>of</strong> defining IIR filter specifications is to find the desirable normalized cut<strong>of</strong>f frequencies (ωc,<br />

ωc1, ωc2), transition width, maximum passband attenuation and minimum stopband attenuation. The type <strong>of</strong><br />

analog prototype filter as well as the filter order will be specified according to these parameters.<br />

Now, it is time to specify the type <strong>of</strong> reference analog prototype filter. Be aware that every type has its good and<br />

bad sides. It is only important that its characteristics can satisfy the given specifications. However, it is<br />

preferable to specify such a type <strong>of</strong> analog prototype filter that can produce the lowest order IIR filter.<br />

After this step, that is, when the type <strong>of</strong> analog proptotype filter is known, it is necessary to specify or compute<br />

the filter order required for a given set <strong>of</strong> specifications. The initial value <strong>of</strong> the filter order is roughly estimated<br />

and is changed after that depending on the obtained characteristics and requirements. When both type and order<br />

<strong>of</strong> analog prototype filter are known, it is possible to find its transfer function.<br />

The transfer function <strong>of</strong> analog prototype filter depends on frequencies which are not scaled into the desirable<br />

range. For this reason, it is necessary to perform scaling <strong>of</strong> the transfer function so that cut-<strong>of</strong>f frequencies go<br />

into the desirable range. This operation is actually conversion <strong>of</strong> reference analog prototype filter into analog<br />

filter with desirable characteristic.<br />

Finally, the transfer function <strong>of</strong> the specified type <strong>of</strong> reference analog prototype filter is obtained by converting<br />

analog filter into digital one. This book represents the most commonly used conversion known as bilinear<br />

transformation.<br />

385


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4. Problem Description<br />

When a mobile user moves from one region to another region, a different channel is allotted to the user<br />

depending upon the availability <strong>of</strong> the channel. A Band Pass IIR filter is designed which is used to give the<br />

response <strong>of</strong> a particular channel. Two band pass filters are used to give the responses <strong>of</strong> two available channels.<br />

5. System Modeling<br />

The filter consists <strong>of</strong> two stages connected in cascading. The single stage is designed in the direct form two. In<br />

the first stage x (n) is input and y 11 (n) is the output and Z -1 represents the delay element. The output <strong>of</strong> delay<br />

element is multiplied by the coefficients <strong>of</strong> numerator and denominator respectively and then fed the adder. The<br />

output <strong>of</strong> first stage y 11 (n) is fed to the input <strong>of</strong> second stage. The output <strong>of</strong> second stage is represented by y 1 (n).<br />

Thus the system is designed using cascaded structure while the individual stage is designed using direct form<br />

two structure.<br />

Fig. 1. Structure <strong>of</strong> band pass filter<br />

6. Mathematical Analysis<br />

The filter is having two stages in cascade form while the individual stage is designed in the direct form two<br />

structure.<br />

The band pass filter transfer function is<br />

− 1<br />

1 − z<br />

H ( z ) =<br />

(1)<br />

−1<br />

− 2<br />

1 − 0 .07 z + 0 .07 z<br />

Substituting<br />

j T<br />

e ω for z in equation (1)<br />

H<br />

1 − e<br />

= (2)<br />

1 − 0.07 e + 0.07 e<br />

− jω<br />

T<br />

( ω T )<br />

− jω<br />

T<br />

− 2 jω<br />

T<br />

Rearranging the terms to produce positive and negative exponents <strong>of</strong> equal magnitude in equation (2)<br />

H ( ωT<br />

) =<br />

H ( ωT<br />

) =<br />

e<br />

e<br />

− jωT<br />

jωT<br />

/ 2 jωT<br />

/ 2 − jωT<br />

/ 2<br />

[ e − e ]<br />

jωT<br />

− jωT<br />

[ e − 0.07 + 0.07e<br />

]<br />

−<br />

jωT<br />

/ 2 jωT<br />

/ 2 − jωT<br />

/ 2<br />

e [ e − e ]<br />

jωT<br />

− jω<br />

[ e − 0.07( 1 − e )]<br />

T<br />

(3)<br />

(4)<br />

Substituting inside the parentheses, the relation e<br />

j ω T = cos( ωT<br />

) + j sin( ωT<br />

)<br />

jωT<br />

/ 2<br />

e [ cos( ωT<br />

/ 2) + jsin(<br />

ωT<br />

/ 2) − cos( ωT<br />

/ 2) + j sin( ωT<br />

/ 2) ]<br />

H(<br />

ωT)<br />

=<br />

[ cos( ωT)<br />

+ jsin(<br />

ωT)<br />

] − 0.07 [(1<br />

− cos( ωT)<br />

+ j sin( ωT)<br />

]<br />

(5)<br />

386


jωT<br />

/ 2<br />

e [ 2 j sin( ωT<br />

/ 2) ]<br />

[ cos( ωT)<br />

+ j sin( ωT)<br />

] − 0.07 [(1<br />

− cos( ωT)<br />

+ j sin( ωT)<br />

]<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

H(<br />

ωT)<br />

= (6)<br />

Substituting<br />

∏ / 2<br />

j = e<br />

j in equation (6)<br />

j(<br />

ωT<br />

/ 2+∏<br />

/ 2)<br />

e [2sin( ωT<br />

/ 2)]<br />

H(<br />

ωT)<br />

=<br />

cos( ωT)<br />

− 0.07(1 − cos( ωT)<br />

+ j<br />

[ sin( ωT)<br />

− 0.07sin( ωT)<br />

]<br />

(7)<br />

H ( ω T )<br />

=<br />

(1 .07<br />

j ( ω T / 2 + ∏ / 2 )<br />

e [2 sin( ω T / 2)]<br />

cos( ω T ) − 0 .07 ) + j0 .93 sin( ω T )<br />

(8)<br />

Thus the magnitude response<br />

H(<br />

ωT)<br />

= [2sin( ωT<br />

/ 2)]<br />

(1.07cos( ωT)<br />

− 0.07) + j 0.93sin( ωT)<br />

(9)<br />

Magnitude in dB = H ( ωT<br />

)<br />

<strong>20</strong> log 10<br />

And the Phase Response is<br />

Θ<br />

( ω ) =<br />

ω T<br />

2<br />

+<br />

∏<br />

2<br />

−<br />

tan<br />

− 1<br />

0 .93 sin( ω T )<br />

1 .07 cos( ω T ) − 0 .07<br />

(10)<br />

Possible solution to this problem can be obtained in the following two steps.<br />

First, an IIR filter is designed; satisfying the magnitude specifications then it is connected in cascade to increase<br />

the gain <strong>of</strong> the filter and reducing the side lobes in the pass band <strong>of</strong> the filter. This filter satisfies the amplitude<br />

specifications and it has linear phase in the pass band [6].<br />

7. Results<br />

The desired magnitude response <strong>of</strong> band pass filter is obtained in the specified range <strong>of</strong> GSM. The band pass<br />

filter is designed which is having a 3 dB bandwidth <strong>of</strong> <strong>20</strong>0 kHz <strong>of</strong> each channel. The phase response <strong>of</strong> the filter<br />

is piecewise linear in the desired range. Thus the phase linearity is preserved in the pass band <strong>of</strong> the filter.<br />

Fig. 2. Magnitude response <strong>of</strong> band pass filter<br />

387


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5.9175 x 109 Frequency(MHz)----------><br />

5.917<br />

5.9165<br />

phase in degree<br />

5.916<br />

5.9155<br />

5.915<br />

5.9145<br />

9.41 9.4105 9.411 9.4115 9.412 9.4125 9.413 9.4135 9.414<br />

x 10 8<br />

Fig. 3. Phase response <strong>of</strong> band pass filter<br />

8. Conclusion<br />

A filter is designed having a bandpass response for the frequency range 941.12 MHz to 941.32 MHz for one<br />

channel having 3 dB bandwidth <strong>of</strong> <strong>20</strong>0 kHz, which is the requirement <strong>of</strong> GSM specifications. The phase<br />

response <strong>of</strong> this filter is piecewise linear. Several digital filters are designed using this technique and yields the<br />

better error performance. It is indeed suitable for time-domain digital system design and implementation. The<br />

advantage <strong>of</strong> proposed IIR filter design algorithm is that it uses real time application.<br />

References<br />

[1] CHARLES S. BURRUS AND THOMAS W. PARKS, <strong>19</strong>69, Time Domain Design <strong>of</strong> Recursive Digital<br />

Filter, IEEE Trans. Audio Electra oust, vol. AU18, pp.137-141..<br />

[2] KENNETH STEIGLITZ, <strong>19</strong>69, Computer-aided Design <strong>of</strong> Recursive Digital Filter, IEEE Trans. Audio<br />

Electracoust, AU18, 123-129.<br />

[3] RICHARD HASTINGS-JAMES AND SHASHI K.MEHRA,<strong>19</strong>77, Extensions <strong>of</strong> the Pade-<br />

Approximant Technique for the Design <strong>of</strong> Recursive Digital Filters, IEEE Trans. on Accoustics, Speech<br />

and Signal Processing, ASSP-25(6), 501-509.<br />

[4] CHI-TSONG CHEN, <strong>19</strong>80, Pade Approximants <strong>of</strong> Noncausal Digital Filters, Journal <strong>of</strong> Franklin<br />

Institute, 310, 210-213.<br />

[5] G.CICCARELLA AND P.MARIETTI, <strong>19</strong>87, Time Domain Approach to Recursive DigitalFilter<br />

Synthesis”, Elsevier <strong>Science</strong> B.V. Signal Processing, 12, 385-393.<br />

[6] BOR-SEN CHEN, CHIN-WEI LIN, <strong>19</strong>94, Multiscale Wiener Filter for the Restoration <strong>of</strong> Fractal Signals:<br />

Wavelet Filter Bank Approach, IEEE Transactions on Signal Processing, 42( 11), 2972-2982.<br />

[7] ASHRAF ALKHAIRY, <strong>19</strong>94, An Efficient Method for IIR Filter Design, IEEE Trans. Audio<br />

Electracoust, 569-571.<br />

[8] ARNAB K.SHAW, <strong>19</strong>95, Design <strong>of</strong> denominator Separable 2-D IIR Filters”, Elsevier <strong>Science</strong> B.V.<br />

Signal Processing, 42, <strong>19</strong>1-<strong>20</strong>6.<br />

[9] OLLI VAINIO, TAPIO SARAMALU, <strong>19</strong>97, Recursive Implementation <strong>of</strong> FIR Differentiators with<br />

Optimum Noise Attenuation, IEEE Transactions on Instrumentation and Measurement, 46(5), 1<strong>20</strong>2-1<strong>20</strong>.<br />

[10] HARTMUT BRANDENSTEIN AND ROLF UNBEHAUEN, <strong>19</strong>98, Least-Squares Approximation <strong>of</strong><br />

FIR by IIR Digital Filters’’ IEEE Trans. on Signal Processing, 46(1),.21-30.<br />

[11] BOR-SEN CHEN, YUE-CHIECH CHUNG, AND DER-FENG HUANG, <strong>19</strong>98, Optimal Time –<br />

Frequency Deconvolution Filter Design for Nonstationary Signal Transmission through a Fading<br />

Channel: AF Filter Bank Approach, IEEE Transactions on Signal Processing, 46(12), 32<strong>20</strong>-3234.<br />

[12 ] CUMHUR ERKUT1, VESA VÄLIMÄKI1, MATTI KARJALAINEN1, AND MIKAEL LAURSON,<br />

<strong>20</strong>00, Extraction <strong>of</strong> Physical and Expressive Parameters for Model-Based Sound Synthesis <strong>of</strong> The<br />

Classical Guitar, Journal <strong>of</strong> Audio Engineering Society, Inc, 1-16.<br />

[13] BOR-SEN CHEN AND LI-MEI CHEN, <strong>20</strong>00, Optimal Reconstruction in Multirate Transmultiplexer<br />

Systems under Channel Noise: Wiener Separation Filtering Approach”, Elsevier <strong>Science</strong> B.V. Signal<br />

Processing, 80, 637-657.<br />

388


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[14] AYUCHI KUROSU, SYOICHIRO MIYASE, SHIGENORI TOMIYAMA and T. SUYOSHI TAKEBE,<br />

<strong>20</strong>03, A Technique to Truncate IIR Filter Impulse Response and Its Application to Real-Time<br />

Implementation <strong>of</strong> Linear-Phase IIR Filters, IEEE Transactions on Signal Processing, 51(5), 1284-1292.<br />

389


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

FINITE ELEMENT ANALYSIS OF BEAM<br />

Hasan Zakir Jafri 1 , I.A. Khan 2 , S.M. Muzakkir 3<br />

1, Research Scholar, Faculty <strong>of</strong> Engineering & <strong>Technology</strong>, Jamia Millia Islamia<br />

2-3, Faculty <strong>of</strong> Engineering & <strong>Technology</strong>, Jamia Millia Islamia<br />

Maulana Mohammad Ali Jauhar Marg, Jamia Nagar, New Delhi-25<br />

e-mail: hasan.jafri@rediffmail.com 1<br />

Abstract<br />

With the increasing demand for newer products, subsequent design changes and introduction <strong>of</strong> newer models, such as in<br />

case <strong>of</strong> automobile industry, there is a need <strong>of</strong> quick and reliable method <strong>of</strong> product design and analysis. The finite element<br />

Analysis (FEA) has gained a lot <strong>of</strong> popularity in the present scenario as they can be used for quick design and analysis. But<br />

the FE predictions are <strong>of</strong>ten called into question as they are, at times, in conflict with test results because <strong>of</strong> inaccuracies in<br />

FE models which can arise due to use <strong>of</strong> incorrect modeling <strong>of</strong> boundary conditions, incorrect modeling <strong>of</strong> joints, and<br />

difficulties in modeling <strong>of</strong> damping etc. This paper presents the work that shows the need <strong>of</strong> correct selection <strong>of</strong> finite<br />

elements and nodes in order to get a correct prediction <strong>of</strong> dynamic behavior <strong>of</strong> the body or machine part under<br />

consideration which saves time and provides fairly good results. A Cantilever beam is modeled using Finite Element method<br />

using different nodes and elements and then the results are compared with analytical solution which shows that the<br />

significant error may arise in FE models. Thus there is a need <strong>of</strong> choosing the right elements and nodes while performing<br />

analysis, in order to predict the correct dynamic behavior as the analytical results may not be available or may be too<br />

complex to obtain.<br />

Keywords: FEM, ANSYS.<br />

1. Introduction<br />

Most <strong>of</strong> the beam theories were introduced as early as <strong>19</strong>21, and the problem <strong>of</strong> the transversely vibrating beam<br />

was formulated in terms <strong>of</strong> the partial differential equation <strong>of</strong> motion, an external forcing function, boundary<br />

conditions and initial conditions. However, work on this subject was done in a patchwork fashion by showing<br />

parts <strong>of</strong> the solution at a time, and there is no paper that presents the complete solution. The most complete<br />

study was done by Traill-Nash and Collar [1]. An exact formulation <strong>of</strong> the beam problem was first investigated<br />

in terms <strong>of</strong> general elasticity equations by Pochhammer (1876) and Chree (1889) [2]. They derived the<br />

equations that describe a vibrating solid cylinder. Since it is not practical to solve the full problem because it<br />

yields more information than usually needed in applications, therefore, the approximate solutions for transverse<br />

displacement are sufficient. The Euler-Bernoulli model includes the strain energy due to the bending and the<br />

kinetic energy due to the lateral displacement. Many advances on the elastic curves were made by Euler [3]. The<br />

Euler-Bernoulli beam theory is the most commonly used because it is simple and provides reasonable<br />

engineering approximations for many problems. However, the Euler-Bernoulli model tends to slightly<br />

overestimate the natural frequencies. This problem is exacerbated for the natural frequencies <strong>of</strong> the higher<br />

modes. Also, the prediction is better for slender beams than non-slender beams. Timoshenko (<strong>19</strong>21, <strong>19</strong>22) [4, 5]<br />

proposed a beam theory which adds the effect <strong>of</strong> shear as well as the effect <strong>of</strong> rotation to the Euler-Bernoulli<br />

beam. The Timoshenko model is a major improvement for non-slender beams and for high-frequency responses<br />

where shear or rotary effects are not negligible. Following Timoshenko, several authors have obtained the<br />

frequency equations and the mode shapes for various boundary conditions. Some are Kruszewski (<strong>19</strong>49) [6],<br />

Traill-Nash and Collar (<strong>19</strong>53) [1], Dolph (<strong>19</strong>54) [7], and Huang (<strong>19</strong>61) [8].<br />

Assumptions made by all models are as follows.<br />

1. One dimension (axial direction) is considerably larger than the other two.<br />

2. The material is linear elastic.<br />

3. The Poisson effect is neglected.<br />

4. The cross-sectional area is symmetric so that the neutral and centroidal axes coincide.<br />

5. Planes perpendicular to the neutral axis remain perpendicular after deformation.<br />

6. The angle <strong>of</strong> rotation is small so that the small angle assumption can be used.<br />

The common approach currently used in the structural analysis is the finite element method. The elements used<br />

in the finite element method are usually void <strong>of</strong> dynamics. The consequence is that hundreds and thousands <strong>of</strong><br />

elements are needed to represent large flexible structures in order to acquire analytical accuracy. To avoid the<br />

large dimensionality the current practice is to reduce the order <strong>of</strong> the model for structural system identification<br />

and control synthesis. This approximation, however, can lead to system instability due to the dynamics which<br />

are ignored. In contrast, distributed parameter modeling seems to <strong>of</strong>fer a viable alternative to the finite element<br />

approach for modeling large flexible structures. The essential difference between the distributed parameter<br />

approach and the finite element approach is that instead <strong>of</strong> the approximate shape functions by interpolating<br />

polynomials the solutions to the PDE's are used to describe the structural elements [11]. Finite Element Analysis<br />

390


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

(FEA) on other hand can be used for solving such problems by using available computer programs such as<br />

described in [15-16].<br />

2. Methodology<br />

The Finite Element method is used to solve physical problems in engineering analysis and design. The<br />

idealization <strong>of</strong> physical problem to mathematical model requires certain assumptions that together lead to<br />

differential equation governing the mathematical model. The FEA solves this mathematical model. Here the<br />

mass matrix formulation is carried out. A two-element cantilever beam is used in order to develop the consistent<br />

mass matrix. The six degrees <strong>of</strong> freedom lumped mass is used for constructing the lumped mass matrix The<br />

global mass matrix is built up as an assemblage <strong>of</strong> element mass matrices. A method analogous to static<br />

condensation, Guyan reduction, is used to reduce the size <strong>of</strong> the two-element cantilever problem. The model is<br />

then solved for its eigenvalues using Guyan reduction.<br />

Element Stiffness Matrix<br />

The element stiffness matrix is developed by using basic strength <strong>of</strong> materials techniques to analyse the forces<br />

required to displace each degree <strong>of</strong> freedom a unit value in the positive direction:<br />

Beam Node Definitions<br />

The two-beam elements are made identical, with the same E, I and length; the global stiffness matrix can then be<br />

rewritten as:<br />

⎡ 24 –12 6 ⎤<br />

0<br />

k<br />

g<br />

⎢ 3<br />

1<br />

⎢<br />

⎢ 0<br />

= ⎢<br />

⎢ –12<br />

⎢ 3<br />

1<br />

⎢ 6<br />

⎢ 2<br />

⎣ 1<br />

8<br />

1<br />

– 6<br />

2<br />

1<br />

2<br />

1<br />

3<br />

1<br />

– 6<br />

2<br />

1<br />

12<br />

3<br />

1<br />

– 6<br />

2<br />

1<br />

2<br />

1 ⎥<br />

2 ⎥<br />

⎥<br />

1 ⎥<br />

– 6⎥<br />

2<br />

1 ⎥<br />

4 ⎥<br />

⎥<br />

1 ⎦<br />

For solving the dynamics <strong>of</strong> the cantilever beam, a mass matrix is developed to complete the equations <strong>of</strong><br />

motion. For a beam finite element, there are a number <strong>of</strong> different mass matrix formulations as discussed in [13-<br />

15] out <strong>of</strong> which Consistent mass – distributed mass is used.<br />

391


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Consistent mass<br />

The consistent mass matrix for a beam element is a filled matrix. The filled matrix can be combined with other<br />

consistent mass matrices <strong>of</strong> other elements <strong>of</strong> the structure, in the same manner as the element stiffness matrices<br />

are combined, to yield the final global mass matrix. The element consistent mass matrix for a prismatic beam is,<br />

with mass per unit length m and length l.<br />

m<br />

e<br />

=<br />

ml<br />

4<strong>20</strong><br />

⎡ 156<br />

⎢<br />

221<br />

⎢<br />

⎢ 54<br />

⎢<br />

⎣−131<br />

221<br />

41<br />

2<br />

131<br />

2<br />

− 31<br />

54<br />

131<br />

156<br />

− 221<br />

−131⎤<br />

2<br />

− 31<br />

⎥<br />

⎥<br />

− 221⎥<br />

2 ⎥<br />

41 ⎦<br />

Assuming the two elements have the same properties and lengths, the global mass matrix becomes:<br />

2<br />

2<br />

⎡ 156m1 22m1 54m1 −13m1<br />

0 0 ⎤<br />

⎢ 2<br />

3<br />

2<br />

3<br />

⎥<br />

⎢ 22m1 4m1 13m1 − 3m1 0 0 ⎥<br />

⎢<br />

2<br />

2<br />

1 54m1 13m1 312m1 0 54m1 −13m1<br />

⎥<br />

mg<br />

= ⎢<br />

2<br />

3<br />

3<br />

2<br />

3<br />

⎥<br />

4<strong>20</strong> ⎢−13m1<br />

− 3m1 0 8m1 13m1 − 3m1 ⎥<br />

⎢<br />

2<br />

2<br />

0 0 54m1 13m1 156m1 − 22m1 ⎥<br />

⎢<br />

⎥<br />

2<br />

3<br />

2<br />

3<br />

⎢⎣<br />

0 0 −13m1<br />

− 3m1 − 22m1 4m1 ⎥⎦<br />

Taking into account the two constrained degrees <strong>of</strong> freedom at the built in end, we can eliminate the first two<br />

rows and columns:<br />

m<br />

g<br />

=<br />

1<br />

4<strong>20</strong><br />

⎡ 312m1<br />

⎢<br />

⎢<br />

⎢<br />

⎢<br />

⎣<br />

0<br />

54m1<br />

2<br />

−13m1<br />

0<br />

8m1<br />

3<br />

13m1<br />

2<br />

3<br />

− 3m1<br />

54m1<br />

13m1<br />

2<br />

156m1<br />

2<br />

− 22m1<br />

−13m1<br />

− 3m1<br />

− 22m1<br />

4m1<br />

3<br />

3<br />

2<br />

2<br />

⎤<br />

⎥<br />

⎥<br />

⎥<br />

⎥<br />

⎦<br />

Having the mass and stiffness matrices allows us to solve the eigenvalue problem for the homogeneous<br />

equations <strong>of</strong> motion:<br />

mg ž + kgz<br />

= [ 0]<br />

It is better to reduce the 4x4 problem down to 2x2 size. Therefore, the Guyan reduction [15] will be used to<br />

reduce the size <strong>of</strong> the problem.<br />

Two element cantilever eigen value closed form solution using guyan reduction<br />

Repeating the rearranged global stiffness matrix from the static run,<br />

⎡ 24<br />

– 12<br />

⎢<br />

0<br />

3<br />

3<br />

1<br />

1<br />

⎢<br />

8 – 6<br />

⎢ 0<br />

2<br />

k = ⎢<br />

1 1<br />

g<br />

EI<br />

⎢ – 12 – 6 12<br />

⎢ 3<br />

2<br />

3<br />

1 1 1<br />

⎢ 6 2 – 6<br />

⎢<br />

2<br />

2<br />

⎣ 1 1 1<br />

6<br />

2<br />

1<br />

2<br />

1<br />

– 6<br />

2<br />

1<br />

4<br />

1<br />

⎤<br />

⎥<br />

⎥<br />

⎥<br />

⎥<br />

⎥<br />

⎥<br />

⎥<br />

⎥<br />

⎦<br />

Equation <strong>of</strong> motion is: mss<br />

x + kssx = [0]<br />

392


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

⎡1<br />

⎢<br />

⎢<br />

0<br />

⎢0<br />

⎢<br />

⎢0<br />

⎣<br />

0<br />

1528ml<br />

1715<br />

0<br />

241ml<br />

1372<br />

0<br />

0<br />

1<br />

0<br />

0<br />

241ml<br />

1372<br />

0<br />

471ml<br />

1715<br />

⎤ ⎡ ⎤ ⎡ 0<br />

⎥<br />

x 1<br />

⎢ <strong>19</strong>2EI<br />

⎢ ⎥<br />

⎥ ⎢ x 2<br />

⎥ ⎢ 3<br />

+ 14l<br />

⎥ ⎢ ⎥ ⎢<br />

⎥ x 0<br />

3<br />

⎢ ⎥ ⎢ − 60EI<br />

⎥ ⎣ x 4 ⎦ ⎢<br />

3<br />

⎦ ⎣ 14l<br />

− 1<br />

0<br />

0<br />

0<br />

0<br />

− 60EI<br />

3<br />

14l<br />

0<br />

24EI<br />

3<br />

14l<br />

0 ⎤<br />

⎥<br />

0<br />

⎥<br />

− 1⎥<br />

⎥<br />

0 ⎥<br />

⎦<br />

⎡ x<br />

⎢<br />

x<br />

⎢<br />

⎢ x<br />

⎢<br />

⎣ x<br />

1<br />

2<br />

3<br />

4<br />

⎤<br />

⎥<br />

⎥<br />

⎥<br />

⎥<br />

⎦<br />

=<br />

⎡0⎤<br />

⎢<br />

0<br />

⎥<br />

⎢ ⎥<br />

⎢0⎥<br />

⎢ ⎥<br />

⎣0⎦<br />

Pre multiplying the equation <strong>of</strong> motion by identity matrix<br />

⎡1<br />

⎢<br />

0<br />

⎢<br />

⎢0<br />

⎢<br />

⎣0<br />

0<br />

1<br />

0<br />

0<br />

0<br />

0<br />

1<br />

0<br />

0⎤<br />

0<br />

⎥<br />

⎥<br />

0⎥<br />

⎥<br />

1⎦<br />

⎡ x<br />

⎢<br />

⎢x<br />

⎢ x<br />

⎢<br />

⎣x<br />

1<br />

2<br />

3<br />

4<br />

⎤<br />

⎥<br />

⎥<br />

⎥<br />

⎥<br />

⎦<br />

⎡ 0<br />

⎢ 4340280EI<br />

⎢<br />

4<br />

+ <strong>20</strong>5367ml<br />

⎢ 0<br />

⎢ − 5980800EI<br />

⎢<br />

4<br />

⎣ <strong>20</strong>5367ml<br />

− 1<br />

0<br />

0<br />

0<br />

0<br />

− 14<strong>19</strong>600EI<br />

<strong>20</strong>5367ml<br />

0<br />

2189880EI<br />

<strong>20</strong>5367ml<br />

4<br />

4<br />

0 ⎤<br />

⎥<br />

0<br />

⎥<br />

− 1⎥<br />

⎥<br />

0 ⎥<br />

⎦<br />

⎡ x<br />

⎢<br />

x<br />

⎢<br />

⎢ x<br />

⎢<br />

⎣x<br />

1<br />

2<br />

3<br />

4<br />

⎤<br />

⎥<br />

⎥<br />

⎥<br />

⎥<br />

⎦<br />

=<br />

⎡0⎤<br />

⎢<br />

0<br />

⎥<br />

⎢ ⎥<br />

⎢0⎥<br />

⎢ ⎥<br />

⎣0⎦<br />

Rewriting without the identity matrix:<br />

⎡x<br />

⎢<br />

⎢x<br />

⎢x<br />

⎢<br />

⎣x<br />

1<br />

2<br />

3<br />

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⎤ ⎡ 0<br />

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⎥ = <strong>20</strong>5367ml<br />

⎥ ⎢ 0<br />

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<strong>20</strong>5367ml<br />

4<br />

0⎤<br />

⎡x<br />

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3<br />

4<br />

⎤<br />

⎥<br />

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Using a symbolic algebra program to solve for the eigenvalues<br />

f<br />

1,2<br />

⎛ 1 ⎞ ⎛ 2 ⎞<br />

⎜ ⎟ ⎜ ⎟<br />

⎝ 2π ⎠ ⎝ <strong>20</strong>5367⎠<br />

43127070<br />

EIm(3887 ± <strong>20</strong><br />

ml<br />

2<br />

34178)<br />

=<br />

eq.1<br />

The above equation is used to solve the natural frequency <strong>of</strong> cantilever beam which is listed in table [1].<br />

Analytical modeling <strong>of</strong> cantilever beam<br />

The analytical solution for resonant frequencies will be obtained from the exact analysis to confirm the validity<br />

<strong>of</strong> FE Model solution. The analytical solution <strong>of</strong> resonant frequencies <strong>of</strong> continuous systems is given in<br />

references [13-15].<br />

The dimensions <strong>of</strong> the cantilever beam are as follows:<br />

Thickness <strong>of</strong> the cantilever beam 0.005 m.<br />

Width 0.01 m<br />

Length 0.09 m<br />

The equation for solving the natural frequency <strong>of</strong> a cantilever beam is given by:<br />

393


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2<br />

λi<br />

EI<br />

= (i 1, 2, 3,...)<br />

Eq. 2<br />

2ππ M<br />

fi =<br />

2<br />

Using the following properties <strong>of</strong> the material:<br />

Young’s modulus, E =<strong>20</strong>6 GPa<br />

Poisson’s ratio ν=0.3.<br />

Density ρ=7.8×103 kg/m3<br />

The values <strong>of</strong> constants are: λ 1 = 1.875 λ 2 = 4.694 λ 3 = 7.85<br />

For this set <strong>of</strong> data the analytical solutions are obtained and listed in table 1.<br />

Fig.1 First three mode shapes obtained by ANSYS<br />

3. Results<br />

The results obtained by solving the equation 1 and 2 and the solution obtained from ANSYS s<strong>of</strong>tware using<br />

different Elements are shown in the table below, the following results are obtained.<br />

Table 1: Natural Frequency <strong>of</strong> different FE Models<br />

MOD NO.<br />

EXACT<br />

SOLN<br />

1-<br />

ELEMENT<br />

BEAM<br />

2-<br />

ELEMENT<br />

BEAM<br />

10-<br />

ELEMENT<br />

BEAM<br />

50-<br />

ELEMENT<br />

BEAM<br />

100-<br />

ELEMENT<br />

BEAM<br />

150-<br />

ELEMENT<br />

BEAM<br />

<strong>20</strong>0-<br />

ELEMENT<br />

BEAM<br />

250-<br />

ELEMENT<br />

BEAM<br />

1 512.5 514.65 512.47 512.23 512.23 512.23 516.35 512.23 516.35<br />

2 3212 5035.9 3225.5 3<strong>19</strong>8.8 3<strong>19</strong>8.7 3<strong>19</strong>8.7 3224.3 3<strong>19</strong>8.7 3224.3<br />

3 8994 15741 10828 8907.8 8905.5 8905.5 8976.5 8905.5 8976.5<br />

4 - - 14644 14290 14276 14275 14333 14275 14333<br />

5 - - 30558 17325 17309 17309 17445 17309 17445<br />

6 - - 51159 28384 28315 28315 28536 28315 28536<br />

394


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The analytical model was solved to obtain the Natural Frequency from the analytical expression. It gives the<br />

following first three Natural Frequency <strong>of</strong> 512.5, 3212 and 8994 Hz. The first three Natural Frequencies for a<br />

one element FE model are determined as 514.65, 5035.9 and 15741Hz, indicating huge differences between the<br />

second and third Natural Frequency <strong>of</strong> analytical model and one element FE model. This is due to the gross<br />

approximation in the FE model. The percentage error comes out to be 0.41776 %, 36.21796% and 42.86 % in<br />

first, second and third Natural Frequency respectively.<br />

The first three Natural Frequencies for a two element FE model are determined as 512.47, 3225.5 and 10828 Hz<br />

and are fairly close to the analytical model. The percentage error comes out to be -.0058%, 0.41854 and 16.93%<br />

in first, second and third Natural Frequencies respectively.<br />

The first three Natural Frequencies for a ten element FE model using ANSYS are determined as 512.23, 3<strong>19</strong>8.8<br />

and 8109.8 Hz and are much closer to the analytical model. The percentage error comes out to be -0.05271%, -<br />

0.41265 and 0.9679% in first, second and third Natural Frequencies respectively. This clearly establishes that as<br />

the number <strong>of</strong> elements is increased the percentage error is reduced further.<br />

Therefore a FE model with large number <strong>of</strong> elements is desirable to obtain accurate results. The first three<br />

Natural Frequencies for a ten element FE model using ANSYS are determined as 512.23, 3<strong>19</strong>8.6 and 8905.5 Hz<br />

and are much closer to the analytical model. The percentage error comes out to be -0.05271%, -0.41579% and<br />

0.99377% in first, second and third Natural Frequency respectively.<br />

As seen from the above, the error for the first natural frequency is fairly constant and is around -0.05 % but for<br />

the second natural frequency the error is quite high for one element FE model but is quite less for the higher<br />

number <strong>of</strong> nodes. Same trend can be seen for the third natural frequency <strong>of</strong> higher number <strong>of</strong> nodes.<br />

Table 2: Percentage error in different FE models<br />

MOD NO.<br />

1-<br />

ELEMENT<br />

BEAM<br />

2-<br />

ELEMENT<br />

BEAM<br />

10-<br />

ELEMENT<br />

BEAM<br />

50-<br />

ELEMENT<br />

BEAM<br />

100-<br />

ELEMENT<br />

BEAM<br />

150-<br />

ELEMENT<br />

BEAM<br />

<strong>20</strong>0-<br />

ELEMENT<br />

BEAM<br />

250-<br />

ELEMENT<br />

BEAM<br />

1 0.41776 -0.00585 -0.05271 -0.05271 -0.05271 0.74561 -0.05271 0.74561<br />

2 36.21796 0.41854 -0.41265 -0.41579 -0.41579 0.38147 -0.41579 0.38147<br />

3 42.86259 16.93757 -0.96769 -0.99377 -0.99377 -0.<strong>19</strong>49 -0.99377 -0.<strong>19</strong>495<br />

4. Conclusion<br />

The exact solution obtained from the differential equations gives us the basis to correlate the results obtained<br />

using the FE solution. As the table.1 shows that one element FE solution gives very crude results as expected<br />

because the error involved in analysis is more and it further increases as the modes are increased. As the number<br />

<strong>of</strong> nodes are increased the results tends to improve further but it shows a wavy pattern because <strong>of</strong> rounding <strong>of</strong>f<br />

errors involved in adding different beam elements.<br />

The following conclusions may be drawn from the results thus obtained.<br />

1. A huge amount <strong>of</strong> errors may be involved in the FE analysis if element selection is not proper thus<br />

needs a considerable experience for making the choice <strong>of</strong> selecting the elements.<br />

2. The time involved in analysis, which adds to the cost <strong>of</strong> analysis and processing time also depends<br />

upon the choice <strong>of</strong> the elements.<br />

3. For complicated or huge structures as used in mechanical and civil engineering the analytical solution<br />

may not be available or may be too complex to obtain.<br />

Therefore it may be concluded that for complex structures or real structures the choice <strong>of</strong> elements in FEA has a<br />

great impact on results and should be carefully chosen.<br />

395


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

References<br />

1. R.W.Traill-nash and A.R.Collar, <strong>19</strong>53, Quarterly Journal <strong>of</strong> Mechanics and Applied Mathematics 6, 186-<br />

213. “The effects <strong>of</strong> shear flexibility and rotatory inertia on the bending vibrations <strong>of</strong> beams”<br />

2. A.E.H.Love <strong>19</strong>27 “Treatise on the Mathematical theory <strong>of</strong> Elasticity. New York: Dover Publications, Inc.<br />

3. S.P.Timoshenko, <strong>19</strong>53, History <strong>of</strong> Strength <strong>of</strong> Materials. New York: Dover Publications, Inc.<br />

4. S.P.Timoshenko, <strong>19</strong>21, Philosophical Magazine, 744. “On the correction for shear <strong>of</strong> the differential<br />

equation for transverse vibrations <strong>of</strong> bars <strong>of</strong> uniform cross-section”<br />

5. S.P.Timoshenko, <strong>19</strong>22, Philosophical Magazine, 125. “On the transverse vibrations <strong>of</strong> bars <strong>of</strong> uniform<br />

cross-section”<br />

6. E.T.Kruszewski, <strong>19</strong>49, National Advisory Committee for Aeronautics, <strong>19</strong>09. “Effects <strong>of</strong> transverse shear<br />

and rotary inertia on the natural frequencies <strong>of</strong> a uniform beam”<br />

7. C.L.Dolph, <strong>19</strong>54, Quarterly <strong>of</strong> Applied Mathematics 12, 175-187. “On the Timoshenko theory <strong>of</strong> transverse<br />

beam vibrations”<br />

8. T.C.Huang, <strong>19</strong>61, Journal <strong>of</strong> Applied Mechanics, 579-584. “The effect <strong>of</strong> rotatory inertia and <strong>of</strong> shear<br />

deformation on the frequency and normal mode equations <strong>of</strong> uniform beams with simple end conditions”<br />

9. M.Levinson, <strong>19</strong>81, Journal <strong>of</strong> Sound and vibration 77, 440-444. “Further results <strong>of</strong> a new beam theory”<br />

10. M.Levinson, <strong>19</strong>81, Journal <strong>of</strong> Sound and vibration 74, 81-87. “A new rectangular beam theory”<br />

11. J.Y. Shen, Jen K. Huang and Lawrence W. Taylor, Jr., "Timoshenko Beam Modeling for Parameter<br />

Estimation <strong>of</strong> NASA Mini-Mast Truss", the Journal <strong>of</strong> Vibration and Acoustics, Transaction <strong>of</strong> the ASME,<br />

Vol. 115, Jan. <strong>19</strong>93, pp. <strong>19</strong>-24.<br />

12. Thomson, W.T. ‘Vibration Theory and Applications’ George Allen and Unwin Ltd., <strong>19</strong>73.<br />

13. Den Hartong, J.P., ‘Mechanical Vibrations’ McGraw-Hill Book Co.4 th ed., New York <strong>19</strong>56.<br />

14. Rao, J.S and Gupta, K. ‘Introductory Course on Theory and Practice <strong>of</strong> Mechanical Vibrations’ Wiley<br />

Eastern Limited (India) <strong>19</strong>87<br />

15. Stolarski, T., Nakasone, Y., Yoshimoto, S. ‘Engineering Analysis with ANSYS S<strong>of</strong>tware’ Elsevier<br />

Butterworth-Heinemann, Oxford, <strong>19</strong>88<br />

16. Hatch, R.Michael, ‘Vibration Simulation Using MATLAB and ANSYS’ CRC Press, Florida <strong>20</strong>01<br />

396


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

DESIGN AND OPTIMISATION OF ROBOTIC GRIPPER: A REVIEW<br />

Vaibhav Raghav 1 , Jitender Kumar 2 and Shailesh S.Senger 3<br />

1,2,3 M.Tech. Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong>UST, Faridabad<br />

Abstract<br />

In this paper, the field <strong>of</strong> robotic gripper and the work in this area over the last two decades has been reviewed.<br />

In the recent past many different robot grippers have been developed to grasp one or a few specific objects.<br />

Those grippers are well suited for continuous work in structured environments. On the other hand, some<br />

researchers have focused their attention on sophisticated general purpose grippers having kinematics and<br />

dextrousness similar to the human hand. With the evolution <strong>of</strong> automation in industries, grasping become an<br />

important topic in robotics research community.The paperemphasis on study <strong>of</strong> current existing robotic grippers,<br />

their basic design and optimization <strong>of</strong> the same.<br />

Keywords: Robotic gripper, Design, Flexibility, Optimization parameters.<br />

1. INTRODUCTION<br />

A gripper is the mechanical interface between the robot and its environment. Without it, the robot cannot perform<br />

the pick-and-place functions .In industrial applications it is common to handle objects with different geometries<br />

and weights. Variety <strong>of</strong> robotic grippers are developed highly flexible and multi functioned.<br />

Particularly humanoid robotic technology attracts high attention <strong>of</strong> researchers. The highly dynamic and highly<br />

accelerated gripper model can be easily set at intermediate positions by regulating the pressure. Pneumatic<br />

grippers are very easy to handle and are generally cost-effective because air hoses, valves and other pneumatic<br />

devices are easy to maintain.<br />

Since a gripper gives a great contribution to practical success <strong>of</strong> using an automated and/or robotized solution, a<br />

proper design may be <strong>of</strong> fundamental importance[6].<br />

A proper gripper design can simplify the overall robot system assembly. It also increases the overall system<br />

reliability and decreases the cost <strong>of</strong> implementing the system[5]. Thus, the design <strong>of</strong> the gripping system is very<br />

important for the successful operation.<br />

It is not possible literally to apply all the guidelines to a specific set <strong>of</strong> design. As one guideline may suggest one<br />

design direction while another may suggest the opposite.<br />

So the most suitable technique is to examine each particular station and then coming to a conclusion which<br />

favours the more relevant guidelines.<br />

The design guidelines may be as follows [4]:-<br />

1) Gripper weight should be minimized. This favors the robot to accelerate more quickly<br />

2) Grasping <strong>of</strong> objects should be secure: This allows the robot to run at higher speeds in zig-zag pr<strong>of</strong>ile thereby<br />

reducing the cycle time.<br />

3) Grip multiple objects with a single gripper. It helps to avoid tool changes hereby reduce idle time.<br />

4) Completely encompass the object with the gripper: This is to help hold the component securely.<br />

5) Grasp the object without deformation: the object are easily deformed and so care should be taken during<br />

grasping these objects.<br />

6) Minimize finger length: The longer the fingers <strong>of</strong> the gripper the more they are going to deflect during<br />

grasping an object.<br />

7) Design for proper gripper-object interaction: If, however, a flat surface is being used, then a high friction<br />

interface is desired since the part would not be aligned anyway and the higher friction increases the security<br />

<strong>of</strong> the grasp.<br />

8) Flexibility: The ability <strong>of</strong> a gripper to conform to parts that have irregular shapes and to adapt to parts that is<br />

inaccurately oriented with respect to the gripper.<br />

The ideal gripper design should be synthesized from independent solutions to the three considerations shown in<br />

Figure 1. Grippers essentially replace the human hand. If the gripping abilities <strong>of</strong> a mechanical five-fingered<br />

397


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

“hand” are denoted as 100%, a four-fingered hand has 99% <strong>of</strong> its ability, a three-fingered hand about 90%, and a<br />

two-fingered hand 40% .<br />

Gripper Design<br />

Match the abilities<br />

<strong>of</strong> the arm and<br />

controller<br />

Grasp and hold the<br />

object securely<br />

Complete the<br />

manufacturing<br />

Figure 1.<br />

OPTIMALITY CRITERIA- In general, an optimum design procedure can be considered by means the<br />

followingsteps:<br />

1) Identification <strong>of</strong> design constraints and performance characteristics for a given application;<br />

2) Formulation <strong>of</strong> basic performances;<br />

3) Analysis <strong>of</strong> optimality criteria through numerical algorithms;<br />

4) Formulation <strong>of</strong> a single and/or multi-objective optimization problem for design purposes;<br />

5) Numerical solution <strong>of</strong> the multi-objective optimization and interpretation <strong>of</strong> results;<br />

6) Determination <strong>of</strong> a design solution through a suitable model;<br />

7) Mechanical design <strong>of</strong> all the components and details<br />

2. Literature Works<br />

1.) K.S. Venkatesh, A. Dutta, P. Guha, T. Mishra[7]-In the last two decades several researchers have<br />

studied the problem <strong>of</strong> grasping <strong>of</strong> a moving rigid object based on vision data. However the problem <strong>of</strong> grasping<br />

a moving and deforming object still remains unsolved. In this paper, they have presented the development <strong>of</strong> a<br />

fast algorithm for the computation <strong>of</strong> the optimal force on a slowly moving and deforming object so that grasp<br />

point could be known. Their main focus was to find the best grasp points as the object deforms, to track objects<br />

position at a future instant and then transfer gripper grasp to that location. At first the potential grasping<br />

configurations satisfying force closure are evaluated through an objective function that maximizes the grasping<br />

span while minimizing the distance between the object centroid and the intersection <strong>of</strong> the fingertip normal. A<br />

population based stochastic search strategy was adopted by them. They conducted Experiments to prove that the<br />

object can be tracked in real time and the optimal grasp points can be determined so that a robot can capture it.<br />

This method works in real time so it has great potential for application in industries for grasping objects whose<br />

shapes are not clearly defined (e.g. cloth), deforming objects, or objects that are partially occluded.<br />

2.) G. Bretthauer, D. Osswald, J. Martin, C. Burghart, R. Mikut, H. Wörn [8]-This article presents the<br />

approaches taken to integrate a novel anthropomorphic robot hand into a humanoid robot. The requisites enabling<br />

such a robot hand to use everyday objects in an environment built for humans are presented. Starting from a<br />

design that resembles the human hand regarding size and moving ability <strong>of</strong> the mechatronical system, a low-level<br />

control system providing reliable and stable controllers for single joint angles and torques, entire fingers and<br />

several coordinated fingers. Also the high-level control systems connecting the low-level control system with the<br />

rest <strong>of</strong> the humanoid robot are presented. It provides grasp skills to the superior robotic control system,<br />

coordinates movements <strong>of</strong> hand and arm determines grasp patterns, depending on the component to grasp and<br />

the task to execute. Finally some preliminary results <strong>of</strong> the system, which were currently tested in simulations,<br />

were presented<br />

3.) L. Saggere, S. Krishnan [9] - This paper presents the design and development <strong>of</strong> a new tool, called the<br />

micro-clasp gripper, for accomplishing firm and stable gripping and manipulation <strong>of</strong> complex-shaped micro-scale<br />

objects in any orientation using a single rectilinear actuator. The micro-clasp gripper is a compliant mechanism<br />

comprised <strong>of</strong> an end-effector with a closed-loop boundary that can be folded and unfolded in a plane by the<br />

action <strong>of</strong> the rectilinear actuator. Upon actuation, the end-effector <strong>of</strong> the micro-clasp gripper clasps an object by<br />

398


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

first encircling the object, and then, folding to the object to accomplish multi-point contact with the object. This<br />

clasping <strong>of</strong> the micro-object with multi-point contact ensures a stable grip on the object regardless <strong>of</strong> its shape<br />

and initial orientation, even in presence <strong>of</strong> ambient disturbances the transport <strong>of</strong> the object or complex<br />

micromanipulation and micro-assembly tasks. The design <strong>of</strong> the micro-clasp gripper is obtained through a<br />

systematic modelling and topology optimization techniques, and a pro<strong>of</strong>-<strong>of</strong>-principle device is micro-fabricated<br />

using conventional micromachining techniques. The device design is validated through experiment-model<br />

correlation studies on the input-output characteristic <strong>of</strong> the micro-machined prototype, and practical feasibility <strong>of</strong><br />

the clasping functionality <strong>of</strong> the gripper is demonstrated through experiments involving grasping and<br />

repositioning <strong>of</strong> irregularly shaped micro-particles on a glass substrate.<br />

4.) D. Rituparnaand D. Kalyanmoy[1]-In this paper, A multicriteria optimization <strong>of</strong> robot gripper design<br />

problem was solved using two different configurations involving two conflicting objectives and a number <strong>of</strong><br />

constraints. The main objective was minimization <strong>of</strong> the difference between maximum and minimum gripping<br />

forces and simultaneous minimization <strong>of</strong> the transmission ratio between the applied gripper actuator force and<br />

theforce experienced at the gripping ends.<br />

5.) Chiara Lanni and Marco Ceccarelli[6]-The author has analysed the mechanisms in two-finger<br />

gripper to formulate an optimum design procedure. The design problem has been approached and formulated as<br />

a new optimization problem by using fundamental characteristics <strong>of</strong> grasping mechanisms. In order to optimize a<br />

mechanism for two-finger gripper, an original multi-objective optimum algorithm was used by considering four<br />

different objective functions including grasping index, encumbrance <strong>of</strong> grasping mechanism, acceleration and<br />

velocity for finger gripper with confined working area. This new formulation will achieve a kinematic design <strong>of</strong><br />

gripper mechanism with optimal characteristics even as improvement <strong>of</strong> existing solutions.<br />

6.) JianqiangWang- The author has tried to achieve Intelligent gripping through gripper design, automated<br />

part recognition, intelligent algorithm for control <strong>of</strong> the gripper, and on-line decision-making based on sensory<br />

data. A three-fingered gripper actuated by a linear servo actuator designed and developed in this project for<br />

precise speed and position control is capable <strong>of</strong> handling a large variety <strong>of</strong> objects also Generic algorithms for<br />

intelligent part recognition were developed. Fuzzy logic was successfully utilized to enhance the intelligence <strong>of</strong><br />

the robotic system.<br />

7.) A. M. Zaki, O. A. Mahgoub, A.M. El-Shafei, A. M. Soliman[4]-In this paper, a gripper was designed<br />

and implemented to grasp unknown objects with different masses, geometry, and surface roughness. The design<br />

and control <strong>of</strong> the gripper system has taken into consideration simplicity in the mechanical system, large variety<br />

<strong>of</strong> grasped objects and low cost. The proposed grasping process during object lifting and handling was mainly<br />

based on the slip reflex principle, as applying insufficient force leads to object slipping, and dropping may also<br />

occur. On the other hand, applying extra force during grasping may lead to object crushing. A new system<br />

controller using fuzzy logic based on empirical investigation <strong>of</strong> the human hand skills was<br />

proposed.Experimental confirmation was obtained for <strong>of</strong> the distance <strong>of</strong> the slippage and process time.<br />

Simulation and experimental results were discussed.<br />

8.) S.Costo, G.Altamura, L.E.Bruzzone, R.M.Molfino, M.Zoppi[10]-This paper deals with the design <strong>of</strong><br />

the mechtronic device enabling the multi point grasp and firm hold <strong>of</strong> limp one layer <strong>of</strong> leather sheets for the<br />

automation <strong>of</strong> leather manufacturing operation in industries. The design assures low inertia, high modularity and<br />

full flexibility adapting to the environment.<br />

Conclusion<br />

This paper presents a survey <strong>of</strong> work in design <strong>of</strong> robotic gripper over the last twenty years. It is impossible to do<br />

justice to all the work in this area, particularly because <strong>of</strong> the breadth <strong>of</strong> the field and its close connection to<br />

dexterous manipulation.<br />

From the above study it is concluded that an object can be tracked in real time and the optimal grasp points can<br />

be determined by use <strong>of</strong> a fast algorithm for the computation <strong>of</strong> the optimal grasp force, so that a three finger<br />

robot can capture it.<br />

A Grasp skill can be provided to a superior robot system which can coordinate movement <strong>of</strong> hand <strong>of</strong> a robot and<br />

arm <strong>of</strong> a gripper to determine grasp patterns depending upon the object shape.<br />

399


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Different Systematic grasping and control algorithm can be proposed to adjust the motion <strong>of</strong> the gripper without<br />

the risk <strong>of</strong> object crushing or dropping and also to maintain the object slip in a reasonable limit.<br />

With the help <strong>of</strong> a new methodology, micro-clasp gripper, stable gripping and manipulation <strong>of</strong> micro scale<br />

complex shaped object can be accomplished.<br />

A formulation can be achieve for a kinematic design <strong>of</strong> gripper mechanism with optimal characteristics with<br />

improvement <strong>of</strong> existing solutions.<br />

REFERENCES<br />

[1] D. Rituparna, D. Kalyanmoy- Optimizing and Deciphering Design Principles <strong>of</strong> Robot Gripper<br />

Configurations Using an Evolutionary Multi-Objective Optimization Method, February 10, <strong>20</strong>11<br />

KanGAL Report Number <strong>20</strong>11002<br />

[2] M. R. Cutkoski. On Grasp Choice, Grasp Models, and the Design <strong>of</strong> Hands for Manufacturing Tasks. IEEE<br />

Trans. Robot. Automat, 5(3):269– 279, <strong>19</strong>89.<br />

[3] A. Osyczka. Evolutionary algorithms for single and multicriteria design optimization. Heidelberg: Physica-<br />

Verlag, <strong>20</strong>02.<br />

[4] A.M. Zaki, O.A. Mahgoub, A.M. El-Shafei, A.M. Soliman - Design and Implementation <strong>of</strong> Efficient<br />

Intelligent Robotic Gripper, Issue 11, Volume 9, November <strong>20</strong>10<br />

[5] R. G. Brown and R. C. Brost, “A 3-d Modular Gripper Design Tool”, IEEE International Conference on<br />

Robotics and Automation Proceedings, <strong>19</strong>97, pp. 2332-2339.<br />

[6] C. Lanni and M. Ceccarelli-An Optimization Problem Algorithm for Kinematic Design <strong>of</strong> Mechanisms for<br />

Two-Finger Grippers, The Open Mechanical Engineering Journal, <strong>20</strong>09,Volume 3.<br />

[7] K.S. Venkatesh, A. Dutta, P. Guha, T. Mishra- Stochastic re-grasp planning for vision aided capture <strong>of</strong><br />

deforming and moving object, Volume <strong>19</strong>, Issue 4, June <strong>20</strong>09, Pages 510–5<strong>19</strong>.<br />

[8] G. Bretthauer, D. Osswald, J. Martin, C. Burghart, R. Mikut, H. Wörn -Integrating a flexible<br />

anthropomorphic, robot hand into the control, system <strong>of</strong> a humanoid robot, Volume 48, Issue 4,31 October<br />

<strong>20</strong>04, Pages 213–221.<br />

[9] L. Saggere, S. Krishnan- Design and development <strong>of</strong> a novel micro-clasp gripper for micromanipulation <strong>of</strong><br />

complex-shaped objects, Volume 38, Issue 12, December <strong>20</strong>03, Pages1509–1522.<br />

[10] S.Costo, G.Altamura, L.E.Bruzzone, R.M.Molfino, M.Zoppi- Design <strong>of</strong> a re-configurable gripper for the<br />

fast robotic picking and handling <strong>of</strong> limp sheets, Proc. Of the 33 rd International symposium on robotics,<br />

Stockholm, Sweden, October 7-11,<strong>20</strong>02.<br />

400


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Electrical Discharge Machining <strong>of</strong> Aluminum Metal Matrix Composites- A<br />

Review<br />

Bhaskar Chandra Kandpal 1*, Jatinder kumar 2 , Hari Singh 3<br />

1 Assistant pr<strong>of</strong>essor, Mechanical engineering, Inderprastha Engineering College ,Ghaziabad, U.P.<br />

2 Assistant pr<strong>of</strong>essor,Mechanical engineering,National Institute <strong>of</strong> <strong>Technology</strong>,Kurukshetra, Haryana<br />

3 Associate pr<strong>of</strong>essor,Mechanical engineering,National Institute <strong>of</strong> <strong>Technology</strong>,Kurukshetra, Haryana<br />

1* E-mail:kandpalbhaskar<strong>20</strong>00@gmail.com, Ph. No – 9717508244<br />

Abstract<br />

Electrical discharge machining (EDM) is the process <strong>of</strong> machining electrically conductive materials by using<br />

precisely controlled sparks that occur between an electrode and a work piece in the presence <strong>of</strong> a dielectric<br />

fluid. Aluminium metal matrix composites (AMMCs) refer to the class <strong>of</strong> light weight high performance<br />

aluminum ceramic material systems. The reinforcement in AMMCs could be in the form <strong>of</strong> continuous /<br />

discontinuous fibers, whiskers or particulates, in volume fractions ranging from a few percent to 70%. These<br />

materials are extensively used in industry. Greater hardness and reinforcement makes it difficult to machine<br />

using traditional techniques, which has impeded the development <strong>of</strong> AMMCs. These materials can be machined<br />

by many non traditional methods like water jet and laser cutting but these processes are limited to linear cutting<br />

only. This paper presents a review <strong>of</strong> research work related to electrical discharge machining process <strong>of</strong><br />

aluminium metal matrix composites (AMMCs).<br />

Keywords: EDM (Electrical discharge machining), aluminium metal matrix composite (AMMC).<br />

1. Introduction<br />

Electric discharge machining (EDM), sometimes colloquially also referred to as spark machining, spark eroding,<br />

burning, die sinking or wire erosion, is a manufacturing process whereby a desired shape is obtained using<br />

electrical discharges (sparks).<br />

1.1 Working principle <strong>of</strong> electrical discharge machining<br />

The working principle <strong>of</strong> EDM process as shown in figure 1 is based on the thermoelectric energy. This energy<br />

is created between a workpiece and an electrode submerged in a dielectric fluid with the passage <strong>of</strong> electric<br />

current. The workpiece and the electrode are separated by a specific small gap called spark gap. Pulsed arc<br />

discharges occur in this gap filled with an insulating medium, preferably a dielectric liquid like hydrocarbon oil<br />

or de- ionized water. Electrical discharge machining is a machining method primarily used for hard metals or<br />

those that would be very difficult to machine with traditional techniques.<br />

Figure 1: Schematic Diagram <strong>of</strong> EDM Process<br />

2. Aluminium metal matrix composite materials<br />

Aluminium metal matrix composite (AMMCs) refer to the class <strong>of</strong> light weight high performance aluminium<br />

centric material systems. The reinforcement in AMMCs could be in the form <strong>of</strong> continuous / discontinuous fibres,<br />

whisker or particulates, in volume fractions ranging from a few percent to 70%. Properties <strong>of</strong> AMMCs can be<br />

tailored to the demands <strong>of</strong> different industrial applications by suitable combination <strong>of</strong> matrix, reinforcement and<br />

processing routes. There are various types <strong>of</strong> AMMCs like Al/ SiC , Al/ Al 2 O 3 , Al. Ti C, etc. which are<br />

401


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

commonly used in automotive and defense. These AMMCs have greater demand because <strong>of</strong> their advanced<br />

properties like greater strength, improved stiffness, reduced density, improved high temperature properties,<br />

controlled thermal expansion coefficient, enhanced and tailored electrical properties, improved abrasion and<br />

wear resistance, control <strong>of</strong> mass ,improved damping capabilities.<br />

2.1 Research work in EDM <strong>of</strong> Aluminium metal matrix composite materials<br />

Manish Vishwakarma, Vishal Parashar, V.K.Khare(<strong>20</strong>12) found that existing manufacturing industries are<br />

fronting challenges from these advanced nascent materials viz. nano material ,ceramics, super alloys, and metal<br />

matrix composites, that are hard and difficult to machine, requiring high accuracy, surface quality excellence<br />

which affects and increases machining cost. Electric Discharge Machining (EDM), a unconventional process, has<br />

a extensive applications in automotive, defense, aerospace and micro systems industries plays an outstanding<br />

role in the development <strong>of</strong> least cost products with more consistent quality assurance. Die sinking EDM, Wire<br />

electrical discharge machining (WEDM), Dry EDM, and Rotary disk electrode electrical discharge machining<br />

(RDEEDM) are some <strong>of</strong> the alternates methods <strong>of</strong> EDM.<br />

P. Cichosz, P. Karolczak(<strong>20</strong>08) found the results <strong>of</strong> electrical discharge machining <strong>of</strong> aluminium matrix<br />

composites with particular attention given to thickness <strong>of</strong> the defected layer after machining. Influence <strong>of</strong> various<br />

machining parameters on the behavior <strong>of</strong> saffil fibres and matrix material in the affected zone is presented.<br />

Scanning micrographs and roughness measurements are used to analyze surface finish following machining The<br />

investigation showed that ED machining process parameters affect the condition <strong>of</strong> surface layer in machined<br />

aluminium MMCs. Low current parameters resulted in a thin layer with a recast structure <strong>of</strong> increased hardness.<br />

Reinforcing fibres were generally left undamaged, some <strong>of</strong> them protruding from the surface. There is a need for<br />

working out optimized patterns <strong>of</strong> current density and frequency <strong>of</strong> sparks that would eliminate or reduce the<br />

extent <strong>of</strong> finishing operations necessary for removing the recast layer. Anil Kumar, Sachin Maheshwari, Chitra<br />

Sharma and Naveen Beri (<strong>20</strong>10) found additive mixed electrical discharge machining (AEDM) is a novel<br />

innovation for enhancing the capabilities <strong>of</strong> electrical discharge machining process in this direction. Despite the<br />

promising results, AEDM process is used in the industry at very slow pace. Fundamental issues <strong>of</strong> this new<br />

development, including machining mechanism, are still not well understood. These issues require further<br />

investigations before this process is well accepted by the industry. Mixing <strong>of</strong> additive powder in the dielectric<br />

medium <strong>of</strong> EDM plays a significant role in enhancing the process capabilities <strong>of</strong> EDM. Adding powder causes<br />

gap contamination. This gap contamination lowers dielectric strength and initiates the ignition process, which<br />

increases gap distance and increases the stability <strong>of</strong> the process. Additive powder characteristics (type, shape,<br />

size, concentrations, number <strong>of</strong> particles, and thermal properties) significantly affect process efficiency and<br />

surface characteristics <strong>of</strong> machined surfaces. There is a need to independently study the effect <strong>of</strong> various powder<br />

characteristics with important input process parameter on the phenomenon <strong>of</strong> surface modification and process<br />

capabilities.<br />

Sushant Dhar , Rajesh Purohit , Nishant Saini , Akhil Sharma , G. Hemath Kumar(<strong>20</strong>07) found that the<br />

aluminum matrix composites (AMC) are hard to machine due to the presence <strong>of</strong> hard and brittle ceramic<br />

reinforcements. Additionally, Researchers are turning to particulate-reinforced aluminum-metal matrix<br />

composites (AMCs) because <strong>of</strong> their relatively low cost and isotropic properties especially in those applications<br />

not requiring extreme loading or thermal conditions (e.g., automotive components). They evaluated the effect <strong>of</strong><br />

current (c), pulse-on time (p) and air gap voltage (v) on metal removal rate (MRR), tool wear rate (TWR), radial<br />

over cut (ROC) on machining <strong>of</strong> Al-MMC with <strong>20</strong>% SiC reinforcement. Analysis <strong>of</strong> variance (ANOVA) has<br />

been performed and graphs are plotted. A quadratic mathematical model has also been developed for the same<br />

relating output and input quantities respectively. The MRR is found to increase in an almost linear fashion with<br />

increase in current for constant gap voltage and Pulse on time. MRR is also found to increase slightly with<br />

increase in Pulse duration clearly. And in agreement with the literature reported in TWR is also found to increase<br />

with increase in current as high current results in higher thermal loading on both electrodes (tool and work-piece)<br />

leading to higher amount <strong>of</strong> material being removed from either. It is found to first decrease and then increase<br />

with pulse duration. A similar trend is noticed with Gap Voltage. It is evident that an increase in current<br />

increases the Over Cut. An increase in pulse duration also increases the Over Cut due to the prolonged presence<br />

<strong>of</strong> sparks. An uncommon behavior is observed in the case <strong>of</strong> voltage gap. Adrian Iosub, Eugen Axinte, Florin<br />

Negoescu(<strong>20</strong>10) study found that the influence <strong>of</strong> the most relevant parameters <strong>of</strong> Electrical Discharge<br />

Machining over material removal rate, electrode wear and machined surface quality <strong>of</strong> a hybrid metal matrix<br />

composite material (Al/SiC)has been carried out. The material used in their study was aluminium matrix<br />

composite reinforced with 7 % SiC and 3.5 % graphite.they found that the hybrid SiC/Al composite material can<br />

be machined by EDM and a good surface quality can be obtained by controlling the machining conditions.<br />

Regarding the MRR output parameter, the most influential factors were current intensity, followed by its<br />

402


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

quadratic effect and pulse – <strong>of</strong>f time. The material removal rate increases significantly when current intensity<br />

increases. The same tendency was observed when pulse – <strong>of</strong>f time increases; an empirical model was proposed,<br />

in order to optimise the processes. In the case <strong>of</strong> the electrode wear parameter, the most influential factor is the<br />

current, followed by its quadratic effect and pulse – on time. For a low electrode wear, low values for intensity<br />

and for pulse – on time should be used.<br />

P.Narender Singh, K.Raghukandan, M.Rathinasabapathi and B.C.Pai (<strong>20</strong>04) found that the use <strong>of</strong><br />

unconventional machining techniques in shaping aluminium metal matrix composites (Al-MMC) has generated<br />

considerable interest as the manufacturing <strong>of</strong> complicated die contours in these hard materials to a high degree <strong>of</strong><br />

accuracy and surface finish is difficult. The objective <strong>of</strong> this work is to investigate the effect <strong>of</strong> current (C), Pulse<br />

ON-time (P) and flushing pressure (F) on metal removal rate (MRR), tool wear rate (TWR), taper (T), radial<br />

overcut (ROC), and surface roughness (SR) on machining as-cast Al-MMC with 10% SiC reinforcement.<br />

Analysis <strong>of</strong> variance (ANOVA) was performed and the optimal levels for maximizing the responses were<br />

established. Scanning electron microscope (SEM) analysis was done to study the surface characteristics. They<br />

found that MRR was found to be higher for larger current and pulse on time settings at the expense <strong>of</strong> tapercity,<br />

radial overcut and surface finish.TWR was found to be higher, larger than MRR, for larger current settings but it<br />

effects the dimensional accuracy also. Flushing pressure <strong>of</strong> the dielectric has considerable effect on the MRR and<br />

TWR.D. Satishkumar & M. Kanthababu & V. Vajjiravelu &R. Anburaj & N. Thirumalai Sundarrajan & H.<br />

Arul(<strong>20</strong>11) found in their investigation, the effect <strong>of</strong> wire electrical discharge machining (WEDM) parameters<br />

such as pulse-on time (TON), pulse-<strong>of</strong>f time (TOFF), gap voltage (V) and wire feed (F) on material removal rate<br />

(MRR) and surface roughness (Ra) in metal matrix composites (MMCs)consisting <strong>of</strong> aluminium alloy (Al6063)<br />

and silicon carbide(SiCp). The Al6063 is reinforced with SiCp in the form <strong>of</strong> particles with 5%, 10% and 15%<br />

volume fractions. The experiments were carried out as per design <strong>of</strong> experiments approach using L9 orthogonal<br />

array. The results were analysed using analysis <strong>of</strong> variance and response graphs. The results are also compared<br />

with the results obtained for unreinforced Al6063. It was found that the increase in volume percentage <strong>of</strong> SiC<br />

resulted in decreased MRR and increased Ra. This may be due to the presence <strong>of</strong> harder SiC particles in the<br />

MMCs. The SiC particles will enhance the thermal characteristics <strong>of</strong> aluminium, with consequent reduction in<br />

MRR. But MRR is found to increase with increase in pulse on time because <strong>of</strong> higher intensity <strong>of</strong> the spark in<br />

WEDM process. The results from this study will be useful for manufacturing engineers to select appropriate<br />

WEDM process parameters to machine MMCs <strong>of</strong> Al6063 reinforced with SiCp at various proportions.<br />

Hung N.P., Yang L.J., and Leong K.W (<strong>19</strong>94) paper investigated the feasibility <strong>of</strong> applying electrical discharge<br />

machining (EDM)process for cast aluminum MMCs reinforced with silicon carbide particles (SiCp). It was<br />

found that the SiC particles shield and protect the aluminum matrix from being vaporized, thus reduce the metal<br />

removal rate. The un-melted SiC particles drop out from the MMC together with surrounding molten aluminum<br />

droplets. While some aluminum droplets are flushed away by the dielectric, others trap the loosened SiC<br />

particles then re-solidify onto the surface to form a re-cast layer (RCL). No crack was found in the RCL and the<br />

s<strong>of</strong>tened heat-affected zone (HAZ), which is below the RCL. The input power controls the metal removal rate<br />

and the RCL depth, but the current alone dominates the surface finish <strong>of</strong> an EDM'ed surface.K.M. Patel, Pulak<br />

M. Pandey, P. Venkateswara Rao(<strong>20</strong>09) found that the electric discharge machining (EDM) has been proven as<br />

an alternate process for machining complex and intricate shapes from the conductive ceramic composites. The<br />

performance and reliability <strong>of</strong> electrical discharge machined ceramic composite components are influenced by<br />

strength degradation due to EDM-induced damage. This paper presents a detailed investigation <strong>of</strong> machining<br />

characteristics, surface integrity and material removal mechanisms <strong>of</strong> advanced ceramic compositeAl2O3–<br />

SiCw–TiC with EDM. The surface and subsurface damages have also been assessed and characterized using<br />

scanning electron microscopy (SEM). The results provide valuable insight into the dependence <strong>of</strong> damage and<br />

the mechanisms <strong>of</strong> material removal on EDM conditions.<br />

Biing Hwa Yan, Hsien Chung Tsai, Fuang Yuan Huang, Long Chorng Lee (<strong>20</strong>05) found that alumina particle<br />

reinforced 6061 aluminum matrix composites (Al2O3p/6061Al) have excellent physical and chemical properties<br />

than those <strong>of</strong> a traditional metal; however, their poor machinability lead to worse surface quality and serious<br />

cutting tool wear. The experimental results indicate that the cutting speed (material removal rate), the surface<br />

roughness and the width <strong>of</strong> the slit <strong>of</strong> cutting test material significantly depend on volume fraction <strong>of</strong><br />

reinforcement (Al2O3 particles). Test results revealed that in machining Al2O3p/6061Al composites a very low<br />

wire tension, a high flushing rate and a high wire speed are required to prevent wire breakage; an appropriate<br />

servo voltage, a short pulse-on time, and a short pulse-<strong>of</strong>f time, which are normally associated with a high<br />

cutting speed, have little effect on the surface roughness. Biing Hwa Yan, Che Chung Wang, Han Ming Chow,<br />

Yan Cherng Lin (<strong>20</strong>00)investigated the feasibility and optimization <strong>of</strong> a rotary EDM with ball burnishing for<br />

inspecting the machinability <strong>of</strong> Al2O3/6061Al( volume fraction <strong>of</strong> Al2O3) composite using the Taguchi method.<br />

Three ZrO2 balls attached as additional components behind the electrode tool <strong>of</strong>fer immediate burnishing<br />

403


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

following EDM. They found that peak current and non – load voltage parameters significantly affect the<br />

machining rate for ball EDM process. Either a higher rotational speed <strong>of</strong> electrode tool, or <strong>20</strong> vol. % Al2O3<br />

reinforced particles may increase the wear <strong>of</strong> the ZrO2 ball and generate a rougher surface roughness.<br />

S. Singh (<strong>20</strong>12) applied the designs <strong>of</strong> experiments and grey relational analysis (GRA) approach to optimise<br />

parameters for electrical discharge machining process <strong>of</strong> 6061Al/Al2O3p/<strong>20</strong>P aluminium metal matrix<br />

composites. The process parameters included one noise factor, aspect ratio having two levels and five control<br />

factors, viz. pulse current, pulse ON time, duty cycle, gap voltage and tool electrode lift time with three levels<br />

each. The material removal rate, tool wear rate and surface roughness were selected as the evaluation criteria, in<br />

this study. Optimal combination <strong>of</strong> process parameters is determined by the grey relational grade (GRG)<br />

obtained through GRA for multiple performance characteristics. Analysis <strong>of</strong> variance for the GRG is also<br />

implemented. It is shown that through GRA, the optimization <strong>of</strong> the multiple performance characteristics can be<br />

greatly simplified. The results <strong>of</strong> ANOVA indicated that aspect ratio and pulse current were the most significant<br />

process parameters affecting the multiple performance measures followed by tool electrode lift time and pulse on<br />

time. Che Chung Wang, Biing Hwa Yan(<strong>20</strong>00) work optimized the blind-hole drilling <strong>of</strong> Al2O3/6061Al<br />

composite using rotary electro-discharging machining by using Taguchi methodology. Experimental results<br />

confirm that the revised copper electrode with an eccentric through-hole has the optimum performance for<br />

machining from various aspects. Analysis <strong>of</strong> the Taguchi method reveals that the electrical group has a more<br />

significant effect than the non-electrical group on the machining characteristics. Furthermore, either the polarity<br />

or the peak current most prominently affects the MRR, SR or EWR amongst all <strong>of</strong> the parameters.<br />

3. Conclusion<br />

A review <strong>of</strong> electrical discharge machining process and research work done in EDM on aluminum metal matrix<br />

composites (AMMCs) is presented in this paper. Presently EDM plays an important role in machining <strong>of</strong><br />

composites like aluminum metal matrix composites ( AMMCs) which has been discussed in this paper. For each<br />

and every method introduced in EDM process, the objectives are the same: to enhance the capability <strong>of</strong><br />

machining performance, to get better output, and to have better working conditions.<br />

4. References<br />

Manish Vishwakarma, Vishal Parashar, V.K.Khare, <strong>20</strong>12; “Advancement in electric discharge machining on<br />

metal matrix composite materials in recent: A Review”, International Journal <strong>of</strong> Scientific and Research<br />

Publications, Volume 2, Issue 3.<br />

P. cichosz, P. karolczak,<strong>20</strong>08 ;“ Sinker electric discharge machining <strong>of</strong> aluminium matrix composites”, Materials<br />

<strong>Science</strong>- Poland, , Volume 26, Issue3, pp. 2172-2<strong>19</strong>2.<br />

Anil Kumar, Sachin Maheshwari, Chitra Sharma and Naveen Beri, <strong>20</strong>10, “Research developments in additives<br />

mixed electric discharge machining (AEDM): A state art review”, Materials and Manufacturing Processes, 25,<br />

pp. 1166-1180.<br />

Sushant Dhar, Rajesh Purohit , Nishant Saini , Akhil Sharma , G. Hemath Kumar,<strong>20</strong>07, “Mathematical modeling<br />

<strong>of</strong> electric discharge machining(EDM) <strong>of</strong> Al- 4Cu- 6Si alloy-10%SiC composites”, Journal <strong>of</strong> materials<br />

processing technology, Volume <strong>19</strong>4,pp. 24-29.<br />

Adrian Iosub, Eugen Axinte, Florin Negoescu, <strong>20</strong>10, “ A study about micro drilling by electrical discharge<br />

method <strong>of</strong> an Al/ SiC composite”, International journal <strong>of</strong> academic research ,Volume 2, Issue 3.<br />

P. Narender Singh, K. Raghukandan, M. Rathinasabapathi and B.C. Pai, <strong>20</strong>04, “Electrical discharge machining<br />

<strong>of</strong> Al- 10% SiC as cast metal matrix composites”, Journal <strong>of</strong> materials processing technology, pp. 1653-1657.<br />

D. Satishkumar & M. Kanthababu & V. Vajjiravelu &R. Anburaj & N. Thirumalai Sundarrajan & H. Arul, <strong>20</strong>11,<br />

“Investigation <strong>of</strong> wire electrical discharge machining characteristics <strong>of</strong> Al 6063/ SiC composite”, International<br />

Journal <strong>of</strong> Advanced Manufacturing <strong>Technology</strong>, Volume 56, pp. 975-986.<br />

Hung N.P., Yang L.J., and Leong K.W., <strong>19</strong>94, “Electric discharge machining (EDM) <strong>of</strong> cast metal matrix<br />

composites”, Journal <strong>of</strong> materials processing technology, Volume 44, pp. 229-236.<br />

K.M. Patel, Pulak M. Pandey, P. Venkateswara Rao, <strong>20</strong>09, “Surface integrity and material removal mechanisms<br />

associated with the EDM <strong>of</strong> Al2 O3 ceramic composite”, International Journal <strong>of</strong> Refractory metals and Hard<br />

materials Volume 27,pp. 892-899.<br />

Biing Hwa Yan, Hsien Chung Tsai, Fuang Yuan Huang, Long Chorng Lee ,<strong>20</strong>05, “Examination wire electric<br />

discharge machining(EDM) <strong>of</strong> Al2O3 p/ 6061 Al composites”, International Journal <strong>of</strong> machine tools and<br />

manufacturers,45, pp. 251-259.<br />

Biing Hwa Yan, Che Chung Wang, Han Ming Chow, Yan Cherng Lin ,<strong>20</strong>00, “ Feasibility study <strong>of</strong> rotary<br />

electrical discharge machining with ball burnishing for Al2O3 p/ 6061 Al/ <strong>20</strong>P composites by grey relational<br />

analysis” , International Journal <strong>of</strong> machine tools and manufacturers,40, pp.1403-1421.<br />

404


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

S. Singh, <strong>20</strong>12, “Optimization <strong>of</strong> machining characteristics in Electrical discharge machining <strong>of</strong> Al2O3 p/ 6061<br />

Al cast metal matrix composites”, International Journal <strong>of</strong> Advanced Manufacturing <strong>Technology</strong>.<br />

Che Chung Wang, Biing Hwa Yan,<strong>20</strong>00, “Blind hole drilling <strong>of</strong> Al2O3 p/ 6061 Al composite using electrodischarge<br />

machining”, Journal <strong>of</strong> materials processing technology, Volume 102, pp. 90-102.<br />

405


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Modelling <strong>of</strong> Surface Roughness in WEDM for HSLA Using Response<br />

Surface Methodology<br />

Neeraj Sharma 1* , Kamal Jangra 2<br />

1 Research Scholar, Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> UST, Faridabad, India, 121006<br />

2 Assistant Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> UST ,Faridabad, India,121006<br />

1*<br />

E mail: neeraj.sharma@live.com<br />

Abstract<br />

Wire electric discharge machine (WEDM) is a spark erosion machining process to cut very hard conductive<br />

material with the help <strong>of</strong> a wire electrode. High strength low alloy steel (HSLA) is a hard alloy with high<br />

hardness and wear resisting property. The purpose <strong>of</strong> this study is to investigate the effect <strong>of</strong> parameters on total<br />

surface roughness for WEDM using HSLA as work-piece. HSLA used in cars, trucks, cranes, bridges, roller<br />

coasters and other structures that are designed to handle large amounts <strong>of</strong> stress. It is found that total surface<br />

roughness (R z ) increases with increase in pulse on time, while it decreases with decrease in pulse <strong>of</strong>f time, peak<br />

current, servo voltage and wire tension. In this research paper the evaluation <strong>of</strong> the effect <strong>of</strong> selected process<br />

parameters, the Response Surface Methodology (RSM) is used to formulate a mathematical model which<br />

correlates the independent process parameters with the desired surface roughness. The central composite<br />

rotatable design has been used to conduct the experiment.<br />

Keywords: HSLA, RSM, total surface roughness, WEDM.<br />

Abbreviation:<br />

Pulse on time – Ton<br />

Pulse <strong>of</strong>f Time – T<strong>of</strong>f<br />

Spark Gap Voltage – SV<br />

Peak Current - IP<br />

Wire Tension – WT<br />

Total Surface Roughnee - R<br />

Error - er<br />

Coefficients - b<br />

ii<br />

z<br />

1. Introduction<br />

Electrical discharge wire cutting, more commonly known as wire-EDM (WEDM), is a spark erosion process<br />

used to produce complex two- and three-dimensional shapes through electrically conductive work pieces by<br />

using a wire electrode. The degree <strong>of</strong> accuracy obtainable and the fine surface finishes make WEDM particularly<br />

valuable for applications involving the manufacture <strong>of</strong> stamping dies, extrusion dies and prototype parts. The<br />

fabrication <strong>of</strong> precision work pieces requires many hours <strong>of</strong> manual grinding and polishing in absence <strong>of</strong><br />

WEDM. The microprocessor also constantly maintains the gap between the wire and the work piece, which<br />

varies from 0.025 to 0.05 mm. Very high frequency pulses are generated with the help <strong>of</strong> DC power supply. The<br />

electrical discharge melts or erodes the material in a very small amount which is flushed away by dielectric. The<br />

work piece and wire electrode are separated by de ionized water. The de ionized water works as dielectric fluid<br />

and flushes out the eroded or melted material. WEDM is rarely able to achieve optimal performance due to large<br />

number <strong>of</strong> variables and their stochastic nature. This problem can be solved by determining the relationship<br />

between performance <strong>of</strong> the process and its input parameters using designed experiments.<br />

Kuriakose and Shunmugam [1] observed that more uniform surface characteristics are obtained with coated wire<br />

electrode and the time between two pulses is the most influencing process parameter. Rajurkar and William [2]<br />

reported that wire electrical discharge machine (WEDM) manufacturers and users are to achieve higher<br />

machining rate with desired accuracy and minimum surface damage. The complex and random nature <strong>of</strong> the<br />

erosion process in WEDM requires the application <strong>of</strong> deterministic as well as stochastic techniques. Surface<br />

roughness pr<strong>of</strong>iles were studied with a stochastic modeling and analysis methodology to better understand the<br />

process mechanism. Scanning electron microscopic (SEM) examination highlighted important features <strong>of</strong> WED<br />

machined surfaces. Kanlayasiri and Boonmung [3] investigated the effects <strong>of</strong> machining variables on the surface<br />

roughness <strong>of</strong> wire-EDMed DC53 die steel. In this study, the machining variables investigated were pulse peak<br />

current, pulse-on time, pulse-<strong>of</strong>f time, and wire tension. Analysis <strong>of</strong> variance (ANOVA) technique was used to<br />

find out the variables affecting the surface roughness. Ramakrishnan and Karunamoorthy [4] reported the<br />

development <strong>of</strong> artificial neural network (ANN) models and multi-response optimization technique to predict<br />

406


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

and select the best cutting parameters in WEDM process. Scott et al [5] used a factorial design requiring a<br />

number <strong>of</strong> experiments to determine the most favourable combination <strong>of</strong> the WEDM parameters. They found<br />

that the discharge current, pulse duration and pulse frequency are the significant control factors affecting the<br />

MRR and SF, while the wire speed, wire tension and dielectric flow rate have the least effect. Liao et al. [6]<br />

proposed an approach <strong>of</strong> determining the parameter settings based on the Taguchi quality design method and the<br />

analysis <strong>of</strong> variance. The results showed that the MRR and SF are easily influenced by the table feed rate and<br />

pulse on-time, which can also be used to control the discharging frequency for the prevention <strong>of</strong> wire breakage.<br />

Manna and Bhattacharyya [7] found open gap voltage and pulse on period as the most significant machining<br />

parameters for controlling the metal removal rate using Taguchi method-based analysis for WEDM on<br />

Al/SiCMMC..<br />

In <strong>20</strong>05 El-Taweel et al. [8] revealed that WEDM allowed success in the production <strong>of</strong> newer materials,<br />

especially for the aerospace and medical industries. Using WEDM technology, complicated cuts can be made<br />

through difficult-to-machine electrically conductive components. The high degree <strong>of</strong> the obtainable accuracy and<br />

the fine surface quality make WEDM valuable. In addition, Luo [9] investigated the EDM with a small erosion<br />

area by examining effects <strong>of</strong> spark <strong>of</strong>f time. Takahata and Gianchandani [10] studied the use <strong>of</strong> electrode arrays<br />

for batch EDM generation <strong>of</strong> micro-features. Scott et al. [11] used a factorial design requiring a number <strong>of</strong><br />

experiments to determine the most favourable combination <strong>of</strong> the WEDM parameters. They found that the<br />

discharge current, pulse duration and pulse frequency are the significant control factors affecting the MRR and<br />

SF, while the wire speed, wire tension and dielectric flow rate have the least. I. Cabanes [12] found that the main<br />

challenges in WEDM is avoiding wire breakage and unstable situations as both phenomena reduce process<br />

performance and can cause low quality components. They develop a real time control strategy for increasing the<br />

performance <strong>of</strong> WEDM process. Sharma et al. [13] optimized the process parameters <strong>of</strong> WEDM process<br />

parameters for cutting rate. It increases with increase in pulse on time and peak current and decreases with<br />

increase in pulse <strong>of</strong>f time and servo voltage.<br />

Till now there is no work carried out using HSLA as a die material. As it is hard, wear resistant corrosion<br />

resistant, so HSLA is choose as a work-piece for experimentation. To evaluate the effects <strong>of</strong> machining<br />

parameters on performance characteristics, and to identify the optimal performance characteristics under the best<br />

settings <strong>of</strong> machining parameters, a specially designed experimental procedure called Response Surface<br />

Methodology has been used.<br />

2. PROCESS PARAMETERS OF WEDM<br />

Based on the findings <strong>of</strong> the many researchers, process parameters for WEDM process based on the quality <strong>of</strong><br />

the machining are grouped in various categories. The process parameters, their designated symbols and range are<br />

given in Table 1.<br />

Table 1: Process Parameters, Symbols and their Ranges<br />

Process Parameters Symbol Range (machine units)<br />

Pulse on Time T on (µs)<br />

111-117<br />

Pulse <strong>of</strong>f time T <strong>of</strong>f (µs)<br />

36-50<br />

Spark gap voltage SV (V) 30-50<br />

Peak Current IP (A) 1<strong>20</strong>-180<br />

Wire Tension WT (grams) 6-10<br />

The range <strong>of</strong> all the process parameters is selected for the present study based on the results obtained from<br />

preliminary experiments.<br />

2.1 EXPERIMENTAL METHODOLOGY<br />

The experimental studies were performed using a Electronic Sprint cut 734 WED machine tool. A brass Wire<br />

with a diameter <strong>of</strong> 250 µm was used as an electrode to erode a work piece <strong>of</strong> HSLA Steel (flat plate). The gap<br />

between work piece and wire was flooded with a moving dielectric fluid (distilled water). Machining<br />

Experiments for determining the optimal machining parameters for optimizing response characteristics were<br />

carried out by using distilled water as a dielectric fluid. During the experiments the cutting <strong>of</strong> the work piece was<br />

done. The size <strong>of</strong> work-piece is 5mm×5mm×18mm. The work material, electrode and the other machining<br />

condition are as follows:<br />

1. Work piece height : 18 mm<br />

2. Conductivity : <strong>20</strong> mho<br />

407


3. Cutting voltage (V) : 80V<br />

4. Die-electric temperature : 35 ◦C<br />

5. Injection pressure set point was at 7 unit (105 Kg/cm 2 )<br />

6. Peak Voltage (VP) : 2 unit<br />

7. Servo feed : <strong>20</strong>50 units<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 2: Design <strong>of</strong> experiment<br />

Std Order Run A:Ton B:T<strong>of</strong>f C:SV D:IP E:WT Rz<br />

5 1 111 36 50 1<strong>20</strong> 6 2.9535<br />

3 2 111 50 30 1<strong>20</strong> 6 3.2835<br />

21 3 114 43 <strong>20</strong> 150 8 4.62<br />

8 4 117 50 50 1<strong>20</strong> 6 4.541<br />

4 5 117 50 30 1<strong>20</strong> 10 4.389<br />

<strong>20</strong> 6 114 57 40 150 8 3.9105<br />

9 7 111 36 30 180 6 4.762<br />

22 8 114 43 60 150 8 3.584<br />

<strong>19</strong> 9 114 29 40 150 8 4.653<br />

15 10 111 50 50 180 6 3.342<br />

32 11 114 43 40 150 8 3.6785<br />

23 12 114 43 40 90 8 3.95<br />

1 13 111 36 30 1<strong>20</strong> 10 3.7845<br />

12 14 117 50 30 180 6 4.889<br />

25 15 114 43 40 150 4 3.882<br />

29 16 114 43 40 150 8 3.728<br />

2 17 117 36 30 1<strong>20</strong> 6 4.884<br />

16 18 117 50 50 180 10 3.3765<br />

18 <strong>19</strong> 1<strong>20</strong> 43 40 150 8 4.7685<br />

14 <strong>20</strong> 117 36 50 180 6 4.989<br />

27 21 114 43 40 150 8 3.63<br />

11 22 111 50 30 180 10 3.3495<br />

17 23 108 43 40 150 8 2.5925<br />

6 24 117 36 50 1<strong>20</strong> 10 3.67<br />

28 25 114 43 40 150 8 3.94<br />

24 26 114 43 40 210 8 4.038<br />

10 27 117 36 30 180 10 4.0905<br />

13 28 111 36 50 180 10 3.3165<br />

30 29 114 43 40 150 8 3.63<br />

7 30 111 50 50 1<strong>20</strong> 10 3.3165<br />

31 31 114 43 40 150 8 3.6465<br />

26 32 114 43 40 150 12 2.945<br />

2.2 RESPONSE SURFACE METHODOLOGY<br />

For the present work, RSM has been applied for developing the mathematical models in the form <strong>of</strong> multiple<br />

regression equations for the quality characteristics <strong>of</strong> WEDM process. In applying the RSM, the dependent<br />

parameter was viewed as a surface to which a mathematical model is fitted. For the development <strong>of</strong> regression<br />

equations related to various quality characteristics <strong>of</strong> WEDM process, the second order response surface has<br />

been assumed as:<br />

0<br />

k k k<br />

2<br />

i i ii i ii i j r<br />

i= 1 i= 1 i< j=<br />

2<br />

∑ ∑ ∑ (1)<br />

Y= b + bx+ bx + bxx + e<br />

This assumed surface Y contains linear, squared and cross product terms <strong>of</strong> parameters x i ’s. In order to estimate<br />

the regression coefficients, a number <strong>of</strong> experimental design techniques are available. Box and Hunter [14] have<br />

proposed a scheme, based on central composite rotatable design, which fits the second order response surfaces<br />

very accurately. Also no replication is needed to find error mean square. The error mean square can be found out<br />

by replicating the centre points.<br />

408


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3. RESULTS AND DISCUSSION<br />

The 32 experiments were conducted according to the central composite second order rotatable design for<br />

investigating total surface roughness (R z ). The experimental data along with the experimental design matrix are<br />

given in Table 2. For analyzing the data, the checking <strong>of</strong> goodness <strong>of</strong> fit <strong>of</strong> the model is very much required. The<br />

model adequacy checking includes test for significance <strong>of</strong> the regression model, test for significance on model<br />

coefficients and test for lack <strong>of</strong> fit. For this purpose, analysis <strong>of</strong> variance (ANOVA) is performed. It can be seen<br />

that the regression model is fairly well fitted with the observed values.<br />

Table 3: Pooled ANOVA after pooling insignificant terms<br />

Source Sum <strong>of</strong> squares DF Mean Square F- Value Prob > F<br />

Model 12.11 16 0.76 50.01 < 0.0001 significant<br />

A 5.11 1 5.11 337.68 < 0.0001<br />

B 0.5 1 0.5 32.74 < 0.0001<br />

C 1.5 1 1.5 99.11 < 0.0001<br />

D 0.09 1 0.09 5.94 0.0277<br />

E 1.61 1 1.61 106.72 < 0.0001<br />

2<br />

B 0.6<br />

1 0.6 39.72 < 0.0001<br />

2<br />

C 0.28 1 0.28 18.63 0.0006<br />

2<br />

D 0.15 1 0.15 9.76 0.007<br />

2<br />

E 0.16 1 0.16 10.82 0.005<br />

AB 0.074 1 0.074 4.88 0.0431<br />

AD 0.15 1 0.15 10.2 0.006<br />

AE 0.64 1 0.64 42.38 < 0.0001<br />

BC 0.099 1 0.099 6.53 0.022<br />

BD 0.37 1 0.37 24.57 0.0002<br />

BE 0.076 1 0.076 5.03 0.0405<br />

DE 0.7 1 0.7 46.28 < 0.0001<br />

Residual 0.23 15 0.015<br />

Lack <strong>of</strong> Fit 0.16 10 0.016 1.1 0.489 not<br />

Pure Error 0.071 5 0.014<br />

Cor Total 12.33 31<br />

Std. Dev. 0.1230 R-Squared 0.9816<br />

Mean 3.8792 Adj R-Squared 0.96<strong>20</strong><br />

C.V. 3.1708 Pred R-Squared 0.9123<br />

PRESS 1.0817 Adeq Precision 24.8605<br />

3.1 ANALYSIS OF SURFACE ROUGHNESS<br />

The fit summary recommended that the quadratic model is statistically significant for analysis <strong>of</strong> R z . The pooled<br />

ANOVA for GC are given in Table 3. From the pooled ANOVA analysis, the value <strong>of</strong> R 2 and adjusted R 2 is over<br />

95%. This means that regression model provides an excellent explanation <strong>of</strong> the relationship between the<br />

independent variables (factors) and the response Rz. The associated p-value for the model is lower than 0.05<br />

which indicates that the model is considered to be statistically significant. The lack-<strong>of</strong>-fit term is non significant<br />

as it is desired. Further A-Pulse on time, B-Pulse <strong>of</strong>f time, C-Servo Voltage, D- Peak current, E-Wire<br />

Mechanical Tension. Interaction between pulse on time and pulse <strong>of</strong>f time, pulse on time and peak current, pulse<br />

on time and wire mechanical tension, pulse <strong>of</strong>f time and servo voltage, pulse <strong>of</strong>f time and peak current, pulse <strong>of</strong>f<br />

time and wire mechanical tension, peak current and wire mechanical tension also the second order factors having<br />

significant effect. The other model terms are said to be insignificant. To fit the quadratic model for R z<br />

appropriate, the insignificant terms are eliminated by backward elimination process.<br />

The reduced model results indicate that the model is significant (R 2 and adjusted R 2 are 98.16% and 96.<strong>20</strong>%<br />

respectively), lack <strong>of</strong> fit is non significant as p value is 0.489 (and significant value is less than 0.05), Figure 1<br />

displays the normal probability plot <strong>of</strong> the residuals for R z . It is noticed that the residuals are falling on a straight<br />

line, which means that the errors are normally distributed.<br />

409


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

While after pooling the Final Equation in Terms <strong>of</strong> Actual Factors is as follows:<br />

2<br />

R z =-42.16263+0.44524×T on -0.61505×T <strong>of</strong>f -0.15141×SV+0.16<strong>19</strong>5×IP+4.28286×WT+2.91071E-003 ×T <strong>of</strong>f +<br />

9.76875E-004×SV 2 +7.85417E-005×IP 2 -0.018609×WT 2 +3.23512E-003 ×T on ×T <strong>of</strong>f -1.09097E-003×T on ×IP-<br />

0.033365×T on ×WT+1.12232E-003×T <strong>of</strong>f ×SV-7.25893E-004 ×T <strong>of</strong>f ×IP+4.92411E-003×T <strong>of</strong>f ×WT-3.48646E-<br />

003×IP×WT<br />

Table 4 shows the confirmation test at various selected parameters settings at which surface roughness<br />

minimizes.<br />

4.989<br />

W arning ! Factor involved in an interactio<br />

99<br />

Normal % Probability<br />

95<br />

90<br />

80<br />

70<br />

50<br />

30<br />

<strong>20</strong><br />

10<br />

5<br />

Response 1<br />

4.38988<br />

3.79075<br />

3.<strong>19</strong>162<br />

1<br />

2.5925<br />

-1.80 -0.83 0.13 1.10 2.07<br />

111.00 112.50 114.00 115.50 117.00<br />

Studentized R esiduals<br />

A: Ton<br />

Figure 1: Normal probability plot <strong>of</strong> residuals for R z<br />

Figure 2(a): Effect <strong>of</strong> pulse-on-time on R z<br />

Table 4: confirmation Test<br />

Sr. No. Ton<br />

T<strong>of</strong>f SV IP WT Pred. Rz<br />

Actual Rz<br />

Desirability<br />

1 111 42.59 50 1<strong>20</strong> 8 2.99875 3.14 0.83<br />

2 111 42.78 50 1<strong>20</strong> 8 2.99894 3.07 0.83<br />

3 111 42.49 50 1<strong>20</strong> 8 2.99896 3.02 0.83<br />

4.989<br />

W arning ! Factor involved in an interaction<br />

4.989<br />

W arning ! Factor involved in an interactio<br />

4.38988<br />

4.38988<br />

Response 1<br />

3.79075<br />

Response 1<br />

3.79075<br />

3.<strong>19</strong>162<br />

3.<strong>19</strong>162<br />

2.5925<br />

2.5925<br />

36.00 39.50 43.00 46.50 50.00<br />

30.00 35.00 40.00 45.00 50.00<br />

B: T<strong>of</strong> f<br />

Figure2(c) :Effect <strong>of</strong> servo voltage on R z<br />

C : SV<br />

Figure 2(b):Effect <strong>of</strong> pulse <strong>of</strong>f time on R z<br />

410


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4.989<br />

W arning ! Factor involved in an interactio<br />

4.989<br />

W arning ! Factor involved in an interactio<br />

4.38988<br />

4.38988<br />

Response 1<br />

3.79075<br />

Response 1<br />

3.79075<br />

3.<strong>19</strong>162<br />

3.<strong>19</strong>162<br />

2.5925<br />

2.5925<br />

1<strong>20</strong>.00 135.00 150.00 165.00 180.00<br />

6.00 7.00 8.00 9.00 10.00<br />

D : IP<br />

Figure 2(d): Effect <strong>of</strong> peak current on R z<br />

E: W T<br />

Figure 2(e): Effect <strong>of</strong> Wire Tension on R z<br />

The response surface is plotted to study the effect <strong>of</strong> process variables on the surface roughness and is shown in<br />

Figures 2(a)-2 (e). From Figure 2(a) it is seen that the surface roughness increases with increase in pulse on time.<br />

A probable reason for it may be that with increase in pulse on time, discharge energy increases causing a<br />

stronger spark which increases surface roughness. Now it is seen from Figure 2(b) that higher the pulse <strong>of</strong>f time,<br />

Rz decreases and after certain period it increases again. From figure 2(c) with the increment in the servo voltage,<br />

the longer the discharge wait time leading to a smaller surface roughness. It is observed from Figure 2(d) that the<br />

surface roughness slightly increases with increase in the peak current. This result has been attributed to the<br />

increase in peak current which leads to the increase in the rate <strong>of</strong> the heat energy and hence in the rate <strong>of</strong> melting<br />

and evaporation. It is revealed from figure 2(e) that with increase in wire tension surface roughness increases.<br />

4.CONCLUSION<br />

WEDM has become an important non-conventional machining process for process the hard to cut and conductive<br />

material for obtaining a good surface finish. The Selection <strong>of</strong> control factors is a thorny task in WEDM as it<br />

involves a large numbers <strong>of</strong> control factors. Response Surface Methodology was used for the development <strong>of</strong><br />

mathematical model and ANOVA. The central composite rotatable design <strong>of</strong> half fraction was used for the<br />

reduction in number <strong>of</strong> experiments. This research work suggests the optimal setting for better surface<br />

characteristics. The developed mathematical models are <strong>of</strong> immense important to predict and understand the<br />

proper surface finish for effective machining <strong>of</strong> HSLA steel in advance.<br />

REFERENCES<br />

[1] Shajan Kuriakose, M.S. Shunmugam, Characteristics <strong>of</strong> wire-electro discharge machined Ti6Al4V surface,<br />

<strong>Science</strong> Direct Materials Letters, 58, 2231– 2237, <strong>20</strong>04.<br />

[2] R. E. Williams and K. P. Rajurkar, Study Of Wire Electrical Discharge Machined Surface Characteristics,<br />

Journal <strong>of</strong> Materials Processing <strong>Technology</strong>, 28, 127-138,<strong>19</strong>91.<br />

[3] K. Kanlayasiri, S. Boonmung, Effects <strong>of</strong> wire-EDM machining variables on surface roughness <strong>of</strong> newly<br />

developed DC 53 die steel: Design <strong>of</strong> experiments and regression model, Journal <strong>of</strong> Materials Processing<br />

<strong>Technology</strong>, <strong>19</strong>2-<strong>19</strong>3, 1016-1022, <strong>20</strong>07.<br />

[4] R. Ramakrishnana and L. Krunamoorthy, Modeling and multi-response optimization <strong>of</strong> Inconel 718 on<br />

machining <strong>of</strong> CNC WEDM process, Journal <strong>of</strong> Materials Processing <strong>Technology</strong>, <strong>20</strong>7, 343–349, <strong>20</strong>08.<br />

[5] D. Scott, S. Boyina, K.P. Rajurkar, Analysis and optimization <strong>of</strong> parameter combination in wire electrical<br />

discharge machining, International Journal <strong>of</strong> Production Research ,29 (11), 2189–2<strong>20</strong>7, <strong>19</strong>91.<br />

[6] Y.S. Liao, J.T. Huang, H.C. Su, A study on the machining-parameters optimization <strong>of</strong> wire electrical<br />

discharge machining, Journal <strong>of</strong> Material Processing <strong>Technology</strong>, 71, 487–493, <strong>19</strong>97.<br />

[7] A. Manna and B. Bhattacharyya, Taguchi and Gauss elimination method: A dual response approach for<br />

parametric optimization <strong>of</strong> CNC wire cut EDM <strong>of</strong> PRAlSiCMMC, International Journal <strong>of</strong> Advanced<br />

Manufacturing <strong>Technology</strong> , 28, 67–75, <strong>20</strong>06.<br />

[8] M.S. Hewidy, T.A. El-Taweel, M.F. El-Safty, Modelling the machining parameters <strong>of</strong> wire electrical<br />

discharge machining <strong>of</strong> Inconel 601 using RSM, Journal <strong>of</strong> Materials Processing <strong>Technology</strong>, 169, 328–336,<br />

<strong>20</strong>05.<br />

[9] T. Masuzawa, H.K. Tonsh<strong>of</strong>f, Three-dimensional micromachining by machine tools, Annals <strong>of</strong> the CIRP, 46,<br />

621–628, <strong>19</strong>97.<br />

[10] Z.Y. Yu, T. Masuzawa, M. Fujino, Micro-EDM for three-dimensional cavities-development <strong>of</strong> uniform<br />

wear method, Annals <strong>of</strong> the CIRP, 47, 169–172, <strong>19</strong>98.<br />

[11] T. Masuzawa, K. Okajima, T. Taguchi, M. Fujino, EDM-lathe for micromachining, Annals <strong>of</strong> the CIRP, 51<br />

(1), 355–358, <strong>20</strong>02.<br />

411


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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[12] I. Cabanes, E. Portillo, M. Marcos, J.A. Sanchez, An industrial application for on-line detection <strong>of</strong><br />

instability and wire breakage in wire EDM, Journal <strong>of</strong> Materials Processing <strong>Technology</strong>, <strong>19</strong>5 (3), 101-<br />

109,<strong>20</strong>07.<br />

[13] N. Sharma, Khanna R, Gupta RD, Gupta P., Effect <strong>of</strong> Process Parameters on Cutting Rate in WEDM using<br />

Response Surface Methodology, i-manager’s Journal on Mechanical Engineering, 2(1), 28-34, <strong>20</strong>12.<br />

[14] Box, G.E.P. and Hunter, J.S., ‘Multifactor experimental design’, J. Ann. Math. Statistics, 28, <strong>19</strong>57.<br />

412


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

E-Manufacturing Concept: A Review Paper<br />

Naveen Virmani 1 and Rajeev Saha 2<br />

1 Department <strong>of</strong> Mechanical Engineering, Satyug Darshan Technical Campus, Faridabad (Haryana).<br />

2<br />

Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad (Haryana).<br />

E-mail: naveen_virmani<strong>20</strong>07@yahoo.com<br />

Abstract<br />

E-Manufacturing refers to the use <strong>of</strong> internet and web based applications to control production. Now-a-days,<br />

there is a challenge before manufacturing companies to make product on the fly that will attract new customer<br />

while retaining old customers also. Today the customer wants to get quality product and service without delay.<br />

Enterprises are integrating the e-manufacturing concept within their manufacturing facilities to harness the<br />

pr<strong>of</strong>its. This paper tries to identify various models based on E-Manufacturing Concept.<br />

Keywords: E-Manufacturing.<br />

1. Introduction<br />

In the last decade, <strong>Technology</strong> is found to be changing day by day [7, 9]. Now days, customers demand valuable<br />

products at reasonable price. Manufacturers are fast accepting the fact that in order to boost the sales and<br />

increase the pr<strong>of</strong>its they need to pay more attention to customer satisfaction. Advance Manufacturing Methods<br />

was thought as sufficient for customer driven market approach but yet success was only partial in today’s<br />

internet-driven economy i.e. respond to customer demand in real time. This can be achieved by integrating AMT<br />

with internet and web based applications to form integral part <strong>of</strong> E-Business [1]. Today, the customer do not<br />

want to take any risk, so before purchasing the product, he ask from the known persons about the product i.e.<br />

enquire about the product, so there is a need for manufacturing companies to adapt a strategy which can provide<br />

products at reasonable price without compromising with the quality. For this, E manufacturing could be a<br />

solution. It is the application <strong>of</strong> internet and web based application to control production. E-Manufacturing can<br />

integrate customers, products, suppliers with the help <strong>of</strong> Internet <strong>Technology</strong>. E-Manufacturing results in<br />

frictionless exchange <strong>of</strong> information all over the world.<br />

Now days, almost all big companies like Tata, Ashok Leyland, Maruti, and JCB are using automation to some<br />

extent. These companies are using CNC’S, Robotics, Automatic material handling system and many other<br />

automation equipments. Figure 1(a) shows after collecting data by production persons, they make reports and<br />

further send it to the management. To get any information regarding production equipment or production,<br />

management people ask the production department executives every time the information is needed. Figure 1(b)<br />

shows that by using E–manufacturing technique, different equipments can be connected via intranet or internet to<br />

ERP (Enterprise Resource Planning) [2] and finally the information can be accessed from various departments.<br />

Figure 1(a): Before implementing E-Manufacturing [2]<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 1(b): After implementing E-Manufacturing [2]<br />

It is clear from the diagrams that information needed by various departments can be directly collected with the<br />

help <strong>of</strong> E-Manufacturing technique.<br />

1.1 Definition by Koç [11]<br />

“It is a system methodology that enables the manufacturing operations to successfully integrate with the functional<br />

objectives <strong>of</strong> an enterprise through the use <strong>of</strong> internet, tether-free (i.e. wireless, web, etc.) and predictive<br />

technologies.<br />

Customer is a king is traditional misnomer in most businesses. Today we are using information technology<br />

everywhere whether it is in banks, airports, corporate, educational institutions. Now a days, we are using it on the<br />

shop floor also<br />

2. Tools <strong>of</strong> E-Manufacturing<br />

2.1 Design<br />

Today the customer demands changes very frequently. So there is a need to design a production system that can<br />

meet the changing demand pattern <strong>of</strong> customer. The system should be flexible enough so that new part designs<br />

can be introduced into system with relative ease [3,9]<br />

2.2 Operate<br />

High productivity is always desired .For this, equipments must work properly and products are <strong>of</strong> required<br />

quality at desired pace. For this, various techniques like six sigma, lean manufacturing, JIT, SPC are used [3,5].<br />

.<br />

2.3 Maintain<br />

It is about maintain the resources efficiently to achieve continuous production. It is also called the managing<br />

things like materials, processes and employees in order to get continuous production at right quality [8,10].<br />

2.4 Synchronize<br />

It is important tool which can links various groups such as manufacturer and supplier .For example if CNC<br />

machine tool operating on shop floor need a replacement <strong>of</strong> tool then information is sent from first the<br />

manufacturer to the supplier and tool maker where tool can be assessed [4,6].<br />

Figure 2 shows how the manufacturing technology changes with the 21 st century. Today all most all<br />

manufacturing companies are using computers for designing process (CAD) and for manufacturing (CAM), its<br />

planning and quality control. Today companies adopt Just in Time concept to eliminate the inventory cost.<br />

Companies are making their full efforts to make the production system agile which can respond quickly as per<br />

the changing demand patterns.<br />

E-Manufacturing concept has been practiced by more and more companies including small and medium sized<br />

enterprises’-Manufacturing includes online manufacturing activities for products and services, including product<br />

design and development, maintenance, supply chain management, sales and service through the internet. Most<br />

<strong>of</strong> the people are using internet for on line purchasing and selling <strong>of</strong> things. We cannot use E –Manufacturing<br />

414


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

technology blindly. Success comes to those firms who adopt the best strategy as per the requirement and<br />

opportunities.<br />

The developments in manufacturing technology have been very well depicted in figure 2.<br />

Fig 2: Development in manufacturing technology as adapted from Cheng [3].<br />

Supply Chain is very important concept in E-Manufacturing. E-Manufacturing is a Vertical(business) and<br />

Horizontal(Supply Chain) integration <strong>of</strong> system to ensure the correct dissemination <strong>of</strong> information throughout<br />

the value chain <strong>of</strong> a business, making use <strong>of</strong> appropriate technology like the internet to ensure that real time<br />

accurate information is available at all decision points throughout an organization and value chain. As<br />

enumerated by Greeff [13<br />

Fig 3: The transformation <strong>of</strong> e-Manufacturing for unmet needs in SCM as depicted in Koç [12].<br />

Supply chain encompasses all activities associated with flow and transformation <strong>of</strong> materials from raw material<br />

stage to the end user. It involves involvement <strong>of</strong> four flows in a supply chain- Material, Information, Money and<br />

Ownership.<br />

Integration <strong>of</strong> all tools and techniques like SCM, CRM etc. is basis for successful e-business. Similarly<br />

Collaborative planning, Real time information, Asset Management etc. are required for E-Manufacturing.<br />

As discussed by Koç [12] synchronization <strong>of</strong> all integral tools, techniques and processes <strong>of</strong> e -Business, e<br />

manufacturing and e maintenance need to be addressed as shown in figure 4.<br />

415


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig 4: Integration <strong>of</strong> e-manufacturing with e-business and e-maintenance as depicted in Koç[12].<br />

3. Conclusion<br />

Various models <strong>of</strong> E-Manufacturing have been discussed in this paper. Usually, in most <strong>of</strong> the companies,<br />

method <strong>of</strong> manufacturing involves manual data information flow which takes a lot <strong>of</strong> time but the use <strong>of</strong> E-<br />

Manufacturing helps in frictionless exchange <strong>of</strong> information and system becomes capable to respond to changing<br />

demand patterns <strong>of</strong> customers. Mostly, when customer demand changes, it takes time to reach this information to<br />

the organization but use <strong>of</strong> E-Manufacturing involves exchange <strong>of</strong> information in real time thereby helping in<br />

quick response from the organization. This will also results in increase in productivity and helps in producing<br />

quality products. Case studies shows that Alex Engineering has installed better CNC machine and other tooling,<br />

to implement a job shop managing system with an emphasis on capacity planning and job costing. The<br />

installation cost is <strong>20</strong>,000 £. Also, Good ridge installed a scalable, multi-language currency integrated ERP system<br />

handling everything from order entry to manufacturing, with five new assembly shops. The installation cost is<br />

400,000 £[3].<br />

References<br />

[1] Saha R, Grover S. “Identifying Enablers <strong>of</strong> E-Manufacturing” ,ISRN Mechanical Engineering Journal,<strong>20</strong>11<br />

[2] “E Manufacturing a <strong>Technology</strong> Review”, Proceedings <strong>of</strong> the world congress on engineering <strong>20</strong>08 Volume<br />

II, July 2- 4, <strong>20</strong>08, London,U.K.<br />

[3] Cheng Kai and Batman, Richard J. “ E-Manufacturing : Characteristics, applications and Potentials.”Progress<br />

in Natural <strong>Science</strong> 18(<strong>20</strong>08):1323-1328<br />

[4] White Paper “Making Sense <strong>of</strong> E-Manufacturing: A roadmap for manufacturers industry” Rockwell<br />

Automation <strong>20</strong>02, http://www.rockwellautomation.com<br />

[5] www.esrc.ac.uk [accessed on 14/08/<strong>20</strong>12]<br />

[6] www.epsrc.ac.uk [accessed on 14/08/<strong>20</strong>12]<br />

[7]Cheng K, editor E-Manufacturing fundamentals and applications, London, WIT, Press; <strong>20</strong>05<br />

[8] Chan H, Lee R, Dillon T, et al. E –Commerce: fundamentals and applications .Chichester: John Wiley and<br />

Sons Ltd; <strong>20</strong>01<br />

[9] Society <strong>of</strong> Manufacturing Engineers (SME), less factory downtime with ‘predictive intelligence’,<br />

Manufacturing Engineering Journal, Feb. <strong>20</strong>02, www. sme.org<br />

[10] How the machine will fix itself in Tomorrow’s world, Tooling and Production Magazine, November <strong>20</strong>00,.<br />

[11] Koç M and Ni J. Introduction <strong>of</strong> E-Manufacturing. Proceedings <strong>of</strong> the International Conference on Frontiers<br />

on Design and Manufacturing, Dalian, China, July <strong>20</strong>02<br />

[12] Koç, Muammer and Lee, Jay. “E Manufacturing- fundamentals, requirements, and expected impacts”.<br />

International Journal <strong>of</strong> Advanced Manufacturing Systems. Vol 6, Issue 1, 29-46.<strong>20</strong>03<br />

[13] Greeff, Gerhard and Ghosal Ranjan and Mackay, Steve. Practical E-Manufacturing and supply chain<br />

Management. Chapter-1, Page 2. Pub Elsevier Ltd. ISBN: 978-0-7506-6272-7.<strong>20</strong>04<br />

416


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Investigation <strong>of</strong> the effect <strong>of</strong> Process Parameters on Surface Roughness<br />

in Wire Electric Discharge Machining <strong>of</strong> En31 Tool Steel<br />

Dharmender 1 , Rajeev Kumar 2 and Anmol Bhatia 3<br />

1 Research Scholar, <strong>YMCA</strong> <strong>University</strong> Of <strong>Science</strong> & <strong>Technology</strong>,Faridabad., Haryana<br />

2 Assistant Pr<strong>of</strong>essor, IIMT College <strong>of</strong> Engineering, Greater Noida,UP<br />

3 Sr.Lecturer, Echelon Institute <strong>of</strong> <strong>Technology</strong>, Faridabad, Haryana<br />

Abstract<br />

Modernization <strong>of</strong> mechanical industry has lead to the increase in demand for hard and tough materials<br />

and thus various non traditional methods have been developed in order to machine such hard and tough<br />

materials. Wire Electric discharge machine is one <strong>of</strong> the most commonly used machine which is employed in<br />

machining <strong>of</strong> conductive metals <strong>of</strong> any hardness or that are difficult or impossible to cut with traditional<br />

methods. WEDM is one <strong>of</strong> the most popular machining methods in present industry which specializes in<br />

cutting complex shapes or geometries. The literature survey has revealed that very less work has been done in<br />

order to achieve optimal levels <strong>of</strong> process parameters for Tool Steel-En31 using Brass wire electrode.<br />

This paper deals with the study the effect <strong>of</strong> different process parameters viz. peak current, pulse on time, pulse<br />

<strong>of</strong>f time, Wire Tension on the response variable- Surface roughness using Brass wire electrode (0.25 mm<br />

diameter). Taguchi design methodology has been chosen for design <strong>of</strong> experiment and L 9 orthogonal array<br />

has been selected for present study. In this study MINITAB s<strong>of</strong>tware was used to find the effect <strong>of</strong> each<br />

parameter on response characteristic and to predict the setting <strong>of</strong> control parameters. ANNOVA and main<br />

effect plot have been used to find the significant process parameters and their effect on the response<br />

variables. The predicted optimal value <strong>of</strong> Surface Roughness is further verified by confirmation experiments.<br />

Keywords: WEDM, Process parameters, ANNOVA, En-31 tool steel.<br />

1. Introduction<br />

Wire Electrical discharge machining (WEDM) is a nontraditional, thermoelectric process which erodes material<br />

from the work piece by a series <strong>of</strong> discrete sparks between a work and tool electrode immersed in a liquid<br />

dielectric medium. Melting and vaporization due to electrical discharge removes minute amounts <strong>of</strong> the work<br />

material, which are then ejected and flushed away by the dielectric. The schematic representation <strong>of</strong> the WEDM<br />

cutting process is shown in Figure 1.Wire electrical discharge machining (WEDM) is a specialized thermal<br />

machining process capable <strong>of</strong> producing accurately machined parts with different hardness or complex shapes,<br />

which have sharp edges that are very difficult to be machined by conventional machining processes. At present,<br />

WEDM is a widely used technique in industry for high-precision machining <strong>of</strong> all types <strong>of</strong> conductive materials<br />

such as metals, metallic alloys, graphite, or even some ceramic materials, <strong>of</strong> any hardness [1-3]. Many Wire-<br />

EDM machines have adopted the pulse generating circuit using low power for ignition and high power for<br />

machining. However, it is not suitable for finishing process since the energy generated by the high-voltage subcircuit<br />

is too high to obtain a desired fine surface, no matter how short the pulse-on time is assigned [4].As newer<br />

and more advance as well as exotic materials are developed, and demand <strong>of</strong> more complex shapes ,conventional<br />

machining operations will continue to reach their limitations[5].<br />

WEDM is considered as variants <strong>of</strong> the conventional EDM process, which uses an electrode to initialize the<br />

sparking process. However, WEDM utilizes a continuously travelling wire electrode made <strong>of</strong> thin copper, brass<br />

or tungsten <strong>of</strong> diameter 0.05-0.30 mm, which is capable <strong>of</strong> achieving very small corner radii. The wire is kept in<br />

tension using a mechanical tension providing device reducing the tendency <strong>of</strong> producing inaccurate parts.<br />

Fig (1):Schematic representation <strong>of</strong> WEDM cutting process<br />

417


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. LITERATURE REVIEW<br />

Eduardo Weingartner et al [6] investigated the influence <strong>of</strong> high-speed rotating work pieces on wire electrical<br />

discharge machining (WEDM), single discharge experiments were carried out inside a grinding machine, in a<br />

self-designed wire electrical discharge dressing device (WEDD-device). Kamal Jangra et al [7] evaluated the<br />

machinability <strong>of</strong> tungsten carbide composite using Graph theoretic approach(GTA). Factors affecting the<br />

machinability and their interactions are analyzed by developing a mathematical model using digraph and matrix<br />

method.D.V. Ghewade et al [8] investigated the cutting <strong>of</strong> Inconel 718 material using electro discharge<br />

machining (EDM) with a copper electrode by using Taguchi methodology has been reported. The Taguchi<br />

method is used to formulate the experimental layout, to analyse the effect <strong>of</strong> each parameter on the machining<br />

characteristics.D. Welling et al [9] presented a comparison between grinding and WEDM <strong>of</strong> Ti6Al4V<br />

concerning surface integrity aspects proved by bending fatigue life is set up. Due to visual inspections and<br />

surface roughness measurements a higher fatigue life <strong>of</strong> the ground specimen is assumed. Sarkar et al [10]<br />

presented an in depth study on wire lag phenomenon. A novel method to measure gap force intensity and wire<br />

lag under any given machining condition has been proposed by developing an analytical model. Patil and<br />

Brahmankar et al [11] investigated electrical and non electrical process parameters for machining metal matrix<br />

composite. The metal matrix composite chosen for this experiment is reinforced aluminium matrix<br />

composite and wire used is a brass wire <strong>of</strong> 0.25 mm diameter. Process parameters that have been chosen<br />

were reinforcement percentage current, pulse on-time, <strong>of</strong>f time, servo reference voltage, maximum feed<br />

speed, wire speed, flushing pressure and wire tension whereas the response parameters were cutting speed<br />

surface finish, and kerf width. Islam et al. [12] investigated the WEDM process for its dimensional accuracy. Mild<br />

steel 1040 is used as work piece material for the investigations and the wire material used is brass <strong>of</strong> 0.25 mm<br />

diameter. Process parameters for WEDM were varied to have obtained different results. Experimental results were<br />

analyzed by three different techniques namely traditional analysis, the Taguchi method, and Pareto ANOVA<br />

analysis. The effect <strong>of</strong> the process parameters was related to three different accuracy characteristics which<br />

are dimensional errors, flatness errors, and perpendicularity err ors <strong>of</strong> corner surfaces.<br />

Kapoor et al. [13] presented a study on different Wire electrodes which are being used in the industry and some<br />

high performance electrodes have been observed. It has been investigated that wire electrode contribute<br />

directly to cutting speed and dimensional accuracy. Some <strong>of</strong> the electrodes studied are copper, brass and coated<br />

wire electrodes. It been observed that for different materials different metal wire electrodes are preferred they<br />

<strong>of</strong>fer better response parameters such as better surface finish, higher MRR etc Composite wires have replaced<br />

zinc coated wires. Hsien-Ching Chen et al [14] analyzed variation <strong>of</strong> cutting velocity and workpiece surface<br />

finish depending on wire electri-cal discharge machining (WEDM) process parameters during manufacture <strong>of</strong><br />

pure tungsten pr<strong>of</strong>iles. A method integrating back-propagation neural network (BPNN) and simulated annealing<br />

algorithm (SAA) is proposed to determine an optimal parameter setting <strong>of</strong> the WEDM process. The specimens<br />

are pre-pared under different WEDM process conditions based on a Taguchi orthogonal array table. The results<br />

<strong>of</strong> 18 experimental runs were utilized to train the BPNN predicting the cutting velocity, roughness aver-age (Ra),<br />

and roughness maximum (Rt) properties at various WEDM process conditions and then the SAA approaches was<br />

applied to search for an optimal setting. In addition, the analysis <strong>of</strong> variance (ANOVA) was implemented to<br />

identify significant factors for the WEDM process and the proposed algorithm was also compared with respect to<br />

the confirmation experiments. Mu-Tian Yan et al [15] presented the development <strong>of</strong> a high-frequency power<br />

supply for surface quality improvement <strong>of</strong> wire electrical discharge machining (wire-EDM). A novel fixed pulsewidth<br />

modulation pulse control method is proposed to generate high-frequency and short-duration pulse control<br />

signals. A spark gap model using a resistance–capacitance (RC) circuit and a Zener diode is proposed for circuit<br />

design and simulation analysis. Tests revealed that the developed power supply using anti-electrolysis circuitry<br />

and digital signal processor-based pulse control circuit can provide very low discharge energy pulses with a<br />

frequency <strong>of</strong> 4.4 MHz, discharge duration <strong>of</strong> 90 ns and a peak current <strong>of</strong> 1.2 A.<br />

Susanta Kumar Gauri et al [16] Studied that weighted principle component(WPC) processes and showed that<br />

WPC method <strong>of</strong>fers significantly better overall quality the other approaches method is used to optimize the<br />

multi responses <strong>of</strong> WEDM Taguchi's robust design method which combines the experimental design technique<br />

with quality loss consideration as used. They observed that the set <strong>of</strong> multiple responses is transformed into asset<br />

<strong>of</strong> small no <strong>of</strong> uncorrelated principle components. Most importantly there is no need for an input during analysis<br />

<strong>of</strong> experimental data in WPC method. Aminollah Mohammadi et al [17] presented the application <strong>of</strong> wire<br />

electrical discharge machining (WEDM) for machining <strong>of</strong> precise cylindrical forms on hard and difficult-tomachine<br />

materials. At first, the design <strong>of</strong> a precise, flexible and corrosion-resistant rotary spindle submerged is<br />

introduced. The spindle has been mounted on a five-axis wire EDM machine to rotate the work piece in order to<br />

generate free form cylindrical geometries. The material removal rate (MRR) is an important indicator <strong>of</strong> the<br />

efficiency and cost-effectiveness <strong>of</strong> the process. Several experiments are conducted to consider effects <strong>of</strong> power,<br />

time-<strong>of</strong>f, voltage, servo, wire speed, wire tension, and rotational speed (factors) on the MRR (response). An L 18<br />

(2 1 ×3 7 ) Taguchi standard orthogonal array is chosen for the design <strong>of</strong> experiments. Analyses <strong>of</strong> variance<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

(ANOVA) as well as regression analysis are performed on experimental data. The signal-to-noise (S/N) ratio<br />

analysis is employed to find the optimal condition.<br />

S. Sarkar et al [18] predicted the optimal machining conditions for required surface finish and dimensional<br />

accuracy plays a very important role in process planning <strong>of</strong> wire electrical discharge machining. The present<br />

work deals with the features <strong>of</strong> trim cutting operation <strong>of</strong> wire electrical discharge machining <strong>of</strong> ϒ -titanium<br />

aluminide. A second-order mathematical model, in terms <strong>of</strong> machining parameters, was developed for surface<br />

roughness, dimensional shift and cutting speed using response surface methodology (RSM). The experimental<br />

plan was based on the face centered, central composite design (CCD). The residual analysis and experimental<br />

results indicate that the proposed models could adequately describe the performance indicators within the limits<br />

<strong>of</strong> the factors that are being investigated. Finally the trim cutting operation has been optimized for a given<br />

machining condition by desirability function approach and Pareto optimization algorithm. It was observed that<br />

performance <strong>of</strong> the developed Pareto optimization algorithm is superior compared to desirability function<br />

approach. R. Ramakrishnan et al [<strong>19</strong>] describes the development <strong>of</strong> artificial neural network (ANN) models and<br />

multi-response optimization technique to predict and select the best cutting parameters <strong>of</strong> wire electro-discharge<br />

machining (WEDM) process. To predict the performance characteristics namely material removal rate and<br />

surface roughness, artificial neural network models were developed using back-propagation algorithms. Inconel<br />

718 was selected as work material to conduct experiments. A brass wire <strong>of</strong> 0.25mm diameter was applied as tool<br />

electrode to cut the specimen. Experiments were planned as per Taguchi’s L 9 orthogonal array. Experiments<br />

were performed under different cutting conditions <strong>of</strong> pulse on time, delay time, wire feed speed, and ignition<br />

current. The responses were optimized concurrently using multi response signal-to-noise (MRSN) ratio in<br />

addition to Taguchi’s parametric design approach. Analysis <strong>of</strong> variance (ANOVA) was employed to identify the<br />

level <strong>of</strong> importance <strong>of</strong> the machining parameters on the multiple performance characteristics. Finally,<br />

experimental Confirmations were carried out to identify the effectiveness <strong>of</strong> this proposed method. A good<br />

improvement was obtained.<br />

3. Objectives <strong>of</strong> the Present Study<br />

• Investigation <strong>of</strong> the working ranges and levels <strong>of</strong> the WEDM process parameters using one factor at a time<br />

approach.<br />

• Experimental determination <strong>of</strong> the effects <strong>of</strong> the various process parameters viz pulse on time, pulse <strong>of</strong>f<br />

time, spark gap set voltage, peak current, wire feed and wire tension on the surface roughness in WEDM<br />

process.<br />

• Predict the optimal value <strong>of</strong> each response characteristic corresponds to their optimal parameter setting<br />

using MINITAB 16.<br />

• Optimization <strong>of</strong> the process parameters <strong>of</strong> WEDM process using Taguchi’s technique.<br />

• Optimization <strong>of</strong> the performance measures using Taguchi method.<br />

• Validation <strong>of</strong> the results by conducting confirmation experiments.<br />

4. Loss Function and S/N Ratio<br />

Taguchi defines quality loss via his 'loss-function'. He unites the financial loss with the functional specification<br />

through a quadratic relationship that comes from Taylor series expansion [<strong>20</strong>]<br />

L(y) =k(y-m) 2<br />

Where, L = loss in monetary unit<br />

M-value at which the characteristic should be set<br />

Y-actual value <strong>of</strong> characteristic<br />

K-constant depending on the magnitude <strong>of</strong><br />

characteristic and monetary unit involved.<br />

The S/N ratio for surface Roughness will be <strong>of</strong> lower the better type & is expressed by the formula given below<br />

( S N)<br />

Where<br />

LB<br />

= −10 log( MSD)<br />

R<br />

1 2<br />

MSDLB<br />

= ∑ ( y<br />

j<br />

)<br />

R j=<br />

1<br />

5. Experimentation<br />

using Taguchi's L 9<br />

LB<br />

In this experimentation Taguchi parametric design methodology was used. The experiments were conducted by<br />

OA array.<br />

4<strong>19</strong>


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 1: Levels <strong>of</strong> different process parameters<br />

Process<br />

Parameter<br />

Symbol<br />

Used<br />

S.I Units<br />

Range<br />

Peak Current A Amperes 90-230<br />

Pulse On Time B µs 115-130<br />

Pulse Off Time C µs 48-56<br />

Wire Tension D grams 5-10<br />

The En31 Rectangular bar <strong>of</strong> 100mm x <strong>20</strong>mm x 15mm is mounted on Electronic a Sprint Cut Wire EDM<br />

machine tool and the specimens <strong>of</strong> size 15mm x <strong>20</strong> mm x 8 mm are cut.<br />

Fig (2): Cut Specimens<br />

In this phase, four process parameters viz. peak current, pulse on time, pulse <strong>of</strong>f time, and wire tension were<br />

selected as given in table(3) Experiments were conducted according to the test conditions specified by the L 9<br />

Orthogonal Array as described.<br />

Table (3): Response table for Surface Roughness<br />

Expt<br />

Run<br />

(<br />

A<br />

)<br />

P<br />

C<br />

(<br />

B<br />

)<br />

(<br />

C<br />

)<br />

T<br />

o<br />

n<br />

T<br />

o<br />

ff<br />

(<br />

D<br />

)<br />

W<br />

T<br />

R<br />

a<br />

1<br />

R<br />

a<br />

2<br />

T<br />

r<br />

i<br />

a<br />

l<br />

T<br />

r<br />

i<br />

a<br />

l<br />

2<br />

Mea<br />

n <strong>of</strong><br />

Ra 1<br />

&<br />

Ra 2<br />

1 1 1 1 1 1.58 1.54 1.56<br />

2 1 2 2 2 1.76 1.75 1.755<br />

3 1 3 3 3 3.43 3.42 3.425<br />

4 2 1 2 3 1.51 1.51 1.51<br />

5 2 2 3 1 3.69 3.67 3.68<br />

6 2 3 1 2 3.02 3.01 3.015<br />

7 3 1 3 2 4.48 4.41 4.445<br />

8 3 2 1 3 5.00 4.48 4.74<br />

9 3 3 2 1 3.83 3.82 3.825<br />

Avg. <strong>of</strong> Surface<br />

Roughness=3.106<br />

6. Results & Discussions<br />

6.1 Normal probability plot for Surface Roughness<br />

The normal probability plot is a graphical technique for assessing whether or not a data set is approximately<br />

normally distributed. The points on this plot form a nearly linear pattern, which indicates that the normal<br />

distribution is a good model for this data set. The normal probability plot showed the set <strong>of</strong> value <strong>of</strong> response<br />

variables are very close to median <strong>of</strong> set <strong>of</strong> values and not deviate from mid value.<br />

Fig: (3) Normal Probability plot for Surface Roughness<br />

4<strong>20</strong>


6.2 Effect <strong>of</strong> input factors on Surface Roughness<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 4: Response Table for Signal to Noise Ratio for Surface Roughness (Smaller is better)<br />

Level A B C D<br />

1 -6.480 -6.800 -8.988 -8.944<br />

2 -8.161 -9.906 -6.706 -9.143<br />

3 -12.709 -10.644 -11.656 -9.263<br />

Delta 6.228 3.844 4.950 0.3<strong>19</strong><br />

Rank 1 3 2 4<br />

Figure 4: Main effects plot for S/N ratio <strong>of</strong> Surface Roughness<br />

Table 5: Response Table for Means for Surface Roughness<br />

Level A B C D<br />

1 2.247 2.505 3.105 3.022<br />

2 2.735 3.392 2.363 3.072<br />

3 4.377 3.422 3.850 3.225<br />

Delta 2.090 0.917 1.487 0.<strong>20</strong>3<br />

Rank 1 3 2 4<br />

Figure 5: Main effects plot for means <strong>of</strong> Surface Roughness<br />

Table (6) ANNOVA Table for Mean Data <strong>of</strong> Surface Roughness<br />

Source DOF SS MS Percentage<br />

Contribution<br />

A 2 9.374 4.687 26.2772<br />

B 2 8.7634 4.3817 24.5656<br />

C 2 8.948 4.474 25.0831<br />

D 2 8.588 4.294 24.0739<br />

Total 8 35.6734<br />

It is clear from S/N plots that the max S/N ratio occurs corresponding to A 1 B 1 C 2 D 1 . Y optimal<br />

performance + Contribution <strong>of</strong> significant factors at optimum levels<br />

= Average<br />

Y<br />

optimal T + ( A1 − T ) + ( B1<br />

− T ) + ( C 2 − T ) + ( D1<br />

− T )<br />

= Optimal Value <strong>of</strong> Surface Roughness = 2.343667 µm<br />

421


6.3 CONFIRMATION EXPERIMENTS<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The data from the confirmation runs and their comparisons with the predicted values. From the analysis, we can<br />

observe that the calculated error is small.<br />

Quality<br />

Charac<br />

teristic<br />

Optimal<br />

setting<br />

Of<br />

process<br />

paramet<br />

Predicte<br />

d<br />

optimal<br />

value<br />

Confor<br />

mation<br />

Values<br />

Surface<br />

Roughness<br />

A 1 B 1 C 2 D 1 . 2.3436 µm 2.21 µm<br />

7. Conclusion<br />

The Taguchi methodology is employed to find out the main parameters that affect the<br />

different machining criteria, such as average cutting speed and surface roughness in the<br />

present set <strong>of</strong> study. Four control factors have been studied simultaneously to establish the<br />

trend <strong>of</strong> variation <strong>of</strong> a few important machining criteria with these control factors. A rough<br />

cut has been considered as a machining operation. Target was to get the range <strong>of</strong> different<br />

parameters which are taken under consideration. The Taguchi methodology is applied to<br />

know which parameters are significant and to find out the optimum level <strong>of</strong> various process<br />

parameters so as to obtain maximum cutting speed and minimum surface roughness. After<br />

applying the Taguchi methodology optimum level <strong>of</strong> the parameters for the maximum cutting speed is<br />

A 1 B 1 C 2 D 1 . The experimentation is summarized as under. The surface roughness (SR) is mostly influenced by<br />

T on time and T <strong>of</strong>f time.<br />

• The combination <strong>of</strong> A1 B 1 C 2 D 1 (i.e. A=90A, B=115µs, C=50µs, D=5g) gives minimum surface roughness<br />

<strong>of</strong> 2.3436 µm.<br />

• The normal probability plot for SR is normally distributed because set <strong>of</strong> values <strong>of</strong> all values are mostly<br />

close to mid value.<br />

• The error between experimental and predicted values for SR is 5.67 %.<br />

REFERENCES<br />

[1] K.H. Ho, S.T. Newman, S. Rahimifard, R.D. Allen, State <strong>of</strong> the art in wire electrical discharge machining<br />

(WEDM), International Journal <strong>of</strong> Machine Tools and Manufacture 44(<strong>20</strong>04), 1247-1259.<br />

[2] A. Gatto, L. Luliano, Cutting mechanisms and surface features <strong>of</strong> WEDM metal matrix composite, Journal <strong>of</strong><br />

Material Processing <strong>Technology</strong> 65 (<strong>19</strong>97) <strong>20</strong>9-214.<br />

[3] I. Puertas, C.J. Luis, A study on the machining parameters optimization <strong>of</strong> electrical discharge machining,<br />

Journal <strong>of</strong> Materials Processing <strong>Technology</strong>, 143-144 (<strong>20</strong>03) 521-526.<br />

[4] Y.S. Liao, J.T. Huang, Y.H. Chen, A study to achieve a fine surface finish in Wire-EDM, Journal <strong>of</strong><br />

Materials Processing <strong>Technology</strong> 149 (<strong>20</strong>04) 165-171.<br />

[5] T.A. Spedding, Z.Q. Wang, Study on modeling <strong>of</strong> wire EDM process, Journal <strong>of</strong> Materials Processing<br />

<strong>Technology</strong> 69 (<strong>19</strong>97) 8-28.<br />

[6] Eduardo Weingartner, Konrad Wegener, Friedrich Kuster [<strong>20</strong>12] ”Wire electrical discharge machining<br />

applied to high-speed rotating work pieces” Journal <strong>of</strong> Materials Processing <strong>Technology</strong> vol. 212, pp.1298–<br />

1304<br />

[7] Kamal Jangra, Sandeep Grover, Felix T. S. Chan & Aman Aggarwal [<strong>20</strong>11],” Digraph and matrix method to<br />

evaluate the machinability <strong>of</strong> tungsten carbide composite with wire EDM” International Journal <strong>of</strong><br />

Advanced Manufacturing <strong>Technology</strong> vol.56, pp.959–974.<br />

[8] D.V. Ghewade and S.R Niparkar [<strong>20</strong>11] ”Experimental Study <strong>of</strong> Electro Discharge Machining For Inconel<br />

Material” Journal <strong>of</strong> Engineering Research and Studies Vol.2, pp.107-112.<br />

[9] F. Klocke, D. Welling & J. Dieckmann [<strong>20</strong>11],”Comparison <strong>of</strong> grinding and Wire EDM concerning fatigue<br />

strength and surface integrity <strong>of</strong> machined Ti6Al4V components” Procedia Engineering vol.<strong>19</strong>,pp. 184 – 18.<br />

[10] S. Sarkar, M. Sekh, S. Mitra & B. Bhattacharyya [<strong>20</strong>11],” A novel method <strong>of</strong> determination <strong>of</strong> wire lag for<br />

enhanced pr<strong>of</strong>ile accuracy in WEDM” Precision Engineering vol.35,pp.339–347.<br />

[11] N. G. Patil and P. K. Brahmankar [<strong>20</strong>10], “Some Studies into Wire Electro- Discharge Machining <strong>of</strong><br />

Alumina Particulate-Reinforced Aluminum Matrix Composites”, International Journal <strong>of</strong> Advanced<br />

Manufacturing <strong>Technology</strong>, vol. 48, 537–555.<br />

[12] M. N. Islam, N. H. Rafai and S. S. Subramanian [<strong>20</strong>10], “An Investigation into Dimensional Accuracy<br />

Achievable in Wire-cut Electrical Discharge Machining”, Proceedings <strong>of</strong> the World Congress on<br />

Engineering, Vol. 3<br />

422


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[13] Kapoor, S. Singh and J. S. Khamba [<strong>20</strong>10], “Recent Developments in Wire Electrodes for High<br />

Performance WEDM”, Proceedings <strong>of</strong> the World Congress on Engineering, Vol.2.<br />

[14] Hsien-Ching Chen, Jen-Chang Lin & Yung-Kuang Yang, [<strong>20</strong>10],” optimization <strong>of</strong> wire electrical<br />

discharge machining for pure tungsten using a neural network integrated simulated annealing approach”,<br />

Expert Systems with Applications,vol.37,pp.7147–7153.<br />

[15] Mu-Tian Yan & Yi-Ting Liu [<strong>20</strong>09],” Design, analysis and experimental study <strong>of</strong> a high-frequency power<br />

supply for finish cut <strong>of</strong> wire-EDM”, International Journal <strong>of</strong> Machine Tools & Manufacture, vol. 49,<br />

pp.793–796.<br />

[16] Susanta Kumar Gauri & Shankar Chakraborty [<strong>20</strong>09], “Optimisation <strong>of</strong> multiple responses for WEDM<br />

processes using weighted principal components” International Journal <strong>of</strong> Advanced Manufacturing<br />

<strong>Technology</strong>, Vol. 40, pp.1102–1110.<br />

[17] Aminollah Mohammadi, Alireza Fadaei Tehrani, Ehsan Emanian & Davoud Karimi [<strong>20</strong>08],” Statistical<br />

analysis <strong>of</strong> wire electrical discharge turning on material removal rate” Journal <strong>of</strong> materials processing<br />

technology, vol.<strong>20</strong>5, pp.283–289.<br />

[18] S. Sarkar, M. Sekh, S. Mitra & B. Bhattacharyya[<strong>20</strong>08],”Modeling and optimization <strong>of</strong> wire electrical<br />

discharge machining <strong>of</strong> ϒ -TiAl in trim cutting operation”, Journal <strong>of</strong> materials processing technology,<br />

vol.<strong>20</strong>5, pp. 376–387.<br />

[<strong>19</strong>] R. Ramakrishnan & L. Karunamoorthy [<strong>20</strong>08],”Modeling and multi response optimization <strong>of</strong> Inconel 718<br />

on machining <strong>of</strong> CNC WEDM process”, Journal <strong>of</strong> materials processing technology, vol. <strong>20</strong>7, pp. 343–349.<br />

[<strong>20</strong>]Ross, Philip J., Taguchi Techniques for Quality Engineering, McGraw Hill Book Company, New York,<br />

<strong>19</strong>96<br />

423


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Flexible Manufacturing Systems: Recent Development and Trends<br />

Neeraj Lamba<br />

Assistant Pr<strong>of</strong>essor, Shri Ram College <strong>of</strong> Engineering And Management Palwal, Faridabad, Haryana<br />

Email:.nlamba33@gmail.com<br />

Abstract<br />

Implementing Flexible Manufacturing Systems (FMS) has been motivated by the desired to respond more rapidly<br />

to dynamic changes both in demand and in product mix. There have been several successful implementation and<br />

the resulting improvements to product flow have been considerable. This paper describes the present<br />

development and trends <strong>of</strong> FMS. In this work attempts for defining the FMS, motivation for pursuing FMS,<br />

examples <strong>of</strong> FMS, implementation rate <strong>of</strong> FMS is investigated. The evidence suggests that in spite <strong>of</strong> a high<br />

degree <strong>of</strong> promise from FMS, the growth rate <strong>of</strong> FMS implementations is surprising low. The major reasons for<br />

this technical, cost and justification problems – are discussed and the main research/development issues arising<br />

are described. Finally, the trend in Flexible manufacturing Systems towards a more gradualist approach,<br />

building up from Flexible manufacturing cells is also described<br />

Keywords: Flexible Manufacturing Systems, Automation, Manufacturing control, Robotics, Computer<br />

Integrated Manufacturing.<br />

1.Introduction: Definition <strong>of</strong> Flexible Manufacturing Systems<br />

Flexible Manufacturing Systems (FMS) has a number <strong>of</strong> potential definitions. The literal meaning is a logical<br />

arrangement (system) <strong>of</strong> transformation processes (manufacturing) that is adjustable to change (flexible): a<br />

Flexible Manufacturing System. This definition would encompass a wide variety <strong>of</strong> manufacturing activities<br />

including for example, skilled manual workers such as tool and die makers. Different researchers have given<br />

different definitions <strong>of</strong> FMS. Like young and Greene [2] <strong>of</strong>fer for consideration <strong>of</strong> following definition <strong>of</strong> FMS:<br />

“A group <strong>of</strong> CNC (Computer numeric control) machine tools linked by an automated materials handling system,<br />

whose operation is integrated by supervisory computer control. Integral to an FMS is the capability to handle any<br />

number <strong>of</strong> similar families <strong>of</strong> parts in random order”. A similar definition is given by Draper labs [3].Both<br />

highlight the feature <strong>of</strong> FMS which is that <strong>of</strong> automation, thereby excluding manufacturing systems that are<br />

primarily manual in operation.<br />

A further background on FMS can be found in Kuemmel [4], Ingersoll Engineers [5], Draper Laboratories [3],<br />

Ranky [6], and Hartley [7].<br />

The distinction between stand alone machines, Flexible Manufacturing Cells (FMC), FMS and Flexible Transfer<br />

Lines is made by Greene [1]. “The stand alone machine is typically a machining center or turning center with<br />

some method <strong>of</strong> automatic material handling…..All <strong>of</strong> the features typical <strong>of</strong> the fully automated flexible system<br />

are available in the stand alone machine, including probing, inspection, tool monitoring, and adaptive control.<br />

However, in the stand alone machine, these features are initiated and controlled at the machine control level.”<br />

“The FMC can take a number <strong>of</strong> configurations, but it generally has more than one machine tool with some form<br />

<strong>of</strong> pallet –changing equipment, such as a robot or other specialized material- handling device. In some cases, the<br />

grouping <strong>of</strong> machines is small and <strong>of</strong>ten uses a common pallet or part –fixturing device.”<br />

“The flexible manufacturing system (FMS) includes at least three elements: a number <strong>of</strong> workstations, an<br />

automated material –handling system supervisory control. The FMS is typically designed to run for long periods<br />

with little or no operator attention….Central computer control over real-time routing, load balancing, and<br />

production scheduling distinguish FMS from FMC.”<br />

“A considerable amount <strong>of</strong> ambiguity surrounds the term flexibility. The distinction between flexible transfer<br />

lines and flexible manufacturing systems is a case in point. A flexible transfer line can contain several machine<br />

tools linked by an automated work piece flow system. The flexible transfer line is capable <strong>of</strong> simultaneously or<br />

sequentially machining a small number <strong>of</strong> different work pieces (which distinguishes it from a conventional<br />

transfer line), but the pieces run through the system along a fixed path, unlike a FMS where work pieces may<br />

move randomly”. [1]<br />

Bushong [8] provides a three-dimensional graphical representation <strong>of</strong> the productivity, flexibility, and<br />

management trade-<strong>of</strong>fs associated with each <strong>of</strong> the major types <strong>of</strong> flexible automation. He suggests that the<br />

specific type <strong>of</strong> flexible automation appropriate depends on what levels <strong>of</strong> these three attributes are desired. In<br />

essence, Bushong suggests Flexible Transfer Lines for high productivity/low management requirements. This<br />

reinforces the properties <strong>of</strong> the various flexible automation techniques suggested by young and Greene [2].<br />

424


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. The Motivation for FMS<br />

There is a general perception that manufacturing industry has to alter more rapidly now than in past. This<br />

exemplified by the following:<br />

“Automobile production in the U.S was down a million cars in <strong>19</strong>27- not because it was a bad year<br />

economically , but because Henry ford’s plant took five months from may 26 to November 1.to switch<br />

production from model T to model A. In <strong>19</strong>27, many <strong>of</strong> Henry’s customers and dealers were content to wait. But<br />

in today’s market place such a long changeover could spell corporate suicide.” [9]<br />

FMS have been viewed as helping the process <strong>of</strong> rapid changeover. According to Palframan [10], “The figures<br />

are impressive .FMS promise 50% reduction in lead and machining times using only a handful <strong>of</strong> machining<br />

times using only a handful <strong>of</strong> machines and a few operators.” Green [1] is more specific in his list <strong>of</strong> potential<br />

benefits:<br />

‣ Increased machine utilization;<br />

‣ Reduced -work in –process inventory;<br />

‣ Increased productivity <strong>of</strong> working capital;<br />

‣ Reduced number <strong>of</strong> machine tools;<br />

‣ Reduced labor costs;<br />

‣ Reduced led times;<br />

‣ Less floor space;<br />

‣ Reduced setup costs;<br />

Molins Ltd. Is credited with introducing the ideas behind the ideas behind FMS in the mid-<strong>19</strong>60’s and their<br />

design embodied many <strong>of</strong> today’s essential FMS characteristics- in particular, the importance <strong>of</strong> streamlining the<br />

manufacturing process.<br />

However growth in the use <strong>of</strong> FMS technology has been slow. In <strong>19</strong>81 the world FMS population was only [2]<br />

115.By <strong>19</strong>86 the population had grown to <strong>20</strong>0, an average increase <strong>of</strong> only 17 systems per year. These figures<br />

are based on the definition <strong>of</strong> FMS given by Young and Greene [2]. Slightly different and more detailed<br />

estimates are given by Owen [11]. Approximately half <strong>of</strong> the installations are in Europe; the remainder split<br />

between Japan and the U.S. In the U.S. and Europe, FMS are mostly found in the automotive industry. Japan is<br />

thought to use FMS primarily in Machine tool industry [2].<br />

3. Examples <strong>of</strong> FMS installations<br />

The present development status <strong>of</strong> FMS can be illustrated by the examples <strong>of</strong> the FMS at Cummins Engine Co.,<br />

Applied Power Inc., International-Hough., Iveco and by the success stories reported by the success stories<br />

reported by Dornan [12]. Other reviews <strong>of</strong> implemented FMS’s are contained in draper labs [3], Dupont-<br />

Gatelmand [13], Bilalis [14], American Machinist [15] and Techno craft [16].<br />

The FMS at Cummins Engine Co., Walesboro, Indiana was supplied by LeBlond Makino Cincinnati, Ohio at a<br />

cost <strong>of</strong> $2.5 million [17]. It is mainly being used to machine a family <strong>of</strong> parts for lubricator, Water pumps, and<br />

other components used on diesel engines. All parts are being machined from cast iron. The FMS contains three<br />

MC65-A123 horizontal machining centers, one Baron 50 two-axis turning center, a rail-guided vehicle for parts<br />

transport, a Devlieg tool presetter, two pallet queue areas, and a computer control system. It is reportedly planned<br />

to expand the FMS to include a total <strong>of</strong> six MC65-A123 machining centers. It helps in decreased lead times,<br />

reduced inventory, higher quality and the ability to make parts to order in small quantities and on short notice are<br />

reportedly listed as reasons for turning to FMS.<br />

The FMS at Applied power Inc., Milwauke, Wisconsin was supplied by Toyada Machinery USA Inc.,<br />

Schumburg, Illinois. It is used for the manufacture <strong>of</strong> hydraulic tools, including clamping systems, modular<br />

fixtures and systems, and related power supplies [18]. The international-Hough division <strong>of</strong> Dresser industries,<br />

Inc., Libertyville, Illinois have an FMS supplied by Giddings & Lewis unit <strong>of</strong> AMCA international, Fond du<br />

Lac, Wisconsin at a cost $7 million. The FMS was originally designed for a series <strong>of</strong> six crawler tractor rear<br />

mainframes, including a 3100-lb model TD12 rear mainframe housing, one <strong>of</strong> the more complex parts machined<br />

on the FMS. The FMS consists <strong>of</strong> four DNC horizontal machining centers, each equipped with two pallet<br />

stations, a material transporter system and two load and unload stations [<strong>19</strong>]. All four machines perform milling,<br />

boring, drilling and tapping operations. Each machine is equipped with a 100-tool capacity automatic tool<br />

changer.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4. FMS problems.<br />

That there are so few FMS implementations and that, more significantly, the growth rate <strong>of</strong> FMS<br />

implementations is so slow should give some pause for thought. This is especially so in light <strong>of</strong> the benefits<br />

allude to in earlier sections. The seemingly consensus opinions in literature for the lack <strong>of</strong> any real growth in<br />

FMS implementation are problems associated with technical viability, cost and the resultant justifiability<br />

4.1 Technical viability and cost<br />

As indicated in the previous section, some industries are experiencing a degree <strong>of</strong> success with flexible systems:<br />

“Aerospace companies, the defense industry, and , <strong>of</strong> course, many machine tool builders have already installed<br />

highly sophisticated FMS’s that for the most part are operating successfully…… Vought Aerospace, for<br />

example has been operating an FMS in Dallas since <strong>19</strong>84 that is now capable <strong>of</strong> economically producing lot<br />

sizes <strong>of</strong> one….. The system has already paid for itself.” [10]<br />

However, opposing viewpoints are not uncommon. For example, in reference to the FMS at the John Deere,<br />

Waterloo, Indiana site, Jim Lardner, Vice president <strong>of</strong> Deere’s components group, had this to say about FMS:<br />

“Given the history <strong>of</strong> manufacturing industries that have embraced computers and computer system, there is<br />

substantial anecdotal evidence that we computerized utter confusion and inefficiency……what with the start up<br />

costs, the support system, the programmers, the automatic transfer devices, and so on.”[10]<br />

Lardner’s comments tend to suggest there are still many aspects <strong>of</strong> true flexible automated manufacturing<br />

systems that need to be worked out. Bergstrom [18] addresses the issue this way “FMS did seem to hold out<br />

promise on a grand scale …… But then something happened. Some <strong>of</strong> the luster began to fade. Stories about<br />

downtime and s<strong>of</strong>tware nightmares rose to the surface.[18]<br />

4.2 Justification<br />

Just as with discerned technical difficulties, problems in economic justification <strong>of</strong> FMS have also slowed the<br />

growth <strong>of</strong> FMS. Justifying the investment in the FMS is central to the growth <strong>of</strong> FMS implementations and<br />

Dornan [12] comments on the importance <strong>of</strong> appropriate automation procedures. It has now become a longargued<br />

point that traditional cost accounting techniques are simply inadequate for use in automation technology<br />

justification- particularly when there is an element <strong>of</strong> flexibility involved. Indeed many accounting systems<br />

revolve around labor savings. [<strong>19</strong>]<br />

There has been much written on how to better evaluate automation technology costs and savings Rohan [23]<br />

recommends an overall strategy for justification that takes all company goals into consideration rather than just<br />

engineering and accounting concerns. Dornan [12] emphasizes the importance <strong>of</strong> developing an overall corporate<br />

plan. She <strong>of</strong>fers a three-tiered approach to business planning based on:<br />

1.Strategic plan: Outlines generic survival tactics.<br />

2.Business plan: Develops strategies to compete globally.<br />

3.Manufacturing plan: Identifies activities in support <strong>of</strong> the business and strategies plans.<br />

One <strong>of</strong> the basic problems <strong>of</strong> FMS justification is quantifying the intangible benefits <strong>of</strong> increased quality and<br />

increased flexibility. Dornan [12] suggests that some <strong>of</strong> the data that is more difficult to quantify can be obtained<br />

from the FMS already implemented. She further suggests that one further benefit that could be included is the<br />

potential value <strong>of</strong> significantly extended capital equipment and capital investment life cycles.<br />

5. FMC versus FMS-Present trends<br />

We have seen that flexible automated manufacturing systems, although possessing the potential for being<br />

extremely valuable, have associated technical, cost and justification problems. As a result, much attention has<br />

begun to be focused on FMC’s .Steven E. Klabunde, vice president <strong>of</strong> manufacturing systems at Giddings &<br />

Lewis in Janesville, Wisconsin says.<br />

“What we’re seeing is something rethinking. People are beginning to recognize the complexity <strong>of</strong> the full- blown<br />

systems and they’re having second thoughts. They look at the complexity, the dollar investment, and they’re<br />

looking at their needs. Many companies can’t handle an FMS –certainly the smaller ones. So they are looking to<br />

something else, and something else is the cell.” [18] Bushong [8] concurs with this view. He goes on to suggest<br />

that a cell can be bought for the first 78% <strong>of</strong> what a system costs and without the problems associated with<br />

implementing a full FMS. The approach now being taken appears to bee invest in cells, get them working and<br />

then working, then worry about integrating the resultant islands <strong>of</strong> automation into a system later when<br />

technology makes it affordable. Droy[<strong>20</strong>]. Recognizing the trend toward cell manufacturing, <strong>of</strong>fers some basic<br />

guidelines for cell development. He also provides a list <strong>of</strong> substantial cost reductions associated with a well<br />

planned cell.<br />

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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

6. Research and development Issues<br />

The technical difficulties associated with FMS have certainly slowed the growth rate <strong>of</strong> FMS implementations.<br />

These difficulties give rise to two main technical research/development areas, namely FMS control and flexible<br />

fixturing (although there are other research / development issues also.)<br />

6.1 FMS control research/Development issues<br />

The task <strong>of</strong> FMS control is to plan, schedule and control the FMS so as to effectively use the FMS resources to<br />

achieve good due date performance. However, there is general acceptance <strong>of</strong> the complexity <strong>of</strong> the problem<br />

Barash et al. [21]. By its very nature flexibility implies the ability to adapt to environmental changes. The<br />

challenge, therefore, for makers and sellers <strong>of</strong> flexible automated manufacturing systems is to create an<br />

automated system capable <strong>of</strong> handling the various changes in everyday production environment on a real-time<br />

basis. The complexity <strong>of</strong> the FMS control task has prompted many researchers to suggest a hierarchical form <strong>of</strong><br />

control [22] and several hierarchies <strong>of</strong> control have been formulated [22]. Opposing this view is that <strong>of</strong><br />

hierarchical control Piper [23].<br />

6.2 Flexible Fixturing Research/ Development issues<br />

FMS control, although one major cause <strong>of</strong> insufficient flexibility in FMS is to certainly not the only cause.<br />

Ogorek poses a familiars question about a different side <strong>of</strong> FMS:<br />

“Small lot sizes and variety <strong>of</strong> parts are basic to FMS but are today’s work holding systems flexible enough”<br />

Gandhi and Thompson agree:<br />

“In order for a flexible manufacturing system to be truly flexible, all <strong>of</strong> the subsystem must be flexible.<br />

Too….The absence <strong>of</strong> adequate flexible fixturing methodologies is a significant impediment to the evolution <strong>of</strong><br />

truly flexible manufacturing systems.”<br />

The challenge, then, is therefore to develop work holding that is sturdy, precise, universal, and able to handle a<br />

wide variety and that can be made at a relatively low cost. Part <strong>of</strong> the present problem seems to be that work<br />

holding is not being addressed from a generic perspective; rather, that unique solutions are being developed for<br />

specific problems.<br />

7. Conclusion<br />

In this work the present development status and trends in Flexible Manufacturing Systems (FMS), motivation for<br />

pursuing FMS and some example <strong>of</strong> FMS has been described. Some <strong>of</strong> the major FMS problems have been<br />

indicated including both technical and justification aspects. The trend in FMS towards a gradualist approach<br />

building up from FMC has been described. Finally two major research & development issues (FMS control and<br />

flexible fixturing) are discussed<br />

Overall, the outlook for FMS is still extremely good with much research/development underway in the problem<br />

areas. The significant increase in the number <strong>of</strong> FMC would indicate FMS (arising out <strong>of</strong> the integration <strong>of</strong><br />

several FMC) will show considerable growth over the past, therefore is, the Trunkey FMS will have been<br />

replaced by this gradualist approach <strong>of</strong> building up from FMC. It would be expected that implementation<br />

difficulties would be less severe under this scenario.<br />

References<br />

[1] R.G Green, “Flexible manufacturing systems: Are they in your future”Tooling prod, July <strong>19</strong>86, pp. 35-38.<br />

[2] C.Young and A.Greene, Flexible Manufacturing Systems, American Management Association, New York,<br />

NY, <strong>19</strong>86.<br />

[3] Draper laboratories, Ch. Stark, Flexible Manufacturing System Handbook, Vols1-5, U.S. Dept. Commerce,<br />

NTIS puls.No.AD/A127927-930,<strong>19</strong>83.<br />

[4] T.J Kuemmel, “System considerations in Flexible Manufacturing systems” HOSTEX conference<br />

Monograph MF81-101, SME, Dearborn, MI, <strong>19</strong>81.<br />

[5] Ingersoll Engineers, The FMS Report, IFS, Bedford, U.K <strong>19</strong>82.<br />

[6] P.Ranky, the Design and Operation <strong>of</strong> FMS, IFS/North Holland, Amsterdam, <strong>19</strong>83.<br />

[7] J.Hartly, FMS at Work, IFS/Elsevier, Bedford, U.K.<strong>19</strong>84.<br />

[8] J.J Bushong, “Straight talk on cells vs. FMSs”. Production, Vol.97, November <strong>19</strong>85, pp 56-59.<br />

[9] “How Should Management Assess Today’s Advanced Manufacturing Options” Industry week, May 26,<br />

<strong>19</strong>86 pp45-88<br />

[10] D.Palframan “FMS too much too soon”. Manuf .Engg. March <strong>19</strong>87, pp.34-38<br />

[11] T.Owen, Strategic Issues in Automated Production. Cranfield Press, Cranfield, U.K., <strong>19</strong>85.<br />

[12] S.B Dornan, “cells and systems, justifying the investment”. Production, Vol.99, Febraury <strong>19</strong>87, pp.30-35.<br />

[13] C.Dupont-Gatelmand “A Survey Of Flexible Manufacturing Systems”, J.Manuf.Syst. Vol.<strong>19</strong>82, p.1<br />

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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[14] N.Bialalis, “The Design and Control <strong>of</strong> flexible Manufacturing Systms for rotational parts”, ph.D. Thesis,<br />

Loughborough Universty <strong>of</strong> <strong>Technology</strong>, <strong>19</strong>83.<br />

[15]“CAM :an International comparison”, Special report 740,Am. Machnist,Nov,<strong>19</strong>81.<br />

[16]“Features <strong>of</strong> Japanese Flexible Manufacturing systems”. Technocraft, Vol. 16, No. 4, <strong>19</strong>83.<br />

[17] J.C. Quinalan, “The many Faces <strong>of</strong> flexible turning”, tooling prod, July, <strong>19</strong>86, pp.52-56.<br />

[18] R.P .Bergstrom, “FMS: The drive toward cells”. Manuf. Eng., August <strong>19</strong>85, pp, 34-38.<br />

[<strong>19</strong>] Th.M. Rohan, “Justifying your CIM investment”. Ind.Week, March 9, <strong>19</strong>87, pp. 33-35.<br />

[<strong>20</strong>] J.Droy, “Tips on developing cells”, Prod Engg. March <strong>19</strong>87, pp.53-55.<br />

[21] M.M Barsh, F.F. Leimkuhlar, J.J Solberg and J.J Talavage,“Optimal planning <strong>of</strong> computerized<br />

manufacturing systems”.8 th NSF Grantees conf. Stanford, January 27-29, <strong>19</strong>81, NTIS, Washington, DC,J-<br />

1.<br />

[22] P.Jo’Grady, controlling Automated Manufacturing Systems, Champan Hall/Kogan Page, London, <strong>19</strong>87.<br />

[23] N.A Duffie and R.S Piper “Non- hierarchical control <strong>of</strong> a flexible manufacturing cell”, Robot. Computer<br />

Integrated Manufacturing. Vol.3 No.2 <strong>19</strong>87, pp175-179.<br />

[24] M.V.Gandhi and B.S Thompson. “Automated design <strong>of</strong> modular fixtures for flexible manufacturing<br />

systems”, J. Manuf.Syst. Vol.5 No.4, <strong>19</strong>86, pp 243-244.<br />

-3615/<br />

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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

COMPUTER INTEGRATED MANUFACTURING: A POWERFUL<br />

TECHNIQUE FOR IMPROVING PRODUCTIVITY<br />

Neeraj Lamba<br />

Assistant Pr<strong>of</strong>essor, Shri Ram College <strong>of</strong> Engineering and Management, Palwal, Faridabad<br />

E-mail: nlamba33@gmail.com<br />

Abstract<br />

This paper emphasizes the significant role <strong>of</strong> Computer Integrated Manufacturing (CIM) to the national<br />

economy. Ranges <strong>of</strong> topics have been covered in this paper: CIM definition, history, organization, and<br />

application. Today’s industry competes in a truly international marketplace. Efficient transportation networks<br />

have created a “world market” in which we participate on a daily basis. For any industrial country to compete<br />

in this market, it must have companies that provide economic high-quality products to their customers in a timely<br />

manner. The importance <strong>of</strong> integrating product design and process design to achieve design for production<br />

system cannot be overemphasized. However, even once a design is finalized, manufacturing industries must be<br />

willing to accommodate their customers by allowing last-minute engineering-design changes without affecting<br />

shipping schedules or altering product quality. Therefore, Most U.S.-based manufacturing companies look<br />

toward CAD/CAM and CIM to provide this flexibility in their manufacturing system. The Indian industry would<br />

have to change from a conventional manufacturing style to computer integrated manufacturing style in order to<br />

cope with the emerging market requirements. The paper discusses productivity improvement by using computer<br />

integrated manufacturing in India.<br />

Keywords: Productivity Improvement, Computer integrated manufacturing [CIM].<br />

1. Introduction<br />

Computer Integrated Manufacturing (CIM) is management philosophy in which the functions <strong>of</strong> design and<br />

manufacturing are rationalized and coordinated using computer, communication, and information technologies<br />

“according to Bedworth et al. (<strong>19</strong>91). CIM has the capability to largely or entirely automate flexible<br />

manufacturing by coordinating work cells, robots, automatic storage and retrieval facilities and material handling<br />

systems.“CIM is a new kind <strong>of</strong> philosophic theory used in organizing, managing, and running the enterprise’s<br />

production; it takes advantage <strong>of</strong> computer s<strong>of</strong>tware and hardware, synthetically uses modern managing<br />

technology, manufacturing technology, information technology, automatic technology, system engineering the<br />

whole process <strong>of</strong> enterprise’s production, as well as information flow and material flow, and runs them<br />

optimally, to make service excellent, bring products to market timely, and realize product’s high quality, low<br />

cost, so that enterprises will win the market competition technology, and it integrates organically the three<br />

relative factors <strong>of</strong> Person, <strong>Technology</strong>, Running Management in the whole process <strong>of</strong> enterprises production, as<br />

well as information flow and material flow, and runs them optimally, to make service excellent, bring products to<br />

market timely, and realize products high quality, low cost, so that enterprise will win the market competition”.<br />

Simply, CIM is the use <strong>of</strong> computer systems to integrate a manufacturing enterprise. CIM provides the tools to<br />

enable the use <strong>of</strong> organizational programs such as Total Quality Management, Continuous Improvement,<br />

Concurrent Engineering, and Design for Manufacturability, Design for Assembly, and back-to basics concept <strong>of</strong><br />

“Do it right the first time “Integrating information and organizations will decrease the logistical size <strong>of</strong> a<br />

company, making it appear to be small again-at least from the management, administration and informationsharing<br />

viewpoints. The goal <strong>of</strong> CIM is to provide the computer applications and communications needed to<br />

bring about the integration (with matching Organizational changes) that will allow a company to take Advantage<br />

<strong>of</strong> these new capabilities. The CIM Technologies may include:<br />

‣ Computer-aided design<br />

‣ Computer-aided manufacturing<br />

‣ Computer numerically controlled machines<br />

‣ Flexible manufacturing systems<br />

‣ Robotics<br />

‣ Automated material handling systems<br />

‣ Group technology<br />

‣ Manufacturing resource planning<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. Productivity Improvement Through Computer Integrated Manufacturing<br />

2.1. The causes <strong>of</strong> slowdown in US manufacturing industries<br />

The need for integration has evolved in response to the problems faced by the traditional manufacturing process<br />

<strong>of</strong> industrial automation. Individual automation in each functional unit created islands <strong>of</strong> automation. These<br />

islands <strong>of</strong> automation did not facilitate communication between the functional units. Errors in data sharing and<br />

other mismatches with these islands <strong>of</strong> automation continually plagued the Manufacturing industry. The<br />

complexity <strong>of</strong> new manufacturing technologies, economics, increasing human limitations, computer<br />

developments, and competition from abroad has forced the initiation <strong>of</strong> integrated computer aided manufacturing<br />

(ICAM) program by the United States <strong>of</strong> America Air force. The ICAM program conducted in <strong>19</strong>83 found the<br />

following critical problems in industrial automation:<br />

‣ Information could not be controlled by users,<br />

‣ Changes were too costly and time consuming,<br />

‣ Systems were not integrated, and<br />

‣ Data quality was not suitable for integration.<br />

Manufacturing managers consider and adopt innovative and advance technologies due to the global competition,<br />

which exists today, not only from Japan and Europe, but also form low labor cost countries such as China. The<br />

manufacturing engineer today must understand and be able to plan for these new technologies to survive in the<br />

present world condition. They should have a clear concept <strong>of</strong> automating the manual and semiautomatic<br />

machinery to reap the benefits <strong>of</strong> these emerging technologies. Implementation <strong>of</strong> CIM could help companies<br />

achieve their competitive goals to survive in the global market environment as long as the technologies chosen<br />

are appropriate to meet their objectiveTop and Bottom Margin: 25 mm.<br />

Provide a space <strong>of</strong> 60 pts before the title <strong>of</strong> the paper. It may be created using “Format – Paragraph – Indent and<br />

Spacing – Spacing: Before 60 pt” option.<br />

2.2. Benefits from CIM<br />

The integration <strong>of</strong> the technologies brings the following Benefits:<br />

‣ Faster responses to data-changes for manufacturing Flexibility.<br />

‣ Increased flexibility towards in <strong>of</strong> new Products.<br />

‣ Improved accuracy and quality in the manufacturing Process.<br />

‣ Improved quality <strong>of</strong> the products.<br />

‣ Control <strong>of</strong> data-flow among various units and Maintenance <strong>of</strong> user-library for system-wide data.<br />

‣ Reduction <strong>of</strong> lead times which generates a competitive advantage.<br />

‣ Streamlined manufacturing flow from order to delivery.<br />

‣ Easier training and re-training facilities.<br />

2.3. Why is CIM very important to National Economy<br />

In today’s competitive international business environment, companies are calling for new approaches to<br />

manufacturing. Also, the growth in computer based technology during the <strong>19</strong>80s, coupled with the emergence <strong>of</strong><br />

flexible manufacturing systems (FMS) and just-in-time(JIT) inventory control forced movement away from the<br />

traditional product focused manufacturing paradigms <strong>of</strong> the mass production era to that <strong>of</strong> a process-focused<br />

paradigm. Through the use <strong>of</strong> various computer-aided technologies, computer integrated manufacturing (CIM)<br />

attempts to pull all <strong>of</strong> the functional areas <strong>of</strong> a business into a cohesive, interconnected, interactive, self-aware<br />

whole. CIM includes such activities as product/process design, manufacturing technology, material acquisition,<br />

information resource management and total quality management. CIM utilizes enterprise-wide computer-aided<br />

technologies to maintain quality, speed new product development, minimize costs and maximize flexibility to<br />

respond to ever-changing customer desires. Thus, the competitive advantage <strong>of</strong> CIM in industry comes from its<br />

ability to:<br />

‣ Develop a large quantity <strong>of</strong> new products quickly;<br />

‣ Produce small production runs <strong>of</strong> custom-made items efficiently;<br />

‣ Maximize the flexibility <strong>of</strong> the manufacturer in responding quickly to changes in the environment.<br />

Historical manufacturing paradigms cannot deliver all these goals simultaneously, but CIM holds the potential to<br />

do so. The current state <strong>of</strong> expectations is that Compute Integrated Manufacturing (CIM) will ultimately<br />

determine industrial growth <strong>of</strong> world nations within the next few decades. Computer Aided Design (CAD),<br />

Computer Aided Manufacturing (CAM), Flexible Manufacturing Systems (FMS), Robotics together with<br />

knowledge and Information Based Systems and Communication Networks are expected to develop to a mature<br />

state to respond Effectively to the managerial requirements <strong>of</strong> the factories <strong>of</strong> the future that are becoming highly<br />

integrated and complex. CIM represents a new production approach that will allow the factories to deliver a high<br />

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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

variety <strong>of</strong> products at a low cost and with short production cycles. The new technologies for CIM are needed to<br />

develop manufacturing environments that are smarter, faster, close coupled, integrated, optimized, and flexible.<br />

2.4. Barriers to CIM adoption<br />

Despite all the money, energy, and time spent by Companies trying to automate their factory, CIM is still an<br />

unfulfilled promise for many. Managers have continually struggled with the problem <strong>of</strong> successfully putting the<br />

pieces together to get the most out <strong>of</strong> CIM technology. In the past few years, several surveys have attempted to<br />

investigate the problem identify the primary obstacles to more rapid adoption <strong>of</strong> CIM technology. Some <strong>of</strong> the<br />

findings are identified below.<br />

2.4.1. Management perception and attitude<br />

In late <strong>19</strong>70s and early <strong>19</strong>80s, as CIM advanced quite rapidly in the USA, disillusionment with automation has<br />

surfaced. Frequently, top executives viewed CIM as just technology – a master computer controlling many<br />

robots and automated machines. They are wrong; if CIM were just technology, there would not have been as<br />

many companies having difficulty implementing it. CIM is the management <strong>of</strong> technology rather than a<br />

technology itself. It is the integration <strong>of</strong> people and functions utilizing the computer and communication<br />

networks to transform automation into interconnected manufacturing systems. CIM requires a new perspective<br />

on the part <strong>of</strong> management – maybe even a new philosophy. Top management, manufacturing and industrial<br />

engineers must change their way <strong>of</strong> thinking and develop new skills<br />

2.4.2. Top management commitment<br />

In many companies where CIM does not fail to realize its potential “top management’s commitment and ongoing<br />

support” is cited as a major reason. The magnitude <strong>of</strong> undertaking can be a great problem if there is not major<br />

and absolute commitment by management <strong>of</strong> the necessary time and resources. CIM installation must start from<br />

the top with a commitment to provide the necessary time; money; and other resources needed to make the<br />

changes that CIM requires.<br />

2.4.3. Lack <strong>of</strong> planning<br />

CIM success requires deliberate and careful planning <strong>of</strong> the technical element in conjunction with training from<br />

day one. Lack <strong>of</strong> understanding <strong>of</strong> the technology and suitable infrastructures to support the new technology,<br />

inappropriate matching <strong>of</strong> technology to organizational strengths and weaknesses will all contribute to top<br />

management’s failure to appreciate the promise <strong>of</strong> CIM. Organizational design is an integral part <strong>of</strong> CIM,<br />

promoting or inhibiting the implementation.<br />

2.4.4. Integration challenge<br />

Experts agree that the important issue to be addressed before CIM can become a reality is integration. The<br />

ultimate objective <strong>of</strong> CIM is the integration <strong>of</strong> all parts <strong>of</strong> the organization across the major functional<br />

boundaries. If the company environment is right, CIM can even assist in pulling together teams <strong>of</strong> people to<br />

work on project. To take full advantage <strong>of</strong> CIM’s benefits, the entire manufacturing process from product design<br />

to procurement, production scheduling, management, production and delivery must be integrated.<br />

2.4.5. Organizational structure<br />

CIM requires flexible organizational structure. There is a growing consensus that old fashioned approaches to<br />

manufacturing and rigid corporate rules are a significant barrier to CIM. The majority <strong>of</strong> manufacturing<br />

organizations in this country were designed to support Specialization as opposed to integration.<br />

In summary, the following are the major problems faced by manufacturers that may lead to failure in CIM (or<br />

FMS) implementation.<br />

‣ Inadequate measurement system.<br />

‣ Partially obsolete facilities.<br />

‣ Inadequate database.<br />

‣ User hostility.<br />

‣ Shortage <strong>of</strong> technical skill.<br />

‣ Incompatibility between systems.<br />

‣ Management generation gap.<br />

‣ Changes in management philosophy.<br />

‣ Facilities with mixed processing.<br />

‣ Dynamic volume and mix.<br />

‣ Outdated organization.<br />

‣ Varieties <strong>of</strong> process options.<br />

‣ Loss <strong>of</strong> superior/subordinate support.<br />

431


2.5. Design <strong>of</strong> the CIM System<br />

The following business and manufacturing objectives<br />

Should be considered in the design <strong>of</strong> the CIM system:<br />

‣ To maintain the consistency <strong>of</strong> the quality <strong>of</strong> Products.<br />

‣ To deliver products on time.<br />

‣ To <strong>of</strong>fer more products to customers.<br />

‣ To design products that will improve performance.<br />

‣ To design electronic device that can be made on shop floor.<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2.6. Rising Needs<br />

CIM is the concept <strong>of</strong> a totally automated factory in which all Manufacturing processes are integrated and<br />

controlled by a CAD/CAM system. It enables production planners and schedulers, shop-floor foremen, and<br />

accountants to use the same database as product designers and engineers. It is one <strong>of</strong> the most advanced tools for<br />

improving the economic performances. It is also becoming a fundamental base for designing and building the<br />

next even more advanced generation <strong>of</strong> manufacturing systems presently called as Intelligent Manufacturing<br />

Systems (IMS). It <strong>of</strong>fers a number <strong>of</strong> useful and potential opportunities for improving the competitiveness <strong>of</strong><br />

manufacturing. The motivation for CIM has been based on the perceived need vices that can be made on form<br />

manufacturing industry to respond to changes more rapidly than in the past. CIM has potential applications in the<br />

manufacturing strategies such as agile, lean and virtual enterprises. Therefore, there is a need to investigate the<br />

areas <strong>of</strong> further development, applications and implications <strong>of</strong> CIM in the next generation manufacturing<br />

organizations. Rather than CIM, today's concepts seem to center more on ERP (Enterprise Resources Planning,<br />

but not really restricted to planning) and MES (Manufacturing Execution Systems).<br />

2.7. Working principles<br />

The following working principles may lead towards Implementing CIM for productivity improvement:<br />

‣ Guiding by application, driving by technology, adopting finite targets, stressing the main points, combining<br />

with the situation in India, paying attention to practical results and forming business.<br />

‣ Adopting expert leading mechanism under the leadership <strong>of</strong> Ministry <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>.<br />

‣ Emphasizing on Team Work, which cooperates multidiscipline’s to work and system integration.<br />

‣ Paying attention towards building CIM groups, especially training <strong>of</strong> youth in this subject. Strengthening<br />

international cooperation.<br />

3. Implementing Computer Integrated Manufacturing<br />

3.1. Application Basic Research<br />

The research task on application basic technology is a kind <strong>of</strong> technology-driven research under certain<br />

application background. This task develops necessary explorations, verifications, and new ideas in the concepts,<br />

principles, and methodology suitable for the forward development <strong>of</strong> worldwide CIM science and technology.<br />

This task can be divided into following sub-topics:<br />

‣ Management Information System (MIS)<br />

‣ Design Automation and CAD/CAM Integration<br />

‣ Shop floor Automation<br />

‣ Quality, and others<br />

3.1.1. Proposed Application Basic Research Topics<br />

The subscript is a short list <strong>of</strong> potential topics for further research in the field <strong>of</strong> Computer Integrated<br />

Manufacturing in India<br />

‣ Experiences with the implementation <strong>of</strong> integration in Computer-Integrated Manufacturing Systems (CIMS)<br />

in different countries.<br />

‣ Design methodologies <strong>of</strong> integration systems including architectures and evaluation <strong>of</strong> adaptability.<br />

‣ Object-oriented modeling methods for the design <strong>of</strong> CIMS.<br />

‣ Knowledge-based decision support system for CIM.<br />

‣ Human role in Computer-Integrated Manufacturing<br />

‣ Quality management in CIMS.<br />

‣ Strategic and organizational adaptation <strong>of</strong> Computer-Integrated Manufacturing Systems (CIMS) for<br />

21stcentury manufacturing competitiveness.<br />

‣ Implications <strong>of</strong> lean and agility on CIMS.<br />

‣ Design methodologies for CIM systems including architectures and evaluation <strong>of</strong> adaptability for the lean<br />

and agile manufacturing, and value chain integration.<br />

‣ CIM in a Physically Distributed Manufacturing Environment.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

‣ Enterprise integration and environmental issues as the main objectives in the design and implementation <strong>of</strong><br />

CIMS.<br />

‣ Rapid prototyping, virtual design, manufacturing, enterprise and CIM.<br />

‣ Investment Justification in the future CIMS.<br />

‣ Operations Control (productivity, quality, flexibility, cost and dependability) in the future CIMS.<br />

‣ CIM in Small and Medium Enterprises as the Qualifying Criterion to become a Partner <strong>of</strong> Virtual<br />

Enterprises.<br />

‣ Human factors and CIM in 21st Century management in CIM in 21 st century Manufacturing Environments.<br />

3.2. Pre-Research and Development<br />

This is the kind <strong>of</strong> product pre-research with major study and development for the market requirement after 3 to<br />

5years, on the base <strong>of</strong> product and achievement technology combining with new ideas, concepts, and principles<br />

<strong>of</strong> product developed in the world. Presently, when India has to start from a scratch, this pre-research is also<br />

needed extensively while setting up CIM research labs.<br />

3.3. Applied Engineering<br />

Applied Engineering should be one <strong>of</strong> the important considerations while implementing laboratories concept.<br />

The reasons for setting up applied engineering are listed in the following text:<br />

‣ CIMS is an integration or optimization system <strong>of</strong> people, organization, technology, management, and<br />

administration; therefore it is necessary to master CIM technology completely by typical enterprise<br />

practicing.<br />

‣ The works <strong>of</strong> typical enterprises practicing can guide the carrying out <strong>of</strong> CIMS in other enterprises <strong>of</strong><br />

Pakistan.<br />

‣ The practice <strong>of</strong> applied enterprises and research labs.<br />

‣ Will counter check each other for better results.<br />

4. International Aspects <strong>of</strong> CIM in International Trade Scenario<br />

4.1. The International Role Models<br />

Today, Japan is one <strong>of</strong> the more advanced countries in implementing CIM in the world. Nevertheless, the<br />

implementation <strong>of</strong> CIM in Japan has some differences to that <strong>of</strong> Western countries. Among these companies we<br />

have Hitachi Ltd, Mitsubishi Electric Corporation, Toyota Motor Corporation, Toshiba, Toyo Engineering<br />

Corporation, Omron Corporation, Tokyo Electric Corporation, Fanuc Ltd., Shimizu Corporation and Nippon<br />

denso Corporation. The CIM study concerning Intelligent Manufacturing Systems (IMS) and the basis for<br />

preparation <strong>of</strong> the so-called Future Generation <strong>of</strong> Manufacturing Systems (FGMS) permits a better understanding<br />

<strong>of</strong> Japanese competitiveness using advanced technology. This is an important point when the economies enter in<br />

the global world market, and when Japan is passing to the so-called "Open-CIM", a new CIM generation that<br />

combines the classical CIM and the more advanced technological advantages <strong>of</strong>fered by the advances in<br />

information technology and telecommunications.<br />

4.2. International Cooperation Required<br />

The national and international conferences in India should include CIM as the topic <strong>of</strong> the day for research<br />

papers and discussions. Scholars should be invited to deliver lectures in India from USA, Europe, Australia,<br />

Japan, China, Taiwan, and other capable countries in this subject. We should strive to achieve great successes in<br />

the main cooperative topics and to open up actively the new prospect in order that the international academic<br />

Exchanges become one <strong>of</strong> the important means for promoting the development <strong>of</strong> our CIM technology.<br />

Development <strong>of</strong> regular links with related international societies is an ample need <strong>of</strong> the hour. The list includes<br />

Society <strong>of</strong> Mechanical Engineering-USA, Society <strong>of</strong> Manufacturing Engineering-USA, and Society for<br />

Computer Simulation International-Belgium, International Fuzzy System Association-Canada, and many more.<br />

5. FUTURE DIRECTIONS OF CIM<br />

In today's competitive global market survival <strong>of</strong> any industry depends on its ability to communicate and transfer<br />

the right information at the right time to the right people. Manufacturing cannot escape from this present<br />

requirement. Having an ability to communicate for elective management and manufacturing activities across the<br />

geographical boundaries among the globally.<br />

Distributed resources will significantly benefit manufacturing industries. Today a number <strong>of</strong> global<br />

conglomerates are formed in many facets <strong>of</strong> industry. A virtual enterprise is defined as a network <strong>of</strong><br />

interconnected global conglomerates in this paper. Predicting the future research direction <strong>of</strong> CIM and related<br />

433


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

areas is a difficult task in ever expanding and growing technological development era. However, an attempt is<br />

made to foresee the future direction, which will dominate the researchers ‘mind for the next decade, based on the<br />

current developments in CIM research. Today’s competitive and agility requirements <strong>of</strong> the global market can be<br />

only met by virtual enterprises. To provide a better future in the present market requirements research in virtual<br />

CIM and the application <strong>of</strong> it in worldwide manufacturing industries are beginning to emerge. Application <strong>of</strong><br />

virtual CIM has-been proposed as a necessary step towards the future in manufacturing to face competitive<br />

challenges. However, many development works need to be carried out to face challenges faced by virtual<br />

enterprises. Hence, the research should be further strengthened towards developing a virtual CIM to satisfy the<br />

globalized and distributed manufacturing enterprises <strong>of</strong> today in order to meet the competitive and agility<br />

requirements <strong>of</strong> present market conditions. In a virtual enterprise the integration <strong>of</strong> information is extolled, as<br />

only through information can a virtual organization become meaningful, and only by electing a new generation<br />

<strong>of</strong> information technology can this vision be realized.<br />

6. Conclusion<br />

In summary, CIM is a means <strong>of</strong> using computer systems to integrate a manufacturing enterprise. The scope <strong>of</strong><br />

CIM ranges from product design, process design, product scheduling and control, to advanced integrated<br />

functions within a production facility. It is important that all functions <strong>of</strong> a company be part <strong>of</strong> a CIM plan.<br />

Functions from business planning, strategic planning, and processing to customer should be included. There is no<br />

single Definition <strong>of</strong> CIM because CIM is designed to fit the needs and applications <strong>of</strong> a specific situation. Thus,<br />

each company will implement CIM in a slightly different fashion. The paper tries to enlighten the rising needs<br />

<strong>of</strong>fsetting up industries working on CIM in India <strong>of</strong> 21stcentury. These systems are inevitable to improve<br />

productivity in post WTO scenario.<br />

References<br />

[1] Bedworth, D. D. et al., <strong>19</strong>91. Computer Integrated Design and Manufacturing. New York: McGraw-Hill<br />

International Ed.<br />

[2] Editor I. B. Turksen, <strong>19</strong>87. Computer Integrated Manufacturing-Current Status and Challenges:<br />

NATOASI Series49.<br />

[3] Russell Biekert, <strong>19</strong>98. CIM <strong>Technology</strong>-Fundamentals and Applications<br />

[4] T. C. Chang, R. A. Wysk, and H. P. Wang, <strong>19</strong>98.Computer-Aided Manufacturing. 2nd edition<br />

[5] Tariq Masood, <strong>20</strong>02. Pre-Feasibility Study to implement Computer Integrated Manufacturing in<br />

Pakistan. Lahore:IEEE ISCON-<strong>20</strong>02<br />

[6] NSF, May 21-23, <strong>19</strong>84. Computer-Based Factory Automation. 11th Conference on Production<br />

Automation<br />

[7] G. Boothroyd, <strong>19</strong>92. Assembly Automation and Product Design<br />

[8] B. Selic, G. Gullekson, and P. T. Ward, <strong>19</strong>94. Real-Time Object-Oriented Modeling. Wiley<br />

[9] R. F. Leung, H. C. Leung, and J. F. Hill, <strong>19</strong>95.Multimedia/hypermedia in CIM: state-<strong>of</strong>-the-art review<br />

and research implications (Part I): Computer Integrated Manufacturing Systems. 8(4): 255-260<br />

[10] R. F. Leung, H. C. Leung, and J. F. Hill, <strong>19</strong>95.Multimedia/hypermedia in CIM: state-<strong>of</strong>-the-art review<br />

and research implications (Part II): Computer Integrated Manufacturing Systems. 8(4): 26-268<br />

[11] J. Y. Fuh, C. H. Chang, and M. A. Melkan<strong>of</strong>f, <strong>19</strong>96.The Development <strong>of</strong> an Integrated and Intelligent<br />

CAD/CAPP/CAFP Environment using Logic-Based Reasoning: Computer-Aided Design. 28(3): 217-<br />

232<br />

[12] K. H. Chen, S, J. Chen, L. Lin, and S. W. Chang, <strong>19</strong>98. An Integrated Graphical User Interface (GUI)<br />

for Concurrent Engineering Design <strong>of</strong> Mechanical Parts: Computer Integrated Manufacturing Systems<br />

11(1-2): 91-112<br />

[13] Victor Sandoval, <strong>19</strong>94. Computer Integrated Manufacturing in Japan. Amsterdam: Lab. PL-at<br />

(Manufacturing Engineering) Ecole Centrale Paris ELSEVIER Sc. Pu.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Influence <strong>of</strong> drilling parameters on thrust force in drilling <strong>of</strong> sic and<br />

graphite reinforced aluminium matrix composites by step drill<br />

A. Muniaraj 1, a , Sushil Lal Das 2, b and K. Palanikumarr 3, c<br />

1 Dept. <strong>of</strong> Mechanical Engineering, Sathyabama <strong>University</strong>, Chennai, India.<br />

2 Dept. <strong>of</strong> Mechanical Engineering, Jeppiaar Engineering College, Chennai, India.<br />

3 Dept. <strong>of</strong> Mechanical Engineering, Sri Sai Ram Institute <strong>of</strong> <strong>Technology</strong>, Chennai, India.<br />

a<br />

raniraj5@gmail.com ,<br />

b sushil_das@rediffmail.com and c palanikumar_k@yahoo.com<br />

Abstract<br />

Hybrid metal matrix composites (MMCs) find diverse applications in many engineering fields. applications <strong>of</strong><br />

these composite materials are among the most important developments in materials engineering in recent years.<br />

Metal matrix composites have became the necessary materials in various engineering applications like<br />

aerospace ,marine, automobile and turbine-compressor engineering applications, because <strong>of</strong> their light-weight,<br />

high strength, stiffness and resistance to high temperature. MMCs should continue to focus on two important<br />

aspects, including improving the properties <strong>of</strong> MMCs and finding more economical techniques to produce mmcs.<br />

Machining is a material removal process and therefore is important for the final fabrication stage prior to<br />

application, consequently the development <strong>of</strong> effective machining methods leading to a reduction. In overall cost<br />

<strong>of</strong> component is one <strong>of</strong> the major challenges yet to be solved. Drill geometry is considered the most important<br />

factor that affects drill performance. A major concern in drilling <strong>of</strong> composite materials is the delamination that<br />

occurs in the exit as well as in the entrance planes. The delamination damage caused by the tool thrust is known<br />

as one <strong>of</strong> the major concerns during the drilling process. This paper discusses the influence <strong>of</strong> cutting parameter<br />

on Thrust force <strong>of</strong> when drilling aluminum alloy reinforced with silicon carbide and graphite hybrid metal<br />

matrix composite. The experiments are conducted to study the effect <strong>of</strong> spindle speeds: 1000, <strong>20</strong>00 and 3000<br />

rpm, feed rate: 0.05, 0.10 and 0.15mm/rev and different diameter <strong>of</strong> drill: 4 mm, 8 mm and 12 mm. This study<br />

included dry drilling with TiN coated solid carbide step drills.<br />

Keywords: Hybrid metal matrix composites, Drilling, Step drill, Thrust force<br />

1. Introduction<br />

Metal matrix composites (MMC) are the new class <strong>of</strong> materials and are rapidly replacing conventional materials<br />

in various engineering applications such as the aerospace and automobile industries. Some <strong>of</strong> the typical<br />

applications are bearings, automobile pistons, cylinder liners, piston rings, connecting rods, sliding electrical<br />

contacts, turbocharger impellers, space structures, etc. The performance <strong>of</strong> MMCs is superior to conventional<br />

materials in terms <strong>of</strong> improved physical, mechanical, and thermal properties that include high specific strength<br />

and modulus, low density, high abrasion and wear resistance and high thermal conductivity [1–3]. The most<br />

popular reinforcements are silicon carbide (SiC) and alumina (Al 2 O 3 ). Aluminum, titanium, and magnesium<br />

alloys are commonly used as the matrix phase. The density <strong>of</strong> most <strong>of</strong> the MMCs is approximately one third that<br />

<strong>of</strong> steel,resulting in high-specific strength and stiffness [4].SiCp-reinforced aluminium composites have found<br />

many applications in the aerospace and automotive industry. However, due to hard ceramic reinforcing<br />

components in metal matrix composites (MMCs), they are difficult to machine and attempts to do so frequently<br />

results in accelerated tool wear and premature failure in accelerated tool wear and premature failure [5–7].<br />

Coating is also used on cutting tools to provide improved lubrication at the tool/chip and tool/ tool/workpiece<br />

interfaces and to reduce friction, and consequently reduce the temperatures at the cutting edge. During<br />

machining, coated carbide tools ensure higher wear resistance, lower heat generation and lower cutting forces,<br />

thus enabling them to perform better at higher cutting conditions than their uncoated counterparts. The use <strong>of</strong><br />

coated tools to machine difficult-to-cut materials actually represents state <strong>of</strong> the art machining technology and<br />

today’s machining processes are becoming increasingly demanding upon cutting tool materials. Therefore, the<br />

available literature concentrated on the study <strong>of</strong> wear characteristics <strong>of</strong> various tool materials during machining<br />

aluminium-based composites [8–15]. In drilling <strong>of</strong> composite materials is the delamination that occurs in the exit<br />

as well as in the entrance planes. The delamination is primarily a function <strong>of</strong> feed rate and tool geometry<br />

[16].Numerous studies have examined cases in which delamination in drilling have been correlated to the thrust<br />

force during exit <strong>of</strong> the drill [17]. The delamination zone for twist drill has been shown to be related to the chisel<br />

edge [18].Usually, a step drill is employed to make holes <strong>of</strong> different diameters in a single drilling operation. The<br />

function <strong>of</strong> a step drill in drilling <strong>of</strong> composite materials is similar to the pre-drilled pilot hole that can reduce the<br />

delamination [<strong>19</strong>]. The influences <strong>of</strong> drill size and cutting conditions for step drilling have been studied by [<strong>20</strong>].<br />

Most <strong>of</strong> the changes in the characteristics <strong>of</strong> the thrust force were influenced by the smaller drill <strong>of</strong> the step drill<br />

435


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[<strong>20</strong>]. The step drill performs front-edge cutting before step-edge cutting. The delamination formed in the primary<br />

stage cutting by the front cutting edge can be removed in secondary stage cutting by the step edge.<br />

The aim <strong>of</strong> this paper is to analyze the cutting parameters on thrust force in drilling <strong>of</strong> Al-<br />

15%/SiC-4% Graphite metal matrix composites by tin coated solid carbide step drill <strong>of</strong> 4 mm, 8 mm and 12<br />

mm diameter with different spindle speed and feed conditions.. Taguchi’s orthogonal array is used for<br />

conducting the experiments. The experimental results are analysed and presented in this study.<br />

2. Experimental procedure<br />

2.1 Preparation <strong>of</strong> the composite<br />

In this study dry drilling tests were performed on a (CNC) ARIX vertical machining centre. The hybrid<br />

composite comprises 6061 aluminum alloy as matrix and SiC and Graphite are reinforcements. Aluminum alloy<br />

reinforced with 15% volume fraction <strong>of</strong> SiC and 4 % volume fraction <strong>of</strong> graphite with a particle size <strong>of</strong> 50µm<br />

was used as a reinforcement material. The composite were fabricated by stir casting method. The melting was<br />

carried out in electrical resistance furnace. The aluminium scraps <strong>of</strong> 6061 were first preheated at 600°C before<br />

melting. The SiC and graphite were also preheated at the required temperature. The preheated aluminum scraps<br />

were first heated above liquidus temperature to melt them completely, They were then slightly cooled below<br />

the liquidus temperature to maintain the slurry in semi-solid state. The Preheated reinforcement were<br />

mixed manually then composite slurry were heated to a liquid state, The final temperature was controlled to<br />

be within 800° C and pouring temperature was controlled to be around 8<strong>20</strong>° C. The melt was poured in to steel<br />

moulds and allowed to cool to obtain 110mm x110mm x 5 mm size <strong>of</strong> plate. Table 1 shows the chemical<br />

composition <strong>of</strong> the Al 6061 alloy used. The fabricated Al-15%SiC-4%Gr composite chemical composition is<br />

presented in Table 2. The microstructure <strong>of</strong> the composite is shown in Fig. 1.<br />

Aluminum<br />

Graphite<br />

SiC<br />

Fig 1. Microstructure <strong>of</strong> Al-15%SiC-4%Graphite<br />

Table 1. Chemical composition [wt %] <strong>of</strong> Al 6061 alloy<br />

Al Mg Si Iron Cu Zn Ti Mn Cr others<br />

Balance 0.8-1.2 0.4-0.8 Max0.7 0.15-0.40 Max 0.25 Max 0.15 Max0.15 0.04-0.35 0.05<br />

Table 2. chemical compositions [wt %] <strong>of</strong> Al -15%SiC-4%Graphite<br />

Fe Si Mn Cu Cr Ti V Pb Mg Al<br />

0.05 0.781 0.305 0.<strong>20</strong>7 0.03 0.018 0.005 0.0<strong>19</strong> 0.749 Remainder<br />

436


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2.2 Machining<br />

Table 3 shows the various experimental parameters and their levels. The experiments were performed at different<br />

feed rates <strong>of</strong> 0.05 mm/rev, 0.10 mm/rev and 0.15 mm/rev, speeds <strong>of</strong> 1000 rpm,<strong>20</strong>00 rpm, and 3000 rpm and<br />

diameters <strong>of</strong> 4 mm, 8 mm and 12 mm as given in Table 4. The drilling tests are performed on ARIX-CNC<br />

machining center manufactured by ARIX CNC machine Co. Ltd., Taiwan. Coolant was not used in all <strong>of</strong> the<br />

drilling tests. The drill bits used for the experiments are presented in Fig. 2.<br />

Table 3 Experimental parameters and their values<br />

Parameters<br />

Drill Type<br />

Drill Size<br />

Values<br />

Solid carbide TiN coated step drill<br />

Ø 4mm, Ø 8mm and Ø 12mm<br />

Feed rate (mm/rev) 0.05,0.10,0.15<br />

Spindle speed (rpm) 1000,<strong>20</strong>00,3000<br />

Table 4. Variable factor levels<br />

S. No Feed rate, mm/rev Spindle speed, rpm Drill size, mm<br />

1 0.05 1000 4<br />

2 0.05 1000 8<br />

3 0.05 1000 12<br />

4 0.05 <strong>20</strong>00 4<br />

5 0.05 <strong>20</strong>00 8<br />

6 0.05 <strong>20</strong>00 12<br />

7 0.05 3000 4<br />

8 0.05 3000 8<br />

9 0.05 3000 12<br />

10 0.10 1000 4<br />

11 0.10 1000 8<br />

12 0.10 1000 12<br />

13 0.10 <strong>20</strong>00 4<br />

14 0.10 <strong>20</strong>00 8<br />

15 0.10 <strong>20</strong>00 12<br />

16 0.10 3000 4<br />

17 0.10 3000 8<br />

18 0.10 3000 12<br />

<strong>19</strong> 0.15 1000 4<br />

<strong>20</strong> 0.15 1000 8<br />

21 0.15 1000 12<br />

22 0.15 <strong>20</strong>00 4<br />

23 0.15 <strong>20</strong>00 8<br />

24 0.15 <strong>20</strong>00 12<br />

25 0.15 3000 4<br />

26 0.15 3000 8<br />

27 0.15 3000 12<br />

The thrust forces during drilling were measured with a Piezoelectric-dynamometer mean while the signals <strong>of</strong> the<br />

thrust force from the dynamometer was amplified and fed through a data–acquisition system for electronic<br />

storage. The data-acquisition System is based on the dynaware s<strong>of</strong>tware. The experimental setup is shown in Fig.<br />

3.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig 2 Drills used for the experimentation<br />

Drill Head<br />

Composite<br />

[a]<br />

[b]<br />

Fig 3 Experimental set-up [a] Machine center and data acquisition system [b] Experimental device<br />

3. Taguchi method<br />

The Taguchi method can economically satisfy the needs <strong>of</strong> problem solving and product/process design<br />

optimization in industry.For conducting the experiments Taguchi method is used. Taguchi method is<br />

experimental design tool used in analysing and designing <strong>of</strong> experimental results in manufacturing engineering.<br />

Taguchi method uses a special design <strong>of</strong> orthogonal arrays to study the entire parameter space. Taguchi method<br />

is used for analysing the main effects and interaction effects in experimental analysis and is a powerful tool,<br />

which provides a simple, efficient and systematic approach to determine optimal cutting parameters. Compared<br />

to the conventional approach <strong>of</strong> experimentation, this method reduces drastically the number <strong>of</strong> experiments that<br />

are required to model the response functions [21, 22].<br />

Table 5 shows the factors to be studied and the assignment <strong>of</strong> the factors to the corresponding Levels. The array<br />

chosen was the L 27 [3 13 ].which has 27 rows corresponding to the number <strong>of</strong> tests (26 degree <strong>of</strong> freedom) with<br />

13 columns at three levels. The factors and the interactions are assigned to the columns. The plan <strong>of</strong> Experiments<br />

made <strong>of</strong> 27 tests in which first column is assigned to feed rate [f], the second column to spindle speed [n], the<br />

fifth column to drill diameter [d] and the remaining columns were used interaction and other effects.<br />

438


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 5 Orthogonal array <strong>of</strong> L 27 [3 13 ]<br />

Trial 1 2 3 4 5 6 7 8 9 10 11 12 13<br />

1 1 1 1 1 1 1 1 1 1 1 1 1 1<br />

2 1 1 1 1 2 2 2 2 2 2 2 2 2<br />

3 1 1 1 1 3 3 3 3 3 3 3 3 3<br />

4 1 2 2 2 1 1 1 2 2 2 3 3 3<br />

5 1 2 2 2 2 2 2 3 3 3 1 1 1<br />

6 1 2 2 2 3 3 3 1 1 1 2 2 2<br />

7 1 3 3 3 1 1 1 3 3 3 2 2 2<br />

8 1 3 3 3 2 2 2 1 1 1 3 3 3<br />

9 1 3 3 3 3 3 3 2 2 2 1 1 1<br />

10 2 1 2 3 1 2 3 1 2 3 1 2 3<br />

11 2 1 2 3 2 3 1 2 3 2 2 3 1<br />

12 2 1 2 3 3 1 2 3 1 1 3 1 2<br />

13 2 2 3 1 1 2 3 2 3 1 3 1 2<br />

14 2 2 3 1 2 3 1 3 1 2 1 2 3<br />

15 2 2 3 1 3 1 2 1 2 3 2 3 1<br />

16 2 3 1 2 1 2 3 3 1 2 2 3 1<br />

17 2 3 1 2 2 3 1 1 2 3 3 1 2<br />

18 2 3 1 2 3 1 2 2 3 1 1 2 3<br />

<strong>19</strong> 3 1 3 1 1 3 2 1 3 2 1 3 2<br />

<strong>20</strong> 3 1 3 1 2 1 3 2 1 3 2 1 3<br />

21 3 1 3 1 3 2 1 3 2 1 3 2 1<br />

22 3 2 1 2 1 3 2 2 1 3 3 2 1<br />

23 3 2 1 2 2 1 3 3 2 1 1 3 2<br />

24 3 2 1 2 3 2 1 1 3 2 2 1 3<br />

25 3 3 2 3 1 3 2 3 2 1 2 1 3<br />

26 3 3 2 3 2 1 3 1 3 2 3 2 1<br />

27 3 3 2 3 3 2 1 2 1 3 1 3 2<br />

A B AXB AXB C AXC AXC BXC D AXD BXC BXD CXD<br />

4 Result and Discussion<br />

4. 1 Thrust force<br />

Figure 4 (a), (b) and (c) shows the influence <strong>of</strong> feed rate on the thrust force in drilling <strong>of</strong> Al/SiC/Graphite hybrid<br />

metal matrix composites without use <strong>of</strong> coolant. The drilling tests are performed at different cutting speed, feed<br />

rate. Spindle speed and feed rate are the two major drilling parameters that are considered in the experiments<br />

Figure 4(a) shows the influence feed rate on thrust force when drilling at spindle speed 1000, <strong>20</strong>00 and 3000<br />

rpm. The result indicated that thrust force increase with increase in feed rate. From the figure it can be observed<br />

that the thrust force is (57.50 N) lower at higher cutting speed (3000 rpm) than lower cutting speed (1000 rpm).<br />

439


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

<strong>20</strong>0<br />

160<br />

Thrust force [N]<br />

1<strong>20</strong><br />

80<br />

40<br />

0<br />

0.05 0.1 0.15 0.2<br />

Feed [mm/rev]<br />

1000 rpm <strong>20</strong>00 rpm 3000 rpm<br />

Fig 4 (a) Variation <strong>of</strong> Thrust force with feed rate at different drill Speed<br />

Figure 4 (b) shows the influence <strong>of</strong> feed rate and the drill diameter on thrust force in drilling <strong>of</strong> Al/SiC<br />

metal matrix hybrid composites. The feed rate verses thrust force graph shows consistently thrust force is lower<br />

at lower diameter <strong>of</strong> drill than at higher diameter <strong>of</strong> drill. Thrust force is low (65 N) at low feed rate, i.e.0.05 mm<br />

/ rev and thrust force is high (153.35 N) at high feed rate, i.e.0.15mm / rev. The reason being the increase <strong>of</strong> feed<br />

rate increases the load on the tool subsequently increases the thrust force in drilling <strong>of</strong> hybrid composites.<br />

<strong>20</strong>0<br />

160<br />

Thrust force [N]<br />

1<strong>20</strong><br />

80<br />

40<br />

0<br />

0.05 0.1 0.15 0.2<br />

Feed [mm/rev]<br />

4 mm 8 mm 12 mm<br />

Fig 4 (b) Variation <strong>of</strong> Thrust force with feed rate at different drill diameter<br />

Figure 4 (c) show the influence <strong>of</strong> cutting speed and the drill diameter on thrust force. The speed Vs thrust force<br />

graph shown thrust force gradually decreases by increasing cutting speed from 1000 rpm to 3000 rpm<br />

during drilling <strong>of</strong> Al / SiC/ graphite hybrid metal matrix composite. The feed rate is the predominant factor and<br />

as the feed rate increases the thrust force increases for the composite.<br />

Davim and Baptista [32]. were under the opinion that regardless <strong>of</strong> the tool material and work material, the<br />

thrust is highly dependent on feed rate, while cutting speed was found to have insignificant influence on the<br />

degree <strong>of</strong> drilling forces. Charles Lane [33] was under the opinion that the feed rate was determined to be the<br />

most significant parameter affecting the drill life and tool forces. increasing the feed rate increases cutting force<br />

significantly.<br />

440


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

<strong>20</strong>0<br />

160<br />

Thrust force [N]<br />

1<strong>20</strong><br />

80<br />

40<br />

0<br />

1000 <strong>20</strong>00 3000 4000<br />

Speed [rpm]<br />

4. 2 SEM image investigation<br />

4 mm 8 mm 12 mm<br />

Fig 4 (c) Variation <strong>of</strong> Thrust force with speed at different drill diameter<br />

Fig 5 SEM image <strong>of</strong> showing rough drilled surface at<br />

a feed rate <strong>of</strong> 0.05 mm/rev and a speed <strong>of</strong> 1000 rpm<br />

Fig 6 SEM image <strong>of</strong> showing fine drilled surface at<br />

a feed rate <strong>of</strong> 0.05 mm/rev and a speed <strong>of</strong> <strong>20</strong>00 rpm<br />

Fig 5 shows the SEM image <strong>of</strong> rough drilled surface <strong>of</strong> Al-15% SiC-4% Graphite hybrid metal matrix<br />

composites under cutting conditions <strong>of</strong> feed rate 0.05 mm/rev and spindle speed 1000 rpm. In this case, it can be<br />

seen that feed mark is visible on the surface <strong>of</strong> the composites. Surface layer is highly sheared. Alumina and<br />

silicon particles are severely fragment and pulled out <strong>of</strong> the surface during drilling operations; the particles rub<br />

against the tool causing the surface finish as shown in figure. Fig 6 shows the SEM image <strong>of</strong> fine drilled surface<br />

<strong>of</strong> Al-15% SiC-4% Graphite hybrid metal matrix composites under cutting conditions <strong>of</strong> feed rate 0.05 mm/rev<br />

and spindle speed <strong>20</strong>00 rpm, the contact duration <strong>of</strong> the tool with work piece material is reduced, hence the<br />

tool wear is decreased, feed mark is not visible, Surface finish is comparatively better at a speed <strong>of</strong> <strong>20</strong>00 rpm<br />

and 0.05 mm/rev.<br />

CONCLUSIONS<br />

The experiments are conducted on computer numerical control machining centre to study the influence <strong>of</strong><br />

cutting parameters on drilling <strong>of</strong> hybrid metal matrix composites. Based on the experimental results and analysis<br />

the following conclusions are drawn:<br />

1. Feed rate is the main factor, which influence the thrust force in drilling <strong>of</strong> Al/SiC/Gr hybrid metal matrix<br />

composite and as the feed rate.<br />

441


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. Thrust forces vary with feed, feed rate affects drilling forces but cutting speed has not much effect over the<br />

range <strong>of</strong> spindle speeds.<br />

3. Thrust forces decreases with increase in cutting speed and vice versa.<br />

4. Lower speed shows comparatively more thrust force than higher spindle speed.<br />

5. Due to the abrasive action <strong>of</strong> the SiC particles, the coating on the tool material is removed<br />

REFERENCES<br />

1. Suresh S, Mortensen A, Needleman A (<strong>19</strong>93) Fundamentals <strong>of</strong> metal-matrix composites. Butterworth-Heine<br />

-mann, Stoneham, MA.<br />

2. Taya M, Arsenault RJ (<strong>19</strong>89) Metal-matrix composites-thermo mechanical behavior. Pergamon Press, Newy<br />

York.<br />

3. Ibrahim A,Mohammed FA, Lavernia EJ (<strong>19</strong>91)Metal-matrix composites-a review.J Mater Sci 26:1137–1157.<br />

4. QuanY,Ye B (<strong>20</strong>03) The effect <strong>of</strong> machining on the surface properties <strong>of</strong> SiC/Al composites. J Mater Process<br />

Process Technol 138:464–467.<br />

5. M.K. Brun, M. Lee, F. Gorsler, Wear characteristics <strong>of</strong> various hard materials for machining SiCp reinforced<br />

aluminium alloy, Wear 104 (<strong>19</strong>85) 21–29.<br />

6. A.R.Chambers, S.E.Stephens, Machining <strong>of</strong> Al–5Mg reinforced with 5 vol. % Saffil and 15 vol.% SiC fibres,<br />

J. Mater. Sci. Eng. A 135 (<strong>19</strong>90) 287–290.<br />

7. M. El-Gallab, M. Sklad, Machining <strong>of</strong> AlySiCp metal matrix composites part-I: tool performance, J. Mater.<br />

Process. Technol. 83 (<strong>19</strong>98) 151–158.<br />

8. Y.M. Quan, Z.H. Zhou, B. Y. Ye, Cutting process and chip appearance <strong>of</strong> Al matrix composites reinforced<br />

by SiC particles,J. Mater. Process. Technol. 91 (<strong>19</strong>99) 231–235.<br />

9. Q. Yanming, Z. Zehna, Tool wear and its mechanism for cutting SiCp reinforced Al matrix composites, J.<br />

Mater. Process. Technol. 100 (<strong>20</strong>00) <strong>19</strong>4–<strong>19</strong>9.<br />

10. N.P. Hung, F.Y.C. Boey, K.A. Khor, C.A. Oh, H.F. Lee, Machinability <strong>of</strong> cast and powder formed alumini<br />

-um alloys reinforced with SiC particles, J. Mater. Process. Technol. 48(1–4) (<strong>19</strong>95) 291–297.<br />

11. J.T. Lin, D. Bhattacharyya, C. Lane, Machinability <strong>of</strong> a silicon carbide reinforced aluminium metal matrix<br />

composite, Wear 181 (<strong>19</strong>95) 883–888.<br />

12. L.A. Looney, J .M. Monaghan, P. O’Reilly, D.M.R .Taplin, The turning <strong>of</strong> an AlySiC metal composite, J.<br />

Mater. Process.Technol. 33 (<strong>19</strong>92) 453–468.<br />

13. X. Li, W.K.H. Seah, Tool wear acceleration in relation to workpiece reinforcement percentage in cutting <strong>of</strong><br />

metal matrix composites, Wear 247 (<strong>20</strong>01) 161–171.<br />

14. Q. Quigley, J. Monaghan, P. O’Reilly, Factors affecting the machinability <strong>of</strong> an AlySiC metal matrix<br />

composites, J. Mater.Process. Technol. 43 (<strong>19</strong>94) 21–36.<br />

15. K. Weinert, D.Biermann, Turning <strong>of</strong> fibre and particulate reinforced aluminium, in: Processing <strong>of</strong> Internati<br />

-onal Conference.<br />

16. Jain S, Yang DCH (<strong>19</strong>93) Effects <strong>of</strong> feedrate and chisel edge on delamination in composite drilling. ASME<br />

J Eng Ind 115:398–405.<br />

17. Sakuma K, Yokoo Y, Seto M (<strong>19</strong>84) Study on drilling <strong>of</strong> reinforced plastics-relation between tool material<br />

and wear behavior. Bull JSME 27(228):1237–1244.<br />

18. Won MS, Dharan CKH (<strong>20</strong>02) Chisel edge and pilot hole effects in drilling composite laminates. ASME<br />

Manuf Sci Eng 124:242–247.<br />

<strong>19</strong>. Tsao CC, Hocheng H (<strong>20</strong>03) The effect <strong>of</strong> chisel length and associated pilot hole on delamination when<br />

drilling composite materials. Int J Mach Tools Manuf 43(11):1087–1092.<br />

<strong>20</strong>. Xia RS, Mahdavian SM (<strong>20</strong>05) Experimental studies <strong>of</strong> step drills and establishment <strong>of</strong> empirical equations<br />

for the drilling process.Int J Mach Tools Manuf 45(2):235–240.<br />

21. Yang WH, Tang YS (<strong>19</strong>98) Design optimization <strong>of</strong> cutting parameters for turning operations based on the<br />

taguchi method. J Mater Process Technol 84, 122-129.<br />

22. Taguchi G (<strong>19</strong>90) Introduction to quality engineering. Asian Productivity organization, Tokyo.<br />

23. Davim, J.P., Baptista, A.M., <strong>20</strong>01. Cutting force, tool wear and surface finishing drilling Metal matrix<br />

composites .proc.Inst.Mech eng. E 215, 177-183.<br />

24. Lane. C., (<strong>19</strong>93).International conference on advanced composite materials. In; Chandra, T., Dhingra, A.K,<br />

(Eds), The Minerals, Metals and Materials society, pp.1113-1117.<br />

442


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

MODELLING FOR MACHINING SPEED IN WEDM OF WC-5.3%CO<br />

COMPOSITE USING RESPONSE SURFACE METHODOLOGY<br />

Kamal Jangra 1* and Sandeep Grover 2<br />

1 Asst Pr<strong>of</strong>essor,Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> UST, Faridabad, India-121006.<br />

2 Pr<strong>of</strong>essor ,Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> UST,Faridabad, India-121006<br />

1* E-mail: kamaljangra84@gmail.com<br />

Abstract<br />

Wire electrical discharge machining (WEDM) is a well known process for machining hard metal alloys and<br />

metal matrix composites. In this paper, four important WEDM parameters namely pulse-on time, pulse-<strong>of</strong>f time,<br />

servo voltage and wire feed rate have been investigated and modelled for machining speed <strong>of</strong> WC-5.3%Co<br />

composite during rough cutting operation on WEDM. Using response surface methodology, face centered central<br />

composite design has been adopted to perform the experiments. Achieving higher machining speed is the main<br />

objective <strong>of</strong> rough cutting operation. Therefore, using desirability function, parameters have been predicted for<br />

maximizing the machining speed.<br />

Keywords: WEDM, Tungsten carbide, Machining speed, Response surface methodology<br />

1. Introduction<br />

Tungsten carbide (WC-Co) composite is a powder metallurgy product which posses’ high hardness even at<br />

elevated temperatures which makes it suitable for dies and tool industries. Because <strong>of</strong> high hardness (70-90<br />

HRC) and melting point ˃2800 (<br />

0 C) (Scussel, <strong>19</strong>92), tungsten carbide composite is difficult to machine with<br />

conventional manufacturing processes. Wire electrical discharge machining (WEDM) is a special form <strong>of</strong><br />

electrical discharge machining (EDM) which has the capability to produce intricate shapes and pr<strong>of</strong>iles in hard<br />

metal alloys and metal matrix composites, with high degree <strong>of</strong> accuracy, without making any mechanical contact<br />

(Jangra et al. <strong>20</strong>10). In WEDM, surface material is eroded by melting or evaporation due to large amount <strong>of</strong> heat<br />

generated between the work material and downward moving wire electrode as shown in Figure 1.<br />

Figure 1 Schematic Representation <strong>of</strong> WEDM<br />

In WEDM, achieving higher machining speed or material removal rate is prime objective during rough<br />

cutting operation. However, due to large number <strong>of</strong> parameters and their wide varying range in WEDM,<br />

prediction <strong>of</strong> optimal machining parameters is difficult. In order to achieve an efficient process planning in<br />

machining <strong>of</strong> WC-Co composite into desired shape, need <strong>of</strong> accurate machinability data arises. Jangra et al.<br />

(<strong>20</strong>11a) evaluated the effect <strong>of</strong> various factors and their sub-factors on machinability <strong>of</strong> WC-Co composite with<br />

WEDM using digraph and matrix method. They broadly grouped these factors into work material, machine tool,<br />

tool electrode, cutting conditions and geometry to be machined. Machinability was measured in terms <strong>of</strong> material<br />

removal rate (MRR). They concluded that the machine tool is the most influencing factor affecting the<br />

machinability <strong>of</strong> WC-Co composite. Influence <strong>of</strong> composition and grain size <strong>of</strong> WC-based cermets on<br />

machinability by WEDM has been studied by Lauwers et al. (<strong>20</strong>06). It was shown that the cutting rate decreases<br />

with increasing grain size and cobalt percentage, which can be explained mainly by the change in thermal<br />

conductivity <strong>of</strong> the material. Jangra et al., (<strong>20</strong>11b) investigated the effect <strong>of</strong> peak current, pulse on time, pulse-<br />

443


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

<strong>of</strong>f time, servo voltage, dielectric flow rate, wire feed rate, wire tension and taper angle on machinability <strong>of</strong><br />

tungsten carbide composite with WEDM.<br />

According to Garg et al., (<strong>20</strong>10), most <strong>of</strong> the available literatures on machinability <strong>of</strong> WC-Co composite<br />

deals with die sinking EDM (Mahdavinejad, <strong>20</strong>05; Kanagrajan et al., <strong>20</strong>08; Kung et al., <strong>20</strong>09) and more work yet<br />

to be tried on WEDM. Therefore, in present work, four important WEDM parameters have been investigated and<br />

modelled for predicting the machining speed <strong>of</strong> WC-5.3%Co composite on WEDM.<br />

2. Experimentation<br />

In present work, experiments were performed on 5-axis sprint cut (ELPLUS-40) WEDM manufactured by<br />

Electronic Machine Tool Ltd, India. The range <strong>of</strong> variable parameters in present machine tool are as follows:<br />

discharge current, 10-230 ampere; pulse-on time, 100-131machine unit (mu); pulse-<strong>of</strong>f time,14-63mu; wire<br />

speed, 1-15 m/min.; wire tension, 1-15N; servo voltage, 10-90V; dielectric flow rate 0-12 litre per minute<br />

Tungsten carbide composite having low cobalt concentration (5.3%) has been taken as a work material in the<br />

form <strong>of</strong> rectangular block <strong>of</strong> thickness 13mm. The density and hardness <strong>of</strong> WC-5.3%Co composite was<br />

measured as 14.95g/cm 3 and 77 HRC respectively. Machining speed (MS) was measured as surface area<br />

removed per minute (mm 2 /min). It was obtained by multiplying the workpiece thickness (13mm) with linear<br />

cutting speed (mm/min) displaying on machine tool monitor screen.<br />

Four variables namely pulse-on time, pulse-<strong>of</strong>f time, servo voltage and wire feed rate have been considered.<br />

Discharge current was kept at optimum value <strong>of</strong> 90amp which has been taken on the basis <strong>of</strong> preliminary<br />

experiments (Jangra et al., <strong>20</strong>11). Dielectric flow rate was kept at 12LM -1 . High flow rate results in quick and<br />

complete flushing <strong>of</strong> melted debris out <strong>of</strong> the spark gap. Zinc coated brass wire <strong>of</strong> diameter 0.25mm was used as<br />

an electrode because <strong>of</strong> its good capability to sustain high discharge energy. Vertical cutting was performed at<br />

zero wire <strong>of</strong>fset. Wire tension was fixed at 10N.<br />

Table 1 Process parameters and their levels<br />

Symbol Parameters Units Levels<br />

(-1) (0) (+1)<br />

A Pulse-on time (Ton) Machine unit (mu) 108 115 122<br />

B Pulse-<strong>of</strong>f time (T<strong>of</strong>f) Machine unit (mu) 30 40 50<br />

C Servo Voltage (SV) Volt <strong>20</strong> 30 40<br />

D Wire Feed rate (WF) m/min. 4 6 8<br />

Based upon the input factors and their levels as listed in Table 1, the experimental plan was designed on the<br />

basis <strong>of</strong> standard RSM design called face centered Central Composite Design (CCD). This design consists <strong>of</strong><br />

factorial portion with all factors at three levels, eight star points and six central points. The star points are at the<br />

face <strong>of</strong> the cube portion on the design which corresponds to α value <strong>of</strong> 1. The centre points, as implied by the<br />

name, are points with all levels set to coded level 0, the midpoint <strong>of</strong> each factor range. Table 2 shows the<br />

experimental layout and results obtained for machining speed.<br />

Normal Plot <strong>of</strong> Residuals<br />

99<br />

Normal % Probability<br />

95<br />

90<br />

80<br />

70<br />

50<br />

30<br />

<strong>20</strong><br />

10<br />

5<br />

1<br />

-3.00 -2.00 -1.00 0.00 1.00 2.00 3.00<br />

Internally Studentized Residuals<br />

Figure 2 Normal probability plot <strong>of</strong> residuals for MS<br />

444


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 2 Test conditions in face centered central composite design for four parameters<br />

Trial No. A (Ton) B (T<strong>of</strong>f) C (SV) D (WF) MS<br />

(mm 2 /min.)<br />

Coded Actual Coded Actual Coded Actual Coded Actual<br />

1 -1 108 -1 30 -1 <strong>20</strong> -1 4 16.691<br />

2 1 122 -1 30 -1 <strong>20</strong> -1 4 27.97<br />

3 -1 108 1 50 -1 <strong>20</strong> -1 4 6.52<br />

4 1 122 1 50 -1 <strong>20</strong> -1 4 14.22<br />

5 -1 108 -1 30 1 40 -1 4 16.59<br />

6 1 122 -1 30 1 40 -1 4 27.88<br />

7 -1 108 1 50 1 40 -1 4 6.29<br />

8 1 122 1 50 1 40 -1 4 14.12<br />

9 -1 108 -1 30 -1 <strong>20</strong> 1 8 18.57<br />

10 1 122 -1 30 -1 <strong>20</strong> 1 8 32.58<br />

11 -1 108 1 50 -1 <strong>20</strong> 1 8 8.4<br />

12 1 122 1 50 -1 <strong>20</strong> 1 8 16.36<br />

13 -1 108 -1 30 1 40 1 8 16.53<br />

14 1 122 -1 30 1 40 1 8 30.54<br />

15 -1 108 1 50 1 40 1 8 5.12<br />

16 1 122 1 50 1 40 1 8 14.32<br />

17 -1 108 0 40 0 30 0 6 12.01<br />

18 1 122 0 40 0 30 0 6 22.25<br />

<strong>19</strong> 0 115 -1 30 0 30 0 6 24.8<br />

<strong>20</strong> 0 115 1 50 0 30 0 6 12.22<br />

21 0 115 0 40 -1 <strong>20</strong> 0 6 <strong>19</strong>.04<br />

22 0 115 0 40 1 40 0 6 17.97<br />

23 0 115 0 40 0 30 -1 4 17.99<br />

24 0 115 0 40 0 30 1 8 <strong>19</strong>.03<br />

25 0 115 0 40 0 30 0 6 18.35<br />

26 0 115 0 40 0 30 0 6 18.69<br />

27 0 115 0 40 0 30 0 6 18.87<br />

28 0 115 0 40 0 30 0 6 18.48<br />

29 0 115 0 40 0 30 0 6 18.54<br />

30 0 115 0 40 0 30 0 6 18.08<br />

3. Modelling <strong>of</strong> WEDM Parameters<br />

Using the experimental data, regression equations has been developed for correlating the machining speed (MS)<br />

and input WEDM parameters. Design expert (DX8), a statistical tool, has been utilised to analyse the<br />

experimental data. Using Analysis <strong>of</strong> Variance (ANOVA), quadratic Vs two factors interaction (2FI) model has<br />

been suggested for machining speed. Table 3 shows the summary <strong>of</strong> fitted model.<br />

Adequacy <strong>of</strong> the results can be analysed by residual plots (Kanlayasiria and Boonmung, <strong>20</strong>07). Figure 2<br />

shows that the residuals are normally distributed about a straight line and there is no problem with the observed<br />

results.<br />

The final regression equation for performance measures are obtained as follows:<br />

The material speed (MS):<br />

Regression equation in terms <strong>of</strong> coded factors:<br />

MS= 18.51657 + 5.<strong>19</strong>55A - 6.3651B - 0.6106C + 0.73217D - 1.1187AB + 0.4425AD - 0.3774BD<br />

- 0.5549CD -1.4015A 2 (1)<br />

445


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Regression equation in terms <strong>of</strong> actual factors:<br />

MS= - 478.77 + 7.73315A + 1.3575B + 0.01398C – 1.6175D - 0.01598AB + 0.31612AD - 0.01887BD<br />

- 0.02775CD - 0.0286A 2 (2)<br />

Source<br />

Sum <strong>of</strong><br />

Squares<br />

Degree <strong>of</strong><br />

freedom<br />

Table 3 ANOVA table for fitted model<br />

Mean<br />

Square<br />

F-value<br />

p-value<br />

a) For MRR<br />

Model 1277.4 14 91.24 771.23 ˂0.0001 Significant<br />

Residual 1.7746 15 0.1183<br />

Lack <strong>of</strong> fit 1.4007 10 0.1401 1.873 0.2532 Not significant<br />

Pure error 0.3738 5 0.0747<br />

Cor. total 1279.17 29<br />

Standard deviation = 0.34396; R 2 = 0.9986; R 2 (Adj.) = 0.9973<br />

4. Optimization Using Desirability Function<br />

Derringer and Suich (<strong>19</strong>80) described a multiple response method called desirability. It is an attractive and user<br />

friendly method for industry for optimization <strong>of</strong> multiple response characteristics problems. The method makes<br />

use <strong>of</strong> an objective function, D(X), called the desirability function and transforms an estimated response into a<br />

scale free value (d i ) called desirability. The desirable ranges are from zero to one (least to most desirable<br />

respectively). The factor settings with maximum total desirability are considered to be the optimal parameter<br />

conditions. The simultaneous objective function is a geometric mean <strong>of</strong> all transformed responses:<br />

D=<br />

1/<br />

( d × d × d × <br />

) n<br />

1 2 3<br />

× d n<br />

=<br />

⎛<br />

⎜<br />

⎝ ∏<br />

=<br />

n<br />

d i<br />

i 1<br />

Where; n is the number <strong>of</strong> responses in the measure. If any <strong>of</strong> the responses or factors falls outside the<br />

desirability range, the overall function becomes zero.<br />

Desirability is an objective function that ranges from zero outside <strong>of</strong> the limits to one at the goal. The<br />

numerical optimization finds a point that maximizes the desirability function. The characteristics <strong>of</strong> a goal may<br />

be altered by adjusting the weight or importance. For several responses and factors, all goals get combined into<br />

one desirability function. The meanings <strong>of</strong> the goal parameters are:<br />

Maximum:<br />

d i = 0 if response < low value<br />

0 ≤ d i<br />

≤ 1 as response varies from low to high<br />

d i = 1 if response > high value<br />

Minimum:<br />

d i = 1 if response < low value<br />

1 ≥ d i<br />

≥ 0 as response varies from low to high<br />

d i = 0 if response > high value<br />

Target:<br />

d i<br />

0<br />

= 0 if response < low value<br />

≤ d i<br />

≤ 1 as response varies from low to target<br />

1 ≥ d i<br />

≥ 0 as response varies from target to high<br />

d i = 0 if response > high value<br />

Range:<br />

d i = 0 if response < low value<br />

di<br />

= 1 as response varies from low to high<br />

di = 0 if response > high value<br />

⎞<br />

⎟<br />

⎠<br />

1/ n<br />

(3)<br />

446


( ∏d i<br />

) n<br />

The d i<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

for "in range" are included in the product <strong>of</strong> the desirability function "D", but are not counted in<br />

determining "n": D = .<br />

If the goal is none, the response will not be used for optimization.<br />

Table 4 Range <strong>of</strong> Input Parameters and MS for Desirability<br />

Constraint<br />

Name<br />

Goal<br />

Lower<br />

Limit<br />

Upper<br />

Limit<br />

Lower<br />

Weight<br />

Upper<br />

Weight Importance<br />

Pulse-on Time(Ton) is in range 108 122 1 1 3<br />

Pulse-<strong>of</strong>f Time(T<strong>of</strong>f) is in range 30 50 1 1 3<br />

Servo Voltage (SV) is in range <strong>20</strong> 40 1 1 3<br />

Wire feed rate (WF) is in range 4 8 1 1 3<br />

Machining Speed Maximize 5.12 32.58 1 1 3<br />

0.989<br />

1.000<br />

0.800<br />

Desirability<br />

0.600<br />

0.400<br />

0.<strong>20</strong>0<br />

0.000<br />

50.00<br />

45.00<br />

B: T<strong>of</strong>f<br />

40.00<br />

35.00<br />

30.00<br />

122.00<br />

1<strong>20</strong>.00<br />

118.00<br />

116.00<br />

114.00<br />

112.00<br />

A:Ton<br />

110.00<br />

108.00<br />

Figure 3 Desirability plot for maximum MS<br />

[Max. Desiarbility (0.9887) occurs at Ton 122, T<strong>of</strong>f 30, SV: <strong>20</strong>; WF: 8]<br />

4.1 Optimal Solution<br />

The goal <strong>of</strong> optimization is to find a good set <strong>of</strong> conditions that will meet the desired goal. It is not necessary that<br />

the value <strong>of</strong> desirability is always 1.0 as the value is completely dependent on how closely the lower and upper<br />

limits are set relative to the actual optimum value (Aggarwal et. al., <strong>20</strong>08). The set <strong>of</strong> conditions possessing<br />

highest desirability value have been selected as optimum conditions for maximum MS. The constraints for the<br />

optimization <strong>of</strong> MS have been listed in Tables 4. Using Design expert (DX-8), optimal solutions have been<br />

derived for specified design space constraints for machining speed. Table 5 shows the set <strong>of</strong> conditions<br />

correspond to maximum desirability value for MS. Figure 3 shows the 3D surface plot for desirability.<br />

Sr.<br />

No.<br />

Table 5 Optimal conditions for maximizing MS<br />

A B C D Desirability Predicted<br />

(Ton) (T<strong>of</strong>f) (SV) (WF) value Value<br />

1 122 30 <strong>20</strong> 8 0.9887 32.271 32.58<br />

Confirmatory<br />

value<br />

5. Conclusion<br />

In this paper, four important WEDM parameters namely pulse-on time, pulse-<strong>of</strong>f time, servo voltage and wire<br />

feed rate have been investigated and modelled for machining speed <strong>of</strong> WC-5.3%Co composite during rough<br />

cutting operation on WEDM. Using response surface methodology, face centered central composite design has<br />

been adopted to perform the experiments. Quadratic Vs two factors interaction (2FI) has been found the best fit<br />

model for machining speed. Using desirability function, parameters have been predicted for maximizing the<br />

machining speed. Confirmatory results show the adequacy <strong>of</strong> the predicted model.<br />

447


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

References<br />

A. Aggarwal, H. Singh, P. Kumar and M. Singh, “Modelling <strong>of</strong> machining parameters and cooling conditions in<br />

hard turning <strong>of</strong> AISI P-<strong>20</strong> tool steel using response surface methodology and desirability graphs”,<br />

International Journal <strong>of</strong> Machining & Machinability <strong>of</strong> Materials, 4(1), <strong>20</strong>08, pp. 95-110.<br />

D. Deringer, and R. Suich, “Simultaneous optimization <strong>of</strong> several response variables”, Journal <strong>of</strong> Quality<br />

<strong>Technology</strong>, 12, <strong>19</strong>80, pp. 214-2<strong>19</strong>.<br />

R.K. Garg, K.K. Singh, et al., “Review <strong>of</strong> research work in sinking EDM and WEDM on metal matrix composite<br />

materials”, International Journal <strong>of</strong> Advance Manufacturing <strong>Technology</strong>, 50, <strong>20</strong>10, pp. 611-624.<br />

K. Jangra, A. Jain and S. Grover, “Optimization <strong>of</strong> multiple-machining characteristics in wire electrical<br />

discharge machining <strong>of</strong> punching die using grey relational analysis”, Journal <strong>of</strong> Scientific and Industrial<br />

Research, Vol. 69, <strong>20</strong>10, pp. 606-612.<br />

K. Jangra et al., “Digraph and matrix method to evaluate the machinability <strong>of</strong> tungsten carbide composite with<br />

wire EDM”, International Journal <strong>of</strong> Advance Manufacturing <strong>Technology</strong>, Vol. 56 (9-12), <strong>20</strong>11a, pp. 959-<br />

974.<br />

K. Jangra, S. Grover and A. Aggarwal, “Machinabilty Evaluation <strong>of</strong> WC- Composite with Wire EDM”, Journal<br />

<strong>of</strong> Manufacturing <strong>Technology</strong> Research, 3 (1-2), <strong>20</strong>11b.<br />

D. Kanagarajan, R. Karthikeyan, K. Palanikumar, J. Paulo Davim, “Optimization <strong>of</strong> electrical discharge<br />

machining characteristics <strong>of</strong> WC/Co composites suing non-dominated sorting genetic algorithm (NSGA-II)”,<br />

International Journal <strong>of</strong> Advance Manufacturing <strong>Technology</strong>, <strong>20</strong>08, DOI 10.1007/s00170-006-0921-8.<br />

K.-Y. Kung, J.-T. Horng, K.-T. Chiang, “Material removal rate and electrode wear ratio study on the powder<br />

mixed electrical discharge machining <strong>of</strong> cobalt-bonded tungsten carbide”, International Journal <strong>of</strong> Advance<br />

Manufacturing <strong>Technology</strong>, <strong>20</strong>09, DOI 10.1007/s00170-007-1307-2.<br />

K. Kanlayasiria, S. Boonmung, “Effects <strong>of</strong> wire-EDM machining variables on surface roughness <strong>of</strong> newly<br />

developed DC 53 die steel: design <strong>of</strong> experiments and regression model”, Journal <strong>of</strong> Materials Processing<br />

<strong>Technology</strong>, <strong>19</strong>2-<strong>19</strong>3, <strong>20</strong>07, pp. 459-464.<br />

B. Lauwers, W. Liu, W. Eeraerts, “Influence <strong>of</strong> the composition <strong>of</strong> WC-based cermets on manufacturability by<br />

wire-EDM”, Journal <strong>of</strong> Manufacturing process, 8(2), <strong>20</strong>06, pp. 83-89.<br />

R. A. Mahdavinejad and A. Mahdavinejad, “ED machining <strong>of</strong> WC-Co”, Journal <strong>of</strong> Material Processing<br />

<strong>Technology</strong>, Vol. 162-163, <strong>20</strong>05, pp. 637-643.<br />

H.J. Scussel, “Friction and Wear <strong>of</strong> Cemented Carbides”, ASM Handbook, ASM Interantioanl, Vol. 18, <strong>19</strong>92,<br />

pp. 795.<br />

448


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

EFFECT OF TOOL SHAPE ON TENSILE STRENGTH IN SINGLE AND<br />

SEQUENTIAL DOUBLE SIDED FRICTION STIR WELD ON AA1100<br />

ALUMINUM ALLOY<br />

Vinod Kumar 1 , Kamal Jangra 2 and Vikas Kumar 3<br />

1 Research Scholar. Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> UST, Faridabad, India, 121006<br />

2 Assistant Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> UST, Faridabad, India, 121006<br />

3 Associate Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> UST, Faridabad, India, 121006<br />

Abstract<br />

In present work, an investigation has been carried out on friction stir welding (FSW) on AA1100 aluminium<br />

alloy using high carbon high chromium alloy steel tool. Four types <strong>of</strong> tool pin pr<strong>of</strong>iles namely straight<br />

cylindrical, threaded, triangular and square were investigated. Tool rotation and traverse speeds were kept<br />

constant at 1<strong>20</strong>0 rpm and <strong>20</strong>mm/min while shape <strong>of</strong> the tool and number <strong>of</strong> passes were two variables. Results<br />

show that maximum tensile strength occurs across the weld zone as compared to the parent material. Threaded<br />

tool pin pr<strong>of</strong>ile exhibited superior tensile properties compared to other joints, irrespective <strong>of</strong> tool rotational<br />

speed in double pass. The joints fabricated by single pass have shown lower tensile strength and also percentage<br />

<strong>of</strong> elongation compared to the joints fabricated by double pass and this trend is common for all the tool pr<strong>of</strong>iles.<br />

Keywords: Friction Stir Welding, Aluminium Alloy AA1100, Tensile strength.<br />

1. Introduction<br />

AA1100 aluminium alloy (Al–Mg–Si alloy) has been most widely used in the fabrication <strong>of</strong> light weight<br />

structures because <strong>of</strong> requirement <strong>of</strong> a high strength-to-weight ratio and good corrosion resistance. Compared to<br />

the fusion welding processes that are routinely used for joining structural aluminium alloys, friction stir welding<br />

(FSW) process is an emerging solid state joining process in which the material that is being welded does not melt<br />

and recast. Friction stir welding (FSW) is a relatively new solid state welding process which is used for butt<br />

joints. FSW was invented by the Welding Institute, Cambridge, UK in <strong>19</strong>91 and has emerged as a new process<br />

for welding <strong>of</strong> aluminium alloys (Thomas et al. <strong>19</strong>91). This process has made possible to weld a number <strong>of</strong><br />

aluminium alloys that were previously not recommended (<strong>20</strong>00 series & copper containing 7000 series<br />

aluminium alloys) for welding. Because the material subjected to FSW does not melt and re-solidify, the<br />

resultant weld metal is free <strong>of</strong> porosity with lower distortion. An added advantage is that it is an environmentally<br />

friendly process. FSW is a solid state, localized thermo mechanical, joining process.<br />

Figure 1 Schematic representation <strong>of</strong> FSW (Balasubramanian et. al. <strong>20</strong>08)<br />

Figure 1 shows the schematic representation <strong>of</strong> FSW. In FSW, a non-consumable rotating shouldered-pin-tool is<br />

plunged into the interface between two plates being welded, until the shoulder touches the surface <strong>of</strong> the base<br />

material, and then tool is transverse along the weld line. In FSW, frictional heat is generated by rubbing <strong>of</strong> tool<br />

shoulder and base material surface. During traversing, s<strong>of</strong>tened material from the leading edge moves to the<br />

trailing edge due to the tool rotation and the transverse movement <strong>of</strong> the tool, and this transferred material is<br />

consolidated in the trailing edge <strong>of</strong> the tool by the application <strong>of</strong> an axial force (Ma ZY, <strong>20</strong>08). The length <strong>of</strong> tool<br />

pr<strong>of</strong>ile pin is slightly less than thickness <strong>of</strong> the work piece thickness plate and diameter <strong>of</strong> tool pin pr<strong>of</strong>ile is<br />

449


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

slightly greater than thickness <strong>of</strong> plate (Ulysse, <strong>20</strong>02). The welding parameters such as tool rotational speed,<br />

welding speed, axial force, etc., and tool pin pr<strong>of</strong>ile play a major role in deciding the weld quality.<br />

Many attempts have been made on FSW on aluminium alloys. Balasubramanian (<strong>20</strong>08) investigated the<br />

mechanical properties in FSW on aluminium alloy using rotating non-consumable tool. Results concluded that<br />

the process parameter such as tool rotational speed, welding speed, axial force plays a major role in deciding the<br />

weld quality. He studied the effect <strong>of</strong> tool pin pr<strong>of</strong>ile and tool shoulder diameter on FSP zone formation in<br />

AA6061 aluminium alloy. Five different tool pin pr<strong>of</strong>iles (straight cylindrical, tapered cylindrical, threaded<br />

cylindrical, triangular and square) with three different shoulder diameters are used to fabricate the joints.<br />

Cabibbo et al. (<strong>20</strong>07) studied the microstructure and mechanical properties <strong>of</strong> friction stir welded 6056-T6<br />

aluminium alloy using polarized optical and transmission electron microscopy. The microstructure revealed<br />

different grain morphologies in the thermo-mechanically affected zones. Tensile tests showed that yield and<br />

ultimate strength slightly lower across the weld compared to the parent material as well as a reduction in ductility<br />

<strong>of</strong> the weld region. Cavaliere et al., (<strong>20</strong>09) showed the effect <strong>of</strong> process parameters on the mechanical and micro<br />

structural properties <strong>of</strong> dissimilar AA6082–AA<strong>20</strong>24 joints produced by friction stir welding. Zheng et al., (<strong>20</strong>08)<br />

conducted a study on fracture <strong>of</strong> welded thin walled aluminium structures for train safety. The material<br />

characterization for plasticity and fracture <strong>of</strong> each <strong>of</strong> the material zones within the weld is reported as a<br />

combination <strong>of</strong> experimental and numerical studies. Cui et al., (<strong>20</strong>07) showed that a high carbon steel joint can<br />

be successfully friction stir welded without any pre-or post-heat treatment. It was proved that friction stir<br />

welding enables us to properly control the cooling rate and peak temperatures, which was impossible using<br />

traditional welding. Minton and Mynors (<strong>20</strong>06) described a methodology for determining if a conventional<br />

milling machine is capable <strong>of</strong> being used to undertake friction stir welding. The methodology was tested by<br />

providing same thickness welds <strong>of</strong> 6.3 mm and 4.6 mm 6082-T6 aluminium sheets.<br />

Scialpi et al. (<strong>20</strong>07) studied the effect <strong>of</strong> different shoulder geometries on the mechanical and micro-structural<br />

properties <strong>of</strong> a friction stir welded joints. The three different tools differed from shoulders with scroll and fillet,<br />

cavity and fillet, and only fillet were used. Nakata et al. (<strong>20</strong>06) showed that an improvement in the mechanical<br />

properties due to the micro structural modification <strong>of</strong> an aluminium die casting alloy by multi-pass friction stir<br />

processing (MP-FSP), which is a solid-state micro structural modification technique using a frictional heat and<br />

stirring action. The hardness <strong>of</strong> the MP-FSP sample is about <strong>20</strong> Hv higher than that <strong>of</strong> the base metal. The effect<br />

<strong>of</strong> the welding speed on the microstructure, local and overall mechanical properties <strong>of</strong> friction stir welded joints<br />

<strong>of</strong> aluminium alloy 6005A-T6 has been investigated by Simar et al. (<strong>20</strong>08). The fine hardening precipitation<br />

within the heat-affected zone has been characterized by differential scanning calorimetry (DSC) and transmission<br />

electron microscopy (TEM).<br />

Single pass friction stir welding is not able to provide better results in case <strong>of</strong> thick work material plates which is<br />

mainly due to the difficulty in finding a suitable backing material. Obviously the thickness <strong>of</strong> plate that can be<br />

joined by FSW can be increased by passing the tool along both sides <strong>of</strong> the butted plates in sequence. The use <strong>of</strong><br />

the sequential double pass weld can almost double the plate thickness that can be joined, thereby significantly<br />

increasing the industrial utility <strong>of</strong> the FSW joining process for other materials like steels etc. Considering these<br />

facts, the objective <strong>of</strong> the present study is to investigate the influence <strong>of</strong> tool shape on the tensile strength <strong>of</strong> AA<br />

1100 in single and double sided friction stir welds.<br />

2. Experimental Setup<br />

The base material used in this study was aluminium alloy AA1100 plates having thickness <strong>of</strong> 5mm. The base<br />

material tensile strength was 117.33 N/mm² with elongation <strong>of</strong> 14.6 %. FSW trials were carried out on a vertical<br />

milling machine with square butt joint configuration. A pair <strong>of</strong> work pieces <strong>of</strong> dimension <strong>20</strong>0mm ×<strong>20</strong>0mm ×5<br />

mm were abutted and clamped rigidly on the backing plate for welding. The tool geometry with 18 mm diameter<br />

flat shoulder with chamfered edge straight cylindrical (SC), threaded (TH), triangular (TR) and square (SQ) pin<br />

pr<strong>of</strong>ile with circumferential diameter 6mm were used to fabricate the joints.<br />

The tool material was high carbon high chrome steel (HCHCR) which provides high cutting speed with long life<br />

to the material. The tool material is available in <strong>20</strong> mm diameter rod. Straight cylindrical and threaded tool<br />

geometries were processed on the lathe machine and central grinding machine according to the dimensions<br />

specified. Triangular and square pin pr<strong>of</strong>iles were processed on the milling machine by indexing. It had the<br />

maximum size <strong>of</strong> square pin pr<strong>of</strong>iles tool 4.2 mm obtained from circumferential diameter 6mm and for<br />

triangular, it was 5.2 mm sides. It is worth noting that for the double pass weld, the plates were turned over about<br />

an axis along the weld after the first pass was made, so that the two welding passes started at the same position<br />

along the joint interface, and the advancing side <strong>of</strong> the second pass was over the retreating side <strong>of</strong> the first pass<br />

weld. All <strong>of</strong> the welds were carried out along the rolling direction <strong>of</strong> the steel plate.<br />

450


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Tool rotation speed, traverse speeds and tool tilt angle were kept constant at 1<strong>20</strong>0 rpm, <strong>20</strong> mm/min and zero<br />

angle respectively. The process variables were, shape <strong>of</strong> the tool and tool passes on single and double sided. The<br />

axial load was varied by linearly increasing interference between the tool and the base material. In friction stir<br />

welding, the process was used in single pass and double passes. Tool pin length in Single pass FSW and double<br />

pass FSW were 4.7mm and 2.7mm respectively. Time taken for <strong>20</strong>0mm length was 10min. in case <strong>of</strong> single pass<br />

weld while time taken for <strong>20</strong>0mm length in double pass was <strong>20</strong>min. In both cases, depth <strong>of</strong> depression was 0.05<br />

mm and four tools <strong>of</strong> different pin pr<strong>of</strong>iles i.e. straight cylindrical, threaded, triangular and square were used.<br />

3. Results and Discussion<br />

Figure 2 Dimensions <strong>of</strong> Tensile Specimen<br />

The specimens for tensile test were prepared according to the guidelines <strong>of</strong> American Society for Testing <strong>of</strong><br />

Materials (ASTM) as shown in Figure 2. Cross sectional area <strong>of</strong> test specimen were 5 x 15 =75 mm 2 . Tensile test<br />

was carried out in 40 KN; electro-mechanical controlled Universal Testing Machine at a room temperature. The<br />

specimen was loaded as per ASTM specifications, so that tensile specimen undergoes deformation. The<br />

specimen finally failed after necking and the load versus displacement was recorded. The ultimate tensile<br />

strength, percentage elongation and joint efficiency were evaluated. In welding, joint efficiency is the ratio <strong>of</strong> the<br />

strength <strong>of</strong> a joint to the strength <strong>of</strong> the base metal, expressed in percentage:<br />

Joint efficiency η = joint strength / parent strength<br />

Specimen<br />

No.<br />

Table 1 Tensile test results <strong>of</strong> welded specimens in single pass<br />

Ultimate Tensile Strength Percentage Elongation Joint<br />

Efficiency<br />

(%)<br />

Load (KN) Stress<br />

(N/mm 2 )<br />

Elongated<br />

Length (mm)<br />

%<br />

Elongation<br />

S-1 8.4 112 54.4 8.8 95.4<br />

S-3 8.48 113 59.5 <strong>19</strong> 96.3<br />

S-5 8.96 1<strong>19</strong>.4 52.9 5.8 101.7<br />

S-7 9.52 126.9 58.3 16.6 108.1<br />

Specimen<br />

No.<br />

Table 2 Tensile test results <strong>of</strong> welded specimens in double pass<br />

Ultimate Tensile Percentage Elongation<br />

Strength<br />

Load Stress Elongated Length %<br />

(KN) (N/mm 2 ) (mm)<br />

Elongation<br />

S-2 8.88 118.4 61.3 22.6 100.9<br />

S-4 8.92 118.9 63.6 27.2 101.3<br />

S-6 10 133.3 55.5 11 113.6<br />

S-8 9.6 128 62.2 24.4 109.9<br />

Joint<br />

Efficiency<br />

(%)<br />

Variation <strong>of</strong> Ultimate Tensile Strength<br />

Variation Of Percentage Elongation<br />

140<br />

30<br />

Ultimate Tensile Strength<br />

1<strong>20</strong><br />

100<br />

80<br />

60<br />

40<br />

<strong>20</strong><br />

Single Pass<br />

Double Pass<br />

Percentage Elongation<br />

25<br />

<strong>20</strong><br />

15<br />

10<br />

5<br />

Single Pass<br />

Double Pass<br />

0<br />

SC SQ TH TR<br />

0<br />

SC SQ TH TR<br />

Tool Pr<strong>of</strong>ile<br />

Tool Pr<strong>of</strong>ile<br />

\<br />

Figure 3 Variation <strong>of</strong> Ultimate Tensile Strength<br />

Figure 4 Variation <strong>of</strong> Percentage Elongation<br />

451


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The welded specimens were put under tensile testing and the values <strong>of</strong> ultimate tensile strength, percentage<br />

elongation and joint efficiency were noted. The ultimate tensile strength and percentage <strong>of</strong> elongation <strong>of</strong> base<br />

metal are 117.33 N/mm 2 and 14.6%. The results <strong>of</strong> tensile loading <strong>of</strong> the welded specimens in single and double<br />

pass are shown in Table 1 and 2 respectively. Transverse tensile properties <strong>of</strong> FSW joints i.e. ultimate tensile<br />

strength, percentage elongation and joint efficiency were evaluated as shown in Figures 3-5 respectively.<br />

Variation <strong>of</strong> Joint Efficiency<br />

115<br />

110<br />

Joint Efficiency<br />

105<br />

100<br />

95<br />

90<br />

Single Pass<br />

Double Pass<br />

85<br />

SC SQ TH TR<br />

Tool Pr<strong>of</strong>ile<br />

Figure 5 Variation <strong>of</strong> Joint Efficiency<br />

From Figures 3-5, it can be seen that the tool pr<strong>of</strong>ile and passing <strong>of</strong> tool in full depth are influencing parameters<br />

on tensile properties <strong>of</strong> the FSW joints. In single pass, the highest tensile strength <strong>of</strong> the joints was obtained by<br />

using the triangular pin pr<strong>of</strong>ile tool. The triangular pin pr<strong>of</strong>iles tool is best and tensile strength significantly<br />

decreases for threaded, square and cylindrical pin pr<strong>of</strong>ile tool due to defect formation. The welding parameters<br />

have similar effects on the tensile properties for straight cylindrical and square pin pr<strong>of</strong>iles tools.<br />

Threaded tool pin pr<strong>of</strong>ile tool exhibited superior tensile properties compared to other joints, irrespective <strong>of</strong> tool<br />

rotational speed in double pass. Similarly, the joints fabricated by triangular pin pr<strong>of</strong>iled tool are also showing<br />

almost matching tensile properties to that <strong>of</strong> threaded tool pr<strong>of</strong>ile. The joints fabricated by single pass have<br />

shown lower tensile strength and percentage <strong>of</strong> elongation compared to the joints fabricated by double pass and<br />

this trend is common for all the tool pr<strong>of</strong>iles. This is because <strong>of</strong> uniform distribution <strong>of</strong> the finer Si particles,<br />

grain refinement <strong>of</strong> aluminium matrix. From the analysis <strong>of</strong> fractured surface it can be inferred that the defect<br />

free welds are showing uniform deformation across the weld before failure. Welded specimens failed in region<br />

corresponding to the outer HAZ.<br />

The maximum and minimum ultimate tensile strength in using single pass was 126.9N/mm 2 and 112 respectively<br />

while maximum and minimum ultimate tensile strength in double pass was 133.3 N/mm 2 and 118.4 respectively.<br />

4. Conclusion<br />

In this investigation an attempt has been made to study the effect <strong>of</strong> tool pin pr<strong>of</strong>ile (straight cylindrical,<br />

threaded, triangular and square) on tensile strength in single and sequential double sided friction stir welding <strong>of</strong><br />

AA1100, aluminium alloy. Welded specimens were failed in region corresponding to the outer heat affected zone<br />

(HAZ). The joints fabricated by double passes have shown higher ultimate tensile strength and percentage<br />

elongation as compared to the joints fabricated by single pass and this trend is common for all the tool pr<strong>of</strong>iles.<br />

References<br />

Balasubramanian V., Elangovan K. (<strong>20</strong>08), “Relationship between base metal properties and friction stir welding<br />

process parameters”. Materials <strong>Science</strong> and Engineering Journal 480, pp 397–403.<br />

Cavaliere P. , Santis A.De, Panella F., Squillace A. (<strong>20</strong>09), “Effect <strong>of</strong> welding parameters on mechanical and<br />

micro structural properties <strong>of</strong> dissimilar AA6082–AA<strong>20</strong>24 joints produced by friction stir welding”. Materials<br />

and Design Journal 30, pp 609–616.<br />

Cabibbo M., McQueenb H.J., E. Evangelista E., Spigarelli S., Paola M. Di, Falchero A. (<strong>20</strong>07), “Microstructure<br />

and mechanical property studies <strong>of</strong> AA6056 friction stir welded plate”. Materials <strong>Science</strong> and Engineering<br />

Journal A 460-461, pp 86–94.<br />

Cui Ling, Fujii Hidetoshi, Tsujib Nobuhiro and Nogi Kiyoshi (<strong>20</strong>07), “Friction stir welding <strong>of</strong> a high carbon<br />

steel” .Scripta Materialia 56, pp 637–640.<br />

452


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Elangovana K., Balasubramanianb V. (<strong>20</strong>08), “Influences <strong>of</strong> tool pin pr<strong>of</strong>ile and welding speed on the formation<br />

<strong>of</strong> friction stir processing zone in AA22<strong>19</strong>aluminium alloy”. Journal <strong>of</strong> materials processing technology, pp 163–<br />

175.<br />

Ma ZY. (<strong>20</strong>08), “ Friction stir processing technology: a review”. Metall Mater Trans A; 39A, pp 642–58.<br />

Minton T., Mynors D.J., “Utilization <strong>of</strong> engineering (<strong>20</strong>06), “Workshop equipment for friction stir welding”.<br />

Journal <strong>of</strong> Materials Processing <strong>Technology</strong> 177, pp 336-339.<br />

Nakata K., Kima, Y.G., Fujii H., Tsumura T., Komazaki T. (<strong>20</strong>06), “Improvement <strong>of</strong> mechanical properties <strong>of</strong><br />

aluminum die casting alloy by multi-pass friction stir processing”.Materials <strong>Science</strong> and Engineering Journal<br />

437, pp 274–280.<br />

Scialpi A., De Filppis Lac., Cavaliere P. (<strong>20</strong>07), “Influence <strong>of</strong> shoulder geometry on micro-structure and<br />

mechanical properties <strong>of</strong> friction stir welded 6082 aluminum alloy”. Materials and Design Journal 28, pp 1124-<br />

1129.<br />

Simar A., Br´echet Y., Meester B. De, Denquin A., Pardoen T. (<strong>20</strong>08), “Microstructure, local and global<br />

mechanical properties <strong>of</strong> friction stir welds in aluminium alloy 6005A-T6”, Materials <strong>Science</strong> and Engineering<br />

Journal 486, pp 85–95.<br />

Thomas WM. Et al., (<strong>19</strong>91), “Friction Stir Butt Welding”. International Patent Appl. No. PCT/GB92/02<strong>20</strong>3 and<br />

GB patent Appl. No. 9125978.8, U.S. Patent No. 5460,317.<br />

Ulysse P., (<strong>20</strong>02), “Three-dimensional modeling <strong>of</strong> the friction stir welding process”. Int. J. Mach. Tools Manuf.<br />

42 ,pp 1549–1557.<br />

Zheng Petry D., Rapp H., Wierzbicki T. (<strong>20</strong>08), “A characterization <strong>of</strong> material and fracture <strong>of</strong> AA6061 butt<br />

weld”. Thin-Walled Structures 40, pp 1-11.<br />

453


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

STUDY OF VARIOUS MECHANICAL PROPERTIES OF FIBER REINFORCED<br />

CAST IRON<br />

Sanjay kumar 1 , Vasdev Malhotra 2 and Vikas Kumar 3<br />

1 Research Scholar. Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> UST, Faridabad, India,121006<br />

2 Assistant Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> UST, Faridabad, India,121006<br />

3 Associate Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> UST, Faridabad, India,121006<br />

Abstract<br />

This paper is about the study <strong>of</strong> various mechanical properties <strong>of</strong> fiber reinforced cast iron by employing the gas<br />

metal arc welding technique. The welding joints were assessed by measuring the tensile strength. Some<br />

specimens were preheated to 275˚ C for 8 minute and their results were compared with those <strong>of</strong> un preheated<br />

specimens. The weld joints were cooled in air and sand thus giving various cooling rates leading to different<br />

mechanical properties. The higher cooling rate produces joints <strong>of</strong> higher strength and hardness with lower<br />

elongation. Preheating improves the strength and elongation and lowers the hardness. This paper shows the<br />

properties <strong>of</strong> cast iron along with various important parameters.<br />

Key word: Strength, Joint, Properties, Cast iron.<br />

1. INTRODUCTION<br />

Fiber reinforced cast iron is finding applications in various industries for its excellent mechanical and corrosion<br />

resistance properties. Its use requiring joining by welding is limited because it has been considered difficult to<br />

weld. But welding is necessary for founders and end-user to rectify casting defect and machining errors, attach<br />

lugs or to join the casting part with other materials[1]. The poor weldability in fusion welding is due to its high<br />

carbon content which leads to the formation <strong>of</strong> carbides and martensite in the fusion zone. Carbides and<br />

martensite are brittle phases in Fusion zone and can cause deterioration <strong>of</strong> the mechanical properties and<br />

machinability. But by using correct procedures and appropriate materials, casting <strong>of</strong> fiber reinforced cast iron can<br />

be successfully joined with each other by fusion welding[2].<br />

The potential problem <strong>of</strong> high carbon weld metal deposit is avoided by using a nickel or nickel alloy<br />

consumable, which produces finally lower porosity and readily machinable deposit. The formation <strong>of</strong> hard and<br />

brittle phase in the structure <strong>of</strong> Heat affected zone results in its cracking during post weld cooling. Preheating<br />

and slow post-weld cooling reduces its cracking risk. Preheating will slow the cooling rate in fusion and heat<br />

affected zone, thus the martensitic transformation is suppressed with reduced hardness in the heat affected zone.<br />

Preheating also dissipates shrinkage stresses and reduces distortion, reducing the possibility <strong>of</strong> cracking in heat<br />

affected zone.<br />

2 .EXPERIMENTAL PROCEDURE<br />

The specimens for welding were cut from the FRCI block. FRCI block was casted with cast iron and E-glass<br />

fiber using die casting after preparation <strong>of</strong> mould. They were 12cm long, 2cm wide and 0.5cm thick after<br />

machining. For welding they were cut at the middle into two equal pieces, and then welded after edge<br />

preparation as a V joint by GMAW technique using alternative current at 100A. preheating <strong>of</strong> about 300˚C for 10<br />

minute was applied to some specimens in a Muffle furnace. After welding, the specimens were cooled at<br />

different rates; namely in air and in sand, then they were subjected to tensile test using the Jinan tensile testing<br />

machine model no. WAW-100E. specimens were preheated in the muffle furnace for the given time duration.<br />

Micro hardness measurements across the weld joint were carried out using the micro hardness tester, model<br />

Rockwell RASNEP-1 make FI. The micro structure examinations were carried out using optical microscope type<br />

Olmpus model <strong>20</strong>0696. The microstructure <strong>of</strong> FRCI was pearlitic ferritic.<br />

3 .TEST RESULTS AND DISCUSSION<br />

3.1Tensile test<br />

The tensile test results <strong>of</strong> unpreheated specimens are given in table 1 and shown in fig. 1and those for preheated<br />

ones are given in table 2 and fig. 2 for various cooling rates. Comparison <strong>of</strong> these results show higher tensile<br />

strength (σUT) and more elongations for preheated specimens at all cooling rates. The highest σUT and the<br />

lowest elongation were recorded for specimens cooled in air. The lowest σUT and were recorded for sand cooled<br />

specimens but with highest elongation.These results reflect the effect <strong>of</strong> the cooling rate on the microstructure<br />

obtained after various cooling rates. Air cooling produces martensitic structure in the HAZ next to FZ, which is<br />

manifested in higher strength and lower elongation. With decreasing cooling rate, the martensitic structure<br />

454


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

vanishes gradually and tempered martensite and pearlite form with lower strength and higher ductility.<br />

Table 1 Tensile test results <strong>of</strong> FRCI without preheating<br />

Cooling condition Tensile strength(N/mm 2 )<br />

Elongation(mm)<br />

Base metal 228 0.75<br />

Air cooling 148 0.70<br />

Sand cooling 140 0.74<br />

Table 2. Tensile test results <strong>of</strong> FRCI after preheating<br />

Cooling condition Tensile strength(N/mm 2 )<br />

Elongation(mm)<br />

Base metal 228 0.75<br />

Air cooling 171 0.83<br />

Sand cooling 159 0.87<br />

Fig.1 stress-strain curve for FRCI without preheating<br />

Fig.2 stress-strain curve for FRCI after preheating to 300°c<br />

455


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3.2Hardness tests<br />

The higher hardness value for FZ compared with the hardness value <strong>of</strong> the base metal HAZ are attributed to the<br />

fine microstructure and carbide formation due to carbon atom diffusion[3]. The air cooled specimens showed<br />

higher hardness value compared with the hardness <strong>of</strong> the furnace cooled specimens and for the sand cooled<br />

specimens it was in between. These results are in compliance with the phase changes, grain size variation and<br />

carbide formation during various cooling rates. It is well known in heat treatment <strong>of</strong> steel that higher cooling<br />

rates encourage formation <strong>of</strong> stronger and harder phases such as bainite (B) and martensite (M). Hardness values<br />

in preheated specimens are lower compared with the hardness <strong>of</strong> unpreheated specimens for the same zone under<br />

the same condition as shown in Tables 3, Figs. 3 and 4. It is clear from Figs. 3 and 4 that the hardness values in<br />

the base metal remain at about the same level, meaning no phase changes.<br />

For un preheated specimens the average hardness values <strong>of</strong> the base metal, HAZ and FZ are given in Table 3.<br />

Fig.3 shows the change <strong>of</strong> the hardness across the welding joint for these specimens.<br />

Fig.3<br />

Fig.4<br />

Table 3 Average rockwell hardness number(RC) across the welded joint without preheat<br />

Cooling condition Base metal HAZ Weld metal<br />

preheat without preheat without preheat Without<br />

Air cooled 91.67 90.17 95.04 93.92 97.75 95.83<br />

Sand cooled 91.38 88.79 94.42 92.75 96.5 94.67<br />

For preheated specimens the average hardness values <strong>of</strong> the base metal, HAZ and FZ are given in Table 3. Fig.4<br />

shows the change <strong>of</strong> the hardness across the welding joint for these specimens.<br />

4. WELD QUALITY<br />

The quality <strong>of</strong> the material can be assessed by calculation <strong>of</strong> the quality index (QI) [5]:<br />

QI=(Tensile strength) 2 x(Elongation)/1000<br />

1MPa=0.145Ksi<br />

Table 4 Quality index<br />

Cooling condition Unpreheated Preheated<br />

Base metal 0.68 0.68<br />

Air cooling 0.26 0.43<br />

Sand cooling 0.254 0.39<br />

A larger QI value indicates a better combination <strong>of</strong> higher strength and elongation therefore a better materials<br />

performance. The weld quality can be assessed similarly. Higher QI value is related to absence <strong>of</strong> intercellular<br />

precipitates, low volume fraction <strong>of</strong> carbides, and internal porosity. Calculated QI values for unpreheated and<br />

preheated specimens and for various cooling rates are given in Table 4. These results show clearly that<br />

preheating produces welds <strong>of</strong> higher QI values, thus better weld quality. These results show that preheating is<br />

preferred.<br />

456


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5. CONCLUSION<br />

This paper concludes that the various properties related to fiber reinforced cast iron are very important and they<br />

affect on the cooling rates and welded zone. Maximum hardness is obtained in weld zone followed by heat<br />

affected zone and base metal for both preheated and unpre heated specimen and for all cooling conditions.<br />

Maximum tensile strength is obtained in base metal than in air cooled followed by sand cooled that means the<br />

higher cooling rate produces joints <strong>of</strong> higher strength.<br />

REFERENCES<br />

1. Akdemir Ahmet, Kus Recai and Simsir Mehmet (<strong>20</strong>09); “Impact Toughness And Microstructure Of<br />

Continuous Steel Wire-Reinforced Cast Iron Composite”. Material <strong>Science</strong> and Engineering, Vol. 516, No.2,<br />

pp. 1<strong>19</strong>-125.<br />

2. Cerit A. Alper, Karamiş M. Baki, Nair Fehmi and Yildizli Kemal(<strong>20</strong>08); “Effect Of Reinforcement Particle<br />

Size And Volume Fraction On Wear Behaviour Of Metal Matrix Composites”. International Journal Of<br />

Tribology In Industry, Vol.30, No. 3&4, pp. 31-36.<br />

3. Clyne T. W, Bader M. G, Cappleman G. R and Hubert P. A; “use <strong>of</strong> δ-alumina fibre for metal-matrix<br />

composites”. Journal Of Material science, Vol. <strong>20</strong>,No.3, pp. 85-96.<br />

4. Kheder A.R.I., Jubeh N. M. and Tahah E. M. (<strong>20</strong>05); “Fatigue behavior <strong>of</strong> alloyed acicular ductile<br />

iron”.Journal <strong>of</strong> joining <strong>of</strong> Materials, Vol. 17, No.1, pp. 7-12.<br />

5. Kheder A. R. I and Marahleh G. S (<strong>20</strong>07); “ to study the weldability <strong>of</strong> spheroidal graphite cast iron (SGI)<br />

by employing the gas tungsten arc welding (GTAW) technique”. <strong>University</strong> Of Sharjah Journal Of Pure &<br />

Applied <strong>Science</strong>, Vol.4, No.349, pp. 49-67.<br />

6. Kaiser S. D., Faws P.E. and Northey M. (<strong>20</strong>05); “welding cast iron”. Canadian welding Journal, Vol. 5,<br />

No.2, pp. 1-8.<br />

457


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

APPLICATION OF FIBER REINFORCED PLASTICS OR POLYMERS<br />

IN CIVIL ENGINEERING STRUCTURES<br />

Mrs. Meeta Verma<br />

Pursuing PhD from BIT Mesra, Ranchi<br />

Member, Institution <strong>of</strong> Engineers (India)<br />

Presently Associate Pr<strong>of</strong>essor, Dronacharya College <strong>of</strong> Engg, Gurgaon<br />

Abstract<br />

Engineers throughout the world including India have used FRP to solve their structural problems in an efficient<br />

and economical manner. In the field <strong>of</strong> Civil Engineering, most <strong>of</strong> the use <strong>of</strong> FRP is confined to repairing and<br />

strengthening <strong>of</strong> structures. FRPs <strong>of</strong>fer an added advantage over conventional materials and methods <strong>of</strong><br />

retr<strong>of</strong>itting. Like other materials, FRP also has its limitations. After presenting a brief review on these<br />

dimensions, this paper provides thorough information on the compatibility and application <strong>of</strong> FRP in Civil<br />

Engineering in India.<br />

1. General Introduction <strong>of</strong> FRP<br />

Fiber-Reinforced Plastic (FRP),also known as Fiber-Reinforced Polymer is a composite material made <strong>of</strong> a<br />

polymer matrix reinforced with high strength fibers. Matrix is the original plastic material without fiber<br />

reinforcement. The matrix is a tough but relatively weak plastic that is reinforced by stronger stiffer reinforcing<br />

filaments or fibers. The fibers in an FRP composite are the main load-carrying element and exhibit very high<br />

strength and stiffness when pulled in tension. The extent that strength and elasticity are enhanced in a fiber<br />

reinforced plastic depends on the mechanical properties <strong>of</strong> the fiber and matrix, their volume relative to one<br />

another, and the fiber length and orientation within the matrix. Reinforcement <strong>of</strong> the matrix occurs by definition<br />

when the FRP material exhibits increased strength or elasticity relative to the strength and elasticity <strong>of</strong> the matrix<br />

alone. The fibers are usually glass, carbon or aramid, although other fibers such as paper or wood or asbestos<br />

also are sometimes used. FRPs are commonly used in the aerospace, automotive, marine and construction<br />

industries.<br />

1.1 Beginning <strong>of</strong> FRP<br />

The idea <strong>of</strong> combining two different materials to make a single, superior composite material is not new. Some <strong>of</strong><br />

the earliest building materials were composite materials. The ancient Egyptians reinforced their mud bricks with<br />

straw to make them stronger. Fiber Reinforced Polymers (FRPs) are just the latest version <strong>of</strong> this very old idea.<br />

Commercially, it started as early as <strong>19</strong>09 with Bakelite.The development <strong>of</strong> fiber reinforced plastic for<br />

commercial use was extensively researched in the <strong>19</strong>30s particularly <strong>of</strong> interest to the aviation industry.With the<br />

continuing cost reduction in high-performance FRP materials and the growing need for new materials to renovate<br />

civil infrastructures, FRP materials are now finding wider acceptance among civil engineers.<br />

1.2 The Evolution <strong>of</strong> Composites in Civil Engineering<br />

For years, Civil Engineers have been in search for alternatives to steels and alloys to combat the high costs <strong>of</strong><br />

repair and maintenance <strong>of</strong> structures damaged by corrosion and heavy use. For example, cost estimates for<br />

maintenance <strong>of</strong> highway bridge decks composed <strong>of</strong> steel-reinforced concrete are up to $90 billion/year. Since the<br />

<strong>19</strong>40s, composite materials, formed by the combination <strong>of</strong> two or more distinct materials in a microscopic scale,<br />

have gained increasing popularity in the engineering field. Fiber Reinforced Polymer (FRP) is a relatively new<br />

class <strong>of</strong> composite material manufactured from fibers and resins and has proven efficient and economical for the<br />

development and repair <strong>of</strong> new and deteriorating structures in civil engineering. The mechanical properties <strong>of</strong><br />

FRPs make them ideal for widespread applications in construction worldwide.<br />

1.3 FRP Laminate Structure<br />

FRP are typically organized in a laminate structure such that each lamina (or flat layer) contains an arrangement<br />

<strong>of</strong> unidirectional fibers or woven fibers embedded within a thin layer <strong>of</strong> light matrix material. The fibers<br />

typically composed <strong>of</strong> carbon or glass, provide the strength and stiffness. The matrix, commonly made <strong>of</strong><br />

polyester, Epoxy or Nylon, binds and protects the fibers from damage, ensures that the fibers remain aligned,<br />

and allows loads to be distributed among many <strong>of</strong> the individual fibers in the composite.<br />

458


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. Why FRP in Structural Engineering<br />

1. The strength properties <strong>of</strong> FRPs collectively make up one <strong>of</strong> the primary reasons for which civil<br />

engineers select them in the design <strong>of</strong> structures. A material's strength is governed by its ability to<br />

sustain a load without excessive deformation or failure. When an FRP specimen is tested in axial<br />

tension, the applied force per unit cross-sectional area (stress) is proportional to the ratio <strong>of</strong> change in a<br />

specimen's length to its original length (strain). When the applied load is removed, FRP returns to its<br />

original shape or length. In other words, FRP responds linear-elastically to axial stress.<br />

2. FRP has tremendous potential and has great advantages over conventional materials and techniques <strong>of</strong><br />

retr<strong>of</strong>itting <strong>of</strong> RC structures. The increase in use <strong>of</strong> FRP for retr<strong>of</strong>itting <strong>of</strong> RC structure may be<br />

attributed to their advantageous properties mainly - high corrosion resistance, light weight, extremely<br />

high strength to weight ratio, ease <strong>of</strong> handling and installation (hence substantially reduced working<br />

time).<br />

3. The response <strong>of</strong> FRP to axial compression is reliant on the relative proportion in volume <strong>of</strong> fibers, the<br />

properties <strong>of</strong> the fiber and resin, and the interface bond strength.<br />

4. FRP's response to transverse tensile stress is very much dependent on the properties <strong>of</strong> the fiber and<br />

matrix, the interaction between the fiber and matrix, and the strength <strong>of</strong> the fiber-matrix interface.<br />

5. Among FRP's high strength properties, the most relevant features include excellent durability and<br />

corrosion resistance. Furthermore, their high strength-to-weight ratio is <strong>of</strong> significant benefit; a member<br />

composed <strong>of</strong> FRP can support larger live loads since its dead weight does not contribute significantly to<br />

the loads that it must bear. Other features include ease <strong>of</strong> installation, versatility, anti-seismic behavior,<br />

electromagnetic neutrality, excellent fatigue behavior, and fire resistance.<br />

3. Limitations<br />

However, like most structural materials, FRPs have a few drawbacks that would create some hesitancy in civil<br />

engineers to use it for all applications: high cost, brittle behavior, susceptibility to deformation under long-term<br />

loads, UV degradation, photo-degradation (from exposure to light), temperature and moisture effects, lack <strong>of</strong><br />

design codes, and most importantly, lack <strong>of</strong> awareness. FRP composite compression failure occurs when the<br />

fibers exhibit extreme (<strong>of</strong>ten sudden and dramatic) lateral or sides-way deflection called fiber buckling. Shear<br />

stress is induced in the plane <strong>of</strong> an area when external loads tend to cause two segments <strong>of</strong> a body to slide over<br />

one another. The shear strength <strong>of</strong> FRP is difficult to quantify. Generally, failure will occur within the matrix<br />

material parallel to the fibers.<br />

4. Applications <strong>of</strong> FRP Composites in Construction<br />

Composite materials are made by combining at least two different constituent materials with one or more<br />

materials as reinforcements, and one or more materials as the matrix. FRP composite is similar to RC, with a<br />

fiber (such as glass, carbon or aramid) as the reinforcement and a polymer (polymer resin matrix such as epoxy,<br />

polyester) as the matrix.Glass fibers begin as varying combinations <strong>of</strong> SiO 2 , Al 2 O 3 , B 2 O 3 , CaO, or MgO in<br />

powder form.Carbon fibers are created when polyacrylonitrile fibers (PAN), Pitch resins, or Rayon are<br />

carbonized (through oxidation and thermal pyrolysis) at high temperatures.Aramid fibers are most commonly<br />

known Kevlar, Nomex and Technora. Aramids are generally prepared by the reaction between an amine group<br />

and a carboxylic acid halide group (aramid).The fiber reinforcement carries load in pre-designed directions and<br />

the polymer matrix serves as a binder, a medium to transfer loads between adjacent fibers and to provide<br />

protection for the fiber. Current FRP composite materials typically have high strength and high-stiffness<br />

structural fibers embedded in lightweight, low-cost, and environmentally resistant polymers; which have better<br />

mechanical and durability properties than either <strong>of</strong> the constituents alone. FRP products produced for use in<br />

structural engineering can comprise significantly more ingredients than just the primary constituents: fiber and<br />

polymer resins.<br />

There are three broad divisions into which applications <strong>of</strong> FRP in Civil Engineering can be classified:<br />

1. Applications for new construction<br />

2. Repair and rehabilitation applications<br />

3. Architectural applications<br />

4.1 Applications for new construction<br />

FRPs have been used widely by civil engineers in the design <strong>of</strong> new construction. Structures such as bridges and<br />

columns built completely out <strong>of</strong> FRP composites have demonstrated exceptional durability and effective<br />

resistance to effects <strong>of</strong> environmental exposure. Pre-stressing tendons, reinforcing bars, grid reinforcement and<br />

dowels are all examples <strong>of</strong> the many diverse applications <strong>of</strong> FRP in new structures.The technique <strong>of</strong> externally<br />

bonding FRP to reinforced concrete (RC) structures was introduced into China in <strong>19</strong>97. In India, field<br />

459


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

application <strong>of</strong> FRP for structural strengthening could be traced as early as in <strong>19</strong>99. However, FRP is being used<br />

for new construction also in many countries; nothing significant could be traced in India. The material is still<br />

considered relatively new in this part <strong>of</strong> the world. Other countries like China is working on use <strong>of</strong> FRP in new<br />

construction in many directions like FRP bridges, FRP space structure, and concrete filled FRP tube columns.<br />

There exist many FRP footbridges in China.<br />

5. Repair and Rehabilitation Applications<br />

Construction is a major part <strong>of</strong> development plan <strong>of</strong> developing countries including India. To meet the large<br />

demand for infrastructure development, maintenance and life enhancement <strong>of</strong> existing structures are very<br />

important. After many years <strong>of</strong> use, an existing structure <strong>of</strong>ten needs to be repaired or upgraded because <strong>of</strong> so<br />

many reasons like damage due to corrosion or increased load demand etc. There are several methods for<br />

retr<strong>of</strong>itting <strong>of</strong> structures like- guinting, post tensioning, externallybonded steel plates, steel or concrete jackets<br />

etc. Epoxyinjection and newly developed methods like advancedtechniques for corrosion affected RCC and<br />

methods <strong>of</strong>modifying structural properties using active or passivemass damper for high rise buildings are also<br />

there.Several companies across the world are beginning to wrap damaged bridge piers to prevent collapse and<br />

steel-reinforced columns to improve the structural integrity and to prevent buckling <strong>of</strong> the reinforcement.<br />

FRP is now being used in our industry to strengthen concrete, steel and masonry structures. They compete<br />

directly with traditional strengthening techniques like section enlargement, external post-tensioning and steel<br />

plate bonding. Steel plate bonding is a method <strong>of</strong> strengthening a structure by bonding steel plates to the concrete<br />

surface in the areas <strong>of</strong> high tensile stresses.<br />

5.1 Architectural Applications<br />

Architects have also discovered the many applications for which FRP can be used. These include structures such<br />

as siding/cladding, ro<strong>of</strong>ing, flooring and partitions. In Canada, ISIS, Intelligent Sensing for Innovative<br />

Structures, is a program that consists <strong>of</strong> collaborative efforts <strong>of</strong> universities in various disciplines with primary<br />

mission to develop the innovative use <strong>of</strong> FRPs in concrete structures.<br />

6. Examples <strong>of</strong> FRPs Use in Civil Engineering<br />

6.1 Structural Reinforcement<br />

Composite system consisting <strong>of</strong> carbon fiber, aramid or glass impregnated in-situ with the polymer matrix, is<br />

used for the reinforcement <strong>of</strong> elements in concrete, masonry, wood and steel. Among many other applications,<br />

concrete and masonry walls may be strengthened to better resist seismic and wind loads, concrete pipes, silos and<br />

tanks may be lined with FRP to resist higher internal pressures. Glass FRP (GFRP) and Aramid FRP (AFRP) are<br />

excellent for seismic upgrades. In cases where stresses are sustained in the FRP (such as in bending and shear<br />

strengthening), GFRP is avoided because <strong>of</strong> creep rupture effects. Carbon FRP is much more suitable and<br />

durable in these situations.<br />

6.2 Reinforcement in Corrosive Environment<br />

Corrosion <strong>of</strong> steel reinforcements reduces the durability <strong>of</strong> concrete structural elements, leading to serious<br />

maintenance costs. Fields <strong>of</strong> application for GFRP products in corrosive environment are in: harbors, seaside<br />

walkways, <strong>of</strong>fshore structures, water treatment plants, sewage structures, rehabilitation <strong>of</strong> final lining <strong>of</strong> tunnels.<br />

6.3 Synthetic Fibers for FRC<br />

GFRP composite fibers are technically very good alternative to standard fibers for concrete reinforcement made<br />

<strong>of</strong> steel or plastic materials. They have high tensile strength, can be distributed evenly in the concrete without<br />

compromising the workability <strong>of</strong> the same, have high resistance to chemical corrosion and electrostatic, are nonmagnetic,<br />

have lightness <strong>of</strong> handling and deployment.<br />

6.4 Structural Reinforcement <strong>of</strong> Historical Buildings<br />

For several years, innovative materials are applied in the architectural renovation <strong>of</strong> historic buildings. FRP<br />

materials (carbon, aramid and glass) are an alternative consolidated in recovery and reinforcement <strong>of</strong> buildings<br />

<strong>of</strong> traditional value. The lightness combined with high mechanical performance makes it particularly effective<br />

when compliance with the existing and little invasiveness is essential for the success <strong>of</strong> the intervention.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

6.5 Shear Connectors<br />

In concrete paving expansion joints are necessary in order to control the propagation <strong>of</strong> cracks caused by the<br />

withdrawal <strong>of</strong> the concrete and the thermal expansion. Joints artificially create lines <strong>of</strong> weakness in the concrete.<br />

Connectors’ fiberglasses return shear strength along the joint.<br />

6.6 Connectors for Pre-cast Concrete<br />

The growing need to produce pre-cast high performance, led the industry to turn to technology for synthetic<br />

elements or FRP <strong>of</strong> high durability, low costs with excellent isolation heat.<br />

7. Scope <strong>of</strong> FRP in India<br />

The overall composites market in India is relatively small, compared to per capita consumption in other parts <strong>of</strong><br />

the world. A few years ago consumption level <strong>of</strong> composites in India was only about 30,000 MT, as compared to<br />

about 2,00,000 MT in many other parts <strong>of</strong> the world including China. There is enormous scope <strong>of</strong> use <strong>of</strong> FRP in<br />

India, because <strong>of</strong> seismically deficient buildings, long coast line and long monsoon season pressing the use <strong>of</strong><br />

non-corrosive FRP. Traditional materials, such as wood, are in short supply. There are a few examples <strong>of</strong> FRP<br />

application for retr<strong>of</strong>itting before Gujarat earthquake (<strong>20</strong>01) and after this earthquake only, the technique is<br />

gaining attention in India. However, the same is not to the extent warranted by potential <strong>of</strong> the FRP that exist. As<br />

the material is still considered relatively new in India, most <strong>of</strong> the works had been carried out in accordance to<br />

available guidelines and published literature.In spite <strong>of</strong> all the potential <strong>of</strong> India, rapid use <strong>of</strong> FRP in civil<br />

infrastructure is difficult because <strong>of</strong> local code restrictions. There is an urgent need to develop Indian standards<br />

for use <strong>of</strong> FRP and more production facilities. With less than 5% <strong>of</strong> the Asian FRP market, there is plenty <strong>of</strong><br />

room for growth in India.To improve this situation, Civil Engineering and their extension programs must provide<br />

sufficient training on unique features <strong>of</strong> FRPs so that engineers could design or specify them in construction. At<br />

this juncture, there is a need <strong>of</strong> Government- Industry-Institute partnership to exploit full potential <strong>of</strong> FRP. The<br />

increase in use <strong>of</strong> FRP for retr<strong>of</strong>itting is inevitable because <strong>of</strong> its potential.<br />

7.1 Research and Developments <strong>of</strong> FRP in India<br />

In India, in the field <strong>of</strong> education and research related to FRP in construction, IIIts, IISc, Structural Engineering<br />

Research Center (SERC) Chennai, FRP institute Chennai, Indian Society for Advancement <strong>of</strong> Materials and<br />

ProcessEngineering (ISAMPE) (headquarter- Bangalore), Research Design and Standards Organization (RDSO)<br />

under the Ministry <strong>of</strong> Railways at Lucknow, <strong>Technology</strong> Information Forecasting and Assessment Council<br />

(TIFAC) a unit <strong>of</strong> DST, Composites <strong>Technology</strong> Centre (at IITM) are among others, participating actively. For<br />

the composites industry a monthly magazine-‘FRP Today’ is being published in India since the year <strong>20</strong>00. The<br />

Department <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Government <strong>of</strong> India, in collaboration with the universities, is<br />

developing standards for FRP in construction. Focus is placed on the rate <strong>of</strong> degradation <strong>of</strong> glass FRP in view <strong>of</strong><br />

the South Asian environment and the concrete mix typically used in India. The application is targeted at<br />

corrosion damaged structures and seismic retr<strong>of</strong>itting. Composites <strong>Technology</strong> Centre (formerly -Fiber<br />

Reinforced Plastics research Centre) was established in <strong>19</strong>74 at IITM as an interdisciplinary Centre for carrying<br />

out teaching, research, design and development in the field <strong>of</strong> composite materials and their applications. The<br />

Centre was renamed as Composites <strong>Technology</strong> Centre in <strong>19</strong>97.<br />

7.2 Civil Engineering Applications <strong>of</strong> FRP in India<br />

There are many Indian projects to the credit <strong>of</strong> FRP systems by various companies like Fyfe (India) Pvt Ltd,<br />

Fosroc Chemicals (India) Pvt Ltd, Krishna Conchem Products Pvt Ltd, BASF, Sika India Pvt Ltd etc.There are<br />

now well developed design methods for many applications like RC structures using FRP bars, but perhaps there<br />

has been no application so far, because there is not much demand in construction compared to FRP<br />

strengthening. Many projects have been completed by above mentioned companies from <strong>19</strong>99 to strengthen the<br />

deteriorated structures <strong>of</strong> importance.<br />

Some <strong>of</strong> the representative Civil Engineering applications <strong>of</strong> FRP in India in the beginning include:<br />

Structural strengthening <strong>of</strong> circular columns and flat slabs at Shah House, Worli, Mumbai in August <strong>19</strong>99, Slab<br />

strengthening at Sudhakar building Mumbai in September <strong>19</strong>99, Structural strengthening <strong>of</strong> various MTNL<br />

buildings Mumbai in <strong>20</strong>00, Structural strengthening/ protection/corrosive protection <strong>of</strong> St. Thomas school New<br />

Delhi in <strong>20</strong>01, Localized strengthening <strong>of</strong> beam-column junctions at Reserve Bank <strong>of</strong> India Staff quarters<br />

Mumbai in <strong>20</strong>02, Strengthening <strong>of</strong> columns due to low grade concrete in IT S<strong>of</strong>tware Park Hyderabad in <strong>20</strong>04<br />

etc. There are many strengthening works going on in Hyderabad, Bangalore and Pune. There are Indian<br />

applications <strong>of</strong> Tyfo Fiber wrap System in Bridges, water tanks, brick walls in Goa, Delhi and Ahmadabad.<br />

There are some Indian projects where Nitowrap by Fosroc and Sikawrap from Sika India Pvt Ltd has been used.<br />

One <strong>of</strong> the major applications <strong>of</strong> FRP has been in earthquake damaged structures in Gujarat.<br />

461


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

8. Disposal and Recycling <strong>of</strong> FRP<br />

Plastics pose a particular challenge in recycling processes because they are derived from polymers and<br />

monomers that <strong>of</strong>ten cannot be separated and returned to their virgin states, for this reason not all plastics can be<br />

recycled for re-use. Fiber reinforced plastics and their matrices share these disposal and environmental concerns.<br />

In addition to these concerns, the fact that the fibers themselves are difficult to remove from the matrix and<br />

preserve for re-use means FRP amplify these challenges. FRP are inherently difficult to separate into base a<br />

material that is into fiber and matrix, and the matrix into separate usable plastic, polymers, and monomers. These<br />

are all concerns for environmentally informed design today, but plastics <strong>of</strong>ten <strong>of</strong>fer savings in energy and<br />

economic savings in comparison to other materials, also with the advent <strong>of</strong> new more environmentally friendly<br />

matrices such as bio plastics and uv-degradable plastics, FRP will similarly gain environmental sensitivity.<br />

9. Conclusion<br />

The Civil Engineering structures continues to face numerous challenges, i.e., increasing growth demands and<br />

heavier loads as well as trying to preserve aging and rapidly deteriorating structural elements. As we enter into a<br />

new millennium, our strategy is to stay ahead <strong>of</strong> the structural deterioration curve by focusing on the use <strong>of</strong><br />

emerging high performance structural materials and innovative quality designs for more durable and reliable<br />

structures.<br />

Through this pursuit and among many other emerging new materials, the fiber reinforced polymer (FRP)<br />

composite technology has been demonstrated with great success for structural applications. It has been found that<br />

the characteristics <strong>of</strong> a composites element or system can be tailored and designed to meet any desired<br />

specifications. The highly corrosion and fatigue resistance composites materials are making inroads into the civil<br />

infrastructure industry. These outstanding composites are among the leading materials in structural engineering<br />

applications today. The text within this volume will support the following conclusions:<br />

• Fiber reinforced composite plate bonding <strong>of</strong>fers significant advantages over steel plate bonding for the<br />

vast majority <strong>of</strong> strengthening applications.<br />

• Fiber reinforced composite is so versatile that the range <strong>of</strong> applications for which external reinforcing is<br />

appropriate will increase significantly.<br />

• No construction or repair method involving structural analysis and deterioration mechanisms can be<br />

said to be completely understood, including all <strong>of</strong> those currently in everyday use. However, FRP has<br />

been sufficiently researched to enable the techniques to be applied confidently on site, providing care is<br />

taken.<br />

• The masonry walls strengthened with carbon-FRP composites results in increase <strong>of</strong> 24 times the<br />

unreinforced capacity in vertical bending and 7 times in horizontal bending. Use <strong>of</strong> FRP is greatly<br />

accepted and established as structural reinforcement (<strong>of</strong> historical buildings, in corrosive environment<br />

etc.), connectors for shear, pre-cast etc.<br />

10. References<br />

[1] Nangia Sangeeta, Srikanth Gudavalli, Mittal Atul & Biswas Soumitra, “Composites in civil engineering”,<br />

google search<br />

[2] Shrivastava Ravikant, “Earthquake damages tobuildings and their retr<strong>of</strong>itting and restoration”;Civil<br />

Engineering and Construction Review, vol.14, no. 1, January <strong>20</strong>01, pp 23-28.<br />

[3] Shrivastava Ravikant, Gupta Uttamasha andChoubey U B, “FRP the boon for retr<strong>of</strong>itting <strong>of</strong>RC structures”,<br />

proceedings <strong>of</strong> 23rd NationalConvention <strong>of</strong> Civil Engineers and NationalSeminar, Institution <strong>of</strong> Engrs (India),<br />

JabalpurLocal Centre, India, <strong>20</strong>07, pp 150-153.<br />

[4] Shrivastava Ravikant, Uttamasha Gupta and U BChoubey “FRP in construction: Indian scenario”,ISSE<br />

Journal, India, In press.<br />

[5] Mukherjee Abhijit and Joshi Mangesh, “Recentadvances in repair and rehabilitation <strong>of</strong> RCCstructures with<br />

nonmetallic fibers”, google search,<br />

[6] Shrivastava Ravikant, Gupta Uttamasha and Choubey U B, “Research, Education and Application <strong>of</strong> FRP in<br />

Civil Engineering”, International journal <strong>of</strong> recent trends in Engineering, Vol-I<br />

[7] Sireg S.P.A, “FRP and Civil Engineering”, www.sireg.it/en/civil-engineering/products-civil-eng/<br />

[8] “Polymers in Civil engineering”,www.engr.psu.edu/ce/courses/.../CE336-12-Polymer-Composites.ppt<br />

[9] “Advances <strong>of</strong> FRP Composites in Civil Engineering”, www.springer.com › Home › Engineering › Civil<br />

Engineering<br />

462


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Analysis <strong>of</strong> the Depth <strong>of</strong> Penetration using Automatic Robotic Arc Welding<br />

System<br />

Anees Ahmed 1 , Dr. Sanjeev Kumar 2 and Ruchika Singh 3<br />

1 Student (M.Tech), Automation & Robotics, Ajay Kumar Garg Engineering College, Ghaziabad<br />

2 Associate Pr<strong>of</strong>essor, Deptt. <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> UST, Faridabad, Haryana<br />

3 Associate Pr<strong>of</strong>essor, Deptt. <strong>of</strong> EN, Krishna Institute <strong>of</strong> Engineering & <strong>Technology</strong>, Ghaziabad<br />

Abstract<br />

This paper presents an automatic arc welding system used for the analysis <strong>of</strong> the depth <strong>of</strong> penetration on<br />

different specimens welded at different welding speed. Automatic arc welding system has been designed using<br />

mainly a six axes vertically articulated robot, Jigs/fixtures Programmable Logic Controller (PLC), Human<br />

Machine Interface and electrical control panel. Electrical control panel has been used to control the arc welding<br />

robot and jigs/fixtures. The basic system controlling diagram has been presented with I/O address assignment<br />

table. The design <strong>of</strong> jigs/fixtures has been carried out and selection <strong>of</strong> servo motors/drives, arc welding robot,<br />

PLC has been made. In this paper, a system has been presented and demonstrated to assist and simplify<br />

industrial welding procedures. The welding current, arc voltage, welding speed and heat input rate are chosen<br />

as welding parameters. Analysis <strong>of</strong> depth <strong>of</strong> penetration <strong>of</strong> welded specimen has been carried out varying the<br />

welding speed. The depth <strong>of</strong> penetration was measured for each specimen (butt joint) after each weld cycle by<br />

varying the welding speed. A brief overview <strong>of</strong> actual state <strong>of</strong> the art about robotic welding technology is<br />

presented. HMI has been used to monitor welding process and to display the corresponding status.<br />

Keywords: Programmable Logic Controller, Arc Welding Robot, Jigs and Fixtures, Human Machine Interface.<br />

1. Introduction<br />

The MIG/MAG welding is also known as gas metal arc welding process, uses the heat <strong>of</strong> electric arc to melt an<br />

electrode wire and a metallic component to be welded. The fusion is carried out under the protection <strong>of</strong> gas or a<br />

mixture <strong>of</strong> gases in order to prevent the contamination with some gases <strong>of</strong> the atmosphere (oxygen, nitrogen and<br />

hydrogen). MIG is used chiefly in the welding <strong>of</strong> stainless steel, aluminum alloys and titanium alloys while<br />

MAG is used in carbon steel. In manual arc welding, the labor intensity is high, welding inefficient and difficult<br />

to guarantee the weld quality due to the variation in arc length and welding speed. The first prototype <strong>of</strong> an<br />

industrial robot was used in Ford in <strong>19</strong>61 from Unimation. [1]<br />

Welding process emits sound, light and electromagnetic radiation to surrounded space [2]. Manual welding<br />

process is also dangerous for health and safety. Robotic arc welding system has been used which is controlled by<br />

PLC system in order to analyze the depth <strong>of</strong> penetration by varying the welding speed. After getting the optimum<br />

penetration, the welding speed is fixed to perform welding on that particular type <strong>of</strong> specimen. CAD interface<br />

could also be used for fast and simple robot manipulator programming [3].<br />

Jigs and fixtures played major role in this work for positioning and holding the work piece which is to be weld<br />

[4]. HMI has been used to interface the human operator with the machine for setting different input parameters<br />

and getting different machine status such as faults, weld cycle, jig1 and jig2 status, gas ok, air ok, welding torch<br />

tip and home sensor status.<br />

2. MECHANICAL DESIGN<br />

Jigs and fixtures are designed for holding and positioning purpose. In this work, two jigs with fixtures are<br />

designed with same dimensions.<br />

Fig. 1. Schematic <strong>of</strong> Jigs/fixtures<br />

463


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

In case <strong>of</strong> mass production, there is an aim to have high productivity and interchangeability to facilitate easy<br />

assembly. This necessitates production devices to increase the rate <strong>of</strong> manufacture and inspection devices to<br />

speed up inspection procedure. For this purpose there is a need <strong>of</strong> Jigs and Fixtures. Jigs are provided with tool<br />

guiding elements and fixtures hold the work piece securely in the correct position with respect to the machine or<br />

robotic arm.<br />

The jig and fixture is the basic equipment in the automobile industry for machining process and mechanical<br />

assembly. Due to the advancement in the CAD/CAM and wide application <strong>of</strong> CNC machine forced to develop<br />

automatic Jigs/Fixtures system. With the increase in the production system Computer Aided Fixture Design<br />

(CAFD) is used to design the intelligent jig and fixtures. Fixture planning is an important part <strong>of</strong> any<br />

manufacturing system because designing and fabricating <strong>of</strong> fixtures can take up to 10-<strong>20</strong>% <strong>of</strong> total cost <strong>of</strong> the<br />

manufacturing system. Computer-Aided Fixture Planning (CAFP) has been used to improve the fixture<br />

designing simultaneously used to reduce the lead-time and human interaction in fixture planning [5, 6].<br />

Fig. 2. Jigs/Fixtures with Arc Welding Robotic Arm<br />

3. CONTROL SYSTEM<br />

A. The Control Circuit <strong>of</strong> Automatic Arc Welding System<br />

The automatic arc welding system uses the PLC system for controlling the robotic arm, jigs/fixtures and other<br />

devices like servo motor. A combined control panel is designed for controlling the system. The control panel<br />

consists <strong>of</strong> power supply (24VDC, 4.5A), PLC (48 digital inputs/outputs), relay boards (8-channels), MCBs<br />

(single and double pole), isolation transformer (3kVA, 415V, 2 Ph Input and <strong>20</strong>0V, 2<strong>20</strong>V, 100V Outputs), servo<br />

drives, bus duct, cooling fan, connectors etc. In this work, Control Techniques’ two Epsilon EP servo drives<br />

(EP<strong>20</strong>4-100-EN00) and servo motors (XV-13051) are used.<br />

Motoman’s 6-axis vertically articulated arc welding robot (MA-1400) has been used, which has its own<br />

dedicated controller for controlling the motion <strong>of</strong> different links, welding parameters and wire feed.<br />

Fig. 3. Electrical Control Panel<br />

Remote control panels are used where push buttons and selector switches are used for Hold, Cycle Ready,<br />

emergency, Cycle start push buttons and also a selector switch for auto/manual selection. This system can be<br />

operated either by the buttons on the panel or by HMI (touch screen). PLC receives the digital signal either from<br />

HMI or from the buttons on the panel. According to the received signals and internal procedure (program),<br />

output signals <strong>of</strong> the PLC controls the robot weld cycle, fixtures holding/un-holding, servo motor controlling<br />

464


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

(jigs angular motion or positioning) and simultaneously reflect the results and status on the HMI. HMI has been<br />

used to interface the operator to the machine and also used to modify the parameters <strong>of</strong> the system. [7]The 6-axis<br />

vertically articulated robot has been used for welding the work piece on the jig, fixed by fixtures. Robot welds<br />

the work piece in different cycle at different angles which is accomplished by the angular movement <strong>of</strong> the jigs<br />

using servo motor with gear.<br />

The welding torch and the wire feed have been controlled by the robot’s dedicated controller. The welding torch<br />

reaches the destination and welds the job efficiently with greater accuracy. Generally a pair <strong>of</strong> jigs and fixtures is<br />

used for one robot in the cell so that robot can perform its welding cycle while the operator is unloading the<br />

previously welded assembly and loaded the components into the holder <strong>of</strong> the fixture for the next cycle. Like this<br />

robot can be utilized with greater productivity.<br />

B. PLC Selection and Inputs/Outputs Addressing<br />

Mitsubishi’s FX3U-64MR PLC has been used with extension input module FX2N-16Ex and output module<br />

FX2N-16EYR for the system which has 48 digital inputs/outputs. This version <strong>of</strong> PLC is <strong>of</strong> compact type with<br />

its entire modules on single chassis like Power Supply Module, CPU Module and Input/Outputs Module. In<br />

FX3U we can use maximum <strong>of</strong> 256 I/Os. We can also have facility to connect the remote I/O module. FX3U<br />

comes with internal memory <strong>of</strong> 64K steps. For high speed positioning FX3U is designed with six high speed<br />

counters that can each count up to 100 KHz simultaneously per channel. Externally interfacing <strong>of</strong> other modules<br />

such as high speed and pulse train counters is possible with FX3U PLC.<br />

TABLE I Input List For Robot Cell-Sub Assembly Left Hand And Right Hand Welding Fixture<br />

S.No. Inputs Assignment Description Type<br />

1 X0 Emergency Stop Emergency Push Button<br />

2 X1 Auto/Manual S/S Selector Switch<br />

3 X2 Weld On/Off S/S Selector Switch<br />

4 X3 Gas Ok Push Button<br />

5 X4 Air Ok Push Button<br />

6 X5 Component Ok Fix-1 Push Button<br />

7 X6 Spare Spare<br />

8 X7 Spare Spare<br />

9 X10 Cycle Start Opb-1 Push Button<br />

10 X11 Hold Opb-1 Push Button<br />

11 X12 Emergency Opb-1 Emergency Push Button<br />

12 X13 Spare Spare<br />

13 X14 Component Ok Fix-2 Push Button<br />

14 X15 Spare Spare<br />

15 X16 Spare Spare<br />

16 X17 Cycle Start Opb-2 Push Button<br />

17 X<strong>20</strong> Hold Opb-2 Push Button<br />

18 X21 Emergency Opb-2 Emergency Push Button<br />

<strong>19</strong> X22 Spare Spare<br />

<strong>20</strong> X23 Spare Spare<br />

21 X24 Home Position Servo-1 Servo Drive-1<br />

22 X25 1st Position <strong>of</strong> Servo-1 Servo Drive-1<br />

23 X26 2 nd Position <strong>of</strong> Servo-1 Servo Drive-1<br />

24 X27 3 rd Position <strong>of</strong> Servo-1 Servo Drive-1<br />

25 X30 Spare Spare<br />

26 X31 Home Position Servo-2 Servo Drive-2<br />

27 X32 1st Position <strong>of</strong> Servo-2 Servo Drive-2<br />

28 X33 2 nd Position <strong>of</strong> Servo-2 Servo Drive-2<br />

29 X34 3 rd Position <strong>of</strong> Servo-2 Servo Drive-2<br />

30 X35 3 rd Position <strong>of</strong> Servo-2 Servo Drive-2<br />

465


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

31 X36 Robot Input 17 Robot Input 17<br />

32 X37 Robot Input18 Robot Input18<br />

33 X40 Robot Input-1 Robot Input-1<br />

34 X41 Robot Input-2 Robot Input-2<br />

35 X42 Robot Input-3 Robot Input-3<br />

36 X43 Robot Input-4 Robot Input-4<br />

37 X44 Robot Input-4 Robot Input-4<br />

38 X45 Robot Input-6 Robot Input-6<br />

39 X46 Robot Input-7 Robot Input-7<br />

40 X47 Robot Input-8 Robot Input-8<br />

41 X50 Robot Input-9 Robot Input-9<br />

42 X51 Robot Input-10 Robot Input-10<br />

43 X52 Robot Input-11 Robot Input-11<br />

44 X53 Robot Input-12 Robot Input-12<br />

45 X54 Robot Input-13 Robot Input-13<br />

46 X55 Robot Input-14 Robot Input-14<br />

47 X56 Robot Input-15 Robot Input-15<br />

48 X57 Robot Input-16 Robot Input-16<br />

TABLE II Output List For Robot Cell-Sub Assembly Left Hand And Right Hand Welding Fixture<br />

S.No. Outputs Assignment Description Type<br />

1 Y0 Robot Home LED LED 1<br />

2 Y1 Fixture-1 Home LED LED 2<br />

3 Y2 Fixture-2 Home LED LED 3<br />

4 Y3 Spare Spare<br />

5 Y4 Spare Spare<br />

6 Y5 Spare Spare<br />

7 Y6 Spare Spare<br />

8 Y7 Spare Spare<br />

9 Y10 RB External Start<br />

10 Y11 RB Call Master<br />

11 Y12 RB Weld ON/OFF<br />

12 Y13 RB IN-1 Robot Input<br />

13 Y14 RB IN-2 Robot Input<br />

14 Y15 RB IN-3 Robot Input<br />

15 Y16 RB IN-4 Robot Input<br />

16 Y17 RB IN-5 Robot Input<br />

17 Y<strong>20</strong> RB IN-6 Robot Input<br />

18 Y21 RB IN-7 Robot Input<br />

<strong>19</strong> Y22 RB IN-8 Robot Input<br />

<strong>20</strong> Y23 RB IN-13 Robot Input<br />

21 Y24 RB IN-14 Robot Input<br />

22 Y25 RB IN-9 Robot Input<br />

23 Y26 RB IN-10 Robot Input<br />

24 Y27 RB IN-15 Robot Input<br />

25 Y30 Servo Enable-1<br />

26 Y31 Servo Enable-2<br />

27 Y32 1st Position Holder Servo-1 Servo Drive-1<br />

28 Y33 2nd Position Holder Servo-1 Servo Drive-1<br />

29 Y34<br />

Home Position Holder<br />

Servo-1<br />

Servo Drive-1<br />

30 Y35 3rd Position Holder Servo-1 Servo Drive-1<br />

466


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

31 Y36 Hold Indicator LED4<br />

32 Y37 Cycle Start Indicator LED5<br />

33 Y40 1st Position Leg Servo-2 Servo Drive-2<br />

34 Y41 2nd Position Leg Servo-2 Servo Drive-2<br />

35 Y42 3rd Position Leg Servo-2 Servo Drive-2<br />

36 Y43 Home Position Leg Servo-2 Servo Drive-2<br />

37 Y44 Spare Spare<br />

38 Y45 Hold Indicator LED6<br />

39 Y46 Cycle Start Indicator LED7<br />

40 Y47 Spare Spare<br />

41 Y50 Spare Spare<br />

42 Y51 Spare Spare<br />

43 Y52 Spare Spare<br />

44 Y53 Spare Spare<br />

45 Y54 Spare Spare<br />

46 Y55 All Emergency Output<br />

47 Y56 System All Holding Output<br />

48 Y57 Spare Spare<br />

A. PLC Control System<br />

This system has been designed to work both in manual mode and in auto mode. In manual mode, operator has to<br />

run the machine manually. In the manual mode, by pressing certain button the operator can control the welding<br />

torch up, down, forward or back, to ignite and rotate the work-piece clockwise or anticlockwise by rotating the<br />

jigs manually. All weld cycle <strong>of</strong> the robot and positioning <strong>of</strong> the jigs accordingly can be done manually by<br />

pressing different buttons on the control panel. But in automatic mode, operator can press the home position<br />

buttons for robot and jigs, fix the work pieces on the jigs/fixtures and then the component ok button on the<br />

control panel then the system can automatically complete the subsequent weld tasks on both the jigs.<br />

The fitter operator fixes the work-piece on the positioning machine (Jigs/fixtures) and locates the positioning<br />

machine horizontally (0°) which is accomplished by using a proximity sensor for home sensing. After system<br />

power initialization, rotate the auto/ Manual switch to automatic mode, then press the component ok button,<br />

robot home button, servo motor home button, cycle ready button and finally the Start button. After pressing the<br />

weld start button, robot start welding the work piece in different weld cycle at different angles according to the<br />

jigs positioning. Robot first completes its weld cycle at jig 1 and does the same process at the jig 2. Encoders are<br />

used at the shaft <strong>of</strong> the jigs which give the feedback to the servo drive which then controls the servo motor<br />

according to the procedure put in the PLC in ladder logic programming.<br />

Fig. 4: Specimen with Closed Butt Joint<br />

The welding torch and link movement is adjusted to proper position automatically according to the teach<br />

program kept in the dedicated controller <strong>of</strong> the arc welding robot. Robot completes six different weld cycles on<br />

jig 1 and then performs the same sequence <strong>of</strong> operation on jig 2.<br />

In addition to control by the buttons on the control panel, the automatic arc welding machine can also be<br />

controlled via touch screen. Delta’s 7 inch color touch screen (HMI) has been used to monitor welding process<br />

and display the corresponding status. The HMI interface provides three windows: parameters setting window,<br />

alarm window, function keys window.<br />

467


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4. METALLOGRAPHY AND CALCULATION<br />

Metallography<br />

Metallography is used to reveal the microstructure <strong>of</strong> metals, which is affected by alloy composition and<br />

processing conditions including cold working, heat treatment and welding. Metallography surface should be flat<br />

and free from scratches, stains, and other imperfections which tend to mar the surface, contain all non-metallic<br />

inclusions intact, show no chipping or galling <strong>of</strong> hard and brittle intermetallic compounds and be free from all<br />

traces <strong>of</strong> disturbed metal. A metallographic specimen reveals inclusions, porosity, cracks, intergranular<br />

corrosion, surface conditions, etc. After metallography, chemical etching is performed with an acid or basic<br />

chemical solution on specimen.<br />

This process is performed to get information on variations in structure, such as grain size, flow lines, columnar<br />

structure, dendrites, etc., variations in chemical composition as evidenced by segregation, carbide and ferrite<br />

banding, coring, inclusions, and depth <strong>of</strong> carburization or decarburization also show the presence <strong>of</strong><br />

discontinuities and voids, such as seams, laps, porosity, flakes, bursts, extrusion rupture, cracks.<br />

Metallography and etching process also used to study the weld structure, definition <strong>of</strong> weld penetration, dilution<br />

<strong>of</strong> filler metal by base metals, entrapment <strong>of</strong> flux, porosity, and cracks in weld and heat-affected zones, etc.<br />

In welding process, weldments cut perpendicular to the direction <strong>of</strong> welding to measure and study weld<br />

penetration, heat affected zone, structure, etc. Careful preparation is usually rewarded with highly detailed<br />

structure giving a large amount <strong>of</strong> information. Welds involving dissimilar metals will produce problems in<br />

etching. The best method is to etch the least corrosion resistant portion first, and the more resistant portion<br />

afterward. Occasionally an intermediary etchant may be required. The boundaries between etched and unetched<br />

portions will give an idea <strong>of</strong> weld penetration and dilution.<br />

In this work, low alloy steel pipes are used for welding. For measuring the depth <strong>of</strong> penetration <strong>of</strong> weldments,<br />

etchant is prepared by solution <strong>of</strong> hydrochloric acid (HCL) and distilled water (HCL-50ml and H 2 O-50ml). After<br />

preparing solution different specimens are dipped in it at 60 0 to 80 0 C for 30 to 45 minutes. [9]<br />

5. Calculations<br />

In arc welding process, welding current is the most influential variable which is used to control the heat intensity<br />

<strong>of</strong> the electrode. Welding voltage is the potential difference between electrode tip and the surface <strong>of</strong> the<br />

specimen. Welding voltage is very much responsible for the depth <strong>of</strong> the penetration. Welding speed is defined<br />

as the rate <strong>of</strong> travel <strong>of</strong> the electrode along the seam. Varying welding speed, maintaining constant current and<br />

constant voltage results in variation in the depth <strong>of</strong> penetration.<br />

Average Terminal Voltage = <strong>20</strong> V (constant)<br />

Average Welding Current = 100 A (constant)<br />

Speed <strong>of</strong> Welding =<br />

Heat Input Rate or Arc Energy =<br />

V<br />

I<br />

v<br />

Arc Voltage in Volts<br />

Welding Current in Amperes<br />

Speed <strong>of</strong> Welding in mm/min<br />

joules/mm<br />

Only arc time varied to get the variation in heat input rate which directly affects the depth <strong>of</strong> penetration. [8]<br />

Different specimens <strong>of</strong> same dimension welded at different weld speed and cut perpendicular to the direction <strong>of</strong><br />

welding. Macroetching has been used for revealing the large-scale structure <strong>of</strong> a welded specimen, that is,<br />

structure visible with the unaided eye, by etching an appropriately prepared surface. All cut sections <strong>of</strong> specimen<br />

dipped in etchant for 45 minutes for revealing the microstructure <strong>of</strong> metal. Readings has been measured using<br />

venire caliper by measuring the dilution <strong>of</strong> filler metal by base metal. Macroetching reveals the macrostructure<br />

for the examination with the unaided eye or at a magnification <strong>of</strong> 50× or less, for more detailed study <strong>of</strong> the<br />

specimen, microetching has to be used in which magnification <strong>of</strong> 50x or higher is used.<br />

468


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

6. RESULTS AND DISCUSSION<br />

This system has been designed to perform arc welding automatically with maintained depth <strong>of</strong> penetration at<br />

optimum welding speed. Experiment has been carried out to measure the depth <strong>of</strong> penetration at different<br />

welding speed. This setup is PLC-controlled automatic arc welding system, which is simple, easy maintenance<br />

and effective in increasing the production with efficiency. This machine significantly reduced labor intensity and<br />

health/safety hazards to operator with good economic returns increasing the production rate.<br />

Readings <strong>of</strong> depth <strong>of</strong> penetration has been measured and given in table below which has been measured through<br />

measuring instrument after cutting all the welded specimens perpendicular to the direction <strong>of</strong> welding to analyze<br />

the depth <strong>of</strong> penetration. Graph is plotted between welding speed and penetration.<br />

S.No.<br />

TABLE III The Depth Of Penetration Of The Welding Specimens<br />

Average<br />

Welding<br />

Voltage<br />

(V)<br />

Average<br />

Welding<br />

Current<br />

(A)<br />

Welding<br />

Speed<br />

(mm/min)<br />

Heat input<br />

Rate<br />

(J/mm)<br />

Penetration<br />

(mm)<br />

1. <strong>20</strong> 100 94.84 1265.28 4.1<br />

2. <strong>20</strong> 100 102.34 1172.56 4.2<br />

3. <strong>20</strong> 100 110.43 1086.66 4.4<br />

4. <strong>20</strong> 100 121.28 989.44 4.3<br />

5. <strong>20</strong> 100 129.49 926.71 4.2<br />

The system can replace the human performed welding process at higher speed and quality. Alarm window has<br />

been used to set different alarms in case <strong>of</strong> job completion or in case <strong>of</strong> any fault. When the system is running<br />

error, corresponding dynamic screens pop up. Finally function key window is used to perform various actions by<br />

touching the touch screen.<br />

This work is also used to promote the welding automation and adopt new technologies to realize green welding<br />

and eliminate occupational hazards <strong>of</strong> welding to the operator. It has been emphasized that the application <strong>of</strong> the<br />

developed system is effective for the joining <strong>of</strong> steel pipes and successfully applied to the automobile chassis<br />

frame.<br />

Fig. 5. Welding Speed V/S Penetration<br />

469


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

7. CONCLUSION<br />

In this study, a automatic robotic arc welding system has been deigned to study the effect <strong>of</strong> welding speed on<br />

the depth <strong>of</strong> penetration and the deepest depth <strong>of</strong> penetration obtained is 4.4 mm at the speed <strong>of</strong> 110.43 mm/min.<br />

Hence it can be concluded that increasing the speed <strong>of</strong> travel and maintaining constant arc voltage and current will<br />

increase penetration but at an optimum speed, penetration will be maximum. The welding torch speed has to be<br />

fixed at this speed to attain maximum penetration otherwise results decrease in penetration. Finally it is<br />

concluded that robotic arc welding system is capable to maintain the arc length and welding speed to get the<br />

weld quality.<br />

REFERENCES<br />

[1] Gunnar Bolmsjo, Magnus Olsson and Per Cederberg “Robotic Arc Welding-Trends and Developments for<br />

Higher Autonomy” Industrial Robot: An International Journal, vol. 29, pp. 98-104, <strong>20</strong>02<br />

[2] K.Luksa and Z.Rymarski “Collection <strong>of</strong> Arc Welding Process Data” , vol. 17, pp. 377-380, <strong>20</strong>06<br />

[3] J.Norberto Pires, T.Godinho and P.Ferreira “CAD Interface for Automatic Robot Welding Programming”<br />

Industrial Robot: An International Journal, vol. 31, pp. 71-76, <strong>20</strong>04<br />

[4]. J. Norberto Pires, A. Loureiro, P. Ferreira, B. Fernando and J. Margado, “Using Object Oriented and<br />

Distributed S<strong>of</strong>tware to Assist Industrial Robot Welding Applications”, Submitted to IEEE Robotics and<br />

Automation Magazine, pp. 1-24, <strong>20</strong>01<br />

[5]. Kailing Li, Ran Liu, Guiheng Bai, Peng Zhang “Development <strong>of</strong> an Intelligent Jig and Fixture Design<br />

System”, pp. 1-5, <strong>20</strong>06<br />

[6]. Xiumei Kang and Qingjin Peng “Recent Research on Computer-Aided Fixture Planning” Recent Patents on<br />

Mechanical Engineering, vol. 2, pp. 8-18, <strong>20</strong>09<br />

[7]. Ai-Min Li, Chuan-Hui Zhang, Hai-Lin Li, Zhi-Yang Xu, Xiao-Hui Chen, Guang-Le Qin, Sheng-Wei Ye,<br />

“Design <strong>of</strong> Automatic Welding Machine Based on PLC”, Fourth International Conference on Intelligent<br />

Computation <strong>Technology</strong> and Automation, <strong>20</strong>11, pp. 627-630, <strong>20</strong>11<br />

[8] S.P. Tiwari, Ankur Gupta, Jyoti Prakash, “Effect <strong>of</strong> Welding Parameters on the Weldability <strong>of</strong> Material”,<br />

International journal <strong>of</strong> Engineering <strong>Science</strong> and <strong>Technology</strong>, vol. 2(4), pp. 512-516, <strong>20</strong>10<br />

[9] Brent L. Adams et al., “Metallography and Microstructures” ASM International Publication, Vol. 9, <strong>20</strong>04.<br />

470


1<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Application <strong>of</strong> Taguchi Method and Grey Relational Analysis in<br />

Optimization <strong>of</strong> Machining Processes: a Review<br />

Parveen Kamboj 1 , Sunil Kumar 2 ,and Kamal Jangra 3<br />

JCDM College <strong>of</strong> Engieering, Sirsa, Haryana<br />

.<br />

2 Yadavindra College <strong>of</strong> Engineering, Guru Kashi Campus, Talwandi Sabo, Bathinda, Punjab<br />

3<br />

<strong>YMCA</strong> Univrsity <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad, Haryana<br />

E-mail: parveensama@india.com<br />

Abstract<br />

Optimization <strong>of</strong> process parameters is a key objective <strong>of</strong> manufacturers for generating components with high<br />

productivity and low cost. Taguchi method is an effective tool for optimizing process parameters for single<br />

performance characteristic only, while Grey relational analysis (GRA) can be combined with Taguchi method<br />

for optimizing multiple-performance characteristics. This paper presents the application <strong>of</strong> Taguchi and GRA<br />

technique in various machining processes including conventional and non conventional processes<br />

Keywords: Taguchi method, Grey relational analysis, Parameters optimization<br />

1. Introduction<br />

The impetus for developing Modern Machining Processes (MMPs) is the research for finding the efficient and<br />

better way <strong>of</strong> producing intricate geometry with high precision in high hardness and high strength materials like<br />

cemented carbides, titanium alloys, stainless steels, other heat resisting super alloys etc. With the technological<br />

and industrial growth, several non-conventional machining processes like ultrasonic machining (USM), electrical<br />

discharge machining (EDM), wire electrical discharge machining (WEDM), laser beam machining (LBM), water<br />

jet machining (WJM), electro-chemical machining (ECM) etc have been developed. These non-conventional<br />

machining processes work on different principles. Depending upon the work material and objective, suitable<br />

machining process can be selected. For example, EDM and WEDM are commonly used for machining <strong>of</strong><br />

electrical conductive materials only, while USM can machine insulating materials also.<br />

There are several machining parameters available within a machine tool which needs to be optimized before<br />

shaping any material into useful application. Out <strong>of</strong> these, few parameters may be highly significant i.e. they put<br />

appreciable effect on machining characteristics by changing a small value, while other may be insignificant for<br />

that particular process. In order to optimize the machining operation, numbers <strong>of</strong> experiments are required to<br />

carry out for a particular material and machine tool before actual manufacturing. In recent years, Taguchi method<br />

has been successfully applied various fields to optimize the system. Taguchi method is a powerful tool for the<br />

design <strong>of</strong> good quality system. This method has been extensively used for optimization <strong>of</strong> single performance<br />

measure. The main advantage <strong>of</strong> this method is that optimal values are very close to the target values. However,<br />

the original Taguchi method has been designed to optimize the single performance characteristics. The grey<br />

relational analysis (GRA) has proved to be very effective in optimizing the multi performance characteristics.<br />

The objective <strong>of</strong> present paper is to present a review on application <strong>of</strong> Taguchi method and grey relational<br />

analysis (GRA) in optimizing the machining processes.<br />

2.Taguchi Method<br />

The Taguchi method (Ross, <strong>19</strong>96; Roy, <strong>20</strong>01) is a systematic application <strong>of</strong> design and analysis <strong>of</strong> experiments<br />

for the purpose <strong>of</strong> designing and improving product quality. Taguchi's approach to parameter design provides the<br />

design engineer with a systematic and efficient method for determining near optimum design parameters for<br />

performance and cost (Phadke, <strong>19</strong>89; Taguchi <strong>19</strong>86). The Taguchi method utilizes orthogonal arrays (OA) from<br />

design <strong>of</strong> experiments theory to study a large number <strong>of</strong> variables with a small number <strong>of</strong> experiments. This<br />

“OA” s is generalized Graeco-Latin squares. To design an experiment is to select the most suitable OA and to<br />

assign the parameters and interactions <strong>of</strong> interest to the appropriate columns.<br />

Taguchi method follows the following steps (Unal, <strong>19</strong>91):<br />

• Determine the quality characteristic to be optimized. Performance characteristics are characteristics<br />

whose variations have a significant effect on performance <strong>of</strong> any component.<br />

• Identify the noise factors and test conditions. These factors have adverse effect on the performance<br />

measure and product quality. These are those which are uncontrollable.<br />

471


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

• Identify the control factors and their alternative levels. This can either be done on the basis <strong>of</strong> trial<br />

experiments or past research.<br />

• Design the matrix experiment by selecting appropriate orthogonal array. This selection is made on the<br />

basis <strong>of</strong> number <strong>of</strong> process parameter and their levels.<br />

• Conduct the matrix experiment.<br />

• Analyse the data using statistical measure <strong>of</strong> performance characteristics also known as Signal-to-Noise<br />

ratio (S/N ratio) and determine the optimum setting <strong>of</strong> control factors.<br />

• Predict the performance correspond to optimal levels.<br />

• Determine the confidence intervals and perform the confirmation experiments.<br />

2.1 Application <strong>of</strong> Taguchi method<br />

Taguchi method has been widely used by researchers for optimization <strong>of</strong> individual performance characteristics<br />

<strong>of</strong> conventional and non conventional machining processes.<br />

2.1.1 Conventional machining processes:<br />

Kivak (<strong>20</strong>12) optimized the drilling parameters using Taguchi methodology to obtain minimum surface<br />

roughness and thrust force. Experiments were conducted using L 16 orthogonal array on a CNC vertical drilling<br />

machining centre. Wu Gang (<strong>20</strong>11) used Taguchi methodology in CNC milling for designing optimal parameters<br />

to reduce geometric errors. Fratila (<strong>20</strong>11) applied the Taguchi optimization methodology to optimize the cutting<br />

parameters in face milling in order to get the best surface roughness and the minimum power consumption. This<br />

paper presents the application <strong>of</strong> the technique for the single quality characteristics optimization. Kilickap (<strong>20</strong>10)<br />

obtained the optimum drilling parameter combination by using the analysis <strong>of</strong> signal-to-noise ratio. The<br />

conclusion revealed that feed rate and cutting speed were the most influential factor on the delimination,<br />

respectively. The best results <strong>of</strong> the delimination were obtained at lower cutting speeds and feed rates. Tzeng<br />

(<strong>20</strong>07) described the application <strong>of</strong> the Taguchi method coupled with fuzzy logic analysis to optimize the<br />

precision and accuracy <strong>of</strong> the high speed electrical discharge machining process. H. Oktem (<strong>20</strong>06) used Taguchi<br />

optimization method to find the optimal process parameter which minimizes the surface roughness during the<br />

mold surface milling <strong>of</strong> a 7075-76 aluminium block and also concluded that the Taguchi method is very useful in<br />

solving the surface quality problem <strong>of</strong> mold surface. Ghani (<strong>20</strong>04) optimized the cutting parameter in the milling<br />

<strong>of</strong> steel using Taguchi methodology. Davim (<strong>20</strong>03) employed orthogonal array for optimization <strong>of</strong> cutting<br />

parameter in turning and investigated the influence <strong>of</strong> experimental cutting conditions.<br />

2.1.2 Non-conventional Application<br />

Timur (<strong>20</strong>12) employed Taguchi optimization <strong>of</strong> nanosecond Laser for microdrilling on PVE to obtain cavities<br />

having maximum aspect ratio (depth to width ratio). Dongxia (<strong>20</strong>12) successfully applied Taguchi approach for<br />

optimization <strong>of</strong> weld bead geometry in laser welding and obtained optimal combination <strong>of</strong> welding parameters.<br />

From the experimental results, it is found that the effect <strong>of</strong> welding parameters on the welding quality decreased<br />

in the order <strong>of</strong> welding speed, wire feed rate, and laser power. Rao (<strong>20</strong>11) investigated the effect <strong>of</strong> WEDM<br />

conditions on surface roughness and used Taguchi method for optimization <strong>of</strong> WEDM. Chomsamuter (<strong>20</strong>10)<br />

combined the three cutting parameters to obtain the optimal product specifications by using Taguchi<br />

methodology. Yan-Cheng Lin (<strong>20</strong>09) optimized the machining parameters in magnetic force assisted EDM with<br />

the effective utilization <strong>of</strong> Taguchi method and obtained an optimal set <strong>of</strong> control factors through this method.<br />

Matoorian (<strong>20</strong>08) presented the application <strong>of</strong> the Taguchi design method to optimize the precision and accuracy<br />

<strong>of</strong> the electrical discharge machining process. Author employed L18 orthogonal array to investigate the effect <strong>of</strong><br />

process parameters on quality characteristic. Li (<strong>20</strong>07) used Taguchi matrix method to identify optimal laser<br />

parameters for cutting QFN packages to achieve optimal cutting quality. Control factors were lamp current, pulse<br />

repetition rate and cutting speed. Liao (<strong>19</strong>97) developed an approach <strong>of</strong> finding the parameter setting by using<br />

Taguchi quality design method and the analysis <strong>of</strong> variance. The result obtained from this method show that<br />

table feed & pulse on time directly affect the material removal rate and surface finish. For the prevention <strong>of</strong> wire<br />

breakage these parameter can also be used to control the discharge frequency.<br />

3. Grey relational analysis (GRA)<br />

According to Phadke (<strong>19</strong>89), it is difficult to optimize multi performance characteristics in complex process by<br />

Taguchi method and engineering judgement is primarily used to resolve such a complicated problem. The grey<br />

system theory proposed by Deng (<strong>19</strong>82) has been proven to be useful for dealing with the problems with poor,<br />

insufficient and uncertain information.<br />

472


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Grey relational analysis was first proposed by Dr. Deng in <strong>19</strong>82 to fulfil crucial mathematical criteria for dealing<br />

with poor, incomplete and uncertain system (Deng, <strong>19</strong>89). Black, white and grey has special meaning in the grey<br />

relational analysis. Black indicate the system have no information, white indicate the system have full <strong>of</strong><br />

information and grey represent the level <strong>of</strong> information between black and white. This technique solves the<br />

problem <strong>of</strong> optimization <strong>of</strong> multiple-performance characteristics <strong>of</strong> modern machining method.<br />

In GRA, for optimization <strong>of</strong> multiple performance characteristics following steps are followed (Rao, <strong>20</strong>09):<br />

• Conduct the experiments and tabulate the data.<br />

• Normalization <strong>of</strong> the collected data. It is the process <strong>of</strong> transforming the original sequence to a<br />

comparable sequence. Normalization is done in the range <strong>of</strong> zero and one, the process is known as grey<br />

relational generating. Three types <strong>of</strong> data normalization are there in the GRA, lower the better (LB), the<br />

higher the better (HB) and nominal the best (NB).<br />

Lower is better (LB),<br />

(i)<br />

Higher is Better (HB),<br />

Nominal is best (NB),<br />

(ii)<br />

(iii)<br />

Where i = 1,2,………,n; k = 1,2,……, p; is normalized value <strong>of</strong> the kth element in the ith<br />

sequence, is desired value <strong>of</strong> the kth quality characteristic, max is the largest value <strong>of</strong><br />

, and min is the smallest value <strong>of</strong> , n is the number <strong>of</strong> experiments and p is the number<br />

<strong>of</strong> quality characteristics.<br />

• Calculation <strong>of</strong> grey relational coefficient.<br />

• Calculation <strong>of</strong> grey relational grade.<br />

• Predict the single optimal setting for multi performance characteristics.<br />

• Conduct confirmation experiments at optimum level <strong>of</strong> process parameters.<br />

In GRA, optimization <strong>of</strong> multiple performance characteristics is converted into an optimization <strong>of</strong> single<br />

performance characteristic called grey relational grade. Gray relational grade is the weighting sum <strong>of</strong> grey<br />

relational coefficient.<br />

3.1 Application <strong>of</strong> GRA<br />

This methodology has been employed successfully for optimization <strong>of</strong> multiple responses. In last few years, grey<br />

relational analysis with Taguchi method has been extensively used by various researchers for optimization <strong>of</strong><br />

multi-performance characteristics because it gives better results as compared to GRA.<br />

3.1.1 Conventional Machining Processes<br />

Ranganathan (<strong>20</strong>11) optimized the effect <strong>of</strong> cutting speed, feed rate, depth <strong>of</strong> cut and workpiece temperature by<br />

using multi-response analysis. Using grey analysis, a grey relational grade is obtained and based on this value an<br />

optimum level <strong>of</strong> cutting parameters has been identified. Liang Ku (<strong>20</strong>10) used taguchi Design methodology to<br />

conduct the experiment and the multiple performance characteristics correlated with surface roughness and bush<br />

length was investigated by grey relational analysis systematically and comprehensively. The experimental results<br />

show that the thermal friction drilling revealed beneficial effects on Surface roughness and Bush Length for<br />

drilling processes. Moreover, the optimal machining parameters for multiple performance characteristics<br />

associated with Surface Roughness and Bush Length were attained. Tzeng (<strong>20</strong>09) investigated the optimization<br />

<strong>of</strong> CNC turning operation parameters using grey relational analysis. Results show that depth <strong>of</strong> cut influence the<br />

roughness average most. Haq (<strong>20</strong>08) presented a new approach for the optimization <strong>of</strong> drilling parameters on<br />

drilling Al/SiC metal matrix composite with multiple responses based on orthogonal array with grey relational<br />

analysis. A grey relational grade is obtained from the grey analysis. Based on the grey relational grade, optimum<br />

levels <strong>of</strong> parameters have been identified and significant contribution <strong>of</strong> parameters is determined by Analysis <strong>of</strong><br />

variance.<br />

473


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3.1.2 Non-conventional Machining Processes<br />

Murugesan (<strong>20</strong>12) employed the Grey relational analysis theory to resolve the complicated interrelationships<br />

among the multiple performance characteristics. In this study the optimization <strong>of</strong> the Electrical Discharge<br />

Machining (EDM) process with multiple performance characteristics based on orthogonal array with the Grey<br />

relational analysis has been studied. Jangra (<strong>20</strong>11) used grey relational analysis along with Taguchi method to<br />

optimize material removal rate and surface roughness simultaneously for WEDM <strong>of</strong> WC-Co composite. Also, he<br />

challenged that solution from this study will be very helpful for tool manufacturer who are willing to search for<br />

an optimal result <strong>of</strong> control factors. Jangra (<strong>20</strong>10) utilised the grey relational analysis along with taguchi method<br />

to optimize multiple machining characteristics in wire electrical discharge machining <strong>of</strong> punching die. D3 tool<br />

steel was chosen for experimentation. Li (<strong>20</strong>09) demonstrated that gray relational analysis can be applied to laser<br />

beam cutting for flash memory modules with special shapes. Rao (<strong>20</strong>09) applied a hybrid approach <strong>of</strong> Taguchi<br />

design methodology and grey relational analysis to optimize multiple performance characteristics in Laser<br />

cutting. The designed results are used in grey relational analysis and to calculate actual weight <strong>of</strong> quality<br />

characteristics, entropy measurement method is applied. Caydas (<strong>20</strong>08) used the grey relational analysis to<br />

optimize multiple performance characteristics. In this study, the laser cutting parameters such as laser power and<br />

cutting speed were optimized. The response table for each level <strong>of</strong> the machining parameters were obtained from<br />

grey relational grade. Pan (<strong>20</strong>07) demonstrated the effectiveness <strong>of</strong> optimizing multiple performance measures<br />

using taguchi method and grey relational analysis. The calculation <strong>of</strong> grey relational grade helped to quantify the<br />

integrated performance <strong>of</strong> multiple performance measures required in laser welding. Lin and Lin (<strong>20</strong>02)<br />

optimized the multiple performance characteristics in wire electrical discharge machining by combining the<br />

orthogonal array and grey relational analysis. P. N. Singh (<strong>20</strong>04) employed orthogonal array with grey relational<br />

analysis to optimize the multiple performance characteristics <strong>of</strong> electrical discharge machining. Confirmation<br />

result shows that there is considerable improvement in the process.<br />

4. Conclusions<br />

This paper presents the application <strong>of</strong> two optimization approaches namely Taguchi method and grey relational<br />

analysis (GRA). Both approaches have been utilised in many fields to optimize the single and multi performance<br />

characteristics efficiently. Taguchi method is applicable for optimizing the single performance characteristics<br />

while GRA combined with Taguchi method can solve problems having multi performance characteristics. Using<br />

these two approaches, any complex system having multi performance characteristics can be solved efficiently.<br />

References<br />

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Jangra, K., Jain, A. & Groover, S. (<strong>20</strong>10). “Optimization <strong>of</strong> multiple-machining characteristics in wire electrical<br />

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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Kilickap, E. (<strong>20</strong>10). “Optimization <strong>of</strong> cutting parameters on delamination based on Taguchi method during<br />

drilling <strong>of</strong> GFRP composite”. Expert Systems with Applications, 37(8): 6116-6122.<br />

Kivak, T., Samtas, G. & Cicek, A. (<strong>20</strong>12). “Taguchi method based optimisation <strong>of</strong> drilling parameters<br />

indrilling <strong>of</strong> AISI 316 steel with PVD monolayer and multilayer coated HSS drills”. Measurement, 45(6): 1547-<br />

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Ku, W.L., Chow, H.M., Lin, Y.J., Wang, D.A. & Yang, L.D. (<strong>20</strong>10). “Optimization <strong>of</strong> Thermal Friction Drilling<br />

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Liao, Y.S., Huang, J.T. & Su, H.C. (<strong>19</strong>97). “A study on the machining parameter optimization <strong>of</strong> wire electrical<br />

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Li, C.H., & Tsai, M.J. (<strong>20</strong>09). “Multi-objectvie optimization <strong>of</strong> laser cutting for flash memory modules with<br />

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Li, C.H., Tsai, M.J. & Yang, C.D. (<strong>20</strong>07). “Study <strong>of</strong> optimal laser parameters for cutting QFN packages by<br />

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discharge machining process with multiple performance characteristics”. International Journal <strong>of</strong> Machine Tools<br />

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Lin, Y.C., Chen, Y.F., Wang, D.A. & Lee, H.S. (<strong>20</strong>09). “Optimization <strong>of</strong> machining parameter in magnetic force<br />

assisted EDM based on taguchi method”. Journal <strong>of</strong> Material Processing <strong>Technology</strong>, <strong>20</strong>9: 3374-3383.<br />

Matoorian, P., Sulaiman, S., & Ahmad, M.M.H.M. (<strong>20</strong>08). “An experimental study for optimization <strong>of</strong> electrical<br />

discharge turning process”. Journal <strong>of</strong> Materials Processing <strong>Technology</strong>, <strong>20</strong>4: 350-356.<br />

Murugesan, S. & Balamurugan, K. (<strong>20</strong>12). “Optimization by Grey Relational Analysis <strong>of</strong> EDM Parameters in<br />

Machining Al-15% SiC MMC Using Multihole Electrode”. Journal <strong>of</strong> Applied <strong>Science</strong>s, 12: 963-970.<br />

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milling <strong>of</strong> mold surface”. International Journal <strong>of</strong> Advance Manufacturing <strong>Technology</strong>, 28: 694-700.<br />

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using GRA with entropy measurement”. Optics and laser <strong>Technology</strong>, 41: 922-930.<br />

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Improvement”, Wiley-Interscience, New York, 179-186.<br />

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PVC by Taguchi method”, Optics & Laser <strong>Technology</strong>, 44(8) : 2347–2353.<br />

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process using a Taguchi fuzzy-based approach”. Material and Design, 28: 1159-1168.<br />

Unal, R. & Dean, E.B. (<strong>19</strong>91). “Taguchi approach to design optimization for quality and cost: An overview”.<br />

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475


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

To Study the Effect <strong>of</strong> Polarity and Current during Electric Discharge<br />

Machining <strong>of</strong> Inconel 718 with CuW Powder Metallurgy Electrode<br />

Naveen Beri*, Harish Pungotra, Anil Kumar<br />

Department <strong>of</strong> Mechanical Engineering, Beant College <strong>of</strong> Engineering and <strong>Technology</strong>, Gurdaspur, Punjab, India.<br />

*Corresponding Author E-mail: nav_beri74@yahoo.co.in<br />

Abstract<br />

Electrical discharge machining (EDM) is one <strong>of</strong> the earliest non-traditional machining processes which have been<br />

widely used to produce dies, molds and finishing parts for aerospace and automotive industry. In recent years,<br />

powder metallurgy processed electrodes have found wide application as an alternative tooling for EDM. In the<br />

present experimental study an attempt has been made to study the effect <strong>of</strong> electrode polarity and current during<br />

electrical discharge machining <strong>of</strong> Inconel 718 alloy steel with copper tungsten (PM) processed electrode. The<br />

response parameters selected for the study are material removal rate (MRR) surface roughness (SR) Ra Value, tool<br />

wear rate (TWR) and Change in Surface Roughness (SR) Ra Value <strong>of</strong> electrode before and after machining.<br />

Keywords : Electrical discharge machining (EDM), powder metallurgy (PM), material removal rate (MRR), surface<br />

roughness and tool wear rate (TWR)<br />

.<br />

1. Introduction<br />

Electrical discharge machining (EDM) is one <strong>of</strong> the earliest non-traditional machining processes which have been<br />

widely used to produce dies, molds and finishing parts for aerospace and automotive industry and surgical<br />

components [1]. With the use <strong>of</strong> this excellent process one can achieve highly accurate complex shapes on a wide<br />

range <strong>of</strong> conductive and difficult-to-machine materials. Inconel 718 alloy steel is one <strong>of</strong> the most difficult-to<br />

machine nickel based alloy and is widely used in aircraft, gas turbines, space vehicles, rocket engines, nuclear<br />

reactors, submarines, and other high-temperature applications [2]. In EDM process the material is removed through<br />

the action <strong>of</strong> an electrical discharge <strong>of</strong> short duration between the electrode (tool) and the work piece in the presence<br />

<strong>of</strong> a dielectric fluid [3].<br />

Recently, EDM tool electrode manufacturing has became the focus <strong>of</strong> many studies in paralleling the development<br />

<strong>of</strong> EDM process and machine complexity. Tools manufacturing through powder metallurgy process is one <strong>of</strong> the<br />

alternative tooling option for EDM electrodes where the desirable properties <strong>of</strong> different materials can be combined<br />

and a large number <strong>of</strong> tool electrodes can be made from a single die and punch assembly, resulting in an overall<br />

reduction <strong>of</strong> EDM tooling cost [4].<br />

2. Literature review<br />

Marafona and Wykes [5] performed experimental study to optimise material removal rate (MRR) during EDM with<br />

copper-tungsten electrodes using Taguchi L18 orthogonal array and they achieved improvement <strong>of</strong> MRR for a given<br />

tool wear ratio. Shu and Tu [6] performed EDM with Cu-SiCp composite electrode made by the PM method. Tsai et<br />

al. [7] performed blending <strong>of</strong> copper powders containing resin with chromium powders to form tool electrode. The<br />

machined surface showed good corrosion resistance with fewer cracks. Moro et al. [8] applied the technology <strong>of</strong><br />

electrical discharge coating (EDC) and reported improvement in working life <strong>of</strong> the die by three to seven times.<br />

Beri et al. [9] performed experimentation on electric discharge machining <strong>of</strong> AISID2 steel in kerosene with copper<br />

tungsten electrode made through PM technique and conventional Cu electrode and recommended to use<br />

conventional Cu electrode for higher MRR and CuW electrode made through PM for higher surface finish. Kumar et<br />

al. [10] reported the results <strong>of</strong> experimental investigations during EDM <strong>of</strong> OHNS die steel with Inconel electrode<br />

under machining conditions favoring high electrode wear. Ashokan and Senthilkumaar [11] illustrated a new<br />

approach <strong>of</strong> selecting machining parameters during turning <strong>of</strong> Inconel 718 using the multi-objective optimization<br />

coupled with multiple attribute decision-making method. Beri et al. [12] made an attempt to correlate the usefulness<br />

<strong>of</strong> powder metallurgy (PM) electrodes in electrical discharge machining (EDM). It is found that copper tungsten PM<br />

electrode gives better multi-objective performance than conventional copper electrode. Beri et al. [13] evaluated<br />

476


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

surface quality measured in terms <strong>of</strong> surface roughness (Ra value) during electric discharge machining using<br />

orthogonal array L36 (21X 37) based on Taguchi methodology. Experimental data was statistically analyzed using<br />

analysis <strong>of</strong> variance (ANOVA) and optimum condition was achieved for evaluation criteria. It was concluded<br />

minimum Ra is obtained with CuW<strong>20</strong>80 electrode at minimum current and negative polarity and polarity, electrode<br />

type, peek current, have significant effect on surface quality <strong>of</strong> the machined surface.<br />

From the reviewed literature it is observed that PM electrodes are widely acceptable as an EDM electrode and they<br />

significantly contribute for machining and surface quality improvement during the electric discharge machining<br />

process. Polarity and current are significant parameter that effects the machining performance <strong>of</strong> the EDM process.<br />

Thus a need is felt to study the effect <strong>of</strong> electrode polarity and current during electrical discharge machining <strong>of</strong><br />

Inconel 718 alloy steel with copper tungsten powder metallurgy (PM) processed electrode with a view to study their<br />

effect on selected response parameters. The response parameters selected for the study are material removal rate<br />

(MRR), surface roughness (SR) Ra value, tool wear rate (TWR) and Change in Surface Roughness (SR) Ra value <strong>of</strong><br />

electrode before and after machining. EDM oil is used as dielectric during the experimentation.<br />

3. Experimentation<br />

Polarity and current are important parameters which have significant effects on the machining performance <strong>of</strong> the<br />

EDM process. The experimental parameters and their values selected for the study are tabulated in Table 1 all <strong>of</strong> the<br />

other parameters are kept constant.<br />

3.1 Experimental procedure<br />

Experiments were carried out on Electronica make EDM machine; model SMART ZNC (S50). Inconel 718 alloy<br />

steel was used as work piece material with EDM oil as the dielectric medium. Cylindrical powder metallurgy<br />

processed CuW (Cu<strong>20</strong>%W80%) electrode is used for the experimentation. Electrode was rubbed on a fine grade<br />

emery paper and surface roughness (Ra value in microns) was measured using Mitutoyo make surface roughness<br />

tester (SJ400). Work piece and electrode were then weighed on Citizen make digital balance with an accuracy <strong>of</strong> 1<br />

mg to get the initial weight <strong>of</strong> work piece and electrode before machining. Then erosion was switched on for a depth<br />

<strong>of</strong> cut <strong>of</strong> 0.65mm and time taken to complete the operation was noted and the work piece and electrode were then<br />

weighed again to get the final weight after machining. The surface roughness <strong>of</strong> the work piece and electrode were<br />

then was also measure again after each machining operation.<br />

Parameter<br />

( Symbol)<br />

Table 1. Machining Parameters<br />

Units Level 1 Level 2 Level 3<br />

Electrode Type (B) - Copper Tungsten (constant Parameter)<br />

(Cu <strong>20</strong>%W 80%)<br />

Polarity (A) - +ve -ve<br />

Current (C) (Amps.) 4.0 8.0 12.0<br />

Pulse on Time (D) (µ sec) 50 (constant Parameter)<br />

Duty Cycle (E) - 0.7 (constant Parameter)<br />

Gap Voltage (F) (Volts) 40 (constant Parameter)<br />

Retract<br />

(G)<br />

Flushing<br />

(H)<br />

Distance<br />

Pressure<br />

(mm) 1 (constant Parameter)<br />

(Kg/cm 2 ) 0.3 (constant Parameter)<br />

477


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Material removal rate and tool wear rate were obtained using weight loss method and are calculated using equations<br />

1 and 2 respectively. Experiments were performed as per Table 2. Three set <strong>of</strong> experiments were performed and the<br />

average was taken for each output parameter. The experimental results (average values) are tabulated in Table 2.<br />

Material removal rate (mg/min) = Work piece weight loss (mg)<br />

Machining time (min)<br />

Tool wear rate (mg/min) = Electrode weight loss (mg)<br />

Machining time (min)<br />

(1)<br />

(2)<br />

Table 2. Experimental Plan and Results<br />

Exp.<br />

No.<br />

Polarity Current<br />

(amps.)<br />

Material<br />

Removal Rate<br />

(MRR)<br />

(mg/min)<br />

Tool<br />

Rate<br />

(TWR)<br />

(mg/min)<br />

Wear<br />

Surface<br />

Roughness<br />

(SR)<br />

(μm)<br />

Change in<br />

SR<br />

electrode<br />

(μm)<br />

<strong>of</strong><br />

1 -ve 04.0 00.140 1.75 0.79 0.68<br />

2 -ve 08.0 00.489 1.66 0.93 0.80<br />

3 -ve 12.0 01.967 2.09 2.43 0.89<br />

4 +ve 04.0 01.235 0.55 4.34 0.43<br />

5 +ve 08.0 38.<strong>20</strong>0 0.50 5.84 0.81<br />

6 +ve 12.0 97.000 1.00 6.30 0.97<br />

4. Results and Discussions<br />

The experimental results tabulated in Table 2 were used to study the effect <strong>of</strong> input parameters on the selected<br />

output parameters.<br />

Figure 1 shows the effect <strong>of</strong> polarity and current on MRR. From figure 1 it is clear that MRR increases with the<br />

increase in current with both +ve and –ve polarity the slope <strong>of</strong> the curve shows that MRR increases drastically with<br />

the increase in current with +ve polarity as compared to –ve polarity. With an increase in current the available spark<br />

energy during discharge increases leading to higher MRR and in positive polarity the positively charged ions are<br />

emitted from the electrodes which impinge on the work piece. Due to higher mass the momentum <strong>of</strong> these positively<br />

charged ions is greater than that <strong>of</strong> negatively charged electrons this results in more material removal from the work<br />

piece in comparison with the electrodes. Maximum MRR is obtained at 12 amps current with +ve polarity.<br />

Figure 2 shows the effect <strong>of</strong> polarity and current on TWR. TWR decrease slightly with the increase in current for<br />

both +ve and –ve polarity and then it starts increasing. The slight decrease in TWR in the beginning may be due to<br />

the formation <strong>of</strong> carbide layers on the tool surface and less energy associated with the spark at low current. As<br />

current increases the energy associated with the spark increases and the carbide layers gets broken and the TWR<br />

increases. TWR is more with –ve polarity as compared to +ve polarity because <strong>of</strong> lower binding energy <strong>of</strong> the<br />

electrode constituent. Minimum TWR is obtained at 8 amps current with +ve polarity.<br />

Figure 3 shows the effect <strong>of</strong> polarity and current on SR <strong>of</strong> the machined surface. SR increases with the increase in<br />

current with both +ve and –ve polarity. SR obtained with –ve polarity is drastically lower as compared with the SR<br />

obtained with +ve polarity. Lower current values gives lower SR. Increase in SR with increase in current may be<br />

attributed to the increase in energy contents <strong>of</strong> the spark. Minimum SR is obtained at 4 amps current (lower current)<br />

with -ve polarity. At lower current the available spark energy during discharge is less but is enough to break the<br />

binding energy within the constituent <strong>of</strong> the electrode this may lead to the detachment <strong>of</strong> tungsten from the electrode<br />

which may further get deposited on the work surface causing an appreciable reduction in the R a value.<br />

Figure 4 shows the effect <strong>of</strong> polarity and current on change in SR <strong>of</strong> electrode before and after machining. It<br />

increases with increase in current with both +ve and –ve polarity. In the beginning it is less for the +ve polarity and<br />

478


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

more for -ve polarity i.e at 4 amps current and +ve polarity because <strong>of</strong> the formation <strong>of</strong> carbide layers at lower<br />

current values and at higher current values the carbide layers gets broken due to increases in energy content<br />

associated with the spark. Minimum value <strong>of</strong> change in SR <strong>of</strong> electrode before and after machining is obtained at 4<br />

amps current with +ve polarity.<br />

Figure 1 Effect <strong>of</strong> current on MRR<br />

Figure 2 Effect <strong>of</strong> current on TWR<br />

479


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 3 Effect <strong>of</strong> current on SR<br />

Figure 4 Effect <strong>of</strong> current on change in SR <strong>of</strong> electrode<br />

4. Conclusions<br />

Based on the present experimental results following conclusions can be drawn:<br />

1. MRR increases with the increase in current with both +ve and –ve polarity and this increase is higher with<br />

+ve polarity as compared to –ve polarity. Maximum MRR is obtained at 12 amps current with +ve polarity.<br />

2. TWR decrease slightly with the increase in current for both +ve and –ve polarity and then it starts<br />

increasing. This is due to the formation <strong>of</strong> carbide layers on the tool surface and less energy associated with<br />

480


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

the spark at lower current and break down <strong>of</strong> the formed carbide layers at higher current values. TWR is<br />

obtained at 8 amps current with +ve polarity.<br />

3. SR increases with the increase in current with both +ve and –ve polarity. SR obtained with –ve polarity is<br />

drastically lower as compared with the SR obtained with +ve polarity. Minimum SR is obtained at 4 amps<br />

current with -ve polarity.<br />

4. Minimum value <strong>of</strong> change in SR <strong>of</strong> electrode before and after machining is obtained at 4 amps current with<br />

+ve polarity. It increases with increase in current with both +ve and –ve polarity.<br />

5. It is recommended to use +ve polarity to obtain maximum MRR and Minimum TWR whereas –ve polarity<br />

is recommended for Minimum SR.<br />

Acknowledgements<br />

The authors would like to acknowledge the support <strong>of</strong> department <strong>of</strong> mechanical engineering, Beant College <strong>of</strong><br />

Engineering and <strong>Technology</strong>, Gurdaspur, Punjab, India, <strong>University</strong> School <strong>of</strong> Engineering and <strong>Technology</strong> GGSIPU,<br />

Delhi, India and All India Council for Technical Education New Delhi, India for supporting and funding the research<br />

work under research promotion scheme in this direction vide file No.: 8023/BOR/RID/RPS-144/<strong>20</strong>08-09 and<br />

8023/BOR/RID/RPS-86/<strong>20</strong>09-10.<br />

References<br />

1. Ho, K.H., Newman, S.T.: State <strong>of</strong> the art electrical discharge machining (EDM), International Journal <strong>of</strong><br />

Machine Tools & Manufacture 43 (<strong>20</strong>03) 1287–1300.<br />

2. Ezugwu, E.O., Wang Z.M., and Machado, A.R.: Journal <strong>of</strong> Materials Processing <strong>Technology</strong> Vol. 86 (<strong>19</strong>99),p. 1.<br />

3. Thomson P.F.: Mater. Sci. Technol. Vol. 5 (<strong>19</strong>89), p. 1153.<br />

4. Beri, N., Maheshwari, S., Sharma, C. and Kumar, A.: Materials and Manufacturing Processes, Vol. 25 (<strong>20</strong>10), p.<br />

1186.<br />

5. Marafona, J. and Wykes, C. (<strong>19</strong>99) ‘A new method <strong>of</strong> optimizing material removal rate using EDM with copper–<br />

tungsten electrodes’, International Journal <strong>of</strong> Machine Tool and Manufacture, Vol. 40, Issue 2, pp. 153-164.<br />

6. Shu, K.M. and Tu, G.C. (<strong>20</strong>01) ‘Fabrication and characterization <strong>of</strong> Cu-SiC p composites for electrical discharge<br />

machining applications’, Materials and Manufacturing Processes, Vol. 16, Issue 4, pp. 483–502.<br />

7. Tsai, H.C., Yan, B.H. and Huang, F.Y. (<strong>20</strong>03) ‘EDM performance <strong>of</strong> Cr/Cu-based composite electrodes’,<br />

International Journal <strong>of</strong> Machine Tools and Manufacture, Vol. 43, Issue 3, pp. 245–252.<br />

8. Moro, T., Mohri, N., Otsubo, H., Goto, A. and Sait, N. (<strong>20</strong>04) ‘Study on the surface modification system with<br />

electrical discharge machine in the practical usage’, Journal <strong>of</strong> Material Processing <strong>Technology</strong>, Vol.149, Issue<br />

1-3, pp. 65-70.<br />

9. Beri, N., Maheshwari, S., Sharma, C. and Kumar, A. (<strong>20</strong>11) ‘Optimization <strong>of</strong> electrical discharge machining<br />

process with CuW powder metallurgy electrode using grey relation theory’, International Journal <strong>of</strong> Machining<br />

and Machinability <strong>of</strong> Materials, Vol. 9, No.1/2, pp. 103 - 115.<br />

10. Kumar, S, Singh, T.P. and Sethi, B.L. (<strong>20</strong>09) , ‘Surface alloying <strong>of</strong> OHNS die steel by EDM process using<br />

Inconel electrode’ International Journal <strong>of</strong> Machining and Machinability <strong>of</strong> Materials, Vol. 6, No.3/4, pp. 176 –<br />

<strong>19</strong>3.<br />

11. Ashokan, P. and Senthilkumaar, J.S. (<strong>20</strong>10) ‘Intelligent selection <strong>of</strong> machining parameters in turning <strong>of</strong> Inconel-<br />

718 using multi objective optimisation coupled with MADM’ International Journal <strong>of</strong> Machining and<br />

Machinability <strong>of</strong> Materials. Vol. 8, No.1/2, pp. <strong>20</strong>9 - 225.<br />

12. Beri, N., Maheshwari, S., Sharma, C. and Kumar, A. (<strong>20</strong>08) ‘Performance evaluation <strong>of</strong> powder metallurgy<br />

electrode in electrical discharge machining <strong>of</strong> AISI D2 steel using Taguchi method’, International Journal <strong>of</strong><br />

Mechanical, Industrial and Aerospace Engineering, Vol. 2, Issue 3, pp. 167–171.<br />

13. Beri, N.; Maheshwari, S.; Sharma, C. Evaluation <strong>of</strong> surface quality during electrical discharge machining <strong>of</strong><br />

Inconel 718 with powder metallurgy electrodes. Proceedings <strong>of</strong> <strong>20</strong> th International Symposium Processing and<br />

Fabrication <strong>of</strong> Advanced Materials (PFAM XX) Hong Kong Polytechnic <strong>University</strong>, Hong Kong SAR China,<br />

Dec <strong>20</strong>11.<br />

481


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Experimental Evaluations on Surface Quality Improvement in Aluminium<br />

Powder Mixed AEDM <strong>of</strong> Nickel Based Super Alloy 718 with Cryogenically<br />

Treated Copper Electrode<br />

Anil Kumar*, Naveen Beri, Harish Pungotra<br />

Department <strong>of</strong> Mechanical Engineering, Beant College <strong>of</strong> Engineering and <strong>Technology</strong>, Gurdaspur, Punjab,<br />

*Corresponding Author E-mail ID: ak_10<strong>19</strong>68@yahoo.com<br />

Abstract<br />

In this experimental study attempt has been made to realize potential in enhancing surface quality with fine<br />

aluminum additives powders in AEDM <strong>of</strong> nickel based super alloy Inconel 718. L 36 Orthogonal Array has been<br />

selected to conduct and analyze experiments based on Taguchi methodology. Peak current, pulse on time, duty<br />

cycle, gap voltage, retract distance, concentration <strong>of</strong> fine aluminum powder added into the dielectric fluid are<br />

chosen as input process variables to study performance in terms <strong>of</strong> surface roughness using copper and deep<br />

cryogenically treated copper electrode. It is observed that addition <strong>of</strong> 6g/l <strong>of</strong> fine aluminium powder and<br />

cryogenically treated copper electrode improves the surface finish appreciably. The recommended best<br />

parametric settings for minimum surface roughness have been verified by conducting confirmation experiments.<br />

Keywords: AEDM, Taguchi methodology, Orthogonal Array, cryogenic treatment, surface roughness.<br />

1. Introduction<br />

Today’s manufacturing industry is facing challenges like difficulty in machining <strong>of</strong> advance extra hard and tough<br />

materials (super alloys, ceramics, and composites), stringent design requirements (high precision, complex<br />

shapes and high surface quality) and machining costs. The greatly-improved thermal, chemical, and mechanical<br />

properties <strong>of</strong> the material such as improved strength, heat resistance, wear resistance, and corrosion resistance,<br />

while having yielded enormous economic benefits to manufacturing industries through improved product<br />

performance and product design, are making traditional machining processes unable to machine them or unable<br />

to machine them economically. EDM has proven to be applicable to all electrically conductive materials<br />

regardless <strong>of</strong> their physical and metallurgical properties. In EDM, material removal is achieved by preferential<br />

erosion <strong>of</strong> the work piece electrode as controlled discrete discharges are passed between the electrode and the<br />

work piece in dielectric medium. EDM is a widespread technique used in industry for high precision machining<br />

<strong>of</strong> all types <strong>of</strong> conductive materials such as: metals, metallic alloys, graphite or even some ceramic materials and<br />

super alloys such as Inconel, <strong>of</strong> any hardness [1]. Since the invention <strong>of</strong> EDM in <strong>19</strong>40s researchers have made a<br />

lot <strong>of</strong> efforts to improve the machining performance. A number <strong>of</strong> variants have emerged to manifolds the<br />

application <strong>of</strong> EDM process in industry. In traditional EDM process surface roughness is more and material<br />

removal rate is relatively less. To fulfill the objectives <strong>of</strong> improving manufacturing efficiency and quality <strong>of</strong><br />

shaping and finishing processes researchers have taken many directions. A relatively new advancement in this<br />

direction is to use some additives powders suspended in the dielectric fluid <strong>of</strong> EDM to fulfill the requirement <strong>of</strong><br />

minimum surface damage, enhance machining rates and improving surface properties. This new hybrid<br />

machining process is called additive mixed electrical discharge machining [2-5].<br />

The machining mechanism <strong>of</strong> AEDM is different from conventional EDM process [6-7]. In AEDM when a<br />

voltage <strong>of</strong> 80-3<strong>20</strong>V is applied across work piece and electrode electrical intensity in the range <strong>of</strong> 10 5 to 10 7 V/m<br />

is generated. Under the influence this electric intensity additives powder particles get energized and behave in a<br />

zigzag fashion. These additives particles arrange themselves in the form <strong>of</strong> chain at different places under the<br />

sparking area leading to bridge formation. This bridging effect promotes early explosion in the gap. As a result,<br />

the series discharge starts under the electrode area. Due to increase in frequency <strong>of</strong> discharging, faster erosion<br />

takes place from the work piece surface. Therefore gap contamination with fine abrasive conductive particles<br />

facilitates ignition process and increases maching rates and due to better distribution <strong>of</strong> spark energy resulting in<br />

improved surface roughness. Process performance <strong>of</strong> AEDM depends upon electrical parameters (like pulse<br />

frequency, duty cycle, pulse on time, spark gap, current, and voltage), material properties <strong>of</strong> electrode, work<br />

piece and dielectric fluid, and properties <strong>of</strong> abrasive powders (like melting point, specific heat, thermal<br />

conductivity, grain size, and concentration). Therefore, promoting the process performance by developing a<br />

thorough understanding <strong>of</strong> the relationship between these parameters has become a major research concern [8-<br />

11].<br />

Erden and Belgin [12] were the first who studied the effect <strong>of</strong> impurities (copper, aluminium, iron and carbon) in<br />

electrical discharge machining <strong>of</strong> brass steel and copper steel pair and reported increase in machining rates with<br />

482


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

increase in concentration <strong>of</strong> impurities. It was reported that machining becomes unstable at an excessive additive<br />

powder concentration due to the occurrence <strong>of</strong> short-circuits and occurrence <strong>of</strong> discharges at same spot. Since<br />

then a lot <strong>of</strong> research work has been done in the area <strong>of</strong> additive mixed electrical discharge machining and have<br />

shown great effect on process performance in terms <strong>of</strong> material removal rate, surface characteristics, wear ratio<br />

etc.<br />

Jeswani [13] investigated the effect <strong>of</strong> suspended fine graphite powder in dielectric medium <strong>of</strong> electrical<br />

discharge machining on tool steel and reported that addition <strong>of</strong> about 4 g/l <strong>of</strong> fine graphite powder (10 μm in<br />

average size) in kerosene increased metal removal rate (MRR) by 60% and tool wear rate by 15%. This was<br />

attributed to better electrical discharge distribution between spark gap.<br />

Mohri and co worker [14] studied the effect <strong>of</strong> silicon powder in dielectric medium and reported significant<br />

improvement in machining performance. Kumar and Beri studied the effect <strong>of</strong> graphite powder on surface<br />

quality and reported improved surface finish [15]. The aim <strong>of</strong> the present research work was to experimentally<br />

evaluate on surface quality improvement in aluminium powder mixed AEDM <strong>of</strong> Nickel Based Super Alloy 718<br />

with cryogenically treated copper electrode and to find best parametric settings to minimize SR.<br />

2. Experimental Planning and Procedure<br />

Taguchi methodology has been applied to plan and analyze the experiments. The Taguchi method can optimize<br />

performance characteristics through the settings <strong>of</strong> process parameters and reduce the sensitivity <strong>of</strong> the system<br />

performance to sources <strong>of</strong> variation.<br />

Table 1 Process parameters and their levels<br />

Symbol Process parameters units Levels<br />

1 2 3<br />

A Polarity +ve -ve<br />

B Types <strong>of</strong> electrode Copper Cryogenically<br />

treated copper<br />

C Peak current amps 0.5 3 6<br />

D Pulse on time µs 50 100 150<br />

E Duty cycle τ 0.7 0.8 0.9<br />

F Gap voltage volts 40 60 80<br />

G Retract distance mm 1 2 3<br />

H Concentration <strong>of</strong> Powder<br />

(300 Mesh size)<br />

g/l 0 6 12<br />

The experimental parameters and their levels selected for present study are tabulated in Table 1 keeping other<br />

parameters constant based on trial experiments and previous studies. In the present study experiments were<br />

carried out on Electronica make electrical discharge machine; model SMART ZNC (S50).<br />

A copper electrode <strong>of</strong> 8mm φ was subjected to deep cryogenic treatment which consists <strong>of</strong> a slow cool-down rate<br />

(2.5°C/min) from ambient temperature to the temperature <strong>of</strong> liquid nitrogen. When the material reached<br />

approximately at −<strong>19</strong>3.15°C it was soaked for 24 hours.<br />

Experiments were performed with O.A L 36 (2 2 x3 6 ). The results were analyzed for minimum surface roughness<br />

with “smaller the better” quality characteristic with Minitab s<strong>of</strong>tware 15.1.1.The SR was measured in terms <strong>of</strong><br />

arithmetic mean roughness <strong>of</strong> the evaluated roughness pr<strong>of</strong>ile (Ra in µm) by using a Mitutoyo SJ 400 surface<br />

testing analyzer.<br />

3. Results and Discussions<br />

The S/N ratios <strong>of</strong> SR for each trial run have been calculated from experimental data and response table for<br />

smaller the better are summarized in Table 2 giving relative importance <strong>of</strong> each parameter on desired response.<br />

The individual effects <strong>of</strong> input parameters on the S/N ratios for SR are shown in main effect plot (Fig.2).<br />

483


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Main Effects Plot for SN ratios (SR)<br />

Data Means<br />

Polarity<br />

Electrode ty pe<br />

Peak C urrent<br />

-8<br />

-10<br />

-12<br />

Mean <strong>of</strong> SN ratios<br />

-8<br />

-10<br />

-12<br />

-8<br />

-10<br />

-12<br />

-V e<br />

+v e<br />

copper cry ogenic 0.5 3.0 6.0<br />

Ton Time Duty C y cle Gap V olt.<br />

50 100 150 0.7 0.8 0.9 40 60<br />

80<br />

Retarct distance<br />

C oncentration<br />

1<br />

2<br />

3<br />

0<br />

6<br />

12<br />

Signal-to-noise: Smaller is better<br />

Fig.2 Main Effect plot for S/N ratios for SR<br />

Table 2 Response Table for Signal to Noise Ratios<br />

From main effect plot Fig.2 it is observed that polarity, peak current, pulse on time retract distance significantly<br />

Level<br />

Polarity<br />

Electrode<br />

B<br />

Peak<br />

current<br />

C<br />

Pulse on<br />

time<br />

D<br />

Duty<br />

cycle<br />

E<br />

Gap<br />

voltage<br />

F<br />

Retract<br />

distance<br />

G<br />

Concentration<br />

<strong>of</strong> powder<br />

H<br />

A<br />

1 -8.992 -10.511 -6.876 -8.069 -10.063 -10.236 -9.095 -9.972<br />

2 -11.541 -10.022 -10.816 -10.<strong>19</strong>7 -10.852 -9.467 -11.014 -9.891<br />

3 -13.108 -12.535 -9.885 -11.097 -10.691 -10.938<br />

Delta 2.549 0.489 6.232 4.466 0.967 1.630 1.9<strong>20</strong> 1.047<br />

Rank 3 8 1 2 7 5 4 6<br />

effect the surface roughness as these are having steeper slopes in main effect plots. Although slope <strong>of</strong> effect <strong>of</strong><br />

types <strong>of</strong> electrodes and concentration <strong>of</strong> fine abrasives aluminium powder are not steep, still these affect the<br />

desired objective in positive manner. Positive polarity, higher peak current, higher pulse on time contribute more<br />

spark energy leading to deeper and wider craters on the machined surfaces, thereby contributing for higher SR.<br />

whereas uniformly distributed fine abrasive powders particles under sparking area results in distributed sparking<br />

energy give more sparks and shallow craters on the surface. Response for Signals to Noise ratios at different<br />

levels are presented in Table 2. Higher the delta value in response table more the effect <strong>of</strong> parameters on the<br />

desired objective. Rank gives the relative importance <strong>of</strong> selected parameters on SR. Main effect plots suggest<br />

that negative electrode polarity , cryogenically treated copper electrode , 0.5 peak current , 50 µs pulse on time ,<br />

0.9 duty cycle 60 V gap voltage, 1mm retract distance and 6g/l <strong>of</strong> fine aluminium abrasive powder are best<br />

parametric setting for minimum SR. At these settings confirmation experiments were performed and 6.5%<br />

improvement was observed in SR.Provide a space <strong>of</strong> 60 pts before the title <strong>of</strong> the paper. It may be created using<br />

“Format – Paragraph – Indent and Spacing – Spacing: Before 60 pt” option.<br />

4. Conclusions<br />

From present investigations following conclusions are drawn.<br />

1) AEDM is possible option with cryogenically treated copper electrode on Inconel 718.<br />

2) Polarity, peak current and pulse on time effect surface roughness drastically.<br />

3) Cryogenically treated copper electrode and concentration <strong>of</strong> fine aluminium abrasive powder particles<br />

effects the SR in positive manner and enhance SR appreciably.<br />

484


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4) The optimum parametric setting s for minimum SR are negative electrode polarity , cryogenically<br />

treated copper electrode , 0.5 peak current , 50 µs pulse on time , 0.9 duty cycle, 60 V gap voltage, 1mm<br />

retract distance and 6g/l <strong>of</strong> fine aluminium abrasive powder.<br />

Acknowledgements<br />

The authors would like to acknowledge the support <strong>of</strong> department <strong>of</strong> mechanical engineering, Beant College <strong>of</strong><br />

Engineering and <strong>Technology</strong>, Gurdaspur, Punjab, India, <strong>University</strong> School <strong>of</strong> Engineering and <strong>Technology</strong><br />

GGSIPU, Delhi, India and All India Council for Technical Education New Delhi, India for supporting and funding<br />

the research work under research promotion scheme in this direction vide file No.: 8023/BOR/RID/RPS-144/<strong>20</strong>08-<br />

09 and 8023/BOR/RID/RPS-86/<strong>20</strong>09-10.<br />

References<br />

1) Kumar, A., Maheshwari, S., Sharma, C. and Beri, N. (<strong>20</strong>10) , Materials and Manufacturing processes, Vol.<br />

25, No. 10, pp. 1166–1180.<br />

2) Klocke, F.; Lung, D.; Antonoglou, G.; Thomaidis, D. Journal <strong>of</strong> Materials Processing <strong>Technology</strong> <strong>20</strong>04,<br />

149,<strong>19</strong>1–<strong>19</strong>7.<br />

3) Abbas, N.M.; Solomon, D.G.; Bahari, M.F. International Journal <strong>of</strong> Machine Tools and Manufacture <strong>20</strong>07,<br />

47(7-8), 1214-1228.<br />

4) Kumar, A.; Maheshwari, S.; Sharma, C.; Beri N. Journal <strong>of</strong> Mechanical Engineering <strong>20</strong>09, 60(5-6), 298-<br />

304.<br />

5) K.P. Rajurkar, Handbook <strong>of</strong> Design Manufacturing and Automation Chapter 13: Nontraditional<br />

Manufacturing Processes, Wiley, USA, <strong>19</strong>94.<br />

6) Kansal, H.K.; Singh, S.; Kumar, P. Journal <strong>of</strong> Materials Processing <strong>Technology</strong> <strong>20</strong>07, 184, 32-41.<br />

7) Kumar, A.; Maheshwari, S.; Sharma, C.; Beri N. Proc. <strong>of</strong>. Int. Conf. on Advances in Mechanical<br />

Engineering, Trivandrum, Kerala, India, Dec, <strong>20</strong>10, pp. 51-53. (Chapter No. 6)<br />

8) W.S. Zhao, Q.G. Meng and Z.L. Wang,. Journal <strong>of</strong> Materials Processing <strong>Technology</strong>, vol. 129(1-3), 30-33.<br />

<strong>20</strong>02.<br />

9) S. Singh, S. Maheshwari and P.C. Pandey, Journal <strong>of</strong> Mechanical Engineering, vol. 57, no.1, pp.13-33,<br />

<strong>20</strong>06.<br />

10) Kumar, A.; Maheshwari, S.; Sharma, C.; Beri N. Materials and Manufacturing processes, (In press <strong>20</strong>10).<br />

11) Ho, K.H.; Newman, S.T. International Journal <strong>of</strong> Machine Tools and Manufacture <strong>20</strong>03, 43, 1287-1300.<br />

12) Erden, A., and Bilgin, S., Proceedings <strong>of</strong> the 21 th International Machine Tool Design and Research<br />

Conference, Macmillan, London, <strong>19</strong>80, pp. 345-350.<br />

13) Jeswani, M.L. Wear, <strong>19</strong>81, 70(2), 133-139.<br />

14) Mohri, N., Saito, N., Higashi, M.A. Annals CIRP, <strong>19</strong>91, 40(1), <strong>20</strong>7-210.<br />

15) Kumar, A., Maheshwari, S., Sharma, C. Advanced Materials Research, Vol. 410 (<strong>20</strong>12) pp 236-239<br />

485


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

DESIGN AND DEVELOPMENT OF CELLULAR LAYOUT FOR<br />

MACHINING AXLE HOUSING AND CARRIER COMPONENT<br />

BommireddyG.K 1 , Dr DN Shivappa 2 , & Chethan C N 3<br />

1.<br />

PG Student,e-mail:bommi013@gmail.com<br />

2. Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, Sir M. Visvesvaraya Institute <strong>of</strong> <strong>Technology</strong>, Bangalore -<br />

562157, India. e-mail:shivappadn@gmail.com.<br />

3. Divisional Manager, Shakti precision component India Pvt Ltd, Bangalore-560 048.<br />

Abstract<br />

Anew cellular layout for machining <strong>of</strong> Axle Housing and Carrier Component was designed and developed for<br />

Shakti Precision Components India Pvt Ltd Bangalore. Company is doing machining operations in 4 cells at<br />

existing layout, out <strong>of</strong> 4 cells it was found that TAFE cell is more congested. Extensive study <strong>of</strong> existing TAFE<br />

cell has been carried out to understand the cycle time, loading and unloading time, issues related to line<br />

balancing <strong>of</strong> machining operations and WIP inventory. Study has revealed that this cell is over loaded and has<br />

bottlenecks such as higher WIP inventory, unbalanced loading etc and it was decided that machining operations<br />

<strong>of</strong> Axle Housing and Carrier Component are to be separated from this cell. And for machining <strong>of</strong> these<br />

components it was found appropriate to establish One-Piece Flow Cellular layout, accordingly a suitable<br />

cellular layout was developed.<br />

Keywords: Machining operations, Line balancing, One-piece flow, Cellular Layout, Axle Housing, Carrier<br />

Component, Takt time<br />

Abbreviations:<br />

TAFE<br />

WIP<br />

Tractor and Farm Equipment’s<br />

Work in Process<br />

OIB Oil Initial Brake<br />

IDB Integrated Disk Brake<br />

OD Outer Diameter<br />

ID Inner Diameter<br />

VTL Vertical Turn Lathe<br />

VTM Vertical Turn Mill<br />

HMC Horizontal Machining Center<br />

VMC Vertical Machining Center<br />

Dia Diameter<br />

Chf Chamfer<br />

1. Introduction<br />

Company is doing the machining work for oil initial brake axle housing, integrated disc brake and carrier<br />

component for “Tractor and Farm Equipment’s (TAFE)”. Case transmission front and case transmission rear for<br />

'Eicaher. Front and rear case for' Caterpillar'. Common Rail, two and four cylinder pump housing and HFR 16<br />

for 'BOSCH'. Machining work such as milling, drilling, tapping, boring, spot facing and finishing operations are<br />

being carried out using Horizontal Machining Centers, Vertical Turn Mill, Vertical Turn Lathe, Slot Cutting<br />

machine, and Vertical Machining Center. All these machines are housed in four cells in cellular manufacturing<br />

environment. These four cells are; (i) TAFE Cell (ii) BOSCH Cell (iii) Husco Cell (iv) Robo Cell.<br />

Now the company is getting more orders and it is becoming difficult to carry out the machining work in the<br />

existing four cells. Hence the company has taken decision to relocate the machining <strong>of</strong> Axle Housing and Carrier<br />

Component from TAFE cell and develop a separate layout for machining <strong>of</strong> these components.<br />

Cellular manufacturing is an application <strong>of</strong> group technology which involves the grouping <strong>of</strong> machines,<br />

processes and people into cells responsible for manufacturing or assembly <strong>of</strong> similar parts or products. Different<br />

and independent surveys conclude that significant improvements can be achieved as a result <strong>of</strong> implementing<br />

cellular manufacturing in areas such as lead times, set up times, work in process, quality, machine utilization and<br />

employee job satisfaction [1]. In Cellular manufacturing machinery and small team <strong>of</strong> staff are put together so all<br />

the work on a product or part can be accomplished in the same cell eliminating resources that do not add value to<br />

the product.<br />

486


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Cellular layouts are generally more space efficient than other arrangements, and are transferable to other<br />

facilities.The main reason that manufacturing companies are attracted towards implementing cellular<br />

manufacturing is that the benefits <strong>of</strong> Cellular manufacturing can normally be realized with relatively low capital<br />

investment by relocating and possibly duplicating certain machines as opposed to other automated strategies.<br />

Cellular manufacturing is an approach that helps in building <strong>of</strong> variety <strong>of</strong> products with a little waste as possible.<br />

In Cellular manufacturing machinery and small team <strong>of</strong> staff put together so all the work on a product or part can<br />

be accomplished in the same cell eliminating resources that do not add value to the product.It is based on group<br />

<strong>of</strong> different processes located in close proximity to manufacturing a group <strong>of</strong> similar products<br />

[2].NittayaandBusaba [3] in their case study on Electronic Manufacturing Service Plant have identified that<br />

cellular manufacturing systems’also suits for high volume production. Outcome <strong>of</strong> their case study is found to be<br />

very much useful for the present work.<br />

2. Problems Identified in Existing TAFE cell<br />

Detail study <strong>of</strong> production processes at TAFE Cell was carried out; some <strong>of</strong> the important problems identified in<br />

the cell are given below:<br />

• Distance between the machines is 2.1 feet which is to be increased.<br />

• Air cleaning operation is carried out at inside the plant layout which produces a lot <strong>of</strong> noise.<br />

• Electric equipment’s such as panel board, UPS are placed inside the plant layout; it is required to separate the<br />

electric equipment’s from working area.<br />

• Machines are arranged in shop floor without properly analyzing time required for material movements and<br />

cycle time <strong>of</strong> machining work; this has resulted in non-value added time and higher WIP inventory.<br />

• Total 90 cutting tools are used to carry out the machining operations for IDB axle housing components this has<br />

resulted in higher tooling cost.<br />

• At OIB Axle Housing line VTM 02 machine taking more cycle time compared to customer takt time this has<br />

resulted company having 75 components <strong>of</strong> production in place <strong>of</strong> demand rate <strong>of</strong> 115 components.<br />

• At IDB Axle Housing line first operation for 3components is performed in 3 Horizontal Machining Center<br />

A81 machines and second operation is performed at 1 machine <strong>of</strong> Horizontal Machining Center A51 machine.<br />

This is causing over burden on operator working at HMC A51.<br />

• Components are moved in batches without proper scheduling <strong>of</strong> machining work, this is resulting higher WIP<br />

inventory at each machine.<br />

3. Line Balancing for Machining <strong>of</strong> Axle Housing and Carrier Component<br />

In order to develop a new layout for Axle Housing and Carrier components it is necessary to balance the<br />

production load based on takt time. All the details <strong>of</strong> takttime and production line balancing for these components<br />

are discussed in the following sections.<br />

3.1 Takt time for Axle Housing and Carrier Components<br />

Takt time is a common lean concept applicable and beneficial in a number <strong>of</strong> situations. The idea is to produce<br />

product or carry out the work at the rate at which the customer requires it. If the customer demand averages one<br />

unit per production minute, produce the product at this rate (Takt time). It is the ratio <strong>of</strong> available work time to the<br />

customer demand rate [4]. In the present work takt time is considered as important factor to determine the layout<br />

requirements. Takt time is useful foranalysing the process loads and excess capacity.<br />

3.2 Takt time calculations for OIB Axle Housing<br />

Available work time per day= 80460 seconds per day<br />

Daily customer demand for OIB Axle Housing components is 115components/day.<br />

Takt time<br />

=699 sec/piece<br />

Similarly the takt time for IDB Axle Housing is 638 sec/piece and for Carrier component it is 640 sec/piece.<br />

3.3 LineBalancingfor OIB Axle Housing<br />

OIB Axle Housing component has two variants such as shorter and longer. To develop one piece flow line it is<br />

required, that process must be able to scale to the customer takt time. Operation data <strong>of</strong> OIB Axle Housing is given in<br />

Table 1 and the line balancing chart is shown in Figure 1. First operation for shorter component is performed in VTL<br />

machine and for longer component in VTM 01 machine. Time taken for machining in VTL is 1353 sec where as in<br />

487


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

VTM01 is 1526 sec. Due to variation in cycle time <strong>of</strong> both the machines; the component from the VTM 01 machine<br />

gets bottled up in the buffer station due to shorter operation time <strong>of</strong> the VTL machine From the existing line<br />

balancing chart it is clear that there is higher cycle time (918 sec) at second operation VTM 02 compared to customer<br />

takt time <strong>of</strong> 699 sec. To balance the line for customer takt time at VTM 02 machine two operations namely ID<br />

roughing and ID finishing are shifted to Horizontal Machining Centre A81 machine. The cycle time <strong>of</strong> each operation<br />

is given in the Table 1.<br />

From this change the cycle time at VTM 02 is brought down from 918 seconds to 676 seconds, which gets balanced<br />

with customer takt time <strong>of</strong> 699 seconds which is shown in fig 2.<br />

After shifting two operations from VTM 02 to HMC A81 the cycle time at HMC A81 gets increased to 863 seconds<br />

which is more than the takt time <strong>of</strong> 699 seconds.<br />

1000<br />

918<br />

Cycle Time (seconds)<br />

800<br />

600<br />

400<br />

<strong>20</strong>0<br />

7<strong>19</strong><br />

621<br />

475<br />

Takt Time= 699<br />

0<br />

1st 2nd 3rd 4th<br />

Operation<br />

Figure 1 Line Balancing Chart <strong>of</strong> OIB Axle Housing for Existing State<br />

Takt Time= 699<br />

Cycle Time (seconds)<br />

Operation<br />

Figure 2 Modified Line Balancing Chart for OIB Axle Housing<br />

To balance the cycle time <strong>of</strong> HMC A81 machine with takt time four operations namely Dia 80 rough milling, Dia 63<br />

fine milling, Dia 8 drilling and 3/8 turning operations are shifted to HMC A51 machine.<br />

After shifting these four operations to the HMC A51 machine the cycle time <strong>of</strong> machine HMC A81 comes down to<br />

677 seconds which get balanced with customer takt time <strong>of</strong> 699 seconds. With these improvements waiting time for<br />

the material at HMC A51 machine gets reduced. Process inspection is performed at the end <strong>of</strong> machining work and<br />

time taken for process inspection is 60 seconds.<br />

488


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Standardized work for operators and estimation <strong>of</strong> number <strong>of</strong> operators<br />

Standardization <strong>of</strong> operations helps in the elimination <strong>of</strong> variability in the work. With this method each operator is<br />

doing the same amount <strong>of</strong> the work in a line leads better line balancing. The standard loading and un-loading<br />

procedures for the operators at OIB Axle Housing cell is provided.<br />

Number <strong>of</strong> operators required to meet the customer Takt time is determined as follows;<br />

Number <strong>of</strong> operators =<br />

Total work content in the cell is sum <strong>of</strong> the cycle time at each machine (Table 1) is 3453.5<br />

secondsandcustomertakt time for OIB Axle Housing Components is 699 seconds<br />

Number <strong>of</strong> operators = = 5 operators<br />

3.4 Line Balancing for IDB Axle Housing<br />

At IDB Axle Housing line machining work is carried out for three types <strong>of</strong> casting components. First operation for<br />

three casting components performed in three Horizontal Machining Centres (HMC A81) and second operation is<br />

performed in one machine <strong>of</strong> Horizontal Machining Centre (HMCA51). In order to scale the cycle time <strong>of</strong> each<br />

machine to the customer takt time, machining operations are equally divided in to three machines <strong>of</strong> Horizontal<br />

Machining CentresA81. The operations divided to the each machine are discussed here below.<br />

Horizontal Machining Centre [HMC A81/1]<br />

Seven machining operations are carriedout at this machine namely; Dia 80 Rough milling, Dia 80 Shell mill , Dia 25<br />

end mill, Dia 63 fine milling cutter, Dia 32 finish end mill, Dia 298.5 rough boring bar and Dia 298.5 s/f boring<br />

operations. Time taken to perform these operations in HMC A81/1 machine is given in the Table 2.<br />

Horizontal Machining Centre [HMC A81/2]<br />

Nine machining operations are carriedout at this machine namely;Dia 40 milling ,Dia 32 3-lip end mill, Dia 25 L<br />

end mill, 65 & 71.5 rough boring bar, Dia 95 & 107 rough boring bar, Dia 72 chf, 99.75,112.1 chf , Dia 72 Fine<br />

boring, Dia 112.6 fine boring and Dia 250 mill cutter. Time taken to perform these operations in HMCA81/2<br />

machine is approximately equal to the customer takt time <strong>of</strong> 638 sec.<br />

Horizontal Machining Centre [HMC A81/3]<br />

Total 13 machining operations are done on this machine namely;Dia 13.5 drilling, Dia 10.5 drilling, Dia 6.8 drilling,<br />

Dia 28 drilling, Dia 26.5 U- drilling, Dia 31.3 rough boring, Dia 31.9 fine boring, Dia 27 rough milling, Dia 28.8<br />

rough milling, m12*1.5 taping, m8*1.25 taping, Dia 125 back facing milling and Dia32-42 chamfer. Time taken to<br />

carry out these machining operations is also given in the Table 2.<br />

Horizontal Machining Centre [HMC A51]<br />

Milling operations are performed in this machine and time taken to complete the machining operations in HMC<br />

A51 is 8 minutes. At the end <strong>of</strong> machining operations process inspection is performed on the component and time<br />

taken for inspection is 147 seconds. Fig 3 shows the line balancing chart for IDB axle housing.<br />

Standardized work for operators and estimation <strong>of</strong> number <strong>of</strong> operators<br />

Standardizing the workers movements in the cell can eliminates the variability in the process. For the purpose <strong>of</strong><br />

loading and unloading <strong>of</strong> the components standard operating procedures are provided to the each operator working<br />

at IDB Axle Housing line.<br />

Number <strong>of</strong> operators required to meet the customer takttime;<br />

Number <strong>of</strong> operators =<br />

Total work content= 608.4+636.6+627+480= 2351 seconds and customer takt time for OIB Axle Housing<br />

Components is 699 seconds<br />

Number <strong>of</strong> operators =<br />

=3.6 operators<br />

= 4 operators<br />

489


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

700<br />

600<br />

608.82<br />

636.8 627.26 627<br />

Takt Time=638<br />

500<br />

Cycle Time (Seconds)<br />

400<br />

300<br />

<strong>20</strong>0<br />

100<br />

0<br />

A81-`1 A81-2 A81-3 A51<br />

Operation<br />

Figure 3 Line Balancing Chart for IDB Axle Housing<br />

3.5 Line Balancing for Carrier Component<br />

Cycle time <strong>of</strong> slot cutting operation is 162.6 seconds and cycle time for milling and drilling operation is 585.6<br />

seconds. There is an over-production <strong>of</strong> components at 1 st operation (slot cutting operation) hence more bottleneck<br />

is identified at 2 nd operation <strong>of</strong> drilling and milling (Vertical Machining Centre).<br />

Thefixture used for slot cutting operation and the fixture used for drilling and milling operation are arranged in to a<br />

single machine <strong>of</strong> Vertical Machining Centre, With this improvement one operator and one machine gets reduced.<br />

Standardized work for operators and estimation <strong>of</strong> number <strong>of</strong> operators<br />

The standard operating procedures for the operators working at Carrier component line is provided. And number <strong>of</strong><br />

operators required to meet the customer takt time is determined as 1 operator<br />

4. Development <strong>of</strong> New Cellular Layout<br />

In the preceding sections all the requirements for machining <strong>of</strong> Axle Housing and Carrier component are<br />

discussed. In addition to effecting changes discussed above the following requirements are incorporated in new<br />

layout.development <strong>of</strong> one piece flow cellular layout for<br />

(i) The material is handled within the layout by using hand operated low lift pallet truck. The width <strong>of</strong> the crate<br />

is 5.57 feet for safe and easy handling <strong>of</strong> pallet truck aisle width <strong>of</strong> 6.5 feet is considered.<br />

(ii) To eliminate the back tracking <strong>of</strong> the components, the layout is designed such that the components are<br />

entered at one end <strong>of</strong> the layout and exits at other end.<br />

(iii) For safe and easy accessibility <strong>of</strong> coolant tank, machine to machine distance <strong>of</strong> 3 feet is considered.<br />

(iv) To provide safe working environmentair cleaning operation is placed outside the shop floor.<br />

(v) For safety purpose electric equipment’sare to be placed inseparateroom.<br />

Incorporating all the improvements and requirements the new layout is established in separate location with floor<br />

space <strong>of</strong> 14267 square feet. Figure 4 depicts new cellular layout.<br />

5. Conclusion<br />

Study <strong>of</strong> machining operations at existing TAFE Cell revealed that this cell is overloaded and has bottlenecks such<br />

as higher WIP inventory, unbalanced loading etc. After studying machining operations <strong>of</strong> all the components at<br />

TAFE Cell it was decided that machining operations <strong>of</strong> Axle Housing and Carrier Component are to be separated<br />

from this cell. For this it was found appropriate to establish One-Piece Flow Cellular layout, accordingly a suitable<br />

layout was developed. Development <strong>of</strong> new layout has resulted in following improvements.<br />

(i) In IDB Axle Housing production line three HMC A81 machines are allocated in place <strong>of</strong> one machine used<br />

earlier, this has resulted in reduction <strong>of</strong> cutting tools from 87 to 29.<br />

(ii) WIP inventory for machining <strong>of</strong> OIB Axle Housing is brought down from 132 components to 16<br />

components and that <strong>of</strong> IDB Axle Housing from 28 components to 6 components.<br />

490


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

(iii) Line balancing <strong>of</strong> OIB Axle Housing resulted in increase in the machining <strong>of</strong> 115 components against 75<br />

components machined earlier.<br />

(iv) Process inspection for the components is performed at the end <strong>of</strong> all machining operations in place <strong>of</strong><br />

inspections done in between the machining process which was creating problems for workers.<br />

(v) In the new layout air cleaning operation is separated from the work area that has created safe and hazard free<br />

environment. New standard operating procedures have been established for all the activities at new layout.<br />

6. References<br />

[1] MassoudBazargan-Lari, “Layout Design in Cellular Manufacturing”. <strong>University</strong> <strong>of</strong> western Sydney, 258-<br />

259,264-271 (<strong>19</strong>98)<br />

[2] Ladipo M.K, Adelana S.O, “Case study on Cellular Manufacturing using Production Flow Analysis” (<strong>20</strong>11)<br />

[3] NittayaNgampakandBusabaPhruksaphanrat, Cellular Manufacturing Layout Design and Selection: A Case<br />

Study <strong>of</strong> Electronic Manufacturing Service Plant”, IMECS <strong>20</strong>11, March 16-18, <strong>20</strong>11, Hong Kong.<br />

[4] MartonMichal - Paulová, Iveta: “One piece flow - another view on production flow in the next continuous<br />

process improvement”,Slovak <strong>University</strong> <strong>of</strong> <strong>Technology</strong> in Bratislava, Scientific papers in domestic journals,<br />

pp 30-33, <strong>20</strong>08-11), Institute <strong>of</strong> Industrial Engineering, Management and QualityPaulínska 16, 917 24 Trnava<br />

491


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 1 Operations Data for Machining <strong>of</strong> OIB Axle Housing<br />

Man Time<br />

Operation<br />

Seconds<br />

Loading 162<br />

1 OD roughing and face roughing 139<br />

Sl<br />

No.<br />

M/c time<br />

Seconds<br />

Cycle Time<br />

Seconds<br />

Takt Time<br />

Seconds<br />

2 ID roughing 394<br />

3 ID finishing (Dia 264 mm) 268 1353 699<br />

4 OD finishing 21<br />

5 ID finishing 24<br />

6 Back facing 164<br />

Unloading 181<br />

Loading 106<br />

1 OD roughing and face roughing 256<br />

2 ID roughing 470 1526 699<br />

3 ID finishing (Dia 264 mm) 251<br />

4 OD finishing 98<br />

5 ID finishing 50<br />

6 Back facing 218<br />

Unloading 77<br />

Loading 50<br />

1 OD roughing 127<br />

2 ID roughing 154<br />

3 ID face roughing 114<br />

4 ID face finish 62<br />

5 OD finish 76 918 699<br />

6 ID finish 88<br />

7 Back facing 106<br />

8 4mm grooving 99<br />

Unloading 42<br />

Loading 141<br />

1 Dia 80 rough milling 81<br />

2 Dia 63 face milling 37<br />

3 Dia 8 drilling 28<br />

4 3/8 turning 40<br />

5 Dia 11.9 drilling 52<br />

6 Dia 13.6 drilling 66<br />

7 Dia 6.9 drilling 13<br />

8 5/6 taping 28<br />

9 Dia 12.85 drilling 16<br />

10 Dia 24.5 u drilling 21<br />

621 699<br />

11 Dia 25.07 rough milling 15<br />

12 Dia 250 T-slot cutting 12<br />

13 Dia 25 milling 58<br />

14 Dia 28.3 drilling 42<br />

15 Dia 28.75 rough milling 43<br />

16 Dia 25 milling 13<br />

17 Dia 8.52 drilling 28<br />

18 3/8 taping 28<br />

Unloading 122<br />

Loading 66<br />

1 Milling 478 475 699<br />

Unloading 60<br />

Station Name<br />

Vertical Turn Lathe<br />

(VTL)<br />

Vertical Turn Mill<br />

(VTM 01)<br />

Vertical Turn Mill<br />

(VTM 02)<br />

Horizontal machining<br />

center (HMC A81)<br />

Horizontal machining<br />

center (HMC A51)<br />

492


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 2 Operations Cycle Time for IDB Axle Housing Components<br />

Sl No.<br />

Man time<br />

Operation<br />

seconds<br />

Loading 66<br />

M/c Time<br />

Seconds<br />

1 Dia 80 Rough mill cutter 175.696<br />

2 Dia 80 Shell mill cutter 78.84<br />

3 Dia 25 end mill 49.296<br />

4 Dia 63 FMC 129.9<br />

5 Dia 32 finish end mill 75<br />

6 Dia 298.5 rough boring bar 45.55<br />

7 Dia 298.5 s/f boring bar 54.544<br />

Unloading 62<br />

Loading 66<br />

1 Dia 40 milling cutter 173.96<br />

2 Dia 32 3-lip end mill 45<br />

3 Dia 25 L end mill 41.55<br />

4 65 & 71.5 rough boring bar 41.4<br />

5 Dia 95 & 107 rough boring bar 43.584<br />

6 Dia 72 chf, 99.75,112.1 chf 34.64<br />

7 72 Fine boring 46.016<br />

8 Dia 112.6 Fine boring 140.76<br />

9 Dia 250 mill cutter 69.92<br />

Unloading 62<br />

Loading 66<br />

1 Dia 13.5 drill 57.79<br />

2 10.5 drill 40.736<br />

3 Dia 6.8 drill <strong>20</strong>.92<br />

4 Dia 28 drill 77.42<br />

5 Dia 26.5 U- drill 35<br />

6 Dia 31.3 rough bore 32<br />

7 Dia 31.9 Fine boring 32.48<br />

8 Dia 27 rough milling <strong>20</strong>.91<br />

9 Dia 28.8 rough milling 80.448<br />

10 m12*1.5 tap 49.23<br />

11 m8*1.25 tap 23.76<br />

12 Dia 125 back facing mill cutter 97.568<br />

13 Dia 32-42 chamfer 58.16<br />

Unloading 62<br />

Loading 66<br />

1 Machining 480<br />

2 Inspection 147<br />

Unloading 62<br />

Cycle time<br />

seconds<br />

Takt Time<br />

seconds<br />

Station<br />

Name<br />

608.81 638 HMC A81-1<br />

636.82 638 HMC A81-2<br />

627.26 638 HMC A81-3<br />

627 638 HMC A-51<br />

493


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 4 Proposed Cellular Layout<br />

494


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

EFFECTOF INCLUSION ON FRACTURE BEHAVIOUR OF<br />

VISCOELASTIC MATERIALS<br />

Dhairya Partap 1 Singh, Mahesh Chand 2 , Varun Chhabra 3<br />

1. Y.M.C.A. <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad (H.R)Email Id: - d.psingh2<strong>20</strong>785@gmail.com<br />

2. Y.M.C.A. <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad (H.R)Email Id:, mchanddce@gmail.com<br />

3. B.S.A. College <strong>of</strong> Engineering and <strong>Technology</strong>, MathuraEmail Id: - varunmak1@gmail.com<br />

Abstract<br />

This paper deals with a finite element analysis <strong>of</strong> crack opening displacement and the effect <strong>of</strong> inclusions on<br />

fracture behavior <strong>of</strong> viscoelastic materials. A finite element model <strong>of</strong> edge crack is established for the planar<br />

fracture problems <strong>of</strong> linear viscoelastic medium. This finite element model describes time-dependent deformation<br />

behavior <strong>of</strong> viscoelastic materials with changing microstructures. Finite element s<strong>of</strong>tware Abaqus has been used<br />

with time- dependent material parameters. The numerical example shows that the present results are in good<br />

arrangement with those analytical.<br />

Keywords: Finite element method (FEM), Linear viscoelasticity, Inclusion, Crack opening displacement,<br />

Abaqus.<br />

1. Introduction<br />

The use <strong>of</strong> polymeric materials increasing day by day for engineering application which demands a better<br />

understanding <strong>of</strong> fracture behaviors. A Viscoelastic material shows the time-dependent behavior. So, that the<br />

fracture behavior <strong>of</strong> viscoelastic problem is dependent on both current state and the whole history. Generally, the<br />

stress level is relatively low and loading time is not long, so the mechanical properties <strong>of</strong> many viscoelastic<br />

materials are modeled as linear viscoelastic materials [1]. Numerical method, especially the representative finite<br />

element method (FEM), is currently used to model viscoelastic behavior [2]. It is one <strong>of</strong> the most common<br />

computational methods.<br />

The primary objective <strong>of</strong> this paper is to develop a FEM model for analyzing the effect <strong>of</strong> inclusions on the crack<br />

problem <strong>of</strong> a viscoelastic media. As an assumption Poisson’s ratio is a constant, asymptotic displacement field in<br />

the vicinity <strong>of</strong> a crack in linear viscoelastic isotropic mediumis obtained through the classical viscoelastic- elastic<br />

principle[3].<br />

Abaqus is one <strong>of</strong> the most advanced large-scaled finite element s<strong>of</strong>tware in the world, it possesses robust<br />

computing function and extensive simulated performance and it has a large number <strong>of</strong> different kinds <strong>of</strong> element<br />

models, material models and analytic processes, especially its good nonlinearity mechanical analysis function is<br />

at the world leading level. The integral constitutive equations <strong>of</strong> relaxation shear modulus is adopted in Abaqus<br />

viscoelastic models and expanded by Prony series form [4]. Time domain viscoelasticity is available in<br />

Abaqusfor small-strain applications where the rate independent elastic response can be defined with a linear<br />

elastic material model and for large strain applications where the rate-independent elastic response must be<br />

defined with a hyperelastic or hyperfoam material model [5]. As we know, viscoelastic material shows timedependent<br />

behavior, so that for this analysis finite element s<strong>of</strong>tware Abaqus has been used. To check the validity<br />

<strong>of</strong> the formulae, the numerical results <strong>of</strong> the representative example <strong>of</strong> edge cracked viscoelastic strip are<br />

presented and compared with analytical solutions.<br />

2. Constitutive Equation<br />

In this section, we briefly present the constitutive relation. For a two-dimensional case, in integral form, the<br />

linear viscoelastic constitutive relation is [3]<br />

t<br />

σ(t) = E(t)Dε(0) + E(t − ξ)D dε(ξ) dξ Eq. (1)<br />

dξ<br />

0<br />

where σ and ε are stresses and strains in array form, respectively and t denotes time. In general, as a linear<br />

viscoelastic material, the relaxation modulus E(t) is expressed as [6]<br />

M<br />

E(t) = E ∞ + E m<br />

m=1<br />

exp− t τ m<br />

Eq. (2)<br />

Matrix D depends only on the Poisson’s ratio ν, taking the form <strong>of</strong> [7]<br />

495


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

ν<br />

⎡ 1<br />

0<br />

1 − ν<br />

⎤<br />

⎢ ν<br />

⎥<br />

1 − ν ⎢ 1 0 ⎥<br />

D =<br />

(1 + ν)(1 − 2ν) ⎢1 − ν<br />

⎥ Eq. (3)<br />

⎢<br />

(1 − 2ν)<br />

0 0<br />

⎥<br />

⎢<br />

2(1 − ν) ⎥<br />

⎣<br />

⎦<br />

When the closed crack splits, ∆u 1 (∆a — r, t) and∆u 2 (∆a — r, t) represents, respectively the crack sliding and<br />

opening displacement components at t with the following form [8]:<br />

∆u 1(∆a — r, t) = u 1 (∆a − r, π, t) − u 1 (∆a − r, −π, t)<br />

Eq. (4)<br />

∆u 2 (∆a — r, t) = u 2 (∆a − r, π, t) − u 2 (∆a − r, −π, t)<br />

Where ∆a is the virtual extended length <strong>of</strong> the crack and r is the radial crack length.<br />

3. Numerical Example<br />

In order to validate the effectiveness and accuracy <strong>of</strong> the current method for a cracked linear viscoelastic body, a<br />

fracture example is studied and numerical results are compared to available reference solutions. For the<br />

following example the material is assumed to be a three-parameter linear viscoelastic solid as shown in Figure 1.<br />

Two groups <strong>of</strong> assumed material properties are used in the validation case studies shown in Table 1.<br />

A viscoelastic strip having an edge crack with remotely applied tension as shown in Figure 2 is investigated. The<br />

height <strong>of</strong> strip is H=4W, where W=1 is the width <strong>of</strong> the strip. The crack depth is a=0.3W. Poisson’s ratio ν=0.49.<br />

The unit step loading is applied and the total loading time is T=<strong>20</strong>0. COD {u 2 (r, π, t)—u 2 (r,—π, t)}is computed<br />

at a pair <strong>of</strong> reference points A and B as shown in Figure 3.<br />

The formulation <strong>of</strong> displacement field at crack tip under remotely applied tension is [8]<br />

u 2 (r, θ, t) = Fσ 0 √πa(1 + ν) r<br />

k + 1 − 2π 2cos2 θ sin θ J(t)Eq. (5)<br />

2 2<br />

where u 2 is the y-direction displacement component in Cartesian coordinate system located at crack tip. r and θ<br />

are the polar coordinates defined around the crack tip. F is a nondimensional<br />

coefficient for stress intensity factor with the value 1.6599, J (t) is the creep compliance, and k<br />

is the Kolosov constant takes the value <strong>of</strong> k= (3- 4ν) for plain strain state andσ0 is assumed to be 1 [8].<br />

TABLE I<br />

MATERIAL PARAMETERS OF THE LINEAR VISCOELASTIC SOLID.<br />

Set E ∞ E 1 η 1<br />

A 1.0 1.0 5.0<br />

B 1.0 2.0 5.0<br />

Figure 1: The three-parameter linear viscoelastic solid.<br />

496


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 2:An edge cracked viscoelastic strip under tension load<br />

4. Modeling<br />

The viscoelastic material shows the time-dependent behavior. The time domain viscoelastic material model:<br />

• Describes isotropic rate-dependent material behavior for materials in which dissipative losses primarily<br />

caused by “viscous” (internal damping) effects must be modeled in the time domain.<br />

• can be used only in conjunction with “Linear elastic behavior,”<br />

• is active only during a transient static analysis (“Quasi-static analysis,”) [5]<br />

The problem is assumed to be plane strain type and the material is a three-parameter linear viscoelastic solid. For<br />

this<br />

Figure 3: Reference points for COD<br />

(a)<br />

(b)<br />

497


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 4: (a) Boundary conditions, (b) Finite element mesh model<br />

analysis the half part <strong>of</strong> the crack problem has been considered.<br />

For assigning the viscoelastic material property in Abaqus shear test data has been used. The following<br />

mathematical relations have been used to calculate the shear test data:<br />

In this case, the relaxation modulus in Eq. 2 becomes<br />

E(t) = E ∞ + E 1 exp −t ′ Eq. (6)<br />

τ 1<br />

and the corresponding creep compliance J (t) in Eq. 5 is [7]<br />

E 1<br />

J(t) = 1 −<br />

E ∞ E ∞ (E ∞ + E 1 ) exp −t ′ Eq. (7)<br />

τ 1<br />

with time relaxation<br />

′<br />

τ 1 = 1 E<br />

+ 1 ∞ E<br />

η 1 Eq. (8)<br />

1<br />

whereη 1 is the dashpot constant.<br />

The boundary condition has been assigned to the strip, in which the displacement at the lower part <strong>of</strong> the section<br />

in y- direction is zero (Uy=0) but at right end point <strong>of</strong> the lower half part displacement is zero in both x and y-<br />

direction and 1MPa pressure has been applied to upper part <strong>of</strong> the section (σ0=1MPa) as shown in Figure 4(a).<br />

Four noded quadratic elements have been selected to mesh the model <strong>of</strong> a crack problem as shown in Figure<br />

4(b). The full integration scheme has been selected to solve this problem. After that in this cracked model the<br />

inclusion has been added in 10% <strong>of</strong> fraction to analyze the effect on the fracture behavior <strong>of</strong> viscoelastic<br />

materials, which are shown in Figure 5.<br />

Figure 5:(a) Mesh model <strong>of</strong> viscoelastic strip having 10% inclusion.<br />

498


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 6:Comparison <strong>of</strong> the COD for the strip subjected to tension load with exact solution <strong>of</strong> Set A material<br />

parameters.<br />

Figure 7: Comparison <strong>of</strong> the COD for the strip subjected to tension load with exact solution <strong>of</strong> Set B material<br />

parameters.<br />

5. Results<br />

Taking the material parameters <strong>of</strong> Set A for example, the variation <strong>of</strong> COD with time is shown in Figure 6. The<br />

value <strong>of</strong> COD at initial time in present solution is 0.45 which is muchcloser to the exact solution value 0.47. The<br />

COD increased with time and at a certain instant, it became constantupto the loading time <strong>20</strong>0 sec. Its value<br />

during this period in present solution is 0.94 which is much closer to the exact solution value 0.96. It is clearly<br />

seen that the present results are in good agreement with the exact solutions.<br />

Now taking the material parameters<strong>of</strong> Set B for example, the variation <strong>of</strong> COD is shown in Figure 7. The value<br />

<strong>of</strong> COD at initial time in present solution is 0.30 which is much closer to the exact solution value 0.32. The COD<br />

increased with time and at a certain instant, became constantupto the loading time <strong>20</strong>0 sec. Its value during this<br />

period in present solution is 0.94 which is much closer to the exact solution value 0.957.It is clearly seen that the<br />

present results are in good agreement with the exact solutions.<br />

After validation <strong>of</strong> this example the inclusion has been added in 10% <strong>of</strong> fraction. Taking the material<br />

parameters <strong>of</strong> Set A, the variation <strong>of</strong> COD with time for viscoelastic strip having 10% <strong>of</strong> inclusion is shown in<br />

Figure 8. The COD during inclusion has been reduced in comparison to COD without inclusion for viscoelastic<br />

strip as shown in Figure 8.<br />

499


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

0.34<br />

0.32<br />

0.3<br />

0.28<br />

COD<br />

0.26<br />

0.24<br />

0.22<br />

0.2<br />

0.18<br />

0.16<br />

0 <strong>20</strong> 40 60 80 100 1<strong>20</strong> 140 160 180 <strong>20</strong>0<br />

TIME<br />

Figure 8:COD for the strip having 10% <strong>of</strong> inclusion.<br />

6. Conclusions and Discussion<br />

The FEM was applied to solve crack problems in linear viscoelastic materials using Prony series parameters. One<br />

problem <strong>of</strong> mode I with two groups <strong>of</strong> Prony series parameters was examined to check the validity <strong>of</strong> the current<br />

method. Through the comparison with analytical solutions from the literature, the present method proved to be<br />

accurate and efficient. When alumina particles have been in the form inclusion, the COD reduced due the<br />

stiffening effect. In future this viscoelastic cracked model will also be used to analyze the effect <strong>of</strong> voids and<br />

discontinuity on the fracture behavior <strong>of</strong> viscoelastic materials.<br />

References<br />

[1] K.Y. Sze, Hai-tao Wang, A simple finite element formulation for computing stress singularities at<br />

bimaterial interfaces, Finite Elements in Analysis and Design, 35 (<strong>20</strong>00) 97-118.<br />

[2] R. MoutouPitti, F. Dubois, O. Pop, J. Absi, A finite element analysis for the mixed mode crack growth in a<br />

viscoelastic and orthotropic medium, International Journal <strong>of</strong> Solids and Structures, 46 (<strong>20</strong>09) 3548-3555.<br />

[3] Richard M. Christensen, Theory <strong>of</strong> Viscoelasticity, 2 nd ed., New York: Academic Press, <strong>19</strong>82.<br />

[4] Kong Juan, Yuan Ju-yun, Application <strong>of</strong> linear viscoelastic differential constitutive equation in ABAQUS,<br />

<strong>20</strong> I 0, International Conference on Computer Design and Appliations (ICCDA <strong>20</strong>10).<br />

[5] Simulia, Abaqus 6.11 Analysis User’s Manual, Volume III: Materials, <strong>20</strong>11<br />

[6] Roderic Lakes, Viscoelastic Solid, CRC Press, Florida, <strong>19</strong>98.<br />

[7] H.H. Zhang, G.Rong, L.X.Li, Numerical study on deformations in a cracked viscoelastic body with the<br />

extended finite element method, Engineering Analysis with Boundary Elements 34 (<strong>20</strong>10) 6<strong>19</strong>–624.<br />

[8] J.B. Duan, Y. J. Lei ,D.K.Li, Fracture analysis <strong>of</strong> linear viscoelastic materials using triangular enriched<br />

crack tip elements,Finite Elements in Analysis and Design 47 (<strong>20</strong>11) 1157–1168.<br />

500


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

COMPOUND CASTING - A LITERATURE REVIEW<br />

Rajender Kumar Tayal 1 , Vikram Singh 2 , Sudhir Kumar 3 and Rohit Garg 4<br />

1 Lecturer, Deptt. <strong>of</strong> Mech. Engg., Govt. Polytechnic, Sirsa (Haryana), India. email: tayal.rajender@gmail.com<br />

2 Associate Pr<strong>of</strong>essor, Deptt. <strong>of</strong> Mech. Engg., <strong>YMCA</strong>UST, Faridabad, India. email: singhvikram77@gmail.com<br />

3 Pr<strong>of</strong>essor, Deptt. <strong>of</strong> Mech. Engg., NIET, Greater Noida(U.P), India. email: s_k_tomar02@yahoo.com<br />

4 Principal, Indus Institute <strong>of</strong> Engg. & Tech., Jind (Haryana), India. email: rohit_garg123@yahoo.com<br />

Abstract<br />

The lightweight construction philosophy is based on the principle <strong>of</strong> making the best possible use <strong>of</strong> the material.<br />

Whenever a single material does not satisfy the demands <strong>of</strong> a specific application, compound structures may<br />

generate a solution. Especially in lightweight construction, a multi-material-mix can provide ideal specific<br />

properties that are suitable for the conditions to which a part is subjected. Typically such combinations <strong>of</strong><br />

dissimilar materials provide desired properties in various areas <strong>of</strong> the single part. Compound casting is a<br />

process, which yields such multimaterial components. The technique is not much old and a few researchers have<br />

worked on it. However, the paper presents a recent reviews <strong>of</strong> literature on compound casting. In this paper, the<br />

literature on compound casting is reviewed in a way that would help researchers, academicians and<br />

practitioners to take a closer look at the growth, development and applicability <strong>of</strong> this technique. The review<br />

aims at providing an insight into the compound casting process backgrounds and shows the great potential for<br />

further investigations and innovation in the field. The survey <strong>of</strong> existing works has revealed several gaps in the<br />

fields <strong>of</strong> substrate pretreatments, continuous flow behavior <strong>of</strong> metal during the process, correlation between<br />

mechanical and geometrical part properties, and industrial application <strong>of</strong> some advanced processes.<br />

Keywords: Compound casting, Literature, Interface<br />

1. Introduction<br />

Vehicle construction and aerospace in particular demand solutions which save as much weight as possible while<br />

fulfilling identical or even greater requirements with regard to component properties, and which can be produced<br />

at low cost. Light weight constructions in the transport industry help to reduce weight and thus save fuel. To<br />

optimize performance, a combination <strong>of</strong> materials is the most efficient method, because one material is <strong>of</strong>ten<br />

insufficient. Light metals are not easy to join, though. Weak links arise at the joints such as rivets, welds or<br />

brazing connections.<br />

In lightweight construction, the light metals magnesium and aluminum are employed to an ever increasing extent<br />

as magnesium and aluminum are the first and second engineering light metals, respectively, and are attractive in<br />

vehicle structure applications for improving energy efficiency. For these reasons, efforts are high to work and<br />

research on efficient and economical methods to process these materials and thus to reduce the component’s<br />

dimensions. Whenever a single material does not satisfy the demands <strong>of</strong> a specific application, compound<br />

structures may generate a solution. Especially in lightweight construction, a multi-material-mix can provide ideal<br />

specific properties that are suitable for the conditions to which a part is subjected. Typically such combinations<br />

<strong>of</strong> dissimilar materials provide desired properties in various areas <strong>of</strong> the single part. Components constructed<br />

using hybrid methods have proven to <strong>of</strong>fer a useful approach. The compound casting is the process which meets<br />

a wide range <strong>of</strong> requirements within one component by combining different materials. In addition to saving<br />

weight, it has the added advantage <strong>of</strong> reducing bonding processes.<br />

2. Casting<br />

Casting is a manufacturing process by which a liquid material is usually poured into a mold, which contains a<br />

hollow cavity <strong>of</strong> the desired shape, and then allowed to solidify. The solidified part is also known as a casting,<br />

which is ejected or broken out <strong>of</strong> the mold to complete the process. Casting materials are usually metals or<br />

various cold setting materials. Casting is most <strong>of</strong>ten used for making complex shapes that would be otherwise<br />

difficult or uneconomical to make by other methods.<br />

3. Compound Casting<br />

Compound casting is a process through which two metallic materials—one in solid state and the other liquid—<br />

are brought into contact with each other. In this way, a diffusion reaction zone between the two materials and<br />

thus a continuous metallic transition from one metal to the other is formed. This method could join semi-finished<br />

parts with complex structures, simply by casting a metal onto or around a solid shape. However, many<br />

501


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

researchers have used compound casting to join different similar and dissimilar metallic couples such as<br />

steel/cast iron, steel/Cu, steel/Al, Cu/Al, Al/Al, and Mg/Mg, joining dissimilar light metals such as aluminum<br />

and magnesium by the compound casting process is still a relatively unexplored area. In this study, compound<br />

casting as an economic straightforward in situ technique was used to join dissimilar aluminum and magnesium<br />

light metals.<br />

Through the combination <strong>of</strong> various materials, this compound casting process can help components meet the<br />

most diverse <strong>of</strong> requirements. And with the hybrid construction process, the material bond is created by recasting<br />

– separate hot or cold bonding/jointing processes are not necessary. This in turn reduces the number <strong>of</strong><br />

production steps needed in the manufacturing process.<br />

A good example <strong>of</strong> applications in this field is the manufacturing <strong>of</strong> engine blocks. As a pure sheet steel solution,<br />

it consists <strong>of</strong> numerous individual parts which are joined to one another. In contrast, the compound casting<br />

solution makes it possible to produce this component as a single piece. The intelligently designed casting made<br />

from aluminium or magnesium alloy ensures the high functional integrity <strong>of</strong> flanges and bearing carriers, for<br />

instance.<br />

In difficult areas, a carefully positioned insert such as a semi-finished product made <strong>of</strong> steel or an aluminum<br />

alloy provides the necessary strength. In comparison with conventional die casting, the manufacture <strong>of</strong> a<br />

compound casting piece requires additional handling, for example manipulation <strong>of</strong> inserts or perhaps<br />

pretreatment <strong>of</strong> the surfaces.<br />

3.1. Applications <strong>of</strong> Compound Casting<br />

Compound casting parts are already used in vehicle construction for parts <strong>of</strong> the chassis, such as the engine<br />

block, shock strut supports and gearbox casing, as well as bodywork components, for example door frames and<br />

connection supports and as dashboard mounts in the interior. And according to information from the automotive<br />

industry, multi-material components are on the increase. This is proven by compound cast parts such as the 6-<br />

cylinder magnesium engine with aluminum insert from BMW and other components which are undergoing<br />

development but have not yet been announced. The aircraft industry, too, is relying more and more on compound<br />

cast materials.<br />

3.2. Compound Casting Process<br />

The compound casting process to prepare the Al/Mg couples from commercially pure aluminum and<br />

commercially pure magnesium are as under.<br />

In this process cylindrical inserts with <strong>20</strong> mm diameter and 100 mm height were machined from aluminum and<br />

magnesium ingots. Their surfaces were ground with silicon carbide papers up to 1<strong>20</strong>0 grit, then rinsed with<br />

acetone and placed within a cylindrical cavity <strong>of</strong> a CO2 sand mold with 30 mm diameter and 80 mm height. Two<br />

series <strong>of</strong> samples were prepared. In the first series, aluminum ingots were melted in a clay-graphite crucible<br />

placed in an electrical resistance furnace. The molten aluminum was cast around the magnesium inserts at 700 0 C<br />

under normal atmospheric conditions.<br />

In the second series, magnesium ingots were melted in a steel crucible placed in the same furnace under the<br />

covering flux, to protect magnesium melt form oxidation. The molten magnesium was cast around the aluminum<br />

inserts at 700<br />

0 C under normal atmospheric conditions. Schematic sketches <strong>of</strong> the mold used in the casting<br />

process and the prepared Al/Mg couple are illustrated in Fig. 1.<br />

Figure 1 Schematic sketches <strong>of</strong> (a) the mold used for the casting process and (b) the prepared Al/Mg couple.<br />

502


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4. Literature Review<br />

A lot <strong>of</strong> research material is referred to describe the insights <strong>of</strong> the compound casting process. However 10 major<br />

papers are selected as arranged in descending order <strong>of</strong> their year <strong>of</strong> publication in table-1. These selected papers<br />

are studied in detail so that every aspect <strong>of</strong> the process i.e. from preparation <strong>of</strong> substrate, pretreatments, pouring<br />

system, solidification behavior, microstructural analysis & mechanical properties can be determined.<br />

Table-1 Depicting title <strong>of</strong> papers along with year & journal in which published<br />

S.NO<br />

Title <strong>of</strong> Paper<br />

Year <strong>of</strong><br />

Publication<br />

Name <strong>of</strong> Journal<br />

1.<br />

Dissimilar joining <strong>of</strong> Al/Mg light metals by<br />

compound casting process<br />

<strong>20</strong>11<br />

Journal <strong>of</strong> Materials <strong>Science</strong><br />

2.<br />

Mechanical testing <strong>of</strong> titanium/ aluminium–<br />

silicon interface: Effect <strong>of</strong> T6 heat treatment<br />

<strong>20</strong>11<br />

Materials <strong>Science</strong> and Engineering<br />

A<br />

3.<br />

Aluminium–aluminium compound fabrication<br />

by high pressure die casting<br />

<strong>20</strong>11<br />

Materials <strong>Science</strong> and Engineering<br />

A<br />

4.<br />

Interface formation between liquid and solid Mg<br />

alloys—An approach to continuously<br />

metallurgic joining <strong>of</strong> magnesium parts<br />

<strong>20</strong>10<br />

Materials <strong>Science</strong> and Engineering<br />

A<br />

5.<br />

Effect <strong>of</strong> copper insert on the microstructure <strong>of</strong><br />

gray iron produced via lost foam casting<br />

<strong>20</strong>09<br />

Materials and Design<br />

6.<br />

Light metal compound casting<br />

<strong>20</strong>09<br />

<strong>Science</strong> in China<br />

7.<br />

Solidification processed Mg/Al bimetal<br />

macrocomposite: Microstructure and mechanical<br />

properties<br />

<strong>20</strong>08<br />

Journal <strong>of</strong> Alloys and Compounds<br />

8.<br />

Interface formation in aluminium–aluminium<br />

compound casting<br />

<strong>20</strong>08<br />

Acta Materialia<br />

9.<br />

Mechanical testing <strong>of</strong> titanium/aluminium–<br />

silicon interfaces by push-out<br />

<strong>20</strong>08<br />

Journal <strong>of</strong> Materials <strong>Science</strong><br />

10.<br />

Effect <strong>of</strong> continuous cooling heat treatment<br />

on interface characteristics <strong>of</strong> S45C/copper<br />

compound casting<br />

<strong>20</strong>04<br />

Journal <strong>of</strong> Materials <strong>Science</strong><br />

These selected papers are studied in detail so that every aspect <strong>of</strong> the process i.e. from preparation <strong>of</strong> substrate,<br />

pretreatments, pouring system, solidification behavior, microstructural analysis & mechanical properties can be<br />

determined. Table-2 depicts a detailed review <strong>of</strong> 10 papers on compound casting process or some other processes<br />

which are very similar to compound casting process. Outcomes <strong>of</strong> the different reviews along with testing<br />

mechanisms and few observed values are also shown.<br />

503


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 2 Depicting outcomes <strong>of</strong> the different reviews<br />

• Scanning electron<br />

Paper Material Process Major Findings Testing Method<br />

No.<br />

1 Al-Mg Compound • Joining <strong>of</strong> aluminum and<br />

Al 12 Mg 17 intermetallic<br />

Casting<br />

magnesium by the compound<br />

casting process is possible only<br />

microscope (SEM).<br />

via casting magnesium melt • Energy dispersive<br />

around the aluminum insert, X-ray spectroscopy<br />

while in the case <strong>of</strong> casting (EDS).<br />

aluminum melt around the<br />

magnesium insert, a gap is • Wavelength<br />

formed at the interface due to dispersive X-ray<br />

presence <strong>of</strong> oxide layers on the<br />

surface <strong>of</strong> the aluminum melt and<br />

spectroscopy (WDS)<br />

detectors.<br />

magnesium insert and also<br />

because <strong>of</strong> the interface • X-ray<br />

loosening, caused by higher diffractometer.<br />

coefficient <strong>of</strong> thermal expansion<br />

<strong>of</strong> the magnesium insert than the • Push out test.<br />

cast aluminum.<br />

• Vickers hardness<br />

• Formation <strong>of</strong> the interface in the<br />

compound casting process is<br />

tester.<br />

diffusion controlled and the<br />

interface consists <strong>of</strong> three<br />

different layers.<br />

• The layers adjacent to the<br />

aluminum and magnesium base<br />

metals are composed <strong>of</strong> the<br />

Al 3 Mg 2 intermetallic compound<br />

and the (Al 12 Mg 17 + ) eutectic<br />

structure, respectively, and the<br />

middle layer is composed <strong>of</strong> the<br />

compound.<br />

2 Titanium/alu<br />

minium–<br />

silicon<br />

Ti/Al–7Si–<br />

0.3Mg<br />

Insert<br />

Moulding<br />

(Aluminizi<br />

ng<br />

followed<br />

by<br />

Insertion<br />

process.)<br />

The present paper reports on the<br />

application <strong>of</strong> a T6 heat-treatment to the<br />

chemically bonded Ti/AS7G bimetallic<br />

assemblies.<br />

• The results obtained after pushout<br />

and circular bending tests<br />

highlight the potential <strong>of</strong> this<br />

joining process for producing<br />

bimetallic castings with high<br />

mechanical strengths.<br />

• As expected, the heat treatment<br />

results in an improvement <strong>of</strong> the<br />

mechanical properties <strong>of</strong> the<br />

AS7G matrix itself when applied<br />

to Ti/AS7G assemblies. A<br />

significant increase <strong>of</strong> the load<br />

level characteristic for damage<br />

onset is observed.<br />

• This result is <strong>of</strong> particular<br />

interest, especially when<br />

compared to iron-based inserts in<br />

equivalent matrixes, for which a<br />

• Optical microscopy<br />

(OM).<br />

• Scanning electron<br />

microscopy (SEM).<br />

• Energy dispersive<br />

spectroscopy (EDS).<br />

• Electron probe<br />

microanalysis<br />

(EPMA).<br />

• Classical push-out<br />

test.<br />

• Circular bending<br />

tests<br />

• T6-type heat<br />

treatment<br />

504


3 Al-Al Compound<br />

Casting<br />

using high<br />

pressure<br />

die casting<br />

4 Mg-Mg<br />

Magnesium<br />

melt (pure<br />

Mg or AJ62)<br />

is cast onto a<br />

solid<br />

magnesium<br />

substrate<br />

(AZ31) i.e<br />

(a)<br />

AZ31/AJ62<br />

and<br />

(b)<br />

AZ31/“Mg”<br />

compounds<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

dramatic weakening <strong>of</strong> the<br />

interface chemical bond was<br />

noticed after T6 heat treatment.<br />

• After T6 treatment, the shape <strong>of</strong><br />

the Si particles changes from<br />

angular to round as a result <strong>of</strong> a<br />

partial re-dissolution at 540 ◦C.<br />

Moreover, the size and number <strong>of</strong><br />

these particles decrease<br />

significantly in the vicinity <strong>of</strong> the<br />

insert/alloy interface due to a<br />

selective migration <strong>of</strong> Si towards<br />

the Ti insert by solid-state<br />

diffusion.<br />

• The fabrication <strong>of</strong> an aluminium–<br />

aluminium compound was<br />

successfully realized by high<br />

pressure die casting. A<br />

permanent activation <strong>of</strong> an Al<br />

insert’s surface was achieved by<br />

combining zincate treatment and<br />

zinc galvanizing.<br />

• The layer reacts during the<br />

casting process and a continuous<br />

metallic transition forms. Width<br />

as well as microstructure <strong>of</strong> the<br />

transition zone between matrix<br />

and insert varies with varying<br />

initial layer thickness.<br />

Compound<br />

Casting • A pre-treatment technique to<br />

enable the wettability <strong>of</strong> solid<br />

magnesium substrates by<br />

magnesium melts was realized.<br />

• By means <strong>of</strong> laboratory-scale<br />

compound casting experiments<br />

the reproducible production <strong>of</strong><br />

all-magnesium compounds was<br />

successfully established.<br />

• The newly developed joining<br />

method eliminates many<br />

disadvantages <strong>of</strong> conventional<br />

approaches, considering galvanic<br />

corrosion, welding depth or low<br />

process efficiency.<br />

• The coating, an easily deposited<br />

metallic Zn/MgZn2 layer with<br />

good adhesion, is applied via<br />

combining<br />

chemical,<br />

electrochemical and heat<br />

treatments. It leads to a complete<br />

change <strong>of</strong> the substrate’s surface<br />

reactivity towards Mg melts,<br />

providing excellent wettability.<br />

• An area-wide, continuously<br />

metallurgic, defect-free and welldefined<br />

transition between AZ31<br />

505<br />

• Optical microscopy.<br />

• Scanning electron<br />

microscopy (SEM<br />

Philips XL30).<br />

• The EDX system <strong>of</strong><br />

the SEM are used<br />

for analysing the<br />

element composition<br />

• Hardness tester<br />

using a Vickers<br />

indenter.<br />

• The tensile tests are<br />

performed with the<br />

tensile testing<br />

machine.<br />

• Elongation is<br />

measured with an<br />

extensometer<br />

• Energy-dispersive<br />

X-ray spectroscopy<br />

(EDX).<br />

• Scanning electron<br />

microscope (SEM,<br />

Camscan Series 4).<br />

• Microhardness.<br />

• Differential<br />

scanning<br />

calorimetry


5 Copper<br />

wires with<br />

diameters <strong>of</strong><br />

0.4, 1, and 2<br />

mm into<br />

polystyrene<br />

patterns,<br />

followed by<br />

pouring <strong>of</strong><br />

gray iron<br />

melt.<br />

6 Al-Al,<br />

Al-Mg<br />

(a)AlMg1/Al<br />

Si7<br />

(b)<br />

AlMg1/AlC<br />

u7<br />

Lost foam<br />

casting<br />

(LFC)<br />

process<br />

Compound<br />

Casting<br />

with<br />

Zincate<br />

process<br />

and Zn<br />

galvanizin<br />

g<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

substrate and AJ62 magnesium<br />

cast alloy (as well as 99.98%<br />

pure Mg) was achieved.<br />

• The coating material has only a<br />

minor influence on the<br />

compounds’ microstructure and<br />

mechanical properties<br />

• The melted copper wire dissolved<br />

in the gray iron matrix up to<br />

about 0.9 wt.% and the copper<br />

exceeding the limits <strong>of</strong> solubility<br />

was dispersed throughout the<br />

matrix. Some copper particles<br />

segregated at the bottom <strong>of</strong> the<br />

mold due to their high specific<br />

gravity.<br />

• The graphite morphology in<br />

reference sample (without copper<br />

insert) was type A flakes. In<br />

samples containing copper wire,<br />

graphite type changed to B, D or<br />

E flakes depending on the<br />

experimental variables.<br />

• When the copper insert was<br />

completely or extensively melted,<br />

type D or E flake graphite formed<br />

in the specimen due to the high<br />

undercooling during eutectic<br />

solidification.<br />

• When the copper insert was not<br />

melted or was partially melted,<br />

type B flake graphite appeared<br />

inside the Wire Affected Zone<br />

around the copper wire, due to<br />

rather high undercooling during<br />

eutectic solidification.<br />

• Different metallic or non-metallic<br />

materials in the form <strong>of</strong> wire,<br />

particles, and so on, can be<br />

inserted into the polystyrene<br />

patterns during pattern making<br />

stage <strong>of</strong> lost foam casting<br />

process. This procedure can be<br />

utilized for in-mold alloying,<br />

production <strong>of</strong> bi-metal and<br />

composite materials, study <strong>of</strong><br />

interface between the matrix and<br />

the insert, and investigation <strong>of</strong><br />

reaction phases formed at the<br />

interface.<br />

• Through adequate surface<br />

treatments and coatings, the<br />

AlMg1 substrate’s wettability<br />

was improved in a way that the<br />

couples <strong>of</strong> Al–Al and Al–Mg<br />

were successfully produced.<br />

• Interfaces showed very low (Al–<br />

Mg) to no (Al–Al) formation <strong>of</strong><br />

IMPs, and other defects, such as<br />

oxide inclusions, contraction<br />

• Optical microscopy.<br />

• Scanning electron<br />

microscopes (SEM)<br />

coupled with an<br />

energy dispersive<br />

spectroscopy (EDS)<br />

system<br />

• Electron microscopy<br />

• EDX investigations<br />

• Optical micrographs<br />

• Diffusion<br />

simulations using<br />

DICTRA s<strong>of</strong>tware<br />

506


7 Mg shell and<br />

Al core<br />

Disintegrat<br />

ed melt<br />

deposition<br />

(DMD)<br />

method<br />

and toppouring<br />

followed<br />

by hot<br />

coextrusio<br />

n<br />

8 Al-Al Compound<br />

Casting<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

cavities or cracks.<br />

• The combined coating <strong>of</strong> zincate<br />

treatment and electrolyticallydeposited<br />

zinc for Al–Al<br />

compounds <strong>of</strong>fers major<br />

advantages compared to other<br />

approaches to joining light<br />

metals.<br />

• The zincate treatment is the most<br />

important process step also for<br />

surface preparation <strong>of</strong> the<br />

substrate for Al–Mg compounds.<br />

This treatment is followed by<br />

electrolytic deposition <strong>of</strong> an Mn<br />

layer <strong>of</strong> several microns<br />

thickness to protect the substrate<br />

from liquefaction by the Mg<br />

melt, without sacrificing too<br />

much <strong>of</strong> wettability.<br />

• A thin layer <strong>of</strong> IMPs forms<br />

during couple production, which<br />

might affect mechanical integrity.<br />

Keeping this interface thin is a<br />

possible way to improve the<br />

compound’s properties.<br />

• Mg/Al macrocomposite<br />

containing Mg shell and Al core<br />

can be synthesized using a<br />

combination <strong>of</strong> DMD method<br />

and top-pouring, followed by hot<br />

coextrusion.<br />

• Mg based macrocomposite<br />

containing Mg shell and Al core<br />

is thermally more stable than<br />

monolithic Mg, due to fairly<br />

uniform Al volume fraction and<br />

mechanical interlocking at the<br />

interface.<br />

• Millimeter length scale Al<br />

reinforcement in Mg improves<br />

stiffness and significantly<br />

increases failure strain and work<br />

<strong>of</strong> fracture <strong>of</strong> Mg while 0.2%YS<br />

and UTS are compromised.<br />

• Couples <strong>of</strong> AlMg1 substrate and<br />

various Al alloys were<br />

successfully produced by means<br />

<strong>of</strong> a laboratory-scale compound<br />

casting process.<br />

• A combination <strong>of</strong> pre-treatments<br />

and Zn coatings drastically<br />

enhanced wettability <strong>of</strong> the<br />

substrate, generating defect-free<br />

interfaces.<br />

• The combined coating <strong>of</strong> zincate<br />

treatment and electrolytically<br />

deposited Zn <strong>of</strong>fers major<br />

advantages compared to other<br />

• Olympus<br />

metallographic<br />

microscope.<br />

• Hitachi S4300 fieldemission<br />

scanning<br />

electron microscope<br />

(FESEM).<br />

• Image analysis using<br />

Scion s<strong>of</strong>tware.<br />

• Interfacial integrity<br />

was observed using<br />

FESEM coupled<br />

with energy<br />

dispersive X-ray<br />

spectroscopy (EDS).<br />

• The coefficients <strong>of</strong><br />

thermal expansion<br />

(CTE) using an<br />

automated<br />

thermomechanical<br />

analyser.<br />

• Optical microscopy.<br />

• Glow discharge<br />

optical spectroscopy<br />

(GDOS)<br />

• One-dimensional<br />

diffusion<br />

simulations<br />

performed using<br />

DICTRA s<strong>of</strong>tware.<br />

Microhardness<br />

measurement.xc<br />

507


9 Titanium(ins<br />

ert)/aluminiu<br />

m–silicon<br />

Ti/Al–7Si<br />

Insert<br />

moulding<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

approaches to joining light metals<br />

• Bimetallic specimen test pieces<br />

<strong>of</strong> an AS-7 matrix locally<br />

reinforced with a titanium insert<br />

that have been produced using an<br />

experimental procedure allowing<br />

the control <strong>of</strong> both the interfacial<br />

reaction layer and the<br />

metallurgical health <strong>of</strong> the matrix<br />

(directional solidification).<br />

• The results obtain under push-out<br />

solicitation highlight the potential<br />

<strong>of</strong> the joining process for<br />

producing castings with high<br />

mechanical performances.<br />

• Push-out test and a<br />

variant that is the<br />

circular-bending test<br />

to investigate the<br />

mechanical strength.<br />

• Characterization <strong>of</strong><br />

the interfacial zone<br />

by Optical<br />

Microscopy (OM),<br />

Scanning Electron<br />

Microscopy (SEM)<br />

and Electron<br />

Micropobe Analyses<br />

(EPMA).<br />

• When a chemical bond is<br />

established at the Ti/AS-7<br />

interface an important rise <strong>of</strong><br />

mechanical properties for the<br />

bimetallic assembly is observed:<br />

the mean shear strength value is<br />

about 1<strong>20</strong> MPa whereas it is <strong>of</strong><br />

48 MPa for simply fretted<br />

specimens.<br />

• Finite Element<br />

Modeling (FEM)<br />

was performed to<br />

describe the stress<br />

distribution in a<br />

bimetallic slice<br />

during push-out test<br />

at different load<br />

level.<br />

• A three steps failure sequence<br />

proposed is both characterized by<br />

crack propagation from bottom to<br />

top and matrix yielding from top<br />

to bottom.<br />

10 S45C steel<br />

insert to<br />

copper<br />

Cast<br />

welding or<br />

compound<br />

casting<br />

• Heat treatment formed reacted<br />

layers in the interface. The layer<br />

near the S45C steel matrix was<br />

the cast welding layer; another<br />

close to the copper matrix was<br />

the irregular layer, and the other<br />

between these two layers was the<br />

middle layer.<br />

• The microstructure<br />

<strong>of</strong> the compound<br />

casting was<br />

observed by OM<br />

(optical microscope)<br />

and SEM (scanning<br />

electron<br />

microscope).<br />

• EPMA proved that most <strong>of</strong> the<br />

iron atoms diffused into the<br />

copper matrix and only a few<br />

copper atoms diffused into the<br />

iron matrix during diffusion<br />

occurred between two matrices.<br />

X-ray diffraction showed that the<br />

chemical compounds <strong>of</strong> the<br />

interface were CuFeO2 and C.<br />

• Furnace-cooling yielded the<br />

largest interface shear strength,<br />

and water quenching yielded the<br />

least.The fractured region was<br />

near the S45C steel matrix in the<br />

cast welding layer.<br />

• The interface phase<br />

was analyzed by X-<br />

ray diffraction and<br />

the composition was<br />

determined using<br />

EDS and EPMA<br />

(electron probe<br />

micro-analysis).<br />

• A push-out test was<br />

used to determine<br />

the interface shear<br />

strength<br />

508


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5. Gaps in Existing Literature<br />

A limited work is done on compound casting processes till now. In many cases, one material alone does not<br />

satisfy the requirements <strong>of</strong> lightweight constructions, and dissimilar joining between two metals must be needed.<br />

A variety <strong>of</strong> attempts have been dedicated to joining meals and alloys using different fusion welding and solidstate<br />

joining methods such as tungsten inert gas welding, laser welding, friction-stir welding, and vacuum<br />

diffusion bonding. The major problem in these joining processes is the formation <strong>of</strong> much more intermetallic<br />

compounds with a very high hardness and brittleness between two meats as an interlayer, which is deleterious to<br />

the mechanical properties. However, solid-state joining processes such as friction-stir welding and vacuum<br />

diffusion bonding can achieve relatively higher joining strengths compared to fusion methods, due to elimination<br />

<strong>of</strong> defects like shrinkage, porosities and inclusions. In addition, long process time and high corresponding<br />

operating cost <strong>of</strong> the vacuum diffusion bonding and specific requirements for the shape <strong>of</strong> the substrate in<br />

friction-stir welding may render these solid-state joining processes not easy for practical and industrial<br />

applications. Microstructure and EDX (energy dispersive x-ray) analysis are performed by some scientists<br />

/researchers but Differential Thermal Analysis are not performed. Optimization <strong>of</strong> process parameters <strong>of</strong><br />

compound casting w.r.t. mechanical properties such as tensile strength, hardness, elongation and impact strength<br />

etc. is not reported in literature till now.<br />

6. Conclusion<br />

It may be concluded from above studies that:<br />

• The compound casting process presents a solution for meeting the demands <strong>of</strong> a specific application,<br />

particularly in light weight constructions.<br />

• The compound casting is the process which meets a wide range <strong>of</strong> requirements within one component<br />

by combining different materials.<br />

• It is possible to make light metal compound cast parts using the combination <strong>of</strong> light metals like Al-Al,<br />

Mg-Mg and Al-Mg, Ti-Al, Cu-steel and Cu- grey cast iron etc.<br />

• It is necessary to remove the natural oxide layer for complete diffusion at interface between solid and<br />

melted metal.<br />

• The zincate process followed by Zinc electroplating is the best way to remove the effect <strong>of</strong> oxide layer<br />

at the interface.<br />

• Formation <strong>of</strong> the interface in the compound casting process is diffusion controlled and usually the<br />

interface consists <strong>of</strong> three different layers.<br />

• Heat treatment formed reacted layers in the steel-copper interface. Furnace-cooling yielded the largest<br />

interface shear strength, and water quenching yielded the least.<br />

• The heat treatment results in an improvement <strong>of</strong> the mechanical properties <strong>of</strong> the AS7G matrix itself<br />

when applied to Ti/AS7G assemblies. A significant increase <strong>of</strong> the load level characteristic for damage<br />

onset is observed.<br />

7. References<br />

[1] E. Hajjari, M. Divandari,S. H. Razavi,S. M. Emami,T. Homma,S. Kamado,(<strong>20</strong>11) “Dissimilar joining <strong>of</strong><br />

Al/Mg light metals by compound casting process.”, Journal <strong>of</strong> Material <strong>Science</strong> 46:6491–6499.<br />

[2] O. Dezellus, M. Zhe, F. Bosselet, D. Rouby, J.C. Viala,(<strong>20</strong>11) “Mechanical testing <strong>of</strong> titanium/aluminium–<br />

silicon interface: Effect <strong>of</strong> T6 heat treatment.”, Materials <strong>Science</strong> and Engineering A 528, 2795–2803<br />

[3] M. Rübner, M. Günzl, C. Körner, R.F. Singer,(<strong>20</strong>11) “Aluminium–aluminium compound fabrication by high<br />

pressure die casting.”, Materials <strong>Science</strong> and Engineering A 528, 7024– 7029<br />

[4] K.J.M. Papis, J.F. Löffler, P.J. Uggowitzer, (<strong>20</strong>10)“Interface formation between liquid and solid Mg alloys—<br />

An approach to continuously metallurgic joining <strong>of</strong> magnesium parts.”, Materials <strong>Science</strong> and Engineering A<br />

527, 2274–2279.<br />

[5] M. Mehdi Hejazi, M. Divandari, E. Taghaddos, (<strong>20</strong>09)“Effect <strong>of</strong> copper insert on the microstructure <strong>of</strong> gray<br />

iron produced via lost foam casting.”, Materials and Design 30, 1085–1092<br />

[6] Konrad J. M. Papis, Joerg F. Loeffler & Peter J. Uggowitzer,(<strong>20</strong>09) “Light metal compound casting.”,<strong>Science</strong><br />

in China Series E: Technological <strong>Science</strong>s, vol. 52, no. 1, 46-51<br />

[7] M. Paramsothy, N. Srikanth, M. Gupta,(<strong>20</strong>08) “Solidification processed Mg/Al bimetal macrocomposite:<br />

Microstructure and mechanical properties.” Journal <strong>of</strong> Alloys and Compounds 461, <strong>20</strong>0–<strong>20</strong>8<br />

[8] K.J.M. Papis a, B. Hallstedt b, J.F. Lo¨ffler a, P.J. Uggowitzer, (<strong>20</strong>08)“Interface formation in aluminium–<br />

aluminium compound casting.”, Acta Materialia 56, 3036–3043.<br />

509


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[9] Olivier Dezellus, Lucile Milani, Francoise Bosselet, Myriam Sacerdote-Peronnet, Dominique Rouby, Jean-<br />

Claude Viala,(<strong>20</strong>08) “Mechanical testing <strong>of</strong> titanium/aluminium–silicon interfaces by push-out.”, Journal <strong>of</strong><br />

Materials <strong>Science</strong> 43:1749–1756<br />

[10]Jin-Shin Ho, C. B. Lin, C. H. Liu,(<strong>20</strong>04) “Effect <strong>of</strong> continuous cooling heat treatment on interface<br />

characteristics <strong>of</strong> S45C/copper compound casting.”, Journal <strong>of</strong> Materials <strong>Science</strong> 39, 2473 – 2480<br />

[11]Choudhury, S.K. Hajara, Choudhury, A.K. Hajara, Roy Nirjhar, (<strong>20</strong>11)“Elements <strong>of</strong> Workshop<br />

<strong>Technology</strong>”, Media Promoters & Publishers Private Limited, Mumbai.<br />

[12]Timings, R.L., (<strong>20</strong>10) “Workshop Practices and Materials”, Longman Singapore Publishers (Pte) Limited,<br />

Singapore<br />

[13]Champman, W.A.J., (<strong>20</strong>09) “Workshop <strong>Technology</strong>”, CBS Publishers and Distributors, New Delhi.<br />

[14]Little. Richard L., (<strong>20</strong>09) “Welding and Welding <strong>Technology</strong>”, Tata Mc-graw Hill Publishing Company<br />

Limited, New Delhi.<br />

[15]Heine, Richard W., Loper, Carl N., Rosenthal, Philip C., (<strong>20</strong>07) “Principles <strong>of</strong> Metal Casting”, Tata Mcgraw<br />

Hill Publishing Company Limited, New Delhi.<br />

[16] Abramov, G., (<strong>20</strong>06) “Foundry Practice”, Mir Publishers, Moscow.<br />

[17]A. Bouayad, Ch. Gerometta, A. Belkebir, A. Ambari, (<strong>20</strong>03) “Kinetic Interactions Between Solid Iron and<br />

Molten Aluminium.”, Materials <strong>Science</strong> and Engineering, A363, 53–61<br />

[18]J.C. Viala, M. Peronnet, F. Barbeau, F. Bosselet, J. Bouix, (<strong>20</strong>02) “Interface Chemistry in Aluminium Alloy<br />

Castings Reinforced with Iron Base Inserts.”, Composites, Part A 33, 1417–14<strong>20</strong>.<br />

[<strong>19</strong>]G.X. Wang, E.F. Matthys, (<strong>20</strong>02) “Experimental Determination <strong>of</strong> The Interfacial Heat Transfer During<br />

Cooling and Solidification <strong>of</strong> Molten Metal Droplets Impacting on a Metallic Substrate: Effect <strong>of</strong> Roughness<br />

and Superheat”, International Journal <strong>of</strong> Heat and Mass Transfer, Volume 45, 4967-498.<br />

[<strong>20</strong>]J.Y. Junga, J.K Parkb, C.H. Chunc, (<strong>19</strong>99) “Influence <strong>of</strong> Al Content on Cast Microstructures <strong>of</strong> Ti±Al<br />

Intermetallic Compounds.”, Intermetallics, 7, 1033-1041.<br />

[21]Werner Fragner, Wieland Kniffka, “Compound Casting – Less Weight, Greater Cost Effectiveness”,<br />

(Austria).<br />

510


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

EFFECT OF WEDM PARAMETERS ON MACHINABILITY OF<br />

NIMONIC-90<br />

Vinod Kumar 1 , Kamal Jangra 2 , Vikas Kumar 3<br />

1 Research Scholar, Deptt. <strong>of</strong> Mechanical Engg., <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad<br />

2 Assistant Pr<strong>of</strong>essor, Deptt. <strong>of</strong> Mechanical Engg., <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad<br />

3 Associate Pr<strong>of</strong>essor, Deptt. <strong>of</strong> Mechanical Engg., <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad<br />

1* E-mail: Vinod_kumar9400@yahoo.com<br />

Abstract<br />

Nimonic-90 is a nickel based super alloy which is specifically used in aerospace industry for jet engines, valves,<br />

blades etc owing to its high strength at high temperature, fatigue and corrosion resistance. Present work focuses<br />

on machinability <strong>of</strong> Nimonic-90 with wire electrical discharge machining (WEDM) process. Cutting speed is<br />

considered as machinability attribute in present work. Influence <strong>of</strong> WEDM parameters namely discharge current<br />

(Ip), pulse on time (Ton), pulse <strong>of</strong>f time (T<strong>of</strong>f), servo voltage (SV) and wire feed rate (WF) has been investigated<br />

on cutting speed <strong>of</strong> Nimonic-90.<br />

Keywords: WEDM, Nimonic-90, Machinability, cutting speed<br />

1. Introduction:<br />

Nickel based super alloy are widely used in high temperature and high corrosion environment application such as<br />

aerospace industry, various thermal processing, marine engineering, crude petroleum stills and chlorinated<br />

solvent. In last few years different grades <strong>of</strong> nickel super alloy have been developed such as Inconel 601, Inconel<br />

718, Nimonic-80, Nimonic-90, and Monel etc. Machining characteristics <strong>of</strong> nickel alloys can significantly affect<br />

the working life <strong>of</strong> its components. Several attempts have been made to evaluate the machining characteristics <strong>of</strong><br />

nickel based super alloys with conventional machining methods. Kortabarria et al., (<strong>20</strong>11) reported on residuals<br />

stress pr<strong>of</strong>iles on Inconel 718 developed by dry face turning. Surface integrity condition has been directly<br />

affected by the machine parts fatigue life. Different dry facing turning conditions were used for developing<br />

different residual stress pr<strong>of</strong>ile. Then they were compared by using X- ray diffraction method, hole drilling<br />

method and Finite element method. Aspinwall et al., (<strong>20</strong>07) presented the experimental data for Nickel based<br />

super alloy when machining with pr<strong>of</strong>iled super abrasive grinding wheels. The tool wear <strong>of</strong> grinding wheel CBN<br />

is lower as compared to diamond (D46) grinding wheel at the high rotation speed with lower value <strong>of</strong> surface<br />

roughness. Wei, (<strong>20</strong>02) has been reported on feasibility <strong>of</strong> using milling or grinding as alternatives for the<br />

current EDM process to machine shaped hole in Inconel 718 super heat resistant alloy. The result shows that<br />

milling process <strong>of</strong> Inconel 718 can produce shaped hold with an acceptable surface roughness and geometrically<br />

accuracy efficient after optimizing the cutting condition.<br />

Soo. et al., (<strong>20</strong>11) evaluated the machinability and surface characteristics <strong>of</strong> RR1000 Nickel based super alloy in<br />

drilling and milling process. Experimental data for drilling showed that flank wear < 100 μm, when operating at<br />

45 m/min and measured thrust forces were 1600-1800 N. which is generally used the high pressure compressor<br />

and turbine parts. The roughness <strong>of</strong> end mill specimens achieved up to 0.8 µm when a new tool is to be used.<br />

The significant burr increased micro hardness and white layer formation when we are using worn tools. Kwong<br />

et al., (<strong>20</strong>09) concluded the influence <strong>of</strong> major flank wear <strong>of</strong> drilling tools on the work piece surface integrity and<br />

residual stress distribution for RR1000 a Nickel based super alloy. Hughes et al., (<strong>20</strong>04) had reported on the<br />

effect <strong>of</strong> cutting tools and edge geometry on tool life and surface integrity in turning <strong>of</strong> Nickel based super alloy.<br />

Surface integrity investigation on nickel based super alloy RR1000 have been published by Herbert et al., (<strong>20</strong>09)<br />

for hole making and also present a comprehensive analysis and discussions <strong>of</strong> the influence <strong>of</strong> the drills minor<br />

cutting edge to work piece surface integrity and residual stress distribution for RR1000.Imrarn et al., (<strong>20</strong>11)<br />

conducted micro drilling in Inconel 718 alloy under wet condition and analysis three different zones namely,<br />

nanostructurered surface layer, a deformed subsurface layer and an unaffected parent metal during micro drilling.<br />

The microstructure crystal misorientation, nanohardness, plastic deformation was to be studied.<br />

Wire electrical discharge machining (WEDM) process is best non-conventional machining process to machine<br />

complex geometries in high strength, high hardness materials with high precision. Several investigations have<br />

also been carried out on EDM and WEDM. Kang et al., (<strong>20</strong>03) investigated the EDM characteristics <strong>of</strong> Nickel<br />

based heat resistance alloy Hastelloy–X. Pulse on time was the main factors that affect the surface integrity <strong>of</strong><br />

the work material. Rajesha et al., (<strong>20</strong>10) reported the machining <strong>of</strong> EDM <strong>of</strong> Inconel 718 with hollow Tools. The<br />

most influential factor on MRR was discharge current and duty factor. High value <strong>of</strong> discharge current was<br />

suggested for obtaining high MRR. Krishan, (<strong>20</strong>04) reported on the performance <strong>of</strong> two graphite electrode Poco<br />

511


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

AF 5 and Poco EDM I in EDM <strong>of</strong> seal slots in a jet engine turbine vane. MRR in case EDM - I was higher than<br />

Poco AF 5. Ghewade and Nipanikar, (<strong>20</strong>11) has been reported the machining <strong>of</strong> Inconel 718 using WEDM with<br />

a copper electrode. The Taguchi method is used to analysis the significance effect <strong>of</strong> each parameter i.e. peak<br />

current , gap voltage , duty cycle and pulse on time an machining characteristics such Material Removal Rate<br />

,Electrode wear rate and Radial over cut and half taper angle .Peak current significantly affect the Material<br />

Removal Rate and pulse on time significantly affect the Electrode wear rate. Liu et al., (<strong>20</strong>05) present a process<br />

using micro electro discharge machining combined with high frequency dither grinding to improve the surface<br />

roughness <strong>of</strong> micro hole machining <strong>of</strong> high Nickel alloy. This technique eliminate the micro cracks along with<br />

reduce surface roughness from 2.12 to 0.85 µm Rmax. Liu et al., (<strong>20</strong>06) investigated the significant machine<br />

parameters which are affecting the characteristics <strong>of</strong> micro holes in high Nickel alloy in terms <strong>of</strong> micro hole<br />

expansion, electrode depletion and material removal rate. A proper discharge current is very important to achieve<br />

optimum results.<br />

Hewidy et al.,(<strong>20</strong>05) correlated the various WEDM parameters such as peak current, duty factor, wire tension,<br />

and water pressure with the performance outputs namely metal removal rate (MRR), wear ratio and surface<br />

roughness in WEDM <strong>of</strong> Inconel 601. Aspinwall et al., (<strong>20</strong>08) presents roughing and finishing strategies <strong>of</strong> Ti-<br />

6Al-4V and Inconel 718 after WEDM. The average recast layer thickness less than 11 µm is to be found and<br />

several trim passes showing no apparent recast. There is no significant change in work piece microhardness.<br />

Kumar et al. investigated the optimum WEDM process parameters’ <strong>of</strong> Incoloy 800 super alloy with multiple<br />

machining performance characteristics such as material removal rate , surface roughness and kerf by using Gray<br />

– Taguchi method.<br />

Nimonic 90 is a newly developed Nickel based heat resistance super alloy with high content <strong>of</strong> Cobalt and<br />

Chromium. Processing <strong>of</strong> such type <strong>of</strong> heat resistance alloys has been an active area <strong>of</strong> research due to increasing<br />

demand <strong>of</strong> this class <strong>of</strong> material and typical problems associated with the processing. Machining <strong>of</strong> heat<br />

resistance alloys is difficult due to a combination <strong>of</strong> low thermal conductivity and high temperature strength. It is<br />

very difficult to machine Nimonic 90 by conventional machining processes. Modern machine techniques such<br />

WEDM are increasingly being used for machine such hard material. Hence, this study focused on machining <strong>of</strong><br />

Nimonic 90 using WEDM in order to fulfill the production and quality requirement. In present work, influence<br />

<strong>of</strong> WEDM parameters namely discharge current, pulse-on time, pulse-<strong>of</strong>f time, servo voltage and wire feed rate<br />

have been evaluated on machinability <strong>of</strong> Nimonic-90. Cutting speed is considered as machinability attribute.<br />

2. Experimental Procedure<br />

The machining experiments were performed on 5 axis sprint cut (ELPUSE-40) wire EDM manufactured by<br />

Electronic M/C Tool LTD India.<br />

In present machine tool ,parameters can be varied under following range; discharge current (Ip), 10-230 amp;<br />

pulse on time (Ton) ,101-131 μs; pulse <strong>of</strong>f time (T<strong>of</strong>f) ,10-63 μs ; servo voltage (SV), 0-90 V; dielectric flow<br />

rate (DFR) , 0-12 liter per minute ; wire feed rate(WF) ,1-15 m/min; wire tension (WT) ,1-15 N. Copper coated<br />

brass wire <strong>of</strong> diameter 0.25mm was used as an electrode because <strong>of</strong> its good capability to sustain high discharge<br />

energy. Distilled water was used as a dielectric fluid with conductivity <strong>20</strong> S.<br />

Nimonic-90, a nickel based super-alloy having 60% Ni, <strong>19</strong>.3% Cr, 15% Co, 3.1% Ti, 1.4% Al, was taken as a<br />

work material in the form <strong>of</strong> a rectangular sheet <strong>of</strong> 22.5 mm thickness. The density and melting point <strong>of</strong><br />

Nimonic-90 was measured as 8.18 g/cm 3 and 1370 0 C respectively.<br />

Cutting speed was measured as machinability attribute for Nimonic-90, which was observed directly from<br />

monitor screen <strong>of</strong> the machine tool. Single machining variable is varied at a time to study the influence <strong>of</strong><br />

discharge current (Ip), pulse on time (Ton), pulse <strong>of</strong>f time (T<strong>of</strong>f), servo voltage (SV) and wire feed on cutting<br />

speed (CS).<br />

3. Effect <strong>of</strong> WEDM parameters on cutting speed<br />

3.1. Effect <strong>of</strong> discharge current<br />

The effect <strong>of</strong> discharge current on cutting speed <strong>of</strong> Nimonic 90 with wire EDM is shown in Figure 1 and 2 under<br />

the two different setting <strong>of</strong> pulse on time (108-1<strong>20</strong>μs ) along with two different setting <strong>of</strong> pulse <strong>of</strong>f time (35μs<br />

and 45μs). The other parameters were fixed such as Servo voltage <strong>20</strong>V, Wire tension 10N, Wire feed 5<br />

meters/min., servo feed <strong>20</strong>80 and dielectric flow rate 10 liter per min (upper and lower nozzles).<br />

It is clear from the fig. 1 at low pulse duration (Ton =108µs), the cutting speed is increase slowly with increase<br />

<strong>of</strong> peak current. But at high pulse duration (Ton =1<strong>20</strong>μs) there is sharply increase <strong>of</strong> cutting speed with increase<br />

<strong>of</strong> peak current from 40A to 80 A. Increase in the peak current leads to increase in the rate <strong>of</strong> the heat energy and<br />

hence in the rate <strong>of</strong> melting and evaporation.<br />

512


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure No. 1<br />

Figure No. 2<br />

Increase in peak current higher over a certain limit, leads to arcing, which decrease discharge number and<br />

machining efficiency .Subsequently wire to be break down because <strong>of</strong> short pulse <strong>of</strong>f time .The removal time <strong>of</strong><br />

debris particles from the gap become insufficient. But from figure no. 2, with increase <strong>of</strong> pulse <strong>of</strong>f time along<br />

with pulse on time , maximum cutting speed occurs which is due to complete flushing <strong>of</strong> debris particles and<br />

available a complete deionized fluid for the next discharge . But further increase <strong>of</strong> discharge current will leads<br />

to increase <strong>of</strong> cutting speed. Maximum cutting speed <strong>of</strong> Nimonic 90 with present machine tool occurs at<br />

discharge current <strong>20</strong>0 Amp with pulse <strong>of</strong>f time (T<strong>of</strong>f) 45μs.<br />

3.2. Effect <strong>of</strong> pulse-on time<br />

The effect <strong>of</strong> pulse on time (Pulse duration) on cutting speed is shown in figure no. 3 for two setting <strong>of</strong> T<strong>of</strong>f =35<br />

and T<strong>of</strong>f =40 .The other parameters were kept constant under the condition <strong>of</strong> peak current 1<strong>20</strong> μs, Servo voltage<br />

<strong>20</strong> V, Wire feed 5 meters /min, Wire Tension 10 N, Dielectric flow rate 10 liters per min. and servo feed <strong>20</strong>80.<br />

The cutting speed increases continuously with increase <strong>of</strong> Pulse on Time. The machining becomes unstable at<br />

high pulse duration. At high discharge energy, the amount <strong>of</strong> debris in the gap becomes too great which form an<br />

electrically conductive path between the electrode and workpiece, resulting into development <strong>of</strong> unwanted arc<br />

between them. If we increase the pulse <strong>of</strong>f time with increase <strong>of</strong> pulse duration time, we can provide more time<br />

to flush away the debris. Maximum cutting speed <strong>of</strong> Nimonic 90 with present machine tool occurs at pulse on<br />

time (Ton) 118 μs with pulse <strong>of</strong>f time (T<strong>of</strong>f) 40 μs.<br />

3.3. Effect <strong>of</strong> pulse <strong>of</strong>f time<br />

Figure no. 4 shows the effect <strong>of</strong> pulse <strong>of</strong>f duration for two machining setting Ton 108µs and 1<strong>20</strong>μs with fixed<br />

variables discharge current 1<strong>20</strong> A ,servo voltage <strong>20</strong> V, dielectric flow rate 10 liter per min and servo feed <strong>20</strong>80<br />

and wire feed 5meters per min, Wire Tension 10. The cutting speed increases with increases in pulse <strong>of</strong>f time 25<br />

to 45μs and after that it decrease sharply decrease with increase in pulse <strong>of</strong>f time.<br />

513


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure No. 3<br />

Figure No. 4<br />

Maximum cutting is to be found at T<strong>of</strong>f 45µs due to complete flushing <strong>of</strong> debris from the machining zones. After<br />

that further increase <strong>of</strong> pulse <strong>of</strong>f time dielectric fluid produce the cooling effect on wire electrode and work<br />

material and hence decrease the cutting speed. At high pulse <strong>of</strong> duration (Ton 1<strong>20</strong>µs) the cutting speed increase<br />

very fast as compared to low pulse <strong>of</strong> duration (Ton 108µs)<br />

3.4. Effect <strong>of</strong> servo voltage<br />

The effect <strong>of</strong> servo voltage on cutting speed is shown in figure no. 5 with two different pulse durations (Ton 108<br />

and 1<strong>20</strong>) along with two different values <strong>of</strong> wire feed 5 meters per min and 6 meters per min keeping other<br />

variables fixed such as pulse <strong>of</strong>f time (T<strong>of</strong>f) 35µs, servo voltage <strong>20</strong>V, discharge current 1<strong>20</strong> A and servo feed<br />

<strong>20</strong>80 and Wire Tension 10 N.<br />

Figure No. 5<br />

The cutting speed decrease with increase in servo voltage from <strong>20</strong>V to 60V for wire feed 5 m/ min and from 30V<br />

to 50 V for wire feed 6 m/min. Large servo voltage means large ionization <strong>of</strong> the dielectric fluid between<br />

514


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

workpiece and wire electrode which results in high discharge energy per spark. But further increase <strong>of</strong> servo<br />

voltage will not favor in the cutting speed as the large amount <strong>of</strong> debris are unable to clear <strong>of</strong>f the gap for a given<br />

pulse –<strong>of</strong>f time.<br />

3.5. Effect <strong>of</strong> wire feed rate<br />

The effect <strong>of</strong> wire feed rate on cutting speed is represented in figure no. 6 keeping others fixed parameters such<br />

as pulse on time 108µs ,pulse <strong>of</strong>f time 35µs ,servo voltage <strong>20</strong> V, discharge current 1<strong>20</strong>A and servo feed <strong>20</strong>80,<br />

Wire Tension 10 N.<br />

Figure No. 6<br />

It is clear from figure no. 6 cutting speed increases with increases <strong>of</strong> wire feed from 3 meters per min to 5meters<br />

per min. But further increase <strong>of</strong> wire feed rate has no influence on cutting speed. It implies that with these<br />

discharge parameters, eroded debris are easily clear <strong>of</strong>f from the spark gap at a wire feed rate <strong>of</strong> 5m/min.<br />

4. Conclusions:<br />

In this work, machinability <strong>of</strong> Nimonic-90 has been evaluated on wire electrical discharge machining (WEDM)<br />

process. Cutting speed has been considered as machinability attribute in present work. Influence <strong>of</strong> WEDM<br />

parameters namely discharge current (Ip), pulse on time (Ton), pulse <strong>of</strong>f time (T<strong>of</strong>f), servo voltage (SV) and<br />

wire feed rate (WF) were investigated on cutting speed <strong>of</strong> Nimonic-90. Based on the experimentation, WEDM<br />

parameters namely discharge current, pulse-on time and pulse-<strong>of</strong>f time produces highly noticeable effect on<br />

cutting speed.<br />

References:<br />

Aspinwall D.K., Soo1 S.L., Curtis D.T., Mantle A.L. (<strong>20</strong>07), “Pr<strong>of</strong>iled Superabrasive Grinding Wheels for the<br />

Machining <strong>of</strong> a Nickel Based Superalloy”. Annals <strong>of</strong> the CIRP Vol. 56, pp 335-338.<br />

Aspinwall D.K., Soo S.L., Berrisford A.E. , Walder G. (<strong>20</strong>08) , “ Workpiece surface roughness and integrity<br />

after WEDM <strong>of</strong> Ti–6Al–4V and Inconel 718 using minimum damage generator technology”. Manufacturing<br />

<strong>Technology</strong> 57, pp 187–<strong>19</strong>0.<br />

Ghewade D.V., Nipanikar S.R. (<strong>20</strong>11), “Experimental study <strong>of</strong> Electro Dischrge machining for Inconel<br />

material”. Journal <strong>of</strong> Engineering Research and Studies ,pp 107-112.<br />

Herbert C.R.J., Kwong J., Kong M.C., Axinte D.A., Hardy M.C., Wither P.J. (<strong>20</strong>12), “ An evaluation <strong>of</strong> the<br />

evolution <strong>of</strong> workpiece surface integrity in hole making operations for a nickel-based superalloy” Journal <strong>of</strong><br />

Materials Processing <strong>Technology</strong> 212 ,pp 1723– 1730<br />

Hewidy M.S., El-Taweel T.A. , El-Safty M.F. (<strong>20</strong>05), “Modelling the machining parameters <strong>of</strong> wire electrical<br />

discharge machining <strong>of</strong> Inconel 601 using RSM”. Journal <strong>of</strong> Materials Processing <strong>Technology</strong> 169, pp 328-<br />

336.<br />

Hung-Sung Liu, Biing-Hwa Yan, Fuang-Yuan Huang, Kuan-Her Qiu (<strong>20</strong>05), “A study on the characterization <strong>of</strong><br />

high nickel alloy micro-holes using micro-EDM and their applications”. Journal <strong>of</strong> Materials Processing<br />

<strong>Technology</strong> 169, pp 418–426.<br />

Hung Sung Liu, Biing Hwa Yan, Chien Liang Chen, Fuang Yuan Huang (<strong>20</strong>06), “Application <strong>of</strong> micro-EDM<br />

combined with high-frequency dither grinding to micro-hole machining”. International Journal <strong>of</strong> Machine<br />

Tools & Manufacture 46, pp 80–87.<br />

Imran Muhammad & Mativenga Paul T. & Gholinia Ali (<strong>20</strong>11) , “Evaluation <strong>of</strong> surface integrity in micro<br />

drilling processfor nickel-based superalloy Int J Adv Manuf Technol 55, pp 465–476.<br />

515


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Kortabarria A., Madariaga A., Fernandez E., Esnaola J.A., Arrazola P.J, (<strong>20</strong>11) “ A comparative study <strong>of</strong><br />

residual stress pr<strong>of</strong>iles on Inconel 718 induced by dry face turning”. Procedia Engineering <strong>19</strong>, pp 228 – 234.<br />

Kristian L. Aas (<strong>20</strong>04), “Performance <strong>of</strong> two graphite electrode qualities in EDM <strong>of</strong> seal slots in a jet engine<br />

turbine vane”. Journal <strong>of</strong> Materials Processing <strong>Technology</strong> 149, pp 152–156.<br />

Kumar Muthu, Babu Suresh, Venkatasamy and Raajenthiren (<strong>20</strong>10), “Optimization <strong>of</strong> the WEDM Parameters on<br />

Machining Incoloy800 Super alloy with Multiple Quality Characteristics”. International Journal <strong>of</strong><br />

Engineering <strong>Science</strong> and <strong>Technology</strong> Vol. 2(6), pp1538-1547.<br />

Kwong J. ,.Axinte D.A , Withers P.J. (<strong>20</strong>09), “The sensitivity <strong>of</strong> Ni-based superalloy to hole making operations:<br />

Influence <strong>of</strong> process parameters on subsurface damage and residual stress”. Journal <strong>of</strong> materials processing<br />

technology <strong>20</strong>9, pp 3968–3977.<br />

Rajesha S., Sharma A.K., and Kumar Pradeep (<strong>20</strong>11), “On Electro Discharge Machining <strong>of</strong> Inconel 718 with<br />

Hollow Tool”. ASM International.<br />

Sin Ho Kang, Dae Eun Kim. (<strong>20</strong>03), “Investigation <strong>of</strong> EDM Characteristics <strong>of</strong> Nickel-based Heat Resistant”.<br />

KSME International Journal, Vol.17, pp1475-1484.<br />

Soo S.L., Hood R. , Aspinwall D.K. , Voice W.E., Sage C. (<strong>20</strong>11), “Machinability and surface integrity <strong>of</strong><br />

RR1000 nickel based superalloy”. Manufacturing <strong>Technology</strong> 60, pp 89–92.<br />

Wei X. (<strong>20</strong>02), “ Experimental study on the machining <strong>of</strong> a shaped hole Ni – based super – heat –resistant alloy”.<br />

Journal <strong>of</strong> materials Processing <strong>Technology</strong> 129, pp 143-147.<br />

516


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

EVALUATION OF ELECTRO DISCHARGE SAWING, A MODIFIED<br />

ELECTRO DISCHARGE MACHINING PROCESS<br />

Kalley Harinarayana 1 , T.Raghavender Reddy 2 , Dr.N.Nagabhushana Ramesh 3, Dr.B.Balu Naik 4<br />

1 Research Scholar, Jawaharlal Nehru Technological <strong>University</strong>, Hyderabad, A.P., India<br />

2 Asst. Secretary, State Board <strong>of</strong> Technical Education and Training, Andhra Pradesh, India.<br />

3 Pr<strong>of</strong>essor, CMR Engineering College, Hyderabad, A.P., India<br />

Abstract<br />

Electro Discharge Sawing is a hybrid process combining the features <strong>of</strong> EDM and ECM. Its major characteristic<br />

is extremely fast erosion rate compared to either <strong>of</strong> the above processes. This paper brings out its relative<br />

features associated with erosion mechanism, erosion rate and surface finish and the controlling process<br />

parameters.<br />

1. Introduction<br />

Electro discharge machining (EDM) finds extensive application for machining exotic materials and complex<br />

shapes. But its slow machining rates are a major limitation for its application for sawing <strong>of</strong> large billets or barstocks<br />

<strong>of</strong> high strength materials. Since sawing does not require good surface finish, the modified EDM process<br />

combines the features <strong>of</strong> Electrochemical machining with EDM to obtain very high machining rates. The EDM<br />

process electrode is solid, shaped to the desired contour to be machined. The erosion occurs by high frequency<br />

sparks through a dielectric medium which is kerosene in EDM. Electrochemical machining (ECM) on the other<br />

hand employs an electrolyte for anodic erosion to produce the desired geometry.<br />

In electro discharge sawing(EDS) the features <strong>of</strong> EDM and ECM are combined whereby the dielectric in EDM is<br />

replaced by an electrolyte. This hybridization leads to some interesting phenomena which are actually sought to<br />

be avoided in EDM and ECM .In ECM the occurrence <strong>of</strong> sparking is sought to be avoided and EDM arcing is<br />

considered undesirable. But in the EDS process not only the sparking is developed but further conditioned to<br />

result in arcing.<br />

2. EDM Arcing<br />

A Spark is a sudden transient and noisy discharge between two electrodes, an arc being a stable thermionic<br />

phenomenon. Hence discharges <strong>of</strong> duration <strong>of</strong> approximately 2µs to 1ms could be described as sparks, while for<br />

duration about 0.1s they can be considered to be arcs. Since in the EDS Process the duration, energy and time <strong>of</strong><br />

ignition <strong>of</strong> the “sparks” are under complete control, it would be valid to regard them as arcs <strong>of</strong> short duration and<br />

vice versa i.e. long duration sparks as arc.<br />

Incidentally, continuous sparks at the same spot in EDM due to ineffective deionisation is also termed as<br />

“Arcing” in EDM terminology which is considered harmful to the stable machining and finish <strong>of</strong> the machined<br />

surface. The set up employed in EDM, and EDS are schematic shown in fig 1 (a) and (b) respectively.<br />

517


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig.1.Schematic diagrams <strong>of</strong> the electrical discharge machining processes<br />

Theoretical Description and Evaluation<br />

Their characteristic features are discussed here under:<br />

1. Physical Setup<br />

The processes employ pulsed power sources. The pulse time has two parts i.e., pulse on time(T on ) and pulse <strong>of</strong>f<br />

time (T <strong>of</strong>f ). The <strong>of</strong>f time facilitates deionisation <strong>of</strong> spark channel in the two EDM process and in EDS it permits<br />

the reactions <strong>of</strong> ECM, which are evolution <strong>of</strong> H 2 at cathode and O 2 at anode. In EDM the dielectric in a tank<br />

surrounds the tool work set up to avoid fire hazard by preventing oxygen from spark zone.<br />

2. Electrode<br />

It is a mild steel belt with typical dimensions <strong>of</strong> 0.9 X 35 X 7450 mm and guided through ceramic assemblies.<br />

The belt is formed by resistance butt welding and ground to uniform belt thickness. The belt runs similar to band<br />

saw at a speed <strong>of</strong> 16m/sec.<br />

3. Pulse parameters<br />

The voltage (30 to 60) and current (15 to 300A) are not significantly different than in EDM. However it is the<br />

pulse duration (as high as <strong>20</strong>,000 µs compared to 100 µs in EDM) with negligible pulse <strong>of</strong>f time (compared to<br />

about 40 to 50 percent in EDM).<br />

4. Working fluid<br />

It is an electrolyte (Sodium silicate plus water with a specific gravity <strong>of</strong> 1.25). Similar to EDM it quenches and<br />

removes the eroded debris. The additional functions <strong>of</strong> the electrolyte are a) evolve hydrogen gas to promote<br />

ionization and ionic discharge (b) forms electrolytic cell (c) form passivation film on anode(work piece) to<br />

promote insulation and prevent short circuits. The continuous ionization and insulating film formation facilitates<br />

high pulse on time and low <strong>of</strong>f times thus increasing effective pulse energies.<br />

5.Process parameters<br />

In the following description typical parameters associated and their values are given alongside in brackets to<br />

highlight their difference. The emphasis on the word 'typical' may be noted since in practice the actuals can be<br />

different. The sparks are discrete and triggered through electrical pulses <strong>of</strong> small duration (few tens to a few<br />

hundreds <strong>of</strong> µs), low voltage (80 to 100v) and currents (5 to 50A) through a liquid dielectric (kerosene in EDM).<br />

The electrode in EDM is pre_shaped to the desired geometry <strong>of</strong> final machined component. The EDM (which is<br />

similar to drilling) therefore employs all the listed parameters in the lower range. Modern pulse generators<br />

supply square pulses with high frequency (in a range <strong>of</strong> KHz). Each pulse results in a discrete spark at random<br />

locations along the whole tool work interface simultaneously eroding microscopic material at the spot <strong>of</strong><br />

impingement. Owing to low voltage applied, the spark gaps are very small to facilitate dielectric breakdown and<br />

the onset <strong>of</strong> spark. This spark gap (50 to 100 µm) is servo controlled for efficient sparking without excessive<br />

open circuits or short circuits. By judicious selection <strong>of</strong> polarity (electrode positive in EDM very low compared<br />

to metal erosion.<br />

3. The EDS Process<br />

A modified EDM process is to facilitate high material removal rate. These modifications are listed below.<br />

The use <strong>of</strong> electrolyte in the EDM setup with short <strong>of</strong>f times lead to poor deionization and consequent arcing.<br />

This term refers to continuous sparking at the same location rather than at randomly varying locations associated<br />

518


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

with EDM. The arcs produce high localized material removal and constantly moving belt electrode ensures the<br />

shifting <strong>of</strong> arcs. The vertically downward feed rate given to electrode occasionally results in short circuiting on<br />

touching the work surface. The servo control reverses to electrode feed motion to again create the inter electrode<br />

gap.<br />

The polarity in EDS is always electrode negative because in arc discharges the dominant component <strong>of</strong> pulse<br />

energy is liberated at anode which therefore must be the workpiece.<br />

4. Experimental setup<br />

The machining rates were evaluated in the EDM setup and EDS set up. Owing to the absence <strong>of</strong> exact values <strong>of</strong><br />

process parameters on the knobs <strong>of</strong> the control panels on these machines, it was not possible to select similar<br />

magnitudes <strong>of</strong> the process variables for direct and quantitative comparison. However to demonstrate the highly<br />

superior erosion rates in EDS it was sought through selecting lowest values on EDS and highest possible values<br />

in EDM from the respective technology guidelines provided by the manufactures and listed below.<br />

EDM (Char miles):80v, pulse time <strong>20</strong>0µs, <strong>of</strong>f time 50µm,<br />

EDS (Custom built by Electronica): <strong>20</strong>v, 15Amps, Lowest pulse times.<br />

The surface finish was evaluated by Taylor - Hobson Talysurf which provided both the roughness pr<strong>of</strong>ile and<br />

indices.<br />

Work Materials: Aluminium (Low melting Point )<br />

HSS (High melting point)<br />

Titanium 31 (Very High Melting Point)<br />

(a) Aluminium<br />

(a) Aluminium<br />

(b) HSS (b) HSS<br />

(c ) Titanium (c ) Titanium<br />

Fig 1. EDS surface roughness pr<strong>of</strong>iles<br />

Fig 2. EDM surface roughness pr<strong>of</strong>iles<br />

5<strong>19</strong>


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5. Results:<br />

Erosion rates and roughness Ra are listed in table 1 and table 2 and roughness pr<strong>of</strong>iles <strong>of</strong> Ti, HSS and Al are<br />

shown in fig 1(a), 1(b) and 1(c) for EDS process and 2(a), 2(b) & 2(c) for EDM process respectively.<br />

The findings are as expected but illustrate the considerately high erosion rates and surface roughness in EDS<br />

compared to EDM. Considerable fluctuations in the range <strong>of</strong> R a was observed along EDS surfaces. The results<br />

are attributed to non-uniform erosion owing to spark and arc discharges as well as short circuit current surge. The<br />

preceding section explained the reasons <strong>of</strong> the theory. The eroded surfaces in EDS were very rough with poor<br />

appearance, compare to arc cutting plates which are extremely rough with extensive burrs. The surface finish and<br />

geometric accuracy <strong>of</strong> EDS surfaces have considerable superiority over surfaces from electrical arc cutting but<br />

inferior to EDM surfaces. Sawing operation requires only faster cuts but not any type <strong>of</strong> quality <strong>of</strong> machined<br />

surfaces. EDS is a highly suitable process for sawing large size bars, ingots etc <strong>of</strong> high strength materials.<br />

Table 1.Machining rates (range) in EDM and EDS with two levels (high and low) current settings mg/min<br />

MATERIALS<br />

PROCESS<br />

TITANIUM HSS ALUMINIUM<br />

LOW<br />

CURRENT<br />

HIGH<br />

CURRENT<br />

LOW<br />

CURRENT<br />

HIGH<br />

CURRENT<br />

LOW<br />

CURRENT<br />

HIGH<br />

CURRENT<br />

EDS 185-224 210-277 151-183 212-247 118-158 226-407<br />

EDM 16.7-<strong>20</strong>.1 28.1-34.6 18.8-21.6 31.6-33.4 12.5-16.3 21.9-25.3<br />

Table 2. Surface roughness (Ra ) range in EDM and EDS (µm)<br />

MATERIALS<br />

PROCESS<br />

TITANIUM HSS ALUMINIUM<br />

LOW<br />

CURRENT<br />

HIGH<br />

CURRENT<br />

LOW<br />

CURRENT<br />

HIGH<br />

CURRENT<br />

LOW<br />

CURRENT<br />

HIGH<br />

CURRENT<br />

EDS 6.0-9.2 8.5-14.1 3.6-8.7 6.3-11.4 5.2-9.0 7.4 – 12.8<br />

EDM 1.45-4.23 1.65-5.2 0.91-1.02 1.94-2.63 1.13 -2.3 1.87 – 2.32<br />

The mechanism <strong>of</strong> erosion bears considerable similarity <strong>of</strong> EDM. The erosion rates in EDS are so high that the<br />

high energy pulses and arcing alone may not be the reason but also the short circuits between electrode and work<br />

with current surge. The normal spark and arc discharge major amount <strong>of</strong> molten metal is retained and only a<br />

small part gets removed as atomized droplets.<br />

The short circuits provide much higher expulsion and lower retention <strong>of</strong> molten metal. The erosion mechanism in<br />

EDS needs further exploration.<br />

Another interesting and glaring observation is the higher erosion rates in Titanium 31 compared to steel &<br />

Aluminium in both the versions <strong>of</strong> EDM and EDS. Among the possible reasons, the major one is the higher<br />

thermal and electrical conductivity <strong>of</strong> aluminium resulting in lower energy concentration. The other possibilities<br />

can be lower share <strong>of</strong> the pulse energy and poor compatibility with the electrode. The higher erosion rates with<br />

increasing pulse current has the obvious reason <strong>of</strong> higher pulse energies.<br />

5<strong>20</strong>


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

6. Conclusions<br />

1. Electro discharge sawing is highly suitable for high strength large bars, slabs or ingots for fast and<br />

accurate cuts.<br />

2. High energy arc discharges, there appears to be considerable assistance from short circuit current surges<br />

in the material removal in EDS.<br />

3. In both EDM and EDS aluminium with higher thermal and electrical conductivity shows inferior<br />

erosion rates compared to steel & Titanium 31.<br />

4. Higher erosion rates with increasing current is in conformity to the theory <strong>of</strong> electrical methods <strong>of</strong><br />

machining.<br />

5. Surface roughness also has similar trend as erosion rate in EDM as well as EDM for three Titanium 31,<br />

HSS and Al.<br />

7. References<br />

1. Basak.I, Ghosh A., “Mechanism <strong>of</strong> Spark generation during electrochemical discharge machining. A<br />

theoretical model and experimental verification”, Journal <strong>of</strong> Material processing<br />

<strong>Technology</strong>,Vol.62(<strong>19</strong>96, 46-53)<br />

2. Dolol B., Bhattacharya B., and Sorkhel S.K., “Experimental studies on Electro Chemical Discharge<br />

Machining (ECDM) Characteristics for machining engineering ceramics, Proc. Of 18 th AITDR Conf.,<br />

Dec (<strong>19</strong>98), 322-327.<br />

3. R.F.O’Connor, and T.A. Spedding, “The use <strong>of</strong> a complete surface pr<strong>of</strong>iles description to investigate<br />

the cause and effect <strong>of</strong> surface features”, Int. J. Mach. Tools Manufacture, Vol.32, No. 1/2 pp, 147-154<br />

(<strong>19</strong>92).<br />

4. Shaw, M.C., “Metal cutting Principles, (Oxford university Press, Oxford, <strong>19</strong>89).<br />

5. Murti, V.S.R. “ Variant Electro discharge Machining (EDM) processes for diverse applications,<br />

Proc.AMT -<strong>20</strong>05 Conf., Canada, <strong>20</strong>05 pp 255 -260.<br />

6. K.F. Ehmann,. and M.S. Hong, “ A generalized model <strong>of</strong> the surface generation process in metal<br />

cutting”, Annals <strong>of</strong> CIRP, pp 483 – 486, (<strong>19</strong>94)<br />

7. Soo Miong Lee, Xixoring Li, “Study <strong>of</strong> the surface intensity <strong>of</strong> the machined workpiece in EDM <strong>of</strong><br />

tungsten carbide”, Jl. <strong>of</strong> Materials Processing <strong>Technology</strong> ,Vol.139,<strong>20</strong>03,PP 315-321.<br />

521


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

ANALYSIS ON THE STUDY OF CHANGES IN MECHANICAL<br />

PROPERTIES OF AI6063-SiC<br />

Mandeep Singh 1 , Jaspreet Singh 2 , Dipak Narang 3<br />

1 B.Tech Student (Mech. Eng.g), Maharishi Markandeshwar Univ., Ambala, India. man_deepgill29@yahoo.com<br />

2 M.tech Student, PCET Lalru. jaspreet.deep123@gmail.com<br />

3 PCET Lalru. deepaknarang01@gmail.com<br />

Abstract<br />

The unique tolerability <strong>of</strong> the composite materials for the specific requirements make these materials more<br />

popular in a variety <strong>of</strong> applications such as aerospace, automotive (pistons, cylinder liners, and bearings), and<br />

structural components, resulting in savings <strong>of</strong> money, material, and energy. In this paper; fabrication <strong>of</strong><br />

aluminium metal matrix composite (MMC) is prepared by liquid metallurgy route (stir casting technique). The<br />

objective <strong>of</strong> this experimental investigation is to produce two different metal matrix composite (MMC) specimens<br />

using Al6063 as a base material which reinforced with a ceramic additive (silicon carbide SiC, with grain size<br />

1000 mesh) with same volume fraction <strong>of</strong> 10% by wt. By the addition <strong>of</strong> SiC p particulates into the alloy <strong>of</strong> base<br />

metal Al6063; it was foundincreased value<strong>of</strong> the ultimate tensile strength, andhardnessand decrease elongation<br />

<strong>of</strong> the composites.It was also investigated that the composite poured from lower layer (lower half) <strong>of</strong> melted<br />

matrix from crucible were with less values <strong>of</strong> tensile strength and hardness as compared to the composite poured<br />

from upper layer (upper half).<br />

Key words: Composite materials; Liquid state mixing; Mechanical properties<br />

1. Introduction<br />

Aluminium alloys are widely used in a large number <strong>of</strong> industrial applications due to their excellent combination<br />

<strong>of</strong> properties, for example; good wear resistance, exceptional thermal conductivity, highstrength to weight ratio,<br />

good tensile strength, and high ductility [1, 2]. Aluminium alloy are applicable for manufacturing automobile<br />

and aircraft components because <strong>of</strong> high strength to weight ratio in order to make the moving vehicle lighter,<br />

which results in saving in fuel consumption [3, 4]. Hardness <strong>of</strong> the composites found increased with increased<br />

SiC content. And some authors; G.R.C. Pradeep, A. Ramesh, G.B. Veeresh Kumar studied that finer the grain<br />

size better is the hardness and strength <strong>of</strong> composites leading to lowering <strong>of</strong> wear rates [1]. Most researchers [2-<br />

4,11] agree that the wear rate <strong>of</strong> Al-Si alloys goes through aminimum at certain Si content.Silicon has received<br />

the most attention among all alloying elements studied. This is due to thefact that Al-Si alloys are corrosion<br />

resistant, strong, have low thermal expansion coefficients, and have superior tribologicalcharacteristics compared<br />

to the other aluminium alloys [7]. These alloys have been successfully used as substitutes for cast iron in<br />

applications such as pistons and cylinder linings for internal combustion engines [8,9], swash plates, connecting<br />

rods, and sockets in refrigerant compressors [9]<br />

.The 6061 aluminium alloyexhibited its potential to act effectively as a self lubricating material under dry sliding<br />

conditions recording a minimum wear rate and co efficient <strong>of</strong> friction at 5 Wt % and 15 Wt % graphite content<br />

respectively[12].Earlier authorshave reported that during dry sliding aluminium alloy – graphite composite forms<br />

a layer <strong>of</strong> graphitewith solid lubricant between the contacting surfaces [13]. This helps in reducing the friction<br />

and wearand post pones the onset <strong>of</strong> severe wear. The formation and retention <strong>of</strong> this lubricant layer, itsthickness<br />

and hardness depends largely on the graphite content in the composite. Earlier works havealso identified that<br />

with increasing graphite content richer graphite lubricating film formed on thelubricating surface lowers the wear<br />

rate [13].<br />

In this paper, the material selection criteria involves the requirement <strong>of</strong> high strength and good corrosion<br />

resistance aluminium alloy for the matrix materials, and the inexpensive reinforcement particles which can result<br />

in increased ultimate tensile strength and hardness. The matrix materials used in the present work is Al 6063and<br />

the reinforcement materials are silicon carbide (SiC p ) particulates <strong>of</strong> grain size 1000 mesh) 10% by wt and by<br />

virtue <strong>of</strong> which the tensile strength, hardness, and Al–SiCwere evaluated.And effects <strong>of</strong> SiC p upper layer and<br />

lower layer <strong>of</strong> melted matrix in crucible were investigated in an attempt to understand the uniformity <strong>of</strong> SiC p<br />

through-out the matrix.<br />

522


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. Experimental Techniques<br />

2.1. Stir Casting Design:<br />

The stir casting is one <strong>of</strong> the best known methods <strong>of</strong> preparing metal matrix composites. The components<br />

selected as the parts <strong>of</strong> the casting setup were chosen specifically according to their properties and qualities. In<br />

today’s world there is a tough competition between two technologies viz metal matrix composites and powder<br />

metallurgy. Both are the efficient methods <strong>of</strong> preparing alloys. However the method with least preparing cost<br />

will be preferred. At 1 st it was aim to preparing such a setup which could prove itself useful for the desired<br />

research work. And the setup shown in Fig 1 made by us as our requirements.<br />

Stir Casting Machine<br />

Vickers Hardness Testing Machine<br />

2.2. Casting Operation And Procedure<br />

The liquid metallurgy route (stir casting technique) has been adopted to prepare the cast composites described as:<br />

Preheated SiC powder <strong>of</strong> particle size 1000 mesh was introduced into the vortex <strong>of</strong> the molten alloy after<br />

effective degassing. Mechanical stirring <strong>of</strong> the molten alloy for duration <strong>of</strong> 8 to 12 minute was achieved by using<br />

steel impeller. A speed <strong>of</strong> 650 rpm was maintained. A pouring temperature <strong>of</strong> 900oC was adopted and the molten<br />

composite was poured into mild steel moulds as shown in fig (2). The extent <strong>of</strong> incorporation <strong>of</strong> SiC in the<br />

matrix alloy was 10 % by wt. Thus composites containing particles 10wt % were obtained in the form <strong>of</strong><br />

rectangular <strong>of</strong> 160*125* 25mm size shown in fig (3).<br />

An electrical furnace was used at the first stage for melting the aluminium in a graphite crucible. Subsequent to<br />

the melting <strong>of</strong> the aluminium, the melt temperature was increased to 1000 o C and then 10% by wt. SiC particles<br />

which are preheated at 650 o C were introduced to the melt with vigorous stirring to make the melt homogenous<br />

under protective pure nitrogen gas atmosphere and then the upper layer (upper half) and lower layer (lower half)<br />

<strong>of</strong> melt from crucible were poured into two different permanent mild steel pre-heated (about 150 o C ) moulds and<br />

the pouring temperature noted as 9<strong>20</strong> o C.<br />

2.3. Material Used<br />

The matrix materialfor this experiment used Al60 andmechanical properties and chemical compositions are<br />

given in table (1). The reinforcing material selected was SiC10% by wt. <strong>of</strong> grain size <strong>of</strong> 1000 mesh and table (2)<br />

gives the physical and mechanical properties <strong>of</strong> SiC p .And Graphite crucibles <strong>of</strong> different size are used to heat up<br />

the SiC p and to melt the matrix base material Al6063.<br />

TABLE (1).MECHANICAL PROPERTIES AND CHEMICAL COMPOSITIONS OF MATRIX MATERIAL AL<br />

6063[matweb properties <strong>of</strong> Al 6063]<br />

Alloy H.B. U.T.S.(MPa) M.O.E.(GPa) Y.T.S.(MPa)<br />

6063 <strong>20</strong> 89.6 68.9 43.3<br />

523


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Al Cr Cu Fe Mg Mn Si Ti Zn Other<br />


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

(2) both were prepared <strong>of</strong> size 160*<strong>20</strong>*18mm. And then for hardness testing policing has been done on both<br />

specimens and then Vickers Hardness testing was done for both specimens, and then both specimens were<br />

machined in the form <strong>of</strong> dumbbell for tensile testing, as shown in fig (4, 5)<br />

Figure 4 Al6063 with SiC 10% by wt. from upper layer <strong>of</strong> melted<br />

Figure 5 Al6063with SiCp 10% by wt. from lower layer <strong>of</strong> melted<br />

matrix<br />

matrix<br />

3. RESULTS<br />

3.1. Tensile Property<br />

The tensile properties <strong>of</strong> the composites studied are given in Table 3. It can be seen that the pro<strong>of</strong> stress, the<br />

ultimate tensile strength increased in specimen. And it is observed that %age elongation decrease from 22 to<br />

9.82. A ductile fracture appearance was observed with shearing effects on the surface. The mechanical<br />

properties such as hardness, tensile strength, elongation property test results <strong>of</strong> Al6063 and its composites<br />

containing SiC at various time <strong>of</strong> pouring are presented in these sections. Maximum load for specimen (1) is<br />

given by this graph (1);F m = 30.600 KN and the area on which load was applied = 275.807 mm 2 , so Tensile<br />

Strength = 111 N/mm 2 .<br />

Graph 1 for matrix with SiC 10% by wt. from upper layer <strong>of</strong> melted matrix in crucible<br />

525


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

TABLE (3) PHYSICAL AND MECHANICAL PROPERTIES OF AL6063 AND SIC(10 WT % UPPER LAYER OF<br />

MOLTEN MATRIX FROM CRUCIBLE)<br />

Tensile Strength (Mpa) Hardness (HV) Elongation(%)<br />

111 65.47 9.82<br />

Then tensile strength was tested for specimen (2). Which was found less in comparison that <strong>of</strong> specimen (1).<br />

Maximum force F m = 14.550 KN, and area <strong>of</strong> specimen on which force was applied = 135.494mm 2 . Hence<br />

results for tensile strength <strong>of</strong> specimen (2) found = 107 N/mm 2 as shown in table (4). Testing was done on UTM,<br />

Model No: UTE 100, Sr. No. : 4/<strong>20</strong>10-4328<br />

TABLE (4). PHYSICAL AND MECHANICAL PROPERTIES OF AL6063 AND SIC(10 WT % LOWER LAYER<br />

OF MOLTEN MATRIX FROM CRUCIBLE)<br />

Tensile Strength (Mpa) Hardness (HV) Elongation (%)<br />

107 51.83 10.24<br />

Graph 2 for matrix with SiCp 10% by wt. with lower layer <strong>of</strong> matrix from crucible<br />

3.2 Hardness:<br />

Hardness is closely related to strength. It is the ability <strong>of</strong> a material to resist scratching, abrasion, indentation, or<br />

penetration. It is directly proportional to tensile strength and is measured on special hardness testing machines<br />

526


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

by measuring the resistance <strong>of</strong> the material against penetration <strong>of</strong> an indenter <strong>of</strong> special shape and material under<br />

a given load. The different scales <strong>of</strong> hardness are Brinell hardness, Rockwell hardness,Vicker’s hardness [14].<br />

The Vickers hardness <strong>of</strong> aluminium-SiCp composite specimen (1) and specimen (2) was tested.<br />

The result for specimen (1) is shown in table (3) and that <strong>of</strong> specimen (2) in table (4). The Vickers hardness <strong>of</strong> all<br />

specimens increases due to addition <strong>of</strong> SiCp particles. The increase in hardness for the composites is not<br />

dramatic and may be due to the increase in their brittleness or due to very fine particles <strong>of</strong> grain size 1000 mesh.<br />

The change in the hardness <strong>of</strong> composites with lower portion <strong>of</strong> melted matrix with less content <strong>of</strong><br />

reinforcement SiCp particles which is reduced from 68.47 HV to 51.83.andtable (5) represent the variation in<br />

hardness, tensile strength, and elongation. Hardness is evaluated at a load <strong>of</strong> 1kgfby using Vickers Hardness<br />

Tester; Model No.VM50 pc , Sr. No. 04/<strong>20</strong>10-1118.<br />

TABLE 5 COMPARISON BETWEEN MECHANICAL PROPERTIES OF TWO SPECIMENS<br />

Type Of Specimen Tensile Strength (N/mm 2 ) Hardness (HV)<br />

Elongation (%age)<br />

Specimen (1) 111 65.47 9.82<br />

Specimen (2) 107 51.83 10.24<br />

Figure 5 Specimens after breakage<br />

3.3 Stress-Strain Diagrams:<br />

The internal resistance <strong>of</strong> the material to counteract the applied load is called stress, and the deformation as<br />

strain. There are three types <strong>of</strong> stresses: Tensile stress: force acts to pull materials apart; Compressive stress: the<br />

force squeezes material; Shear stress: the force causes one part to slide on another part [14].There are three types<br />

<strong>of</strong> corresponding strains. The metals are tested on a Universal Testing Machine. The stress-strain diagram is a<br />

diagram with values <strong>of</strong> stress (load) as ordinate and strain (elongation, compression, deflection, twist etc.) as<br />

abscissa.Mechanical properties depend upon the crystal structure, its bonding forces, and the imperfectionswhich<br />

exist within the crystal [14].<br />

Ductility <strong>of</strong> a material enables it to draw out into thin wire on application <strong>of</strong> the load. Mild steel is a ductile<br />

material. The wires <strong>of</strong> gold, silver, copper, aluminium, etc. are drawn by extrusion or by pulling through a hole<br />

in a die due to the ductile property. The ductility decreases with increase <strong>of</strong> temperature. The per cent elongation<br />

and the reduction in area in tension is <strong>of</strong>ten used as empirical measures <strong>of</strong> ductility Stress-Strain curves are<br />

unique for each material and are found by recording the amount <strong>of</strong> deformation (strain) at distinct intervals <strong>of</strong><br />

tensile load. The linear portion <strong>of</strong> the curve is the elastic region and the slope is the modulus <strong>of</strong><br />

elasticity or Young's Modulus [14].<br />

527


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Stress and strain diagram for specimen (2)<br />

4. CONCLUSIONS<br />

The significant conclusions <strong>of</strong> the studies carried out on Al6063 - SiC composites are as follows.<br />

‣ Casting <strong>of</strong> Al6063–SiC p composites were prepared successfully using liquid metallurgy technique (stir<br />

casting method).<br />

‣ Hardness <strong>of</strong> the composites found more in upper layer <strong>of</strong> melted matrix in crucible comparison to lower<br />

layer <strong>of</strong> matrix in crucible.<br />

‣ Hardness decreases by <strong>20</strong>.8% from upper half to lower half.<br />

‣ Grater Tensile strength in upper layer in comparison with lower layer <strong>of</strong> matrix in crucible.<br />

‣ Tensile strength decreases by 3.8% from upper half to lower half.<br />

‣ Percentage elongation is also greater in the lower layer with the difference <strong>of</strong> 0.42.<br />

‣ Percentage elongation increases by 4.49% from upper half to lower half.<br />

REFERENCES<br />

[1] G.R.C. Pradeep, A. Ramesh, G.B. Veeresh Kumar, Published in International Journal <strong>of</strong> Advanced<br />

Engineering & Application, Jan <strong>20</strong>11 Issue<br />

[2] Department <strong>of</strong> Defense handbook composite materials handbook volume 4. metal matrix composites<br />

(mil-hdbk-17-4a volume 4 <strong>of</strong> 5 17 june <strong>20</strong>02 superseding mil-hdbk-17-421 september <strong>19</strong>99).<br />

[3] Dinwoodie, J., "Automotive Applications for MMCs based on Shot StampleAluminumFibers", (<strong>19</strong>87)<br />

[4] A.R.I. Khedera,G.S. Marahleh*,a, D.M.K. Al-JameaaaDepartment <strong>of</strong> Mechanical Engineering, Faculty <strong>of</strong><br />

Engineering <strong>Technology</strong>, Al-Balqa' Applied <strong>University</strong>, Jordan, Volume 5, Number 6, Dec. <strong>20</strong>11 ISSN <strong>19</strong>95-<br />

6665 Pages 533 - 541<br />

528


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[5]Somi Reddy, A., PramHaBai, B. N., Murthy, K. S.S., and Biswas, S. K., Wear and Seizure <strong>of</strong><br />

Binary Al-Si Alloys, Wear, 171 (<strong>19</strong>94) 115-127.<br />

[6]Jogi, B. F., Brahmankara, P. K., Nandab, V. S. and Prasad R. C., -- “Some studies on fatigue crack growth<br />

rate <strong>of</strong> aluminum alloy 6061”, Journal <strong>of</strong> material processing <strong>Technology</strong>, <strong>20</strong>1(1-3), (<strong>20</strong>08), pp 380- 384.<br />

[7]Smale, M.D., "The Mechanical Properties <strong>of</strong> Squeeze Cast Diesel Pistons", P. 29, (<strong>19</strong>85).<br />

[8] T. K. Sheiretov, H. Yoon and C. Cusano, Air Conditioning &Refrigeration Center Mechanical &Industrial<br />

Engineering Dept. <strong>University</strong> <strong>of</strong> Illinois 1<strong>20</strong>6 West Green Street Urbana IL 61801-2173333115<br />

[9] Hanna, A. H. and Shehata, F., Friction and Wear <strong>of</strong> AI-Si AllOYS, Lubrication Engineering, 49, (<strong>19</strong>92) 473-<br />

476.<br />

[10] Konishi, T., Klaus, E. E. and Duda, J. L., Wear Characteristics <strong>of</strong> Aluminum-Silicon Alloy Under<br />

Lubricated Sliding Conditions, SILE Preprint No. 95-MP-5E-1, 50th Annual Meeting <strong>of</strong> SILE, Chicago, Illinois,<br />

May 14-<strong>19</strong>, <strong>19</strong>95.<br />

[11] PramilaBai, B. N, and Biswas, S. K., Scanning Electron Microscopy Study <strong>of</strong> Worn AI-Si Alloy Surfaces,<br />

Wear, 87 (<strong>19</strong>83) 237-249.<br />

[12] A. Baradeswaran;Research Scholar , A. Elayaperumal; Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering<br />

College <strong>of</strong> Engineering Guindy, Anna <strong>University</strong> Chennai - 600025, Tamil Nadu, India, European Journal <strong>of</strong><br />

Scientific Research ISSN 1450-216X Vol.53 No.2 (<strong>20</strong>11), pp.163-170<br />

[13] F.Akhlaghi, A.Zare-Bidaki, Influence <strong>of</strong> graphite content on the dry sliding and oil impregnated sliding<br />

wear behavior <strong>of</strong> aluminium <strong>20</strong>24 – graphite composites produced by in situ powder metallurgy method. Wear<br />

266 (<strong>20</strong>09) 37-45.<br />

[14] Properties Of Materials. (http://www.newagepublishers.com/samplechapter/001653.pdf).<br />

529


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

FRICTION STIR WELDING OF ALUMINIUM ALLOY AND ITS<br />

TENSILE PROPERTIES<br />

Sandhya Dixit 1 and M.L.Aggarwal 2<br />

1 Assistant Pr<strong>of</strong>essor, 2 Pr<strong>of</strong>essor<br />

Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad<br />

Abstract<br />

Aluminium alloys have gathered wide acceptance in the fabrication <strong>of</strong> light weight structures requiring a high<br />

strength-to-weight ratio. Compared to many fusion welding processes that are routinely used for joining<br />

structural aluminium alloys, friction stir welding (FSW) process is an emerging solid state joining process in<br />

which the material that is being welded does not melt and recast. The welding parameters and the tool pin<br />

pr<strong>of</strong>ile play a major role in deciding the weld quality. In this paper an attempt has been made to understand the<br />

influences <strong>of</strong> rotational speed, welding speed and pin shoulder diameter <strong>of</strong> the tool on friction stir processed<br />

(FSP) zone formation in AA1<strong>20</strong>0 aluminium alloy. Two different tool shoulder diameters ( <strong>20</strong> mm and 10 mm )<br />

have been used to fabricate the joints at two different tool rotational speeds (<strong>20</strong>00 rpm and 1400 rpm) and two<br />

different welding speeds ( <strong>20</strong> mm/minute and 10 mm/minute). Tensile properties <strong>of</strong> the joints have been evaluated<br />

to find the ultimate tensile strength <strong>of</strong> the welded specimen.<br />

1. Introduction<br />

Friction Stir Welding [1, 2, 3] is primarily used on aluminum, and most <strong>of</strong>ten on large pieces which cannot be<br />

easily heat treated post weld to recover temper characteristics. In this process a non-consumable rotating tool is<br />

pushed into the materials to be welded and then the central pin, or probe, followed by the shoulder, is brought<br />

into contact with the two parts to be joined, (See fig. 1).<br />

Figure.1 Principle <strong>of</strong> operation <strong>of</strong> FSW<br />

The rotation <strong>of</strong> the tool heats up and plasticizes the material it is in contact with and, as the tool moves along the<br />

joint line, material from the front <strong>of</strong> the tool is swept around this plasticized annulus to the rear, so eliminating<br />

the interface.<br />

Fig.2 shows the schematic diagram <strong>of</strong> the FSW process:<br />

(a) Two dissimilar metal workpieces butted together, along with the tool (with a probe).<br />

530


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

(b) The progress <strong>of</strong> the tool through the joint, also showing the weld zone and the region affected by the tool<br />

shoulder.<br />

(a)<br />

(b)<br />

Figure.2. FSW process<br />

As shown in Fig.2. a cylindrical-shouldered tool, with a pr<strong>of</strong>iled threaded/unthreaded probe (nib or pin) is rotated<br />

at a constant speed and fed at a constant traverse rate into the joint line between two pieces <strong>of</strong> sheet or plate<br />

material, which are butted together. The parts have to be clamped rigidly onto a backing bar in a manner that<br />

prevents the abutting joint faces from being forced apart. The length <strong>of</strong> the nib is slightly less than the weld depth<br />

required and the tool shoulder should be in intimate contact with the work surface. The nib is then moved against<br />

the work, or vice-versa.<br />

Frictional heat is generated between the wear resistant welding tool shoulder and nib, and the material <strong>of</strong> the<br />

work-pieces. This heat, along with the heat generated by the mechanical mixing process and the adiabatic heat<br />

within the material, cause the stirred materials to s<strong>of</strong>ten without reaching the melting point (hence cited a solidstate<br />

process), allowing the traversing <strong>of</strong> the tool along the weld line in a plasticised tubular shaft <strong>of</strong> metal. As<br />

the pin is moved in the direction <strong>of</strong> welding the leading face <strong>of</strong> the pin, assisted by a special pin pr<strong>of</strong>ile, forces<br />

plasticised material to the back <strong>of</strong> the pin whilst applying a substantial forging force to consolidate the weld<br />

metal. The welding <strong>of</strong> the material is facilitated by severe plastic deformation in the solid state involving<br />

dynamic recrystallization <strong>of</strong> the base material.<br />

The method is characterized by a rotating cylindrical tool which has an end tap <strong>of</strong> 5-6 mm in diameter and a<br />

height <strong>of</strong> 5-6 mm. The tool is set in a positive angle <strong>of</strong> some degrees in the welding direction. By pressing the<br />

rotating tool into the middle <strong>of</strong> an I-shaped butt joint friction heat will occur in the joint. The temperature will be<br />

about 450 0 C to 500°C and the tap causes stirring in the hot material so there will be a weld between the two<br />

parts.<br />

531


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The welding equipment can be a conventional milling machine which instead <strong>of</strong> a milling tool carries a welding<br />

tool. The thickness <strong>of</strong> the aluminum material being welded is between 1.5-30 mm.<br />

The advantage is very high welding quality. No pores has been observed and the material structure is very<br />

uniform and <strong>of</strong>ten totally without cracks. Bending tests show very good bending results with no rupture. Tensile<br />

tests give breakage in the heat affected zone (HAZ).<br />

No oxide removal is necessary before welding. The heat influence is very low on the material. Welding speed <strong>of</strong><br />

600 mm/min in 6 mm thick material is possible.<br />

2. Experimental Method<br />

The rolled plates <strong>of</strong> 4mm thickness, AA1<strong>20</strong>0 aluminium alloy, were cut into the required size (<strong>20</strong>0mm×100 mm)<br />

by power hacksaw. Square butt joint configuration was prepared to fabricate FSW joints. The initial joint<br />

configuration was obtained by securing the plates in position using mechanical clamps. The direction <strong>of</strong> welding<br />

was normal to the rolling direction. Single pass welding procedure was used to fabricate the joints. Nonconsumable<br />

tools made <strong>of</strong> HCHCR steel were used to fabricate the joints. The chemical composition <strong>of</strong> base<br />

metal is presented in Table 1.<br />

Table 1. Chemical composition (wt%) <strong>of</strong> base metal<br />

Elements<br />

Percentage/weight base metal<br />

Cu 0.05<br />

Mo 0.05<br />

Si 0.05<br />

Zn 0.1<br />

Ti 0.05<br />

Fe 0.05<br />

Al<br />

Balance<br />

A knee type vertical milling machine (<strong>20</strong>00 rpm) was used to fabricate the joints. Two different tool pr<strong>of</strong>iles, as<br />

shown in Fig. 3 were used to fabricate the joints.<br />

Figure 3. Tool Pr<strong>of</strong>iles<br />

Eight specimens were fabricated using two different tool, two different feeds and two different rotational speeds<br />

(See Table 2) and fractional factorial design was developed<br />

Table 2. Welding parameters and tool dimensions<br />

Process parameters<br />

Values<br />

Rotational speed (rpm) 1400, <strong>20</strong>00<br />

Welding speed (mm/min) 10, <strong>20</strong><br />

Tool shoulder diameter, D (mm) <strong>20</strong>,10<br />

Axial force (kN) 12<br />

Pin length (mm) 3.8<br />

Pin diameter, d (mm) 5<br />

532


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Tool inclined angle (◦) 0<br />

Shoulder deepness inserted into the surface<br />

0.1<br />

<strong>of</strong> base metal (mm)<br />

Tensile testing is done on Universal Testing Machine. The specimens are prepared for tensile testing <strong>of</strong> the<br />

required size by filing having a cross-sectional area <strong>of</strong> 4x15 mm and a gauge length <strong>of</strong> 43.7 mm.<br />

3. Results <strong>of</strong> Tensile Testing<br />

The welded specimens are put under tensile testing and the values <strong>of</strong> yield strength, ultimate tensile strength and<br />

percentage elongation are noted.<br />

The results <strong>of</strong> tensile loading <strong>of</strong> the specimen are shown in table 3 and the variation <strong>of</strong> yield strength, ultimate<br />

tensile strength and percentage elongation are shown in graph 1, graph 2 and graph 3 respectively.<br />

Crosse sectional area <strong>of</strong> test specimen = 4x15 mm= 60 mm<br />

Gauge length =43.7 mm<br />

Specimen<br />

No<br />

Table 3. Tensile test results<br />

Yield Strength Ultimate Strength Elongation<br />

Load(kN) Stress(N/mm 2 ) Load(kN) Stress(N/mm 2 ) Breaking %<br />

length(mm) elongation<br />

S1 3.25 54.17 4.45 74.17 47.6 8.9<br />

S2 2.75 45.83 4.55 75.8 51.9 18.7<br />

S3 2.85 47.5 3.5 58.3 46.2 5.7<br />

S4 2.75 45.8 4.5 75 50.1 14.6<br />

S5 2.85 47.5 4.75 79.17 50.3 15.1<br />

S6 3.35 55.8 4.75 79.17 50.4 15.3<br />

S7 2.75 45.8 4.55 75.8 51.0 16.7<br />

S8 3.25 54.17 4.75 79.17 50.8 16.2<br />

Variation <strong>of</strong> Yield Strength<br />

60<br />

50<br />

Yield Streng<br />

40<br />

30<br />

<strong>20</strong><br />

10<br />

0<br />

0 2 4 6 8 10<br />

Specimen No<br />

Series1<br />

Graph 1: Variation <strong>of</strong> Yield Strength<br />

533


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Variation <strong>of</strong> UTS<br />

Ultimate Tensile Stren<br />

90<br />

80<br />

70<br />

60<br />

50<br />

40<br />

30<br />

<strong>20</strong><br />

10<br />

0<br />

0 2 4 6 8 10<br />

Spaecimen No<br />

Series1<br />

Graph 2: Variation <strong>of</strong> Ultimate Tensile Strength<br />

Variation <strong>of</strong> % Elongation<br />

Percentage Elongati<br />

<strong>20</strong><br />

18<br />

16<br />

14<br />

12<br />

10<br />

8<br />

6<br />

4<br />

2<br />

0<br />

0 2 4 6 8 10<br />

Specimen No<br />

Series1<br />

Graph 3: Variation <strong>of</strong> Percentage Elongation<br />

3.1 Discussion on the tensile test results<br />

In the present study the minimum limit <strong>of</strong> the parameters selected are 1400 rpm, 10 mm / minute welding feed<br />

and 10 mm shoulder dia and the corresponding yield strength and ultimate strength in the specimen are 54.17<br />

N/mm 2 and 74.17 N/mm 2 respectively. The maximum limit <strong>of</strong> the parameters selected are <strong>20</strong>00 rpm, <strong>20</strong> mm /<br />

minute welding feed and <strong>20</strong> mm shoulder dia and the corresponding yield strength and ultimate strength in the<br />

specimen are 54.17 N/mm 2 and 79.17 N/mm 2 respectively. From these two results it is concluded that the<br />

strength <strong>of</strong> the specimen are approximately same. It is because although with increase in rpm <strong>of</strong> the tool the<br />

relative motion increases i.e. the frictional heat generated increases but at the same time with the increase in the<br />

temperature the coefficient <strong>of</strong> friction µ decreases with increases in temperature and it leads to less heat<br />

generated. In other words the frictional heat generated per unit area is remaining almost constant and it is<br />

approximately 0.7 times the melting temperature <strong>of</strong> the alloy.<br />

4. Conclusion<br />

Defects free welds were produced on 4 mm thick aluminum alloy plates with FSW with rotational speeds <strong>of</strong><br />

1400 and <strong>20</strong>00 rpm, travel speed <strong>of</strong> 10 mm/ minute and <strong>20</strong> mm/ minute and shoulder diameter 10 mm and <strong>20</strong><br />

mm. Welded samples failed in the region corresponding to the base metal and demonstrated yield and ultimate<br />

strength comparable to the base metal.<br />

The Friction Stir Welded specimens have average UTS <strong>of</strong> 74.5725 N/mm 2 .<br />

534


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5. References<br />

[1] Fujii H., Cui L., Nogi K., “Effect <strong>of</strong> tool shape on mechanical properties and microstructure <strong>of</strong> friction stir<br />

welded aluminum alloys”, Materials <strong>Science</strong> and Engineering Journal A 4<strong>19</strong>(<strong>20</strong>06), pp. 25-31.<br />

[2] Buffa G., Hua J., Shivpuri R., Fratini L., “Design <strong>of</strong> the friction stir welding tool using the continuum based<br />

FEM model”, Materials <strong>Science</strong> and Engineering Journal A 4<strong>19</strong> (<strong>20</strong>06), pp 381-388.<br />

[3] Scialpi A., De Filppis LAC., Cavaliere P., “Influence <strong>of</strong> shoulder geometry on micro-structure and<br />

mechanical properties <strong>of</strong> friction stir welded 6082 aluminum alloy”, Materials and Design journal 28(<strong>20</strong>07),<br />

pp 1124-1129.<br />

[4] Colegrove Paul A., Shercliff Hugh R., “3-Dimensional CFD modelling <strong>of</strong> flow around a threaded friction stir<br />

welding tool pr<strong>of</strong>ile”, Journal <strong>of</strong> Materials Processing <strong>Technology</strong> 169 (<strong>20</strong>05), pp 3<strong>20</strong>-327.<br />

[5] Barcellona A., Buffa G., Fratini L., Palmeri D., “On microstructural phenomena occurring in friction stir<br />

welding <strong>of</strong> aluminum alloys”, Journal <strong>of</strong> Materials Processing <strong>Technology</strong> 177 (<strong>20</strong>06), pp 340-343.<br />

[6] Kumar K., Kailas Satish V., “On the role <strong>of</strong> axial load and the effect <strong>of</strong> interface position on the tensile<br />

strength <strong>of</strong> a friction stir welded aluminum alloy”, Materials and Design journal (<strong>20</strong>07).<br />

[7] Minton T., Mynors D.J., “Utilization <strong>of</strong> engineering workshop equipment for friction stir welding”, Journal<br />

<strong>of</strong> Materials Processing <strong>Technology</strong> 177 (<strong>20</strong>06), pp 336-339.<br />

[8] Fratini L., Buffa G., Shivpuri R., “Improving friction stir welding <strong>of</strong> blanks <strong>of</strong> different thicknesses”,<br />

Materials <strong>Science</strong> and Engineering Journal (<strong>20</strong>07).<br />

[9] Richard E. Devor, Tsong-how Chang and John W. Sutherland (MMI); “Statical Quality Design and Control”<br />

(2nd Edition) Prentice Hall<br />

535


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

INVESTIGATION AND ANALYSIS FOR THE WRINKLING<br />

BEHAVIOUR OF DEEP DRAWN DIE SHEET METAL COMPONENT<br />

BY USING FAST FORM<br />

Surya Prakash 1, Dinesh Kumar 2<br />

1, 2 Department <strong>of</strong> Mechanical Engineering, ITM <strong>University</strong>, Gurgaon, Haryana, India.<br />

email: suryaprakash@itmindia.edu, +91-9718238577<br />

Abstract<br />

The manual design <strong>of</strong> any type <strong>of</strong> drawing die is complicated and tedious procedure, In spite <strong>of</strong> all precautionary<br />

measures there are several chances <strong>of</strong> denting, cracking and wrinkling which needs to be rectified. As the<br />

design and development <strong>of</strong> sheet metal deep drawn die is a comprehensive technique which needs accuracy in<br />

the apprehension <strong>of</strong> working for high order and its rectification in forming process. The appearance <strong>of</strong><br />

dimensional deviations <strong>of</strong> shape and position, <strong>of</strong> the defects in the metal sheets that have been subjected to a cold<br />

plastic deformation process, represents a critical problem for the specific industry, especially for the mass<br />

production, like the machine manufacturing industry. Thus, there arises the need for development <strong>of</strong> a system for<br />

manufacturing wrinkle free surface <strong>of</strong> deep drawn components. The complex forces act on the sheet metal blank<br />

during drawing are so unpredictable that they are difficult to determine manually and mathematically. These<br />

forces cause wrinkles and other defects on the surface <strong>of</strong> the wall <strong>of</strong> component. The aim <strong>of</strong> this publication is to<br />

present the principal aspects and investigation that effect wrinkling. Firstly component 3D-modeled in CATIA<br />

for analyzing for detecting wrinkle prone area by using fast form s<strong>of</strong>tware. The input to s<strong>of</strong>tware comprises <strong>of</strong><br />

initial graphics exchange system .Cold rolled extra deep drawing quality material <strong>of</strong> sheet metal component has<br />

been utilize. The out put in form <strong>of</strong> results received regarding wrinkle prone area are found in closed agreement<br />

matching with the practical results. One can therefore easily predict and detect the tendency <strong>of</strong> expected wrinkle<br />

formation and stress distribution in any drawn component. Some methods for preventing wrinkling in deep<br />

drawn part are also suggested.<br />

Keywords: Wrinkles, Forming, Sheet Metal, Deep Drawing<br />

1. Introduction<br />

Deep drawing is a process for shaping flat sheet into cup shaped articles, without excessive localized thinning,<br />

fracture or wrinkling. This is done by placing a blank <strong>of</strong> appropriate size over shaped die and pressing the metal<br />

into the die punch. In production <strong>of</strong> passenger car body, motor bike components, deep-drawing is one <strong>of</strong> the<br />

most important manufacturing processes. A usual deep-drawing die is shown in figure 1 (a). It consists <strong>of</strong> a die<br />

cavity, a blank holder and a punch<br />

During the deep-drawing process, the blank is clamped between die cavity and blank holder. The blank holder is<br />

to avoid the occurrence <strong>of</strong> wrinkling and inducing required retracking force. While the punch is forming the<br />

blank into the die cavity, blank material flows into die cavity. This effect is called material flow. In deep-drawing<br />

processes, it is important to control material flow in order to get defect-free components [1].<br />

Figure 1(a) Sheet metal deep drawing process<br />

Depending upon several factors such as geometry, volume material type, deep drawing or stretch forming is used<br />

to form sheet metals. In sheet-forming process, however, several types <strong>of</strong> failures could occur, such as rupturing,<br />

necking, wrinkling and spring back which is undesirable [2]. Main defects in deep-drawing processes are cracks<br />

and sidewall wrinkling, depicted in figure 1(b) & figure 1(c).<br />

536


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 1 (b) cracks and sidewall wrinkling in a deep drawn part<br />

Figure 1(c) Wrinkles formation on the side wall <strong>of</strong> the component<br />

1.1. Deep drawing parts<br />

There are the components which are manufactured with the help <strong>of</strong> deep drawn dies. As shown in the figures-<br />

Figure 2 Car engine part Figure 3 Deep drawn cup Figure 4 Deep drawn sheet<br />

1.2. Wrinkles on deep drawing parts<br />

Material thinning and cracks may arise when local load in the blank increased the level <strong>of</strong> uniform elongation. In<br />

contrast, sidewall wrinkling occurred when tangential compressive stresses led to buckling in the sidewall area.<br />

In deep-drawing, wrinkling and cracks have to be avoided by control <strong>of</strong> material flow. Blank holder force, draw<br />

or lock beads, type and amount <strong>of</strong> lubricant as well as shape and size <strong>of</strong> initial blank represent possibilities to<br />

influence material flow. Wrinkling is usually undesired in final sheet metal parts for functional and aesthetic<br />

reasons. It is unacceptable in the outer skin panels where the final part appearance is crucial. Wrinkling on the<br />

mating surfaces can adversely affect the part assembly and part functions, such as, sealing and welding. In<br />

addition, severe wrinkles may damage or even destroy dies. Therefore, the prediction and prevention <strong>of</strong><br />

wrinkling are extremely important in sheet metal forming parts. One <strong>of</strong> the variable blank holder forces known<br />

from literature has been published by Sheng and is illustrated in figure 5. The depicted blank holder force pr<strong>of</strong>ile<br />

has been utilized for optimization <strong>of</strong> deep- drawing a conical cup. Optimization <strong>of</strong> variable blank holder force<br />

distributions was a deciding factor too.<br />

537


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

1.3. Summary <strong>of</strong> causes Of Wrinkling in Deep Drawn Parts: Several factors can cause wrinkles<br />

in deep drawn parts, including:<br />

• Blank holder pressure<br />

• Die cavity depth and radius<br />

• Friction between the blank, blank holder, punch and die cavity<br />

• Clearances between the blank, blank holder punch and die cavity<br />

• Blank shape and thickness<br />

• Final part geometry<br />

• Punch speed<br />

Figure 5 Variable blank holder forces for a conical cup<br />

Figure 6 silencer protector <strong>of</strong> Yamaha bike<br />

Wrinkling is a phenomenon <strong>of</strong> compressive instability <strong>of</strong> as a result, compressive hoop stresses are generated and<br />

thus wrinkling may be developed in the sheet metal under the holder (flange wrinkling) as well as those in the<br />

side-wall [3]. The prediction on the initiation <strong>of</strong> flange wrinkling has been addressed analytically and<br />

numerically in a number <strong>of</strong> previous works [4-8]. In depth study <strong>of</strong> deep drawing, with a view to provide<br />

explanation <strong>of</strong> certain less understood aspects <strong>of</strong> the process, especially in the case <strong>of</strong> deep drawing <strong>of</strong> non<br />

circular parts and components like protector silencer is taken as shown in figure 6.<br />

2. Literature review<br />

Nonmu [8] is the first person who studied on the wrinkling defect in the deep drawing operation. He examined<br />

actual phenomenon <strong>of</strong> wrinkling in conventional deep drawing without blank holder by considering equilibrium<br />

<strong>of</strong> moment acting on half waves & critical blank thickness. M. M. Alkky & D.M.Woo [9] examined effect <strong>of</strong> die<br />

pr<strong>of</strong>ile one near to tractrix form & other two with large radius <strong>of</strong> curvature on the drawing performance. He<br />

showed that punch load can be reduced by using tractrix type die with large radius <strong>of</strong> curvature. Yossifon and<br />

Tirosh [10] published a series <strong>of</strong> articles dealing with simple analysis <strong>of</strong> the deep drawing process as applied to<br />

the formation <strong>of</strong> cups from metallic materials such as copper, aluminum, steel and stainless steel. Shawki [11]<br />

has systematically investigated the influence <strong>of</strong> different test condition on LDR for two different types <strong>of</strong><br />

pr<strong>of</strong>iles namely conical , tractrix and showed that tractrix die is more effective. Lo, Hsu and Wilson [12]<br />

expanded upon the earlier work <strong>of</strong> Yossifon and Tirosh by applying the deep drawing hydro forming theory to<br />

the analysis <strong>of</strong> the hemispherical punch hydro forming process. The purpose <strong>of</strong> this work was to determine a<br />

theoretical method <strong>of</strong> predicting failure due to wrinkling (buckling) or rupture (tensile instability) during the<br />

punch hydro forming <strong>of</strong> hemispherical cups. This work was basically an extension <strong>of</strong> the work done by Yossifon<br />

and Tirosh by incorporating a general friction-force expression into the analysis and expanding to more<br />

complicated geometries. In <strong>19</strong>94 Naryansamy & Sowerby [13] showed that stainless steel 304 which has low<br />

value <strong>of</strong> anisotropy and high value <strong>of</strong> hardening rate has better resistance to formation <strong>of</strong> wrinkles when deep<br />

drawn through conical die.Wrinkling in sheet metal forming, with tearing, is one <strong>of</strong> the most important<br />

instabilities that occur in parts formed using stamp forming and deep drawing processes. This phenomenon limits<br />

the type <strong>of</strong> parts and geometries that can be formed using these techniques. Simulation <strong>of</strong> wrinkling behavior<br />

using the finite element method (FEM) in sheet metal stamping is an important predictive tool. An accurate finite<br />

element model that could accurately predict the formation <strong>of</strong> wrinkling could also be used at the tooling design<br />

stage <strong>of</strong> parts <strong>of</strong> various shapes.<br />

538


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Klaus M. Wurster etc describes a procedure for automated optimization <strong>of</strong> blank holder force distribution for a<br />

deep-drawing process with segment-elastic blank holder. Thereby, it was possible to identify optimized blank<br />

holder force distribution in space and time without manual investigation <strong>of</strong> optimization results during finite<br />

element analysis prior to manufacturing <strong>of</strong> deepdrawing die. These could be traced back to Yoshida [14], Wang<br />

X. and Cao J. [15], Zhang LC, Yu TX, Wang R.[16], and Fatnassi A, Tomita Y, Shindo [17]. Colgan,<br />

M., Monaghan, J [18] – worked on the initial stages <strong>of</strong> a combined experimental and finite element analysis<br />

(FEA) <strong>of</strong> a deep drawing process. The objective <strong>of</strong> theses work was to determine the most important factors<br />

influencing a drawing process, utilizing the help <strong>of</strong> a design <strong>of</strong> experiments and statistical analysis. M. Firat[<strong>19</strong>]<br />

worked on the finite element simulations <strong>of</strong> a sheet metal forming process. His method helped in designing the<br />

forming interface for a stamping part by shifting the costly press shop try-outs to the computer aided design<br />

environment. The finite element models used in the sheet metal formability and stamping feasibility assessment<br />

studies are commonly based on the ideally rigid die-face design. The results have indicated the relative merits <strong>of</strong><br />

the die-face distortions on the formability and springback deformations.M. Abbasi, M. Ketabchi, at al [<strong>20</strong>]<br />

worked tailor welded blanks (TWBs) that are steel sheets <strong>of</strong> different characteristics welded into a single flat<br />

blank prior to pressing in order to achieve the optimal material arrangement and weight reduction for cars, and to<br />

increase process efficiency and machine flexibility. The results also showed that wrinkle waves just formed in<br />

thin segment <strong>of</strong> TWB, and wrinkling initiated by development <strong>of</strong> three wrinkle waves. Agrawal, A., Reddy, N.<br />

V., etc study the determination <strong>of</strong> optimum process parameters for wrinkle free products in deep drawing process<br />

[21].<br />

3. Methodology<br />

In figure 9 flow diagram is given that shows the steps involved in the present work. 3D data <strong>of</strong> component is<br />

transferred to FASTFORM for developing the blank. Different conditions on 3D deep drawn component for<br />

analysis with FASTFORM were applied.<br />

Figure 7 Top view <strong>of</strong> the silencer protector<br />

Figure 8 Section view <strong>of</strong> Silencer Protector<br />

539


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 9 (a) M e s h e d V i e w o f t h e c o m p o n e n t<br />

Figure 9(b) 3D Left view <strong>of</strong> CATIA model<br />

Figure 10 Front view o f t h e c o m p o n e n t<br />

3.1. Blank developments and analysis<br />

FAST FORM is the s<strong>of</strong>tware which is utilized in the development <strong>of</strong> the blank and analysis. The accuracy <strong>of</strong><br />

development blank is depends on the meshing size.<br />

4. Result and Discussion<br />

Figure 11 Blank developed on the Fast blank<br />

Figure 12 Thickness strain distribution<br />

Figure 13 Silencer protector component analysis result<br />

540


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 14 Equivalent strain<br />

Figure 15 Equivalent stress<br />

Figure 16 X- Direction forming displacements<br />

Figure 17 Forming Zone<br />

From figure 11-17<br />

• Low Strain - Minimal stretch or compression in either the major or minor directions.<br />

• Strong Wrinkle Tendency - Slight stretch in one direction and compression in the other with material<br />

thickening. Wrinkles are very likely to occur.<br />

• Wrinkle Tendency - Stretch in one direction and compression in the other with slight material<br />

thickening. Wrinkles may occur.<br />

• Loose Material - Stretch in one direction and compression in the other with slight material thinning.<br />

Surface issues like "oil canning" may result.<br />

• Semi-Tight Panel - Stretch in one direction and slight compression in the other with material thinning.<br />

• Plain Strain - Stretch in only one direction with material thinning.<br />

• Tight Panel - Stretch in two directions with highest material thinning. Stiff dent resistant panel with<br />

possible thinning problems may result.<br />

541


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5. Methods for preventing wrinkling in deep drawn parts<br />

5.1. Using a Blank Holder<br />

In most deep drawing processes, a constant blank holder pressure is applied throughout the entire drawing action.<br />

Variable blank holder pressure, however, has been employed with some success. A pneumatic or hydraulic blank<br />

holder cushion can vary the blank holder pressure linearly over the stroke <strong>of</strong> the machine. A numerically<br />

controlled (NC) die cushion can be used to provide a variable blank holder pressure over the course <strong>of</strong> drawing<br />

action. An NC die cushion can dramatically increase the allowable die cavity depth while preventing both<br />

wrinkling and cracking.<br />

5.2. Die Cavity Design<br />

Choosing a flange radius that is just large enough to prevent cracking or can minimize the potential for wrinkles.<br />

Additionally, considering minimizing the part complexity and any asymmetry can also help. Incorporating a<br />

multi-step drawing process <strong>of</strong>fers a variety <strong>of</strong> advantages in preventing wrinkling in deep-drawn parts. Designing<br />

the blank geometry to minimize excess material can reduce the potential for wrinkling. Adjusting the sheet metal<br />

grain in an asymmetrical design to minimize the compound <strong>of</strong> grain stresses and the general stresses <strong>of</strong> the deep<br />

draw process is something to take into consideration [24].<br />

5.3. Other Factors<br />

Lubricants reduce the friction between the blank and the punch and die cavity and can be liquid (wet) or films<br />

(dry). Generally, they are applied to the blank before drawing. While lubricants can facilitate the metal flow into<br />

the die cavity, consider increasing the blank holding force to account for the reduced friction. Today, computer<br />

aided design and finite element modelling are used to create part and die designs and to simulate the deep<br />

drawing process, significantly reducing the costs <strong>of</strong> tooling and labour in the design process.<br />

6. Conclusion<br />

The present work investigate and analyses facts like in spite <strong>of</strong> all precautionary measures there are macro and<br />

micro level chances <strong>of</strong> denting, cracking, and wrinkling which needs to be diminished using probabilistic<br />

approach. Component & deep drawn die have been modeled. The IGES data exported easily to the Fast Form<br />

s<strong>of</strong>tware. The component namely Silencer Protector is modeled in CATIA & the Fast Blank s<strong>of</strong>tware has been<br />

utilized for the blank development. Accordingly die and punch system has been modeled and developed too. It<br />

was also observed that the wrinkles generated on the deep drawn parts are found in the thin sheet component and<br />

that wrinkles are generated when die and punch parts not matched and aligned suitably. For enhancing the<br />

quality <strong>of</strong> wrinkle free oriented drawn component hard chrome<br />

plating on die and punch was preferred. It was observed that wrinkle is strong when analysis is performed<br />

without blank holder. Based on the observations some methods for preventing wrinkling in deep drawn parts like<br />

using a blank holder, die cavity design, lubricants, finite element modelling suggested.<br />

References<br />

[1] Klaus M. Wurster etc, Procedure for Automated Virtual Optimization <strong>of</strong> Variable Blank Holder Force<br />

Distributions for Deep- Drawing Processes with LS-Dyna and optiSLang, Weimarer Optimierungs- und<br />

Stochastiktage 8.0 – 24. /25. November <strong>20</strong>11<br />

[2] Matthias Mihm, Department <strong>of</strong> Mechanical Engineering Northwestern <strong>University</strong>, Evanston, IL 60<strong>20</strong>8,<br />

USA January <strong>19</strong>99.<br />

[3] Die Design Handbook, <strong>19</strong>55, ASTME McGraw Hill Book company Inc., New York.<br />

[4] Cao J, Boyce M. Wrinkle behavior <strong>of</strong> rectangular plates under lateral constraint. International Journal <strong>of</strong><br />

Solids and Structure <strong>19</strong>97; 34(2): {153}76.<br />

[5] Wang X, Cao J. An analytical model for predicting flange wrinkling in deep drawing. Transactions <strong>of</strong><br />

NAMRI SME <strong>19</strong>98;XXVI:{25}30.<br />

[6] Cao J, Wang X. An analytical model for plate wrinkling under tri-axial loading and its application.<br />

International Journal <strong>of</strong> Mechanical <strong>Science</strong>s <strong>19</strong>99;42(3):{617}33.<br />

[7] Campion, D.J., <strong>19</strong>76, “Tooling for deep drawing and ironing”, sheet metal industries, pp. <strong>20</strong>-23.<br />

542


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[8] Kawaka M., Olejnik L., Rosochowski A., Sunaga H. and Makinouchi A. “Simulation <strong>of</strong> Wrinkling in<br />

Sheet Metal Forming”, Journal <strong>of</strong> Materials Processing <strong>Technology</strong>, Vol. 109, pp. 283-289, <strong>20</strong>01.<br />

[9] M., M. Alkky & D.M.Woo "A Criterion for Ductile Fracture by the Growth <strong>of</strong> Holes", Journal <strong>of</strong> Applied<br />

Mechanics, Vol. 35, pp. 363-371, <strong>19</strong>80<br />

[10] Shwaki, G., <strong>19</strong>69 ,” Deep drawing with out blank holder in dies having various throat geomateries”,<br />

Bander Blecher rohre.<br />

[11] Nonmu., ,”Wrinkling defects in deep drawing operations”, Bander Blecher rohre. <strong>19</strong>61<br />

[12] Lo, Hsu and Wilson <strong>19</strong>93 “Deep drawing hydro forming theory”, <strong>19</strong>93<br />

[13] Naryanswamy & Sowerby “Deep drawing experiments on the circular blank through tratrix die”, <strong>19</strong>94<br />

[14] Yossifon S, Tirosh J. On suppression <strong>of</strong> plastic buckling in hydr<strong>of</strong>orming process. International Journal <strong>of</strong><br />

Mechanical <strong>Science</strong>s <strong>19</strong>84;26:389}402.<br />

[15] Wang X. and Cao J. “ On the Predication <strong>of</strong> Side-Wall Wrinkling in Sheet Metal Forming Processes”,<br />

International Journal <strong>of</strong> Mechanical <strong>Science</strong>s, Vol. 42, pp. 2369-2394, <strong>20</strong>00.<br />

[16] Zhang LC, Yu TX, Wang R. Investigation <strong>of</strong> sheet metal forming by bending, Part II: plastic wrinkling <strong>of</strong><br />

circular sheets pressed by cylindrical punches. International Journal <strong>of</strong> Mechanical <strong>Science</strong>s<br />

<strong>19</strong>89;{31:301}8.<br />

[17] Fatnassi A, Tomita Y, Shindo A. Non-axisymmetric buckling behavior <strong>of</strong> elastic-plastic circular tubes<br />

subjected to a nosing operation. International Journal <strong>of</strong> Mechanical <strong>Science</strong>s <strong>19</strong>85;27:{643}51.<br />

[18] Colgan, M., Monaghan, J Journal <strong>of</strong> Materials Processing <strong>Technology</strong> Volume 132, Issue 1-3, 10<br />

January <strong>20</strong>03, Pages 35-41.<br />

[<strong>19</strong>] M. Firat - Computer aided analysis and design <strong>of</strong> sheet metal forming processes, Part III, Stamping dieface<br />

design ,Journal <strong>of</strong> Materials and Design 28 (<strong>20</strong>07) 1311–13<strong>20</strong><br />

[<strong>20</strong>] M. Abbasi, M. Ketabchi, T. Labudde, U. Prahl, W. Bleck - New attempt to wrinkling behavior analysis <strong>of</strong><br />

tailor welded blanks during the deep drawing process Journal <strong>of</strong> Materials& Design, Volume<br />

40, September <strong>20</strong>12, Pages 407-414<br />

[21] Agrawal, A., Reddy, N. V., Dixit, P. M., <strong>20</strong>07, Determination <strong>of</strong> Optimum Process Parameters for<br />

Wrinkle Free Products in Deep Drawing Process, Journal <strong>of</strong> Materials Processing <strong>Technology</strong>, V<strong>19</strong>1, 51 –<br />

54.<br />

[22] Cao, J.; Wang, X.; On the Prediction <strong>of</strong> side-wall wrinkling in sheet metal forming processes; In:<br />

International Journal <strong>of</strong> Mechanical <strong>Science</strong>s 42, <strong>20</strong>00.<br />

[23] Sheng, Z.Q.; Jirathearanat, S.; Altan T. Adaptive FEM simulation for prediction <strong>of</strong> variable blank holder<br />

force in conical cup drawing, In: International Journal <strong>of</strong> MachineTools & Manufacture, Vol. 44, <strong>20</strong>03<br />

[24] www.thoumasnet.com/articles/custom-manufacturing-fabricating/wrinkling , <strong>20</strong>/08/<strong>20</strong>12<br />

543


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

MODELING OF Al-<strong>20</strong>wt% SiCp METAL MATRIX COMPOSITE USING<br />

SURFACE-ELECTRICAL DISCHARGE DIAMOND GRINDING<br />

PROCESS<br />

Shyam Sunder 1 , Vinod Yadava 2<br />

1 Associate Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, B.S.A. College <strong>of</strong> Engineering and <strong>Technology</strong>,<br />

Mathura - 281004, Uttar Pradesh, India, email: mtr_shyam@yahoo.co.in<br />

2<br />

Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, Motilal Nehru National Institute <strong>of</strong> <strong>Technology</strong>, Allahabad -<br />

211004, Uttar Pradesh, India<br />

*Corresponding Author: Associate Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, B.S.A. College <strong>of</strong><br />

Engineering and <strong>Technology</strong>, Mathura - 281004, Uttar Pradesh, India, E mail: mtr_shyam@yahoo.co.in TEL:<br />

(+91) 9456288688.<br />

Abstract<br />

This paper reports the development <strong>of</strong> an artificial neural network (ANN) model for surface-electro-discharge<br />

diamond grinding (EDDSG) process to correlate the input process parameters namely current, pulse on-time,<br />

wheel speed, and duty factor, on output process parameters namely material removal rate (MRR) and average<br />

surface roughness (R a ). Experiments were carried out on newly self developed surface grinding setup for<br />

electro-discharge diamond grinding (EDDG) process. The experimentations are planned as per L 9 orthogonal<br />

array with three levels defined for each <strong>of</strong> the factors in order to develop the data base for artificial neural<br />

network (ANN) training using error back-propagation training algorithm (EBPTA). The details <strong>of</strong><br />

experimentation, ANN training and validation are also presented in this paper. The ANN back propagation<br />

algorithm with four inputs two outputs and one hidden layer with 26 neurons have been proposed to establish the<br />

process model. The model after proper training is capable <strong>of</strong> predicting the response parameter.<br />

.<br />

Keywords: EDDG, ANN, Hybrid processes, Metal matrix composite.<br />

1. Introduction<br />

Metal matrix composites (MMCs) materials are gaining abundant acceptance in applications where high specific<br />

strength, good elevated temperature properties and good wear resistance properties are required. In traditional<br />

machining processes, grinding is one <strong>of</strong> the viable method <strong>of</strong> machining because <strong>of</strong> high dimensional accuracy<br />

and surface quality. But grinding <strong>of</strong> composite materials using conventional surface grinding process shows poor<br />

surface finish and accuracy [1]. The decreasing cutting ability <strong>of</strong> the wheel during the grinding <strong>of</strong> MMCs may be<br />

caused by the following phenomena: (1) break out and fragmentation <strong>of</strong> grains due to abrasion <strong>of</strong> reinforcement;<br />

(2) attrition wear <strong>of</strong> the active grains; (3) clogging <strong>of</strong> the wheel caused by the adherence <strong>of</strong> the chips. The last<br />

two forms <strong>of</strong> damage determine the formation <strong>of</strong> wear flats on the wheel surface. EDM is an inefficient<br />

machining process. Thermal modeling <strong>of</strong> the process [2] has indicated that the fraction <strong>of</strong> molten material which<br />

is physically not removed but re-deposited on the parent material could be as high as 80%. EDM <strong>of</strong> composite<br />

materials containing electrically non conducting phases possess few problems. The non-conducting material<br />

particles hamper the process stability and impede the material removal process. These problems can be taken<br />

care <strong>of</strong> in EDDG which is a hybrid machining process comprising <strong>of</strong> diamond grinding (DG) and electrodischarge<br />

grinding (EDG). MRR is enhanced as the abrasive grains eradicate the non-conducting material<br />

particles, with spark discharges having thermally s<strong>of</strong>tened the surrounding binding material.<br />

This hybrid machining process has been developed by combining EDM with metal bonded diamond grinding. In<br />

this process, synergetic interaction effect <strong>of</strong> electro-discharge action and abrasion action are employed to<br />

increase the machining performance <strong>of</strong> constituent processes. The electrical discharges <strong>of</strong> EDDG cause<br />

considerable decrease in grinding forces, and grinding wheel wear; and also effectively re-sharp the grinding<br />

wheel. The abrasive action in this process helps to increase material removal rate (MRR) and surface quality.<br />

EDDG can be operated in three different configurations (1) cut-<strong>of</strong>f-electro-discharge diamond grinding (C-<br />

EDDG) (2) face-electro-discharge diamond grinding (F-EDDG) (3) surface-electro-discharge diamond grinding<br />

(S-EDDG).<br />

EDDSG is used to machine flat surfaces by using periphery <strong>of</strong> the metal bonded diamond grinding wheel. Since<br />

rectangular workpiece is held in a horizontal orientation, peripheral grinding is performed by rotating the<br />

grinding wheel about a horizontal axis perpendicular to the downward motion <strong>of</strong> servo system. The relative<br />

motion <strong>of</strong> the workpart is achieved by reciprocating the workpiece. While machining the rotating wheel is fed<br />

downwards under the control <strong>of</strong> servo system. The metal bonded grinding wheel and work surface are physically<br />

separated by a gap, the magnitude <strong>of</strong> which depends on local breakdown strength <strong>of</strong> the dielectric for a particular<br />

544


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

gap voltage setting. The workpiece is thus simultaneously subjected to heating due to electrical sparks occurring<br />

between the periphery <strong>of</strong> metal bonded grinding wheel and the workpiece, and abrasion action by abrasives <strong>of</strong><br />

diamond wheel having protrusion height more than the inter-electrode gap (IEG).<br />

The objective <strong>of</strong> ANN development is to imitate human brain so as to implement the functions such as<br />

association, self-organization and generalization The ANN has the ability to approximate any functions<br />

accurately and hence is suitable for use in model development <strong>of</strong> highly non-linear processes. The ANN has the<br />

advantages <strong>of</strong> learning ability as well as generalization, thus, can capture non-linear and complex input–output<br />

relationships [3].<br />

1.1. Details about Experimental set up and Taguchi Methodology based<br />

Experimentation<br />

All the experiments have been conducted on a Smart ZNC die-sinking EDM machine. The EDM machine is <strong>of</strong><br />

Elektra, Electronica Machine Tools India make. The negatively charged metal bonded diamond grinding wheel<br />

mounted on the ram <strong>of</strong> the machine with a special attachment (Figs.1 and 2.). The workpiece was mounted such<br />

that its axis was parallel to machine table. The workpiece was completely dipped in dielectric liquid. The<br />

grinding wheel was driven with the help <strong>of</strong> variable-speed D.C. motor through a belt pulley arrangement. The<br />

speed <strong>of</strong> the motor was varied by changing supply voltage with the help <strong>of</strong> a variac. The set up consists <strong>of</strong> a<br />

metal bonded diamond grinding wheel, D.C. motor, shaft, pulley, V-belt and bearing mounted on the ram <strong>of</strong><br />

machine to rotate metal bonded diamond grinding wheel. Here, MS (40C8) material is used for the shaft and<br />

shaft diameter is calculated <strong>20</strong> mm on the basis <strong>of</strong> equivalent twisting moment, yield stress, motor torque etc.<br />

The V-belt is used to transmit power from driver to driven pulley. The V-belt has a trapezoidal cross section so<br />

that it contacts the side <strong>of</strong> the pulley. Belt <strong>of</strong> width 10 mm and thickness 5 mm is selected. Motor is<br />

indispensable part <strong>of</strong> the attachment and is located 350 110 mm horizontal flate plate.<br />

Fig. 1 Fig. 2<br />

Figure 1 Schematic diagram <strong>of</strong> surface-electro-discharge diamond grinding set-up and<br />

Figure 2 Dimension details <strong>of</strong> fabricated attachment attached to Z axis replacing original tool holder <strong>of</strong> EDM<br />

machine<br />

A motor <strong>of</strong> 1.75 hp and 4000 RPM is used for smooth power transmission and for avoiding fluctuations. Bearing<br />

is used to support movement <strong>of</strong> the shaft and permits a relative motion between the contact surfaces <strong>of</strong> the<br />

members while carrying the load. Here bearing having ISI No.30<strong>20</strong>5 is selected based on equivalent load and<br />

dynamic capacity<br />

Since the experiment was to be performed in surface grinding mode, so an automatic table feed arrangement was<br />

made. The lead screw <strong>of</strong> the machine table was driven by reversible synchronous motor. Since for automatic to<br />

and fro motion <strong>of</strong> the table motor should automatically rotate both in clockwise and anticlockwise direction as<br />

and when it is required, therefore a reversible synchronous motor control circuit was designed using relay switch,<br />

two limit switches and regulated power supply. Working <strong>of</strong> this automatic control is very simple. Suppose the<br />

motor is rotating in clockwise direction and as a result table is moving in forward direction. When a lever<br />

attached to machine table presses the limit switches, polarity <strong>of</strong> the motor will automatically changed and motor<br />

will start rotating in anticlockwise direction and therefore table will move in reverse direction. The actual<br />

photograph <strong>of</strong> S-EDG setup is shown in Fig 3a.b.The input process parameters taken are current, pulse on-time,<br />

wheel speed, and duty factor. The output parameters analyzed are MRR and R a . Experiments were performed<br />

Al-<strong>20</strong>%wt. SiC MMC. Each workpiece was machined for 90 minutes before measuring output parameters. Three<br />

545


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

repetitions have been done in each set <strong>of</strong> experiments. Amount <strong>of</strong> material removal after 90 minutes was<br />

obtained by finding weight difference before and after machining using precision electronic digital weight<br />

balance with 0.01 mg resolution.<br />

The MRR is calculated by using the following formula:<br />

where W i is initial weight <strong>of</strong> workpiece in gram (before machining); W f is final weight <strong>of</strong> workpiece in gram<br />

(after machining); t is machining time in minutes.<br />

Fig 3,a Fig 3,b<br />

Figure 3a,b EDSG set up assembled on EDM machine a) Fabricated attachment attached to Z axis replacing<br />

original tool holder <strong>of</strong> EDM machine and (b) Fabricated attachment attached to X axis for an automatic table<br />

feed arrangement<br />

A Talysurf surtronic 25 at 0.8 mm cut <strong>of</strong>f value was applied to measure the R a <strong>of</strong> each machined workpiece. The<br />

specification <strong>of</strong> grinding wheel is shown in Table I. Three levels <strong>of</strong> each process parameters have been selected<br />

without considering<br />

TABLE I Specification <strong>of</strong> grinding wheel<br />

Abrasive<br />

Diamond<br />

Grain size 80/100<br />

Grade<br />

M (Medium)<br />

Concentration 75%<br />

Bonding material Bronze<br />

Depth <strong>of</strong> abrasive 5 mm<br />

Wheel diameter 100 mm<br />

Thickness <strong>of</strong> wheel 10 mm<br />

TABLE II Machining parameters and their levels.<br />

Symbol<br />

Machining Level Level Level<br />

parameter 1 2 3<br />

S<br />

Wheel speed<br />

(RPM)<br />

800 1000 1<strong>20</strong>0<br />

C Current (A) 6 12 18<br />

T<br />

Pulse on-time<br />

(µs)<br />

100 150 <strong>20</strong>0<br />

DF Duty factor 0.492 0.638 0.817<br />

interaction effect. The numerical value <strong>of</strong> process parameters at different levels for machining Al-<strong>20</strong>%wt.SiC is<br />

shown in Table II. Pilot experiments were performed to decide the range <strong>of</strong> parameters.. The experiments were<br />

performed as per standard L 9 orthogonal array (OA) (Table 3).<br />

Table III Experimental observations for Al-<strong>20</strong>%wt.SiC using L 9 OA<br />

Exp. Factor level MRR<br />

No. S C T DF (g/min)<br />

R a (µm)<br />

1. 1 1 1 1 0.0068 6.<strong>19</strong><br />

2. 1 2 2 2 0.0074 6.18<br />

3. 1 3 3 3 0.0112 6.13<br />

4. 2 1 2 3 0.0079 6.31<br />

5. 2 2 3 1 0.0107 7.33<br />

6. 2 3 1 2 0.0098 6.17<br />

7. 3 1 3 2 0.0086 6.68<br />

8. 3 2 2 3 0.0092 6.58<br />

9. 3 3 1 1 0.0114 6.77<br />

546


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 4 Multi-layer feed forward artificial neural<br />

network<br />

2. Artificial Neural NETWORK MODELING<br />

The multi-layer feed forward ANN <strong>of</strong> Fig.4 consists three parts: input layer, the hidden layer, and the output<br />

layer. The neurons between the layers are connected by the links having synaptic weights. The error backpropagation<br />

training algorithm is based on weight updates so as to minimize the sum <strong>of</strong> squared error for -<br />

number <strong>of</strong> output neurons, given as:<br />

Where<br />

= desired output for the th pattern. The weights <strong>of</strong> the links are updated as<br />

where is the learning step, is the learning rate and is the momentum constant<br />

In Eq. (3) is the error term, which is given as follows:<br />

where is the number <strong>of</strong> neurons in the hidden layer.<br />

)<br />

The training process is initialized by assigning small random weight values to all the links. The input-output<br />

patterns are presented one by one and updating the weights each time. The mean square error (MSE) at the end<br />

<strong>of</strong> each epoch due to all patterns is computed as<br />

Where = number <strong>of</strong> training patterns.<br />

The training process will be terminated when the specified goal <strong>of</strong> MSE or maximum number <strong>of</strong> epochs is<br />

achieved. Before training and validation the total input and output data were normalized for increase accuracy<br />

and speed <strong>of</strong> the network.<br />

3. Artificial neural network training<br />

The training <strong>of</strong> ANN for 9 input-output patterns has been carried out using programming in neural network (NN)<br />

toolbox available in MATLAB s<strong>of</strong>tware. First neural network architecture has been decided. The general<br />

network is supposed to be 4–n–2, which implies four neurons in the input layer, n neurons in the hidden layer<br />

and two neurons in the output layer. In the present study we have 4 neurons in the input layer (corresponding to 4<br />

process inputs, current, wheel speed, pulse on-time, and duty factor), 2 neurons in the output layer<br />

(corresponding to 2 outputs MRR and R a and one hidden layer <strong>of</strong> 23 neurons was employed. The following<br />

learning factors are used to successfully train the network.<br />

• Learning rate ( ) = 0.05; momentum factor (α) = 0.85;<br />

• Maximum number <strong>of</strong> epochs = 5000; tolerance for MSE = 0.00001.<br />

The ANN training simulation was carried out using the variable learning rate training procedure “traingdx” <strong>of</strong><br />

the MATLAB NN toolbox. This procedure improves the performance <strong>of</strong> EBPTA by allowing the learning rate to<br />

change based on the complexity <strong>of</strong> the local error surface. Fig.5 shows the variation <strong>of</strong> MSE during the training.<br />

In the present study, the desired MSE achieved after 1466 epochs.<br />

547


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4. Artificial neural network testing<br />

The trained ANN was initially tested by presenting 9 input patterns which were employed for the training<br />

purpose for each input pattern, the predicted value <strong>of</strong> MRR and R a are compared with the respective measured<br />

average values and the absolute percentage error is computed which is given as:<br />

Table IV<br />

Machining conditions for testing patterns <strong>of</strong> ANN<br />

MSE<br />

10 -1<br />

10 -2<br />

10 -3<br />

Performance is 9.97179e-006, Goal is 1e-005<br />

Test no.<br />

Wheel<br />

speed<br />

(RPM)<br />

Current<br />

(A)<br />

Pulse<br />

ontime<br />

(µs)<br />

Duty<br />

factor<br />

1. 700 7 100 0.578<br />

2. 1<strong>20</strong>0 9 <strong>20</strong>0 0.697<br />

10 0 Epochs<br />

10 -4<br />

10 -5<br />

10 -6<br />

0 <strong>20</strong>0 400 600 800 1000 1<strong>20</strong>0 1400<br />

Figure 5 The variation <strong>of</strong> mean squared error (MSE) with number <strong>of</strong> epochs.<br />

where is the measured value (average) and is the ANN predicted value <strong>of</strong> the response for th trial.<br />

It was found that the predicted and experimental values were very quite close to each other Regression analysis<br />

between the network response and the corresponding targets has been performed for measuring the performance<br />

<strong>of</strong> a trained network. This was carried out using the postreg in the NN toolbox. The graphical outputs <strong>of</strong> postreg<br />

are presented in Fig.6 for the training data sets. The correlation coefficient (R value) between the outputs and<br />

targets is a measure <strong>of</strong> how well the variation in the output is explained by the targets. If R value is 1 then it<br />

indicates perfect correlation between targets (T) and predicted outputs (A). In the present case the R value is 1<br />

and 0.999 for MRR and R a , indicating a very good relation.<br />

For the validation purpose, 2 new trials were tested, which do not belong to training data set. Table IV gives the<br />

chosen machining conditions used for the confirmation tests. For these validation data set, the MRR and R a<br />

values are predicted using the ANN model and then compared with the measured values. It was also found that<br />

the maximum absolute percentage error was around 28.11 and 16.77 for MRR and R a respectively. The graphical<br />

output <strong>of</strong> postreg is presented in Fig.7. for the validation datasets and R values are 0.979 and 1 for the outputs<br />

MRR and R a respectively.<br />

Best Linear Fit: A = (0.995) T + (4.49e-005)<br />

7.5<br />

Best Linear Fit: A = (1.01) T + (-0.0396)<br />

Pred MRR (A)<br />

11<br />

10.5<br />

10<br />

9.5<br />

9<br />

8.5<br />

R = 1<br />

11.5 x 10-3 Expt MRR (T)<br />

Data Points<br />

Best Linear Fit<br />

A = T<br />

Pred Ra (A)<br />

7<br />

R = 0.998<br />

Data Points<br />

Best Linear Fit<br />

A = T<br />

8<br />

6.5<br />

7.5<br />

7<br />

6.5<br />

6 7 8 9 10 11 12<br />

x 10 -3<br />

6<br />

6 6.5 7 7.5<br />

Expt Ra (T)<br />

Figure 6 Correlation <strong>of</strong> the training patterns for MRR and R a<br />

548


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5.8<br />

Best Linear Fit: A = (1.2) T + (-0.386)<br />

Best Linear Fit: A = (0.296) T + (0.00579)<br />

5.6<br />

R = .979<br />

R = 1<br />

Pred Ra (A)<br />

5.4<br />

5.2<br />

5<br />

4.8<br />

4.6<br />

Data Points<br />

Best Linear Fit<br />

A = T<br />

Pred MRR (A)<br />

9<br />

8.5<br />

8<br />

9.5 x 10-3 Expt MRR (T)<br />

Data Points<br />

Best Linear Fit<br />

A = T<br />

4.4<br />

7.5<br />

4.2<br />

7<br />

4<br />

3.8<br />

3.8 4 4.2 4.4 4.6 4.8 5<br />

Expt Ra (T)<br />

6.5<br />

6.5 7 7.5 8 8.5 9 9.5<br />

x 10 -3<br />

Figure 7 Correlation <strong>of</strong> the testing patterns for MRR and R a<br />

5. Conclusion<br />

The training and testing data set was taken from experiments on self developed setup on EDM, based on L 9 OA.<br />

The ANN back propagation algorithm with four inputs, two outputs, and one hidden layer with 23 neurons has<br />

been employed to establish the process model. The model after proper training is capable <strong>of</strong> predicting the<br />

response parameter. The number <strong>of</strong> hidden layer neurons and the learning factors employed are found to be<br />

suitable for the present investigation. There exist highly non-linear relationships between MRR, R a and the<br />

machining conditions. This justifies the use <strong>of</strong> ANN to develop the model.<br />

6. References<br />

1.Aguair P. R., Dotto F. R. L. and Bianch E. C. (<strong>20</strong>05), “Study <strong>of</strong> Thresholds to Burning in Surface Grinding<br />

Process,” Journal <strong>of</strong> the Brazillian Society <strong>of</strong> Mechanical <strong>Science</strong>s and Engineering, Vol. 27(2), pp 150-156.<br />

2.Erden A., and Kaftanoglu B. (<strong>19</strong>81), “Heat Transfer Modeling <strong>of</strong> Electric Discharge Machining, in: Proc. 21st<br />

Int. Mach. Tool Des. Research Conf., London.<br />

3.Schalk<strong>of</strong>f, R.B. (<strong>19</strong>97) “Artificial Neural Networks” McGraw-Hill International Ed.<br />

549


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

ROLE OF IT IN MANUFACTURING SECTOR<br />

Amandeep Singh Wadhwa 1<br />

1 Assistant Pr<strong>of</strong>essor, UIET, PU, Chandigarh.<br />

Abstract<br />

Today's manufacturing enterprise, whether it produces consumer goods or weapons systems, must <strong>of</strong>ten juggle a<br />

range <strong>of</strong> conflicting demands. Smaller lot sizes, increased product flexibility, higher product quality, decreased<br />

delivery time, and smaller pr<strong>of</strong>it margins are typical <strong>of</strong> the ambitious goals in many such organizations. Through<br />

it all, the enterprise must consistently aim for the five R's-- produce the right product, with the right quality, in<br />

the right quantity, at the right price, and at the right time-- and it must do more than satisfy its customers; it must<br />

delight them. Correct and timely information is key to meeting these goals, and information technology--<br />

database management systems, enterprise resource planning systems, and simulation and computer-aided design<br />

tools-- has become indispensable to most manufacturing enterprises. Although its role in manufacturing has<br />

been more to support processes, IT is evolving to become a catalyst for process and product change.<br />

1. Literature Review<br />

The automation <strong>of</strong> machine tool control began in the <strong>19</strong>th century with cams that "played" a machine tool in the<br />

way that cams had long been playing musical boxes or operating elaborate cuckoo clocks. Thomas Blanchard<br />

built his gun-stock-copying lathes (18<strong>20</strong>s–30s), and the work <strong>of</strong> people such as Christopher Miner Spencer<br />

developed the turret lathe into the screw machine (1870s). Cam-based automation had already reached a highly<br />

advanced state by World War I (<strong>19</strong>10s). The key development in this area was the introduction <strong>of</strong> the<br />

servomechanism, which produced highly accurate measurement information. Attaching two servos together<br />

produced a selsyn, where a remote servo's motions were accurately matched by another. Using a variety <strong>of</strong><br />

mechanical or electrical systems, the output <strong>of</strong> the selsyns could be read to ensure proper movement had<br />

occurred (in other words, forming a closed-loop control system). The birth <strong>of</strong> NC is generally credited to John T.<br />

Parsons, a machinist and salesman at his father's machining company, Parsons Corp.in <strong>19</strong>42. Ross and Pople<br />

outlined a language for machine control that was based on points and lines, developing this over several years<br />

into the APT programming language. In <strong>19</strong>57 the Aircraft Industries Association (AIA) and Air Material<br />

Command at Wright-Patterson Air Force Base joined with MIT to standardize this work and produce a fully<br />

computer-controlled NC system(CNC). On 25 February <strong>19</strong>59 the combined team held a press conference<br />

showing the results, including a 3D machined aluminum ash tray that was handed out in the press kit. While the<br />

Servomechanisms Lab was in the process <strong>of</strong> developing their first mill, in <strong>19</strong>53, MIT's Mechanical Engineering<br />

Department dropped the requirement that undergraduates take courses in drawing. The instructors formerly<br />

teaching these programs were merged into the Design Division, where an informal discussion <strong>of</strong> computerized<br />

design started. Meanwhile the Electronic Systems Laboratory, the newly rechristened Servomechanisms<br />

Laboratory, had been discussing whether or not design would ever start with paper diagrams in the future.<br />

The proliferation <strong>of</strong> CNC led to the need for new CNC standards that were not encumbered by licensing or<br />

particular design concepts, like APT. A number <strong>of</strong> different "standards" proliferated for a time, <strong>of</strong>ten based<br />

around vector graphics markup languages supported by plotters. One such standard has since become very<br />

common, the "G-code" that was originally used on Gerber Scientific plotters and then adapted for CNC use. The<br />

file format became so widely used that it has been embodied in an EIA standard. In turn, while G-code is the<br />

predominant language used by CNC machines today, there is a push to supplant it with STEP-NC, a system that<br />

was deliberately designed for CNC, rather than grown from an existing plotter standard.While G-code is the<br />

most common method <strong>of</strong> programming, some machine-tool/control manufacturers also have invented their own<br />

proprietary "conversational" methods <strong>of</strong> programming, trying to make it easier to program simple parts and make<br />

set-up and modifications at the machine easier (such as Mazak's Mazatrol and Hurco).<br />

Since about <strong>20</strong>06, the idea has been suggested and pursued to foster the convergence with CNC and DNC <strong>of</strong><br />

several trends elsewhere in the world <strong>of</strong> information technology that have not yet much affected CNC and DNC.<br />

One <strong>of</strong> these trends is the combination <strong>of</strong> greater data collection (more sensors), greater and more automated data<br />

exchange (via building new, open industry-standard XML schemas), and data mining to yield a new level <strong>of</strong><br />

business intelligence and workflow automation in manufacturing<br />

550


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. Introduction<br />

Computer based control systems can be combined with manufacturing technology, such as robots, machine tools,<br />

automated guided vehicles, to improve manufacturing operations. In this role, the computer can assist integrating<br />

these technologies into a lean and efficient factory capable <strong>of</strong> competing in world markets. Organizations such as<br />

Allen-Bradley, black and Decker, and Boeing have used information technology and factory automation to<br />

improve manufacturing operations. This combination <strong>of</strong> information technology and factory automation is <strong>of</strong>ten<br />

called computer- integrated manufacturing.<br />

Numerical control (NC) refers to the automation <strong>of</strong> machine tools that are operated by abstractly programmed<br />

commands encoded on a storage medium, as opposed to manually controlled via handwheels or levers, or<br />

mechanically automated via cams alone. The first NC machines were built in the <strong>19</strong>40s and <strong>19</strong>50s, based on<br />

existing tools that were modified with motors that moved the controls to follow points fed into the system on<br />

punched tape. These early servomechanisms were rapidly augmented with analog and digital computers, creating<br />

the modern computer numerical control (CNC) machine tools that have revolutionized the machining<br />

processes<br />

Figure 1 Basic components <strong>of</strong> NC system<br />

Fig.2 Layout <strong>of</strong> DNC machine<br />

Computer- integrated manufacturing (CIM) blends development in manufacturing with information technology<br />

to achieve competitive advantage. When properly organized, CIM <strong>of</strong>fers the opportunity to automate design,<br />

manufacturing and production planning and control. Each component is described briefly here:<br />

Engineering design through Computer aided design (CAD) allows an organization to make high quality<br />

specialized designs rapidly. The design can be tailored to meet individual customer needs.<br />

Flexibility manufacturing systems (FMSs) can quickly produce a variety <strong>of</strong> high quality product efficiently. An<br />

(FMSs) also allow an organization to produce high specialized designs.<br />

551


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Computer based production planning and control systems allow an organization to cope with the complexity <strong>of</strong><br />

managing facilities that produce a wide variety <strong>of</strong> specialized products without losing efficiency.<br />

When properly combined, these components can yield synergetic results. An organization can have more flexible<br />

and integrated operations, be better equipped to manage complex operations, and exercise better controls than<br />

can a company that operates without CIM. To merge these components into one coordinated whole, staff from<br />

the information systems functions needs to integrate engineering, manufacturing, and business databases into a<br />

cross functional decision support system. Once accomplished, the flexibility to respond to customer demands<br />

with low cost, high quality specialized products becomes a powerful competitive advantage.<br />

2. Effect <strong>of</strong> IT on Supply Chain Management in manufacturing industries<br />

A supply chain is essentially a set <strong>of</strong> three or more companies directly linked by one or more <strong>of</strong> the upstream or<br />

downstream flows <strong>of</strong> products, services, finances and information form a source to customer. Supply chain<br />

management may be defined as the management <strong>of</strong> the different flows in a supply chain with a view to<br />

improving the long term performance <strong>of</strong> the individual firms and the supply chain as a whole. As is evident from<br />

the definition itself, the flow <strong>of</strong> information is vital to the functioning <strong>of</strong> a supply chain. Without information<br />

relayed at the right time to the right place, the whole supply chain would come to a standstill. Hence information<br />

technology, which enables information flow within a firm, between firms, and across the supply chain, goes a<br />

long way towards ensuring effective and efficient supply chain management. Information technology, in short,<br />

forms the backbone <strong>of</strong> most corporate supply chains.<br />

Information technology facilitates the development <strong>of</strong> Information systems designed to provide speedy and<br />

accurate information. The roadmap for a firm wishing to build a supply chain information system would be to<br />

develop an intra-firm information system,expand the capabilities <strong>of</strong> the same by connecting to suppliers and/or<br />

customers, thus creating an inter-firm system, and then, connect to the supplier’s supplier and customer’s<br />

customer, thus resulting in a supply chain information system.<br />

3. Design optimization algorithms in manufacturing industry<br />

Genetic Algorithm are set <strong>of</strong> global search and optimization methods that is fast gaining popularity in solving<br />

complex engineering optimization problems with large search space. G.A is method <strong>of</strong> moving from one<br />

population to a new population <strong>of</strong> chromosomes by using natural selection together with the genetic search<br />

process <strong>of</strong> cross over and mutation GA works on principle <strong>of</strong> survival <strong>of</strong> fittest and the central theme <strong>of</strong> research<br />

on genetic algorithm has been robustness, the balance between efficiency and efficacy necessary for the survival<br />

in many different environments. Tools <strong>of</strong> genetic Algorithm:- Genetic algorithm (GA) operates with the help <strong>of</strong><br />

three operators namely:-<br />

1. Reproduction 2. Mutation 3. Cross Over<br />

3.1. Reproduction<br />

This is the first operator which is applied to the existing population to create new and better <strong>of</strong>fsprings. The<br />

<strong>of</strong>fsprings whose probability <strong>of</strong> selection is less is rejected and the <strong>of</strong>fsprings whose probability <strong>of</strong> selection is<br />

high are selected and carried forward. The probability <strong>of</strong> selection <strong>of</strong> particular string is proportional to its own<br />

fitness.<br />

3.2. Mutation<br />

Mutation is aimed to maintain diversity is population and it creates a new solution in neighborhood <strong>of</strong> current<br />

solution by introduction small change in some aspect <strong>of</strong> current solution, for example in a binary coded digit one<br />

bit may be altered from 0 to 1 or from 1 to and thus creating new solution<br />

Bit Mutated<br />

New Bit<br />

110110 110010<br />

3.3. Crossover<br />

In crossover process the crossing site is randomly chosen along the string length and all the bits to the right side<br />

<strong>of</strong> this crossing site are exchanged between two parent strings as;<br />

0 0 0 |0 0 0 0 0 1 1<br />

1 1 1 1 1 1 1 1 0 0<br />

Application <strong>of</strong> GA in optimization: Let us apply simple genetic algorithm to a particular problem<br />

552


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

<strong>of</strong> optimization step by step. Consider the problem <strong>of</strong> maximizing the function f(X) = X 2 where X is permitted to<br />

vary between 0 and 31. The initial population is randomly generated in terms <strong>of</strong> binary coded strings which are<br />

then converted into equivalent decimal value. The reproduction operator then operates on randomly selected<br />

population and depending upon the probability <strong>of</strong> selection the mating pool is formed. In the mating pool so<br />

formed the good strings are selected and bad strings are rejected. After reproduction theother two operators i.e.<br />

mutation and crossover are applied to the existing population to form new population which have better<br />

<strong>of</strong>fspring. This process keeps on going till optimized result is achieved. Table 1. show the working procedure <strong>of</strong><br />

genetic algorithm to optimize the function f(X) = X 2. whereX varies from 0 to 31.<br />

Table 1. Tabular representation <strong>of</strong> the fitness <strong>of</strong> the given function.<br />

4. Impact <strong>of</strong> IT on Manufacturing<br />

Manufacturing is understood as the process <strong>of</strong> producing the product capabilities according to customer needs,<br />

covering all the steps in the value adding chain. The first impact describes changes in society and industry with a<br />

focus on employment and industrial relations. The second impact is on dynamics <strong>of</strong> technological and business<br />

processes by usage <strong>of</strong> simulation as an interdisciplinary acceleration tool. The third impact deals with both<br />

electronics and s<strong>of</strong>tware as value adding core elements <strong>of</strong> products. A fourth impact may be identified on classic<br />

products, where sensor technologies speed up production processes with a significant quality enhancement.<br />

Finally, the impact <strong>of</strong> information technology on the human user itself is addressed. Cultural change is shown to<br />

be necessary and inevitable to tackle the future economical risks <strong>of</strong> the information age.<br />

5. Conclusion<br />

IT provides features such as bar codes, which can improve quality control. Digital displays and electronic<br />

controls increase precision and speed during the manufacturing process. IT is extensively used in the<br />

manufacturing industry to reduce the cost <strong>of</strong> product design, supply chain management and the manufacturing<br />

process itself. IT can reduce the amount <strong>of</strong> labor required to produce a product, improve its quality and allow<br />

manufacturers to respond faster and more effectively to their customers.Further with the advent <strong>of</strong> IT in field <strong>of</strong><br />

manufacturing design optimization algorithms are developed to manufacture various components <strong>of</strong> the<br />

assembly on the basis <strong>of</strong> the dimensions that are obtained from the optimization algorithms like GA. The<br />

components that are manufactured as per optimization algorithms have more life,less cost and better<br />

performance. In brief we can tabulate the advantages <strong>of</strong> IT in manufacturing sector as:-<br />

1) Improved Engineering Productivity<br />

2) Shorter Lead times<br />

3) Improved accuracy <strong>of</strong> design<br />

4) Better and standardized designs<br />

553


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5) Saves materials and machining times by optimization algorithms<br />

6) Provides better functional analysis to reduce prototype testing<br />

7) FMS enables manufacturers to machine a wide variety <strong>of</strong> work pieces on few machines with low staffing<br />

levels and high degree <strong>of</strong> reliability.<br />

8) Lowers work in process inventories.<br />

9) Reduce scrap rate<br />

10) Reduction <strong>of</strong> floor space<br />

6. References<br />

[1]Banzhaf, Wolfgang; Nordin, Peter; Keller, Robert; Francone, Frank (<strong>19</strong>98) Genetic Programming – An<br />

Introduction, Morgan Kaufmann, San Francisco, CA.<br />

[2]Bies, Robert R; Muldoon, Matthew F; Pollock, Bruce G; Manuck, Steven; Smith, Gwenn and Sale, Mark<br />

E (<strong>20</strong>06). "A Genetic Algorithm-Based, Hybrid Machine Learning Approach to Model Selection". Journal <strong>of</strong><br />

Pharmacokinetics and Pharmacodynamics (Netherlands: Springer): <strong>19</strong>6–221.<br />

[3]Goldberg, David E (<strong>19</strong>89), Genetic Algorithms in Search, Optimization and Machine Learning, Kluwer<br />

Academic Publishers, Boston, MA.<br />

[4]Goldberg, David E (<strong>20</strong>02), The Design <strong>of</strong> Innovation: Lessons from and for Competent Genetic<br />

Algorithms, Addison-Wesley, Reading, MA.<br />

[5]Reintjes, J. Francis (<strong>19</strong>91), Numerical Control: Making a New <strong>Technology</strong>, Oxford <strong>University</strong> Press.<br />

[6]Siegel, Arnold. "Automatic Programming <strong>of</strong> Numerically Controlled Machine Tools", Control<br />

Engineering, Volume 3 Issue 10 (October <strong>19</strong>56), pp. 65–70.<br />

[7]Sorenti, P, "Efficient Robotic Welding in Shipyards – Virtual Reality Simulation Holds the Key",<br />

Industrial Robot, <strong>19</strong>97, 24(4), 278-281<br />

[8] Sivayoganathan K,et al., "Integration <strong>of</strong> CAD/CAM and <strong>of</strong>f-line Programming Systems", proceedings <strong>of</strong><br />

the 10th National Conference on Manufacturing Research, <strong>19</strong>94.<br />

[9]Thrun, Sebastian. "Robotic Mapping: A Survey." CMU-CS-02-111, February <strong>20</strong>02<br />

[10]R. Grabowski, L. Navarro-Serment, and P. Khosla. "An Army <strong>of</strong> Small Robots." SciAm Online May<br />

<strong>20</strong>04<br />

[11]Moravec, Hans. "Robots, After All." Communications <strong>of</strong> the ACM. October <strong>20</strong>03. Vol. 46, No. 10.<br />

[12]Neural Networks, vol. 13, no. 4-5, pp. 431-443, June <strong>20</strong>00.<br />

[13]“Fitness functions in evolutionary robotics: A survey and analysis,” Robotics and Autonomous<br />

Systems, vol. 57, no. 4, pp. 345-370, Apr. <strong>20</strong>09.<br />

[14]zykov-gecco-<strong>20</strong>04 V. Zykov, J. Bongard, H. Lipson, “Evolving dynamic gaits on a physical robot,” <strong>20</strong>04<br />

Genetic and Evolutionary Computation Conference (GECCO), Seattle, WA., <strong>20</strong>04.<br />

554


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

OPTIMIZING SURFACE ROUGHNESS OF HIGH DIE STEEL H13 IN<br />

CNC MILLING USING TAGUCHI TECHNIQUE:<br />

Mandeep Chahal 1 , Vikram Singh 2 , Rohit Garg 3 , Sudhir Kumar 4<br />

1<br />

Asstt. Pr<strong>of</strong>essor, Deptt. <strong>of</strong> Mech. Engg., HCTM, Kaithal (Haryana), India. email: mandeepchahal17@yahoo.in<br />

2 Associate Pr<strong>of</strong>essor, Deptt. <strong>of</strong> Mech. Engg., <strong>YMCA</strong>UST, Faridabad, India. email: singhvikram77@gmail.com<br />

3 Principal, Indus Institute <strong>of</strong> Engineering& <strong>Technology</strong>, Jind (Haryana), India email: rohit_garg123@yahoo.com<br />

4 Pr<strong>of</strong>essor, Deptt. <strong>of</strong> Mech. Engg., NIET, Greater Noida(U.P), India email: s_k_tomar02@yahoo.com<br />

Abstract<br />

This experiment gives the effect <strong>of</strong> different machining parameters (cutting speed, feed, and depth <strong>of</strong> cut) on<br />

Surface Roughness in end milling. Taguchi technique is being used for the various calculations. The study was<br />

conducted in machining operation for hardened die steel H-13. The processing <strong>of</strong> the job was done by solid<br />

carbide four flute end-mill tool under finishing conditions. L-9 standard orthogonal array is used for calculation<br />

<strong>of</strong> no. <strong>of</strong> variables and no. <strong>of</strong> levels. Signal to Noise Ratio and ANOVA techniques are used to draw the graphs<br />

and come to the results.<br />

Keywords: CNC Milling, Surface Roughness (SR), ANOVA, S/N Ratio<br />

1. Introduction & Literature Review<br />

With the more precise demands <strong>of</strong> modern engineering products, the control <strong>of</strong> surface texture together with<br />

dimensional accuracy has become more important. This experimental investigation outlines the Taguchi<br />

optimization methodology, which is applied to optimize machining parameters in end milling operation. The<br />

experiment is conducted on hot die steel H 13. The processing <strong>of</strong> the job is done by solid carbide four flute endmill<br />

tools under finishing conditions. The machining parameters evaluated are cutting speed, feed rate and depth<br />

<strong>of</strong> cut. The experiments are conducted by using L-9 orthogonal array as suggested by Taguchi. Signal-to-Noise<br />

(S/N) ratio and Analysis <strong>of</strong> Variance (ANOVA) is employed to analyze the effect <strong>of</strong> milling parameters on<br />

surface roughness.Milling is a process <strong>of</strong> producing flat and complex shapes with the use <strong>of</strong> multi-tooth cutting<br />

tool, which is called a milling cutter and the cutting edges are called teeth.<br />

2. Experimental Methodology<br />

Dr. Genichi Taguchi gives three philosophies to improve the product quality.<br />

1. Quality should be designed into a product, not inspected into it. Quality is designed into a process through<br />

system design, parameter design, and tolerance design. Parameter design, which will be the focus <strong>of</strong> this article,<br />

is performed by determining what process parameters most affect the product and then designing them to give a<br />

specified target quality <strong>of</strong> product. Quality "inspected into" a product means that the product is produced at<br />

random quality levels and those too far from the mean are simply thrown out.<br />

2. Quality is best achieved by minimizing the deviation from a target. The product should be designed so that it<br />

is immune to uncontrollable environmental factors. In other words, the signal (product quality) to noise<br />

(uncontrollable factors) ratio should be high.<br />

3. The cost <strong>of</strong> quality should be measured as a function <strong>of</strong> deviation from the standard and the losses should be<br />

measured system wide. This is the concept <strong>of</strong> the loss function, or the overall loss incurred upon the customer<br />

and society from a product <strong>of</strong> poor quality. Because the producer is also a member <strong>of</strong> society and because<br />

customer dissatisfaction will discourage future patronage, this cost to customer and society will come back to the<br />

producer.<br />

3. Experimental Setup and Process Parameters Selected<br />

Work piece material<br />

Hot die steel H13 in the plate form <strong>of</strong> size 280x<strong>20</strong>0x32 mm 3 have been used to carry out experiments. H13 die<br />

steel have been chosen because <strong>of</strong> high hardness, excellent wear resistance, hot toughness and good thermal<br />

shock resistance properties. The chemical composition <strong>of</strong> H13 die steel is given in table-1.<br />

555


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table No. 1 Chemical composition <strong>of</strong> hot die steel H13<br />

Element<br />

Weight<br />

percent<br />

Element<br />

Weight<br />

percent<br />

Carbon 0.4 Chromium 5.25<br />

Manganese 0.4 Molybdenum 1.35<br />

Silicon 1.0 Vanadium !.0<br />

Selection <strong>of</strong> Tool for experiment<br />

A four flute solid carbide type flat end mill tool <strong>of</strong> 10 mm diameter is used in this experiment with dry cutting<br />

condition. Haas machining is used for machining. 9 cute are made on the work piece on both sides so that surface<br />

roughness at three points can be evaluated with the help <strong>of</strong> Mitutoyo Surftest instrument.<br />

Array Selector<br />

Table No.2 Array selector<br />

Figure. 1 Experimental set up<br />

556


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Three parameters are selected and three levels <strong>of</strong> each parameter is taken so that L9 orthogonal array can be<br />

used. Surface Roughness is measured at three locations with the help <strong>of</strong> Mitutoyo Surftest and S/N ratio and<br />

mean values are calculated by use <strong>of</strong> Minitab 15 s<strong>of</strong>tware.<br />

Table No. 3 Orthogonal array, L9 for experiment<br />

Parameters<br />

Experiment no.<br />

1<br />

(A)<br />

Spindle speed<br />

(RPM)<br />

2<br />

(B)<br />

Feed Rate<br />

(mm/rev)<br />

3<br />

(C)<br />

Depth <strong>of</strong> cut<br />

(mm)<br />

1 <strong>20</strong>00 0.09 0.2<br />

2 <strong>20</strong>00 0.13 0.3<br />

3 <strong>20</strong>00 0.15 0.4<br />

4 2500 0.09 0.3<br />

5 2500 0.13 0.4<br />

6 2500 0.15 0.2<br />

7 3000 0.09 0.4<br />

8 3000 0.13 0.2<br />

9 3000 0.15 0.3<br />

Table No.4 Roughness at Various Conditions<br />

Ex. No.<br />

(A)<br />

Spindle<br />

Speed<br />

(B)<br />

Feed<br />

Rate<br />

(C)<br />

Depth <strong>of</strong><br />

cut<br />

Surface roughness (Ra) at<br />

Different location<br />

Response Response<br />

Response<br />

Signal to<br />

noise ratio<br />

(dbi)<br />

Mean<br />

response<br />

value<br />

1 2<br />

3<br />

1 <strong>20</strong>00 0.09 0.2 0.547 0.548 0.558 -8.8144 0.75<br />

2 <strong>20</strong>00 0.13 0.3 0.436 0.437 0.446 -10.2569 0.59<br />

3 <strong>20</strong>00 0.15 0.4 0.647 0.656 0.756 -11.8813 1.26<br />

4 2500 0.09 0.3 0 .648 0.666 0.856 -5.3317 1.84<br />

5 2500 0.13 0.4 0.736 0.746 0.778 -7.9496 1.61<br />

6 2500 0.15 0.2 0.237 0.263 0.273 -11.3407 0.70<br />

7 3000 0.09 0.4 0.286 0.299 0.265 -4.2393 0.96<br />

8 3000 0.13 0.2 0.365 0.375 0.375 -8.8571 0.77<br />

9 3000 0.15 0.3 1.009 1.006 1.009 -9.8077 1.04<br />

557


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 2 Main effects plot for SN ratios (surface roughness)<br />

Figure 3 Main effect plots for means (surface roughness)<br />

4. Result<br />

Effect <strong>of</strong> cutting speed on SR<br />

The higher the cutting speed less will be the surface roughness. Surface roughness is minimum at the<br />

higher level <strong>of</strong> cutting speed. The higher cutting speed causes the low burr size thus the surface finish increases.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Effect <strong>of</strong> feed rate on SR<br />

With the decrease <strong>of</strong> feed rate, surface roughness also decreases. It is observed that the minimum<br />

surface roughness value obtained at the first level (.08 m/tooth). Higher the feed rate, higher will be the tool wear<br />

thus increases the value <strong>of</strong> surface roughness.<br />

Effect <strong>of</strong> depth <strong>of</strong> cut on SR:<br />

It is observed that the increased value <strong>of</strong> depth <strong>of</strong> cut will decrease the value <strong>of</strong> surface roughness. The<br />

level considered in this investigation is finishing range. At the lower depth <strong>of</strong> cut the tool deflection high and it<br />

will decreases with increase <strong>of</strong> depth <strong>of</strong> cut in.<br />

5. Conclusion<br />

1. The feed rate and cutting speed are by far the most dominant factor then the depth <strong>of</strong> cut for surface<br />

finish.<br />

2. In end milling, increase in cutting speed, decrease in feed rate and increase in depth <strong>of</strong> cut will<br />

decreases the surface roughness within specified test range.<br />

3. Taguchi’s robust design method is suitable to analyze the metal cutting problem as described in the<br />

present work.<br />

4. Low cutting speed should be used for long cutter life.<br />

5. High cutting speed and low feeds give best surface finishes; depth <strong>of</strong> cut should be low but not so low<br />

that it led to the vibration <strong>of</strong> tool.<br />

6. References<br />

1. Kromanis, A.; Krizbergs, (<strong>20</strong>08) “3d Surface Roughness Prediction Technique In End Milling Using<br />

Regression Analysis” , Tallinn, Estonia Industrial Engineering.<br />

2. Tao Ye, Cai-Hua Xiong, (<strong>20</strong>08)” Geometric Parameter Optimization In Multi-Axis Machining”, Computer-<br />

Aided Design 40 (<strong>20</strong>08) 879–890.<br />

3. Hari Singh And Pradeep Kumar (<strong>20</strong>06) “Optimizing Feed Force For Turned Parts Through The Taguchi<br />

Technique”, S¯Adhan¯A Vol. 31, Part 6, Pp. 671–681.<br />

4. S. Khachan, F. Ismail, (<strong>20</strong>08)” Machining Chatter Simulation In Multi-Axis Milling Using Graphical<br />

Method”,International Journal Of Machine Tools And Manufacture<br />

559


1<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

A REVIEW ON PROCESS PARAMETERS OPTIMIZATION<br />

TECHNIQUES FOR ADVANCED MACHINING PROCESSES<br />

S. Kumar<br />

Department <strong>of</strong> Mechanical & Automation Engineering, <strong>YMCA</strong>UST, Faridabad, Haryana, India<br />

email: sanjaykpec@rediffmail.com<br />

Abstract<br />

In this paper an attempt is made to review the literature on Optimization <strong>of</strong> process parameters <strong>of</strong> advanced<br />

machining processes. Generally, unconventional or advanced machining processes (AMPs) are used only when<br />

no other traditional machining process can meet the necessary requirements efficiently and economically<br />

because use <strong>of</strong> most <strong>of</strong> AMPs incurs relatively higher initial investment, maintenance, operating, and tooling<br />

costs. Therefore, optimum choice <strong>of</strong> the process parameters is essential for the economic, efficient, and effective<br />

utilization <strong>of</strong> these processes. Process parameters <strong>of</strong> AMPs are generally selected either based on the<br />

experience, and expertise <strong>of</strong> the operator or from the propriety machining handbooks. In most <strong>of</strong> the cases,<br />

selected parameters are conservative and far from the optimum. This hinders optimum utilization <strong>of</strong> the process<br />

capabilities. Selecting optimum values <strong>of</strong> process parameters without optimization requires elaborate<br />

experimentation which is costly, time consuming, and tedious. Process parameters optimization <strong>of</strong> AMPs is<br />

essential for exploiting their potentials and capabilities to the fullest extent economically.<br />

Various conventional techniques employed for machining optimization include geometric programming,<br />

geometric plus linear programming, goal programming, sequential unconstrained minimization technique,<br />

dynamic programming etc. The latest techniques for optimization include fuzzy logic, scatter search technique,<br />

genetic algorithm, and Taguchi technique and response surface methodology.<br />

Keywords: Advanced machining processes (AMPs), Machining optimization; goal programming; fuzzy logic;<br />

genetic algorithms; Taguchi technique; response surface methodology.<br />

1. Introduction<br />

Advanced engineering materials such as polymers, ceramics, composites, and super alloys play an ever<br />

increasing important role in modern manufacturing industries, especially, in aircraft, automobile, cutting tools,<br />

die and mold making industries Garmo & Kohser [16]. Higher costs associated with the machining <strong>of</strong> these<br />

materials, and the damage caused during their machining is major impediments in the processing and hence<br />

limited applications. Further, stringent design requirements also pose major challenges to their manufacturing<br />

industries. These include precise machining <strong>of</strong> complex and complicated shapes and/or sizes (i.e. an aer<strong>of</strong>oil<br />

section <strong>of</strong> a turbine blade, complex cavities in dies and molds, etc.), various hole-drilling requirements (i.e. noncircular,<br />

small or micro size holes, holes at shallow entry angles, very deep holes, and burr less curved holes),<br />

machining <strong>of</strong> low rigidity structures, machining at micro or nano levels with tight tolerances, machining <strong>of</strong><br />

inaccessible areas, machining <strong>of</strong> honeycomb structured materials, fabrication <strong>of</strong> micro-electro mechanical<br />

systems (MEMS), and nan<strong>of</strong>inish and surface integrity requirements. Unconventional or advanced machining<br />

processes (AMPs) have been developed since the World War II largely in response to new, challenging, and<br />

unusual machining and or shaping requirements M.K. Groover [28]. Alting [27] classified the AMPs into four<br />

categories according to the type <strong>of</strong> energy used in material removal: chemical, electro-chemical, mechanical and<br />

thermal. Generally AMPs are characterized by low value <strong>of</strong> material removal rate (MRR) and high speci fic<br />

energy consumption. AMPs are used only when no other traditional machining process can meet the necessary<br />

requirements efficiently and economically because most <strong>of</strong> the AMPs are associated with relatively higher initial<br />

investment cost, power consumption and operating cost, tooling fixture and cost, and maintenance cost.<br />

Therefore effective, efficient, and economic utilization <strong>of</strong> capabilities <strong>of</strong> AMPs necessitates selection <strong>of</strong> optimum<br />

process parameters. Generally, values <strong>of</strong> process parameters <strong>of</strong> AMPs are selected either based on the<br />

experience, expertise, and knowledge <strong>of</strong> the operator or from the propriety machining handbooks. Selection <strong>of</strong><br />

process parameters based on the operator experience does not completely satisfy the requirements <strong>of</strong> high<br />

efficiency and good quality. While machining tables can be a better choice in a factory environment for one or<br />

two processes but cannot be used for a wide range <strong>of</strong> machining processes and their operating conditions. In<br />

most <strong>of</strong> the cases, selected parameters are conservative and far from the optimum. This hinders optimum<br />

utilization <strong>of</strong> the process capabilities. Selecting optimum values <strong>of</strong> process parameters without optimization<br />

requires elaborate experimentation which is costly, time consuming, and tedious. Therefore, to exploit potentials<br />

and capabilities <strong>of</strong> AMPs to the fullest extent economically, their process parameters optimization is essential.<br />

560


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Different researchers have carried out process parameters optimization <strong>of</strong> different types <strong>of</strong> AMPs from time to<br />

time using different optimization models and solution techniques.<br />

2. Review <strong>of</strong> traditional optimization techniques<br />

The appropriate meanings <strong>of</strong> the word “experiment” as given in Webster’s Dictionary are: “a trial or special<br />

observation made to confirm or disapprove something doubtful, especially one under conditions determined by<br />

the experimenter; an act or operation undertaken in order to discover some unknown principle or effective or to<br />

test, establish, or illustrate some suggested or known truth.” The honor <strong>of</strong> discovering the idea <strong>of</strong> design <strong>of</strong><br />

experiment belongs to Sir Ronald Fisher. Box and Wilson [9] in their paper proposed that an investigator<br />

organizes consecutive small no <strong>of</strong> trials, in each <strong>of</strong> which all the factors are simultaneously varied according to<br />

definite rules. The series are so organized that after mathematical processing <strong>of</strong> preceding ones it will be possible<br />

to further select the conditions for conducting the experiment that is to design the experiment. The design <strong>of</strong><br />

experiment is the procedure <strong>of</strong> selecting the number <strong>of</strong> trials conditions for running them, essential and sufficient<br />

for solving the problem that has been set with the required precision. The purpose <strong>of</strong> the theory <strong>of</strong> design<br />

experiment is to ensure that the experimenter obtains data relevant to his hypothesis in as economical a way as<br />

possible following a sequential way <strong>of</strong> analysis. The need for selecting and implementing optimal machining<br />

conditions and the most suitable cutting tool has been felt over the last few decades. Optimal machining<br />

conditions are implemented by various traditional design <strong>of</strong> experimentation technique; most <strong>of</strong> them are used<br />

previously in metal cutting in CNC turning and milling. Taylor’s early work on establishing optimum cutting<br />

speeds in single pass turnings after that progress has been slow since all the process parameters need to be<br />

optimized. Furthermore, for realistic solutions, the many constraints met in practice, such as low machine tool<br />

power, torque, force limits and component surface roughness must be overcome. Traditionally, the selection <strong>of</strong><br />

cutting conditions for metal cutting is left to the machine operator. In such cases, the experience <strong>of</strong> the operator<br />

plays a major role, but even for a skilled operator it is very difficult to attain the optimum values each time.<br />

Following the pioneering work <strong>of</strong> Taylor (<strong>19</strong>07) [38] and his famous tool life equation; different analytical and<br />

experimental approaches for the optimization <strong>of</strong> machining parameters have been investigated. Gilbert (<strong>19</strong>50)<br />

[17] studied the optimization <strong>of</strong> machining parameters in turning with respect to maximum production rate and<br />

minimum production cost as criteria. Armarego & Brown (<strong>19</strong>69) [5] investigated unconstrained machineparameter<br />

optimization using differential calculus. A number <strong>of</strong> nomograms were worked out to facilitate the<br />

practical determination <strong>of</strong> the most economic machining conditions. Brewer (<strong>19</strong>66) [8] suggested the use <strong>of</strong><br />

Lagrangian multipliers for optimization <strong>of</strong> the constrained problem <strong>of</strong> unit cost, with cutting power as the main<br />

constraint. Bhattacharya (<strong>19</strong>70) [10]optimized the unit cost for CNC turning, subject to the constraints <strong>of</strong> surface<br />

roughness and cutting power by the use <strong>of</strong> Lagrange’s method. Walvekar & Lambert (<strong>19</strong>70) [46] discussed the<br />

use <strong>of</strong> geometric programming to selection <strong>of</strong> machining variables. Petropoulos (<strong>19</strong>73) [36] investigated optimal<br />

selection <strong>of</strong> machining rate variables by geometric programming. Sundaram (<strong>19</strong>78) [41] applied a goalprogramming<br />

technique in metal cutting for selecting levels <strong>of</strong> machining parameters in a fine turning operation.<br />

Machining process parameters in advanced machining processes are different for different type <strong>of</strong> machining.<br />

For process parameters optimization <strong>of</strong> AMPs, type <strong>of</strong> objective functions and constraints, number <strong>of</strong> objectives,<br />

and extent <strong>of</strong> the importance or priority to be given to each objective depend on: (i) type <strong>of</strong> the application (i.e.<br />

rough or finish machining), (ii) volume <strong>of</strong> production (i.e. mass, batch, job-shop), (iii) nature <strong>of</strong> the work<br />

material (i.e. metallic or non-metallic, brittle or ductile, electrically/thermally conductive or non-conductive,<br />

etc.), and (iv) shape to be produced. Main objective for the bulk material removal processes is to maximize MRR<br />

subjected to constraints on surface roughness produced, power consumption, and tools (or nozzle) wear. The<br />

setting <strong>of</strong> these parameters determines the quality characteristics <strong>of</strong> AMPs.<br />

The non-availability <strong>of</strong> the required technological performance equation represents a major obstacle to<br />

implementation <strong>of</strong> optimized cutting conditions in practice. This follows since extensive testing is required to<br />

establish empirical performance equations for each tool coating–work material combination for a given<br />

machining operation, which can be quite expensive when a wide spectrum <strong>of</strong> machining operations is<br />

considered. Further the performance equations have to be updated as new coatings; new work materials and new<br />

cutting tools are introduced. While comprehensive sets <strong>of</strong> equations are found in some Chinese and Russian<br />

handbooks (Ai et al <strong>19</strong>66; Ai & Xiao <strong>19</strong>85; Kasilova & Mescheryakov <strong>19</strong>85) [2,3], as well in the American<br />

handbook (ASME <strong>19</strong>52) and Kroneberg’s (<strong>19</strong>66) [30], textbook most authors have not included discussions on<br />

the more modern tools, new work materials and tool coatings. Difficulties are experienced in locating the<br />

empirical performance equations for modern tool designs because these are hidden under computerized databases<br />

in proprietary s<strong>of</strong>tware, as noted in recent investigations [4].It is observed that the conventional methods are not<br />

robust because:<br />

- The convergence to an optimal solution depends on the chosen initial solution.<br />

- Most algorithms tend to become stuck on a suboptimal solution.<br />

561


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

- An algorithm efficient in solving one machining optimization problem may not be efficient in solving a<br />

different machining optimization problem.<br />

- Computational difficulties in solving multivariable problems (more than four variables).<br />

- Algorithms are not efficient in handling multiobjective functions.<br />

- Algorithms cannot be used on a parallel machine.<br />

3. Advanced techniques<br />

The latest techniques for optimization include fuzzy logic, scatter search technique, genetic algorithm, and<br />

Taguchi technique and response surface methodology.<br />

3.1 Fuzzy logic<br />

Fuzzy logic has great capability to capture human commonsense reasoning, decision-making and other aspects <strong>of</strong><br />

human cognition. Kosko (<strong>19</strong>97) [29] shows that it overcomes the limitations <strong>of</strong> classic logical systems, which<br />

impose inherent restrictions on representation <strong>of</strong> imprecise concepts. Vagueness in the coefficients and<br />

constraints may be naturally modelled by fuzzy logic. Modelling by fuzzy logic opens up a new way to optimize<br />

cutting conditions and also tool selection.<br />

3.1.a Methodology<br />

As per Klir & Yuan (<strong>19</strong>98) [22] fuzzy logic involves a fuzzy interference engine and fication a fuzzi -<br />

defuzzification module. Fuzzification expresses the input variables in the form <strong>of</strong> fuzzy membership values based<br />

on various membership functions. Governing rules in linguistic form, such as if cutting force is high and<br />

machining time is high, then tool wear is high, are formulated on the basis <strong>of</strong> experimental observations. Based<br />

on each rule, inference can be drawn on output grade and membership value. Inferences obtained from various<br />

rules are combined to arrive at final a decision. The membership values thus obtained are defuzzified using<br />

various techniques to obtain true value, say <strong>of</strong> flank wear. Chakravarthy and Babu [30] used combination <strong>of</strong><br />

simple genetic algorithms (SGA) and fuzzy logic for optimal selection <strong>of</strong> three AWJM parameters namely water<br />

jet pressure, jet traverse rate, and abrasive flow rate. SGA was used to generate a set <strong>of</strong> strings <strong>of</strong> input<br />

parameters. A fuzzy rule base was used to predict depth <strong>of</strong> cut using these parameters as input. Those parametric<br />

combinations, for which predicted depth <strong>of</strong> cut was equal to the desired depth <strong>of</strong> cut within a fied speci error<br />

amount, were identified as feasible combinations.<br />

3.2 Genetic algorithm (GA)<br />

These are the algorithms based on mechanics <strong>of</strong> natural selection and natural genetics, which are more robust<br />

and more likely to locate global optimum. It is because <strong>of</strong> this feature that GA goes through solution space<br />

starting from a group <strong>of</strong> points and not from a single point. The cutting conditions are encoded as genes by<br />

binary encoding to apply GA in optimization <strong>of</strong> machining parameters. A set <strong>of</strong> genes is combined together to<br />

form chromosomes, used to perform the basic mechanisms in GA, such as crossover and mutation.<br />

Crossover is the operation to exchange some part <strong>of</strong> two chromosomes to generate new <strong>of</strong>fspring, which is<br />

important when exploring the whole search space rapidly. Mutation is applied after crossover to provide a small<br />

randomness to the new chromosomes. To evaluate each individual or chromosome, the encoded cutting<br />

conditions are decoded from the chromosomes and are used to predict machining performance measures. Fitness<br />

or objective function is a function needed in the optimization process and selection <strong>of</strong> next generation in genetic<br />

algorithm. Optimum results <strong>of</strong> cutting conditions are obtained by comparison <strong>of</strong> values <strong>of</strong> objective functions<br />

among all individuals after a number <strong>of</strong> iterations. Besides weighting factors and constraints, suitable parameters<br />

<strong>of</strong> GA are required to operate efficiently. GA optimization methodology is based on machining performance<br />

predictions models developed from a comprehensive system <strong>of</strong> theoretical analysis, experimental database and<br />

numerical methods. The GA parameters along with relevant objective functions and set <strong>of</strong> machining<br />

performance constraints are imposed on GA optimization methodology to provide optimum cutting conditions.<br />

3.2a Implementation <strong>of</strong> GA<br />

First <strong>of</strong> all, the variables are encoded as n-bit binary numbers assigned in a row as chromosome strings. To<br />

implement constraints in GA, penalties are given to individuals out <strong>of</strong> constraint. If an individual is out <strong>of</strong><br />

constraint, its fitness will be assigned as zero. Because individuals are selected to mate according to fitness value,<br />

zero fitness individuals will not become parents. Thus most individuals in the next generation are ensured in<br />

feasible regions bounded by constraints. The GA is initialized by randomly selecting individuals in the full range<br />

<strong>of</strong> variables. Individuals are selected to be parents <strong>of</strong> the next generation according to their fitness value. The<br />

larger the fitness value, the greater their possibility <strong>of</strong> being selected as parents [40] have used this technique for<br />

optimization <strong>of</strong> CNC milling machine parameters.[21]<br />

562


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

have used a genetic algorithm based parameter tuning algorithm for multi-dimensional motion control <strong>of</strong> a<br />

computer numerical control machine tool. The feasible parametric combinations were used for optimization to<br />

minimize total cost <strong>of</strong> production. Kovacevic and Fang [35] have applied fuzzy set theory for selecting (though<br />

not the optimum values) four AWJM process parameters namely water jet pressure, jet traverse rate, abrasive<br />

flow rate, and inside diameter <strong>of</strong> AWJ nozzle to achieve the desired depth <strong>of</strong> cut. Universes <strong>of</strong> discourse for<br />

AWJM process parameters were discretized into 17 levels with 5 linguistic terms and triangular membership<br />

function was used for each parameter. Five fuzzy rules were employed for each <strong>of</strong> the four AWJM process<br />

variables. De [29] also used SGAs to optimize five process parameters <strong>of</strong> USM process with the objective <strong>of</strong><br />

maximizing MRR subjected to the surface roughness constraint.<br />

3.3 Scatter search technique (SS)<br />

This technique originates from strategies for combining decision rules and surrogate constraints. SS is<br />

completely generalized and problem-independent since it has no restrictive assumptions about objective function,<br />

parameter set and constraint set. It can be easily fied modito optimize machining operation under various<br />

economic criteria and numerous practical constraints. It can obtain near-optimal solutions within reasonable<br />

execution time on PC. Potentially, it can be extended as an on-line quality control strategy for optimizing<br />

machining parameters based on signals from sensors. Chen & Chen (<strong>20</strong>03) [11] have done extensive work on<br />

this technique.<br />

3.3a Methodology<br />

First <strong>of</strong> all, machining models are required to determine the optimum machining parameters USM including<br />

Amplitude <strong>of</strong> ultrasonic Vibrations (mm), Frequency <strong>of</strong> ultrasonic vibrations (Hz), Mean diameter <strong>of</strong> abrasive<br />

particles (mm),Volumetric concentration <strong>of</strong> abrasive particles, Static feed force (N) in order to minimize unit<br />

production cost. Unit production cost can be divided into four basic cost elements:<br />

• Cutting cost by actual cut in time<br />

• Machine idle cost due to loading and unloading operation and idling tool motion cost<br />

• Tool replacement cost<br />

• Tool cost<br />

For the optimization <strong>of</strong> unit production cost, practical constraints which present the state <strong>of</strong> machining processes<br />

need to be considered. The constraints imposed during machining operations are:<br />

- Parameter constraint – Ranges <strong>of</strong> Amplitude <strong>of</strong> ultrasonic Vibrations (mm),Frequency <strong>of</strong> ultrasonic<br />

vibrations (Hz), Mean diameter <strong>of</strong> abrasive particles (mm),Volumetric concentration <strong>of</strong> abrasive particles,<br />

Static feed force (N)<br />

- Tool life constraint – Allowable values <strong>of</strong> flank wear width and crater wear depth<br />

- Operating constraint – Maximum allowable cutting force, power available on machine tool and surface<br />

finish requirement.<br />

An optimization model for USM operation can be formulated. The model is a constrained nonlinear<br />

programming problem with multiple variables (machining variables). The initial solution for SS is picked in a<br />

random way. The user-specified parameters have to be given. The experimentation can be run on a PC with<br />

Pentium800Mhz processor. The computational results validate the advantage <strong>of</strong> SS in terms <strong>of</strong> solution quality<br />

and computational requirement.<br />

3.4 Taguchi technique<br />

Genichi Taguchi is a Japanese engineer who has been active in the improvement <strong>of</strong> Japan’s industrial products<br />

and processes since the late <strong>19</strong>40s. He has developed both the philosophy and methodology for process or<br />

product quality improvement that depends heavily on statistical concepts and tools, especially statistically<br />

designed experiments. Many Japanese firms have achieved great success by applying his m ethods. Wu (<strong>19</strong>82)<br />

[42] has reported that thousands <strong>of</strong> engineers have performed tens <strong>of</strong> thousands <strong>of</strong> experiments based on his<br />

teachings. Taguchi has received some <strong>of</strong> Japan’s most prestigious awards for quality achievement, including the<br />

Deming prize. In <strong>19</strong>86, Taguchi received the most prestigious prize from the International <strong>Technology</strong> Institute –<br />

The Willard F. Rockwell Medal for Excellence in <strong>Technology</strong>. Taguchi’s major contribution has involved<br />

combining engineering and statistical methods to achieve rapid improvements in cost and quality by optimizing<br />

product design and manufacturing processes. Barker (<strong>19</strong>90) [6] reported that since <strong>19</strong>83, after Taguchi’s<br />

association with the top companies and institutes in USA (AT & T Bell Laboratories, Xerox, Lawrence Institute<br />

<strong>of</strong> <strong>Technology</strong> (LIT), Ford Motor Company etc.), his methods have been called a radical approach to quality,<br />

experimental design and engineering. Sullivan (<strong>19</strong>87) reported that the term “Taguchi methods” (TM) refers to<br />

the parameter design, tolerance design, quality loss function, on-line quality control, design <strong>of</strong> experiments using<br />

orthogonal arrays, and methodology applied to evaluate measuring systems. Pignatiello (<strong>19</strong>88) [34] identi fies<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

two separate aspects <strong>of</strong> the Taguchi methods: the strategy <strong>of</strong> Taguchi and the tactics <strong>of</strong> Taguchi. Taguchi tactics<br />

refer to the collection <strong>of</strong> specific methods and techniques used by Genichi Taguchi, and Taguchi strategy is the<br />

conceptual framework or structure for planning a product or process design experiment. Taguchi addresses<br />

design and engineering (<strong>of</strong>f-line) as well as manufacturing (on-line) quality. This fundamentally differentiates<br />

TM from statistical process control (SPC), which is purely an on-line quality control method.Taguchi’s ideas can<br />

be distilled into two fundamental concepts:<br />

(a) Quality losses must be defined as deviations from targets, not conformance to arbitrary specifications.<br />

(b) Achieving high system-quality levels economically requires quality to be designed into the product. Quality<br />

is designed, not manufactured, into the product ([14]; [37]).<br />

Lin et al (<strong>19</strong>90) [26] stated that Taguchi methods represent a new philosophy. Quality is measured by the<br />

deviation <strong>of</strong> a functional characteristic from its target value. Noises (uncontrolled variables) can cause such<br />

deviations resulting in loss <strong>of</strong> quality. Taguchi methods seek to remove the effect <strong>of</strong> noises.Taguchi (<strong>19</strong>89)<br />

described that quality engineering encompasses all stages <strong>of</strong> product/process development: system design,<br />

parameter design, and tolerance design. Byrne & Taguchi (<strong>19</strong>87) [10], however, pointed out that the key element<br />

for achieving high quality and low cost is parameter design. Through parameter design, levels <strong>of</strong> product and<br />

process factors are determined, such that the product’s functional characteristics are optimized and the effect <strong>of</strong><br />

noise factors is minimized. Kackar & Shoemaker (<strong>19</strong>86) [<strong>19</strong>] observed that parameter design reduces<br />

performance variation by reducing the influence <strong>of</strong> the sources <strong>of</strong> variation rather than by controlling them, it is<br />

thus a very cost-effective technique for improving engineering design.<br />

3.4a Applications<br />

Chanin et al (<strong>19</strong>90) [13] remarked that Japanese companies such as Nip-pon Denso, NEC, and Fugitsu have<br />

become world economic competitors by using Taguchi’s approach which has potential for saving experimental<br />

time and cost on product or process development, as well as quality improvement. Kacker & Shoemaker (<strong>19</strong>86)<br />

[<strong>19</strong>], Phadke (<strong>19</strong>86) [32], and Pao et al (<strong>19</strong>85) pointed out that the methodology advocated by Taguchi has been<br />

applied within AT & T to a variety <strong>of</strong> problems ranging from IC fabrication to response time optimization <strong>of</strong> a<br />

UNIX system since Taguchi’s first visit to AT & T Bell Laboratories in <strong>19</strong>80.Ghosh (<strong>19</strong>90) [15] remarked that<br />

Taguchi’s ideas are also being used in many others US companies such as Ford and Xerox. There are also many<br />

courses on robust parameter design <strong>of</strong>fered by organizations like American Supplier Institute, Rochester Institute<br />

<strong>of</strong> <strong>Technology</strong>, and the Center for Quality and Productivity Improvement at the <strong>University</strong> <strong>of</strong> Wisconsin in<br />

Madison.The American Supplier Institute also has an annual symposium where case studies on the application <strong>of</strong><br />

the Taguchi Methods are presented. Lin & Kackar (<strong>19</strong>85) [25] have shown how a 36-run orthogonal array design<br />

was used to improve a wave soldering process by studying 17 variables simultaneously. Kamat & Rao (<strong>19</strong>94)<br />

[21] have presented a case study <strong>of</strong> Taguchi optimization related to manufacturing processes for die-cast<br />

components. The use <strong>of</strong> optimal parame- ter combinations obtained from the analysis reduced the rejection <strong>of</strong><br />

die-cast components by 90%. Tsui (<strong>19</strong>99) [39] presented robust design optimization for multiple characteristic<br />

problems. Robust design improves product or manufacturing process design by making the output response<br />

insensitive (robust) to difficult-to-control variations. The multivariate quality loss function considered by<br />

Pignatiello (<strong>19</strong>93) [33] has been extended to include the smaller and the larger-the-better type characteristics.<br />

Under various assumptions, appropriate two-step pro- cedures were developed that minimize the average<br />

multivariate loss. The proposed two-step procedure substantially reduces the dimension <strong>of</strong> the design<br />

optimization problem and allows for future changes <strong>of</strong> response target values without re-optimization. The<br />

success <strong>of</strong> many applications has demonstrated the power <strong>of</strong> Taguchi’s overall approach. It is also worth<br />

mentioning that many <strong>of</strong> the specific statistical techniques he has pro -posed for implementing robust parameter<br />

design have generated a great deal <strong>of</strong> controversy. However, most commentators agree that Taguchi’s loss<br />

function concept represents a solid contribution. Furthermore, there is general agreement that <strong>of</strong>f-line<br />

experiments during the product or process design stage are <strong>of</strong> great value and the methodology is based on solid<br />

engineering principles. Reducing quality loss by designing the products and processes to be insensitive to<br />

variations in noise variables is a novel concept to statisticians and quality engineers.<br />

3.5 Response surface methodology (RSM)<br />

Experimentation and making inferences are the twin features <strong>of</strong> general scientific methodology. Statistics as a<br />

scientific discipline is mainly designed to achieve these objectives. Planning <strong>of</strong> experiments is particularly very<br />

useful in deriving clear and accurate conclusions from the experimental observations, on the basis <strong>of</strong> which<br />

inferences can be made in the best possible manner. The methodology for making inferences has three main<br />

aspects. First, it establishes methods for drawing inferences from observations when these are not exact but<br />

subject to variation, because inferences are not exact but probabilistic in nature. Second, it specifies methods for<br />

collection <strong>of</strong> data appropriately, so that assumptions for the application <strong>of</strong> appropriate statistical methods to them<br />

are satisfied. Lastly, techniques for proper interpretation <strong>of</strong> results are devised.<br />

The advantages <strong>of</strong> design <strong>of</strong> experiments as reported by Adler et al (<strong>19</strong>75) [1] and Johnston (<strong>19</strong>64) [18] are as<br />

564


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

follows.<br />

(1) Numbers <strong>of</strong> trials are reduced.<br />

(2) Optimum values <strong>of</strong> parameters can be determined.<br />

(3) Assessment <strong>of</strong> experimental error can be made.<br />

(4) Qualitative estimation <strong>of</strong> parameters can be made.<br />

(5) Inference regarding the effect <strong>of</strong> parameters on the characteristics <strong>of</strong> the process can be made.<br />

Cochran & Cox (<strong>19</strong>62) [12] quoted Box and Wilson [9] as having proposed response surface methodology for<br />

the optimization <strong>of</strong> experiments. In many experimental situations, it is possible to represent independent factors<br />

in quantitative form. Then these factors can be thought <strong>of</strong> as having a functional relationship or response:<br />

Y = φ(X1, X2, . . . , X k ) ± e r ,<br />

Between the response Y and X1, X2, . . . Xk<strong>of</strong> k quantitative factors. The function φ is called response surface or<br />

response function. The residual er measures the experimental error. For a given set <strong>of</strong> independent variables, a<br />

characteristic surface responds. When the mathematical form <strong>of</strong> φ is not known, it can be approximated<br />

satisfactorily within the experimental region by a polynomial. The higher the degree <strong>of</strong> the polynomial the better<br />

is the correlation, though at the same time the costs <strong>of</strong> experimentation become higher. The methodology may be<br />

applied for developing the mathematical models in the form <strong>of</strong> multiple regression equations correlating the<br />

dependent parameters such as cutting force, power consumption, surface roughness, tool life etc. In applying the<br />

response surface methodology, the dependent parameter is viewed as a surface to which a mathematical model is<br />

fitted. For the development <strong>of</strong> regression equations related to various quality characteristics <strong>of</strong> turned parts, the<br />

second-order response surface may be assumed as:<br />

(1)<br />

This assumed surface Y contains linear, squared and cross-product terms <strong>of</strong> variables Xi’s. In order to estimate<br />

the regression coefficients a number <strong>of</strong> experimental design techniques are available. A central composite design<br />

was used to develop the models in order to minimize the amount <strong>of</strong> experimentation.<br />

The models were represented by response surfaces and contours <strong>of</strong> these surfaces were obtained at different<br />

levels <strong>of</strong> each <strong>of</strong> the independent variables in planes <strong>of</strong> the other independent variables<br />

4. Conclusions<br />

A review <strong>of</strong> literature shows that various traditional machining optimization techniques like Lagrange’s method,<br />

geometric programming, goal programming, dynamic programming etc.have been successfully applied in the<br />

past for optimizing the various turning process variables. Fuzzy logic, genetic algorithm, scatter search, Taguchi<br />

technique and response surface methodology are the latest optimization techniques that are being applied<br />

successfully in industrial applications for optimal selection <strong>of</strong> process variables in the area <strong>of</strong> machining. A<br />

review <strong>of</strong> literature on optimization techniques has revealed that there are, in particular, successful industrial<br />

applications <strong>of</strong> design <strong>of</strong> experiment-based approaches for optimal settings <strong>of</strong> process variables. Taguchi<br />

methods and response surface methodology are robust design techniques widely used in industries for making<br />

the product/process insensitive to any uncontrollable factors such as environmental variables. Japanese<br />

companies such as Nippon Denso, NEC, and Fugitsu have become world economic competitors by using the<br />

Taguchi approach that has potential for savings in experimental time and cost on product or process development<br />

and quality improvement. There is general agreement that <strong>of</strong>f-line experiments during product or process design<br />

stage are <strong>of</strong> great value. Reducing quality loss by designing the products and processes to be insensitive to<br />

variation in noise variables is a novel concept to statisticians and quality engineers.<br />

5. References<br />

1. Adler Y P, Markova E V, Granovsky Y V <strong>19</strong>75 The design <strong>of</strong> experiments to find optimal conditions<br />

(Moscow: Mir Publishers)<br />

2. Ai X, Xiao S <strong>19</strong>85 Metal cutting condition handbook (China: Mechanics Industry Press)<br />

3. Ai X, Tao Q, Xiao S <strong>19</strong>66 Metal cutting condition handbook (China: Mechanics Industry Press)ASME <strong>19</strong>52<br />

Research committee on metal cutting data and bibliography. Manual on cutting <strong>of</strong> metals with single point<br />

tools 2nd edn.<br />

4. Armarego E J A, Ostafiev D <strong>19</strong>98 A study <strong>of</strong> a proprietary computerized technological machining<br />

performance database. 8th Int. Manufacturing Conference, pp 26–33<br />

5. Armarego E J A, Brown R H <strong>19</strong>69 the machining <strong>of</strong> metals (Englewood Cliffs, NJ: Prentice Hall) ASME<br />

<strong>19</strong>52 Research committee on metal cutting data and bibliography. Manual on cutting <strong>of</strong> metals with single<br />

point tools 2nd edn.<br />

6. Barker T B <strong>19</strong>90 Engineering quality by design (New York: Marcel Dekker)<br />

7. Brewer R C, Rueda R <strong>19</strong>63 A simplified approach to the optimum selection <strong>of</strong> machining parameters. Eng.<br />

Dig. 24(9): 133–150<br />

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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

8. Bhattacharya A, Faria-Gonzalez R, Inyong H <strong>19</strong>70 Regression analysis for predicting surface finish and its<br />

application in the determination <strong>of</strong> optimum machining conditions. Trans. Am. Soc. Mech.Eng. 92: 711.<br />

9. Box, G.E.P., Wilson, K.B., <strong>19</strong>51, “Experimental attainment <strong>of</strong> optimum conditions,” J.R. Statistical Society<br />

.b13, pp. 1-45.<br />

10. Byrne D M, Taguchi S <strong>19</strong>87 The Taguchi approach to parameter design. Quality Progress <strong>20</strong>: <strong>19</strong>–26<br />

11. Chen M, Chen K Y <strong>20</strong>03 Determination <strong>of</strong> optimum machining conditions using scatter search.<br />

Newoptimization techniques in engineering, pp 681–697.<br />

12. Cochran G, Cox G M <strong>19</strong>62 Experimental design (New Delhi: Asia Publishing House)<br />

13. Chanin M N, Kuei Chu-Hua, Lin C <strong>19</strong>90 Using Taguchi design, regression analysis and simulation to study<br />

maintenance float systems. Int. J. Prod. Res. 28: <strong>19</strong>39–<strong>19</strong>53<br />

14. Daetz D <strong>19</strong>87 The effect <strong>of</strong> product design on product quality and product cost.<br />

15. Ghosh S <strong>19</strong>90 Statistical design and analysis <strong>of</strong> industrial experiments (New York: Marcel Dekker)<br />

16. E.P. De Ga rmo, J.T. Black, R.A. Kohser, Materials and Processes in Manufacturing, Prentice-Hall Inc.,<br />

New Jersey, <strong>19</strong>97.<br />

17. Gilbert W W <strong>19</strong>50 Economics <strong>of</strong> machining. In Machining – Theory and practice. Am. Soc. Met.476–480<br />

18. Johnston R E <strong>19</strong>64 Statistical methods in foundry expts. AFS Trans. 72: 13–24<br />

<strong>19</strong>. Kackar R N, Shoemaker A C <strong>19</strong>86 Robust design: A cost effective method for improving manufacturing<br />

processes. AT & T Tech. J. 65(Mar–Apr): 39–50<br />

<strong>20</strong>. Kamat Y V, Rao M V <strong>19</strong>94 A Taguchi optimization <strong>of</strong> the manufacturing process for die cast components.<br />

Proc. 6th AIMTDR Conference, Bangalore, 174–179<br />

21. Kuo L Y, Yen J Y <strong>20</strong>02 A genetic algorithm based parameter-tuning algorithm for multi dimensional<br />

motion control <strong>of</strong> a computer numerical control machine tool. Proc. Inst. Mech. Eng. B216:<br />

22. Klir G J, Yuan B <strong>19</strong>98 Fuzzy system and fuzzy logic – theory and practice (Englewood Cliffs, NJ: Prentice<br />

Hall)<br />

23. Kosko B <strong>19</strong>97 Neural network and fuzzy systems – A dynamic approach to machine intelligence(New Delhi:<br />

Prentice Hall <strong>of</strong> India)<br />

24. KronebergM<strong>19</strong>66 Theory and practice for operation and development <strong>of</strong> machining process<br />

(Oxford:Pergamon) Edition Longman Group Limited, NewYork.<br />

25. Lin K M, Kackar R N <strong>19</strong>85 Wave soldering optimization by orthogonal array design method.<br />

Electricalpackaging and production 108–115<br />

26. Lin, Paul K H, Sullivan L P, Taguchi G <strong>19</strong>90 Using Taguchi methods in quality engineering. Quality<br />

Progress 55–59<br />

27. L. Alting, Manufacturing Engineering Processes, Marcel Dekker Inc., New York, <strong>19</strong>82.<br />

28. M.K. Groover, Fundamentals <strong>of</strong> Modern Manufacturing: Materials,Processes, and Systems, Prentice-Hall<br />

International Inc., <strong>19</strong>96.<br />

29. M. De, Computer aided process planning for USM, M. Tech. Thesis, Department <strong>of</strong> Mechanical<br />

Engineering, I.I.T, Kanpur-16, <strong>19</strong>97.<br />

30. P.S. Chakravarthy, N.R. Babu, A new approach for selection <strong>of</strong> optimal process parameters in abrasive<br />

water jet cutting, Materials and Manufacturing Processes 14 (4) (<strong>19</strong>99) 581–600.<br />

31. Petropoulos P G <strong>19</strong>73 Optimal selection <strong>of</strong> machining rate variable by geometric programming.Int. J. Prod.<br />

Res. 11: 305–314<br />

32. Phadke M S <strong>19</strong>86 Design optimization case studies. AT&T Tech. J. 65(Mar–Apr): 51–84<br />

33. Pignatiello J J <strong>19</strong>93 Strategies for robust multi-response quality engineering. Inst. Ind. Eng. Trans.25: 5–25<br />

34. Pignatiello J J <strong>19</strong>88 An overview <strong>of</strong> the strategy and tactics <strong>of</strong> Taguchi. Inst. Ind. Eng. Trans. <strong>20</strong>:247–254<br />

35. R. Kovacevic, M. Fang, Modeling <strong>of</strong> the influence <strong>of</strong> the abrasive water jet cutting parameters on the depth<br />

<strong>of</strong> cut based on fuzzy rules, International Journal <strong>of</strong> Machine Tools and Manufacture 34 (1) (<strong>19</strong>94) 55–72.<br />

36. Sundaram R M <strong>19</strong>78 An application <strong>of</strong> goal programming technique in metal cutting. Int. J. Prod.Res. 16:<br />

375–382.<br />

37. Taguchi G <strong>19</strong>89 Quality engineering in production systems (New York: McGraw-Hill)<br />

38. Taylor F W <strong>19</strong>07 On the art <strong>of</strong> cutting metals. Trans. ASME 28: 31–35<br />

39. Tsui K L <strong>19</strong>99 Robust design optimization for multiple characteristics problems. Int. J. Prod. Res. 37:433–<br />

445<br />

40. Wang X, Jawahir I S <strong>20</strong>04 Web based optimization <strong>of</strong> milling operations for the selection <strong>of</strong> cutting<br />

conditions using genetic algorithms. Proc. Inst. Mech. Eng. 218: 212–223<br />

41. Walvekar A G, Lambert B K <strong>19</strong>70 An application <strong>of</strong> geometric programming to machining variable<br />

selection. Int. J. Prod. Res. 8: 3<br />

42. Wu V <strong>19</strong>82 Off-line quality control: Japanese quality engineering (Dearborn, MI: American Supplier<br />

Institute)<br />

566


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

AN ANALYSIS OF SURFACE ROUGHNESS AND MACHINABILITY<br />

OF Al-Fe-Si ALLOYS<br />

Kanwar Pal 1 , Sombir Sharma 1 , B.N.Pathak 3 , Arvind Kumar 4<br />

1 BRCMCET, Bahal, Bhiwani,<br />

2 IMSCET, Ghaziabad<br />

3 <strong>YMCA</strong>UST,Faridabad<br />

Abstract<br />

Machining operations plays the key role in the manufacturing industry since the industrial revolution.<br />

Manufacturing industries strive to achieve minimum cost <strong>of</strong> production with a maximum production rate.<br />

Machinability is one <strong>of</strong> the important parameter that is related to all phases <strong>of</strong> manufacturing. Machinability is<br />

influenced by a number <strong>of</strong> variables, such as the inherent properties or characteristics <strong>of</strong> the work materials,<br />

cutting tool material, tool geometry, the nature <strong>of</strong> tool engagement with the work, cutting conditions, type <strong>of</strong><br />

cutting, cutting fluid, and machine tool rigidity and its capacity. Tool life is affected by machinability <strong>of</strong> the<br />

material at different speeds and temperatures. Worldwide research is going on to improve the machinability <strong>of</strong><br />

the existing materials or to develop new materials with similar properties and improved machinability. Present<br />

work is carried out to improve the machinability <strong>of</strong> an aluminium based alloy (Al-Fe-Si) with an aim to optimize<br />

the effecting parameters. The surface roughness and machinability <strong>of</strong> the material with variation <strong>of</strong> ferrous<br />

percentage is tested and the results are produced.<br />

Key words: Machinability, surface roughness, Al-Fe-Si alloy.<br />

1. Introduction<br />

Traditional machining operations such as turning, milling, boring, tapping, sawing etc. are easily performed on<br />

aluminum and its alloys. The machines that are used can be the same as for use with steel, however optimum<br />

machining conditions such as rotational speeds and feed rates can only be achieved on machines designed for<br />

machining aluminum alloys. Many applications <strong>of</strong> aluminum are undergoing a reduction in weight as strength<br />

and durability <strong>of</strong> aluminum is improved by alloying. Research in many areas <strong>of</strong> aluminum technology, such as<br />

advanced alloys, rapid solidification, composites and corrosion resistance, is aimed at keeping aluminum<br />

material competitive in traditional as well as new applications.<br />

2. Literature Review<br />

Al-Fe-Si alloys, which has the potential applications to use in elevated temperature. Al-Fe-Si alloys are generally<br />

produced through rapid solidification process, which exhibit comparable better mechanical properties to<br />

conventional cast aluminium alloys. The improved performance <strong>of</strong> these alloys at elevated temperature have<br />

made them strong candidates for a variety <strong>of</strong> future aerospace applications such as aircraft fuselage, missile fins<br />

and winglets, rocket motor cases, and various gas turbine engine components. Al-Fe-Si alloys produced through<br />

RSP route is also a cost intensive.<br />

Aluminum alloys such as Al-Si, Al-Cu-Si and Al-Mg-Zn alloys are widely used in aerospace and other<br />

engineering industries due to their light weight and high strength per unit weight. Al-TM (TM - transition metal)<br />

systems have the potential for high temperature applications. Among the Al-TM system, Al-Fe-Si, Systems have<br />

altered considerable interest due to its high strength at room as well as at elevated temperature. Iron increases the<br />

hardness and decreases the ductility [Pathak et al., <strong>20</strong>06] and grain refinement <strong>of</strong> the casting yields several<br />

benefits. A fine grain size results good mechanical properties that are uniform throughout the material. Also, as<br />

the grain size decrease, the distribution <strong>of</strong> secondary phases and porosity is on a finer scale, and machinablity is<br />

improved. Therefore Vanadium is added to these alloys for its grain refining effects [K.L.Sahoo et al., <strong>20</strong>00].<br />

Iron is a common impurity in aluminium and it leads to the formation <strong>of</strong> complex intermetallic phases during<br />

solidification, and how these phases can adversely affect mechanical properties, especially ductility, and also<br />

lead to the formation <strong>of</strong> excessive shrinkage porosity defects in castings. Although iron is highly soluble in liquid<br />

aluminium and its alloys, it has very little solubility in the solid, and so it tends to combine with other elements<br />

to form intermetallic phase particles <strong>of</strong> various types. The differing shapes <strong>of</strong> these iron intermetallics are in part<br />

responsible for the impact <strong>of</strong> iron on castability and mechanical properties. It is consistently reported that as Fe<br />

levels increase, porosity increases & the ductility <strong>of</strong> Al-Si based alloys decreases [John A. Taylor, <strong>20</strong>04]. The<br />

major factors which are highly responsible for the surface roughness are feed rate and tool size. The work piece<br />

had the most surface roughness when the feed rate was high in combination with the highest depth <strong>of</strong> cut and the<br />

lowest spindle speed but it was not consistent with the system response. The combination for achieving this type<br />

567


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

<strong>of</strong> surface finish is best when the spindle speed is running at its highest i.e.,2800 rpm, depth <strong>of</strong> cut was adjusted<br />

to its maximum value <strong>of</strong> 0.075 in with a low feed rate <strong>of</strong> 10 in/min provided the least roughness amongst all<br />

given samples. The tool size <strong>of</strong> 0.5 inches in diameter used for this experiment did not show much variability in<br />

the surface roughness when compared to the tool size <strong>of</strong> 0.25 inches dia. The 0.25 inch tool size did give the<br />

highest and the lowest surface roughness when in combination with the other three parameters [R. Noorani,<br />

<strong>20</strong>09].<br />

3. Experimental Procedure<br />

The compositions <strong>of</strong> different alloys and different modification treatment are given in the Table 1 and Table 2.<br />

Table 1: Compositions <strong>of</strong> the alloys prepared<br />

Alloy<br />

Chemical composition<br />

Designation<br />

(wt. %)<br />

Fe Si Al<br />

S1 1 1 Balance<br />

S2 2 1 Balance<br />

Table 2: Sample size <strong>of</strong> different material<br />

Sample<br />

Al<br />

Fe<br />

Si<br />

Alloy<br />

No.<br />

(kg)<br />

(gm)<br />

(gm)<br />

A 4.90 53.00 53.00 Al-1Fe-1Si<br />

B 4.85 105.00 53.00 Al-2Fe-1Si<br />

4. Preparation <strong>of</strong> alloy<br />

The experimental alloys were prepared in an electric heating furnace in a clay bonded graphite crucible under the<br />

cover <strong>of</strong> Na-free flux. For alloy preparation, Pure Al and Fe were used. At around 600 0 C, weighted quantity <strong>of</strong><br />

99.9% pure aluminium and 99.9% pure Silicon metallic was charged. Just after melting, the molten alloy was<br />

covered with a sodium free flux (2% <strong>of</strong> melt). After melting, sufficient time was given for complete<br />

homogenization <strong>of</strong> the melt. The melt was frequently agitated with a graphite rod for complete mixing. The melt<br />

was then degassed with hexachloroethane. Degasser was wrapped in aluminium foil and plunged into the melt.<br />

After degassing the melt was cast in different moulds. The object is to vary the cooling rates.<br />

5. Pouring <strong>of</strong> melt at different moulds<br />

After complete homogenization at desired temperature the melt was poured in different mould to prepare<br />

different samples. There were five samples prepared which were poured in (a) 12 mm diameter permanent<br />

mould, (b) 25 mm thickness permanent (steel) flat mould, (c) 75 mm diameter permanent mould.The pouring<br />

temperature was maintained approximately at 880 0 C. The fluidity <strong>of</strong> the melt at this temperature was sufficient<br />

for casting test pieces. In all the cases, the mould was preheated approximately up to 1500 0 C to drive <strong>of</strong>f the<br />

moisture.<br />

6. Machinability <strong>of</strong> aluminum alloys<br />

Different samples have been made for machinability test <strong>of</strong> the alloys. The samples were cut in eight pieces from<br />

the cast piece 170 X 75 X <strong>20</strong>mm. The dimension <strong>of</strong> the samples used for milling operation is 40 X 18 X 8mm.<br />

For milling operation 16mm diameter HSS tool were used. The samples were machined under different<br />

parameter <strong>of</strong> machining.<br />

7. Result analysis<br />

Mechanical properties <strong>of</strong> both samples <strong>of</strong> Al alloys are discussed in detail. The hardness <strong>of</strong> the samples that cast<br />

in permanent mould is given in the Table 3.<br />

568


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 3: Vickers’s hardness <strong>of</strong> as cast samples<br />

Hardness (VHN)<br />

Alloy<br />

Permanent mould<br />

Al-1Fe-1Si 35<br />

Al-2Fe-1Si 41<br />

From the Table 3, it is clear that hardness is increases as iron content increases. Table 4 shows the ultimate<br />

tensile strength (UTS), percentage elongation and percentage reduction in area (RA) as cast samples.<br />

Table 4:Mechanical properties <strong>of</strong> as cast alloys<br />

Cast alloy UTS<br />

(MPa)<br />

Elongation<br />

%<br />

RA<br />

%<br />

Al-1Fe-1Si 37 5 4<br />

Al-2Fe-1Si 45 4 3<br />

From the Table 4. it is clear that as iron percentage increase, UTS sharply increases but percentage elongation<br />

decreases. During tensile testing, the massive iron bearing phases also adversely affect effective feeding in the<br />

casting resulting in micro pores. Thus the mechanical properties deteriorate. To avoiding this defect, hot rolling<br />

will be done.<br />

8. Surface roughness <strong>of</strong> Al-1Fe-1Si & Al-2Fe-1Si alloys<br />

The effect <strong>of</strong> depth <strong>of</strong> cut on arithmetic mean roughness Ra (centre-line average) and maximum peak to valley<br />

height roughness Rz values <strong>of</strong> milling Al alloy with HSS are presented in Figure1. Figure 1(a) and 1(b) shows<br />

the influence <strong>of</strong> depth <strong>of</strong> cut on the surface roughness height Ra and Rz during machining <strong>of</strong> Al alloy without<br />

use <strong>of</strong> coolant.<br />

4.5 R z<br />

4.0<br />

3.5<br />

Surface Roughness (µm)<br />

3.0<br />

2.5<br />

2.0<br />

1.5<br />

1.0<br />

0.5<br />

R a<br />

0.0<br />

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6<br />

Depth <strong>of</strong> Cut (mm)<br />

Figure 1 (a) Effect <strong>of</strong> depth <strong>of</strong> cut on surface roughness height for f = 0.5mm/rev<br />

and v = 75m/min <strong>of</strong> Al-1Fe-1Si alloy.<br />

569


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

14 R z<br />

12<br />

Surface Roughness (µm)<br />

10<br />

8<br />

6<br />

4<br />

2<br />

R a<br />

0<br />

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6<br />

Depth <strong>of</strong> Cut (mm)<br />

Figure 1(b) Effect <strong>of</strong> depth <strong>of</strong> cut on surface roughness height for f = 0.5mm/rev<br />

and v = 75m/min <strong>of</strong> Al-2Fe-1Si alloy<br />

9. Discussion<br />

In present work the hardness and tensile strength <strong>of</strong> alloys increases as iron content increases and ductility<br />

decreases as % <strong>of</strong> iron increases. As per appearance <strong>of</strong> chip formation it may be conclude that machinability is<br />

poor as depth <strong>of</strong> cut increases.<br />

From the Figure 1(a) and (b), it can be observed that depth <strong>of</strong> cut and surface finish is not following the trend in<br />

increasing order but it is abruptly changing alternately and it goes up. Initially at 0.25mm depth <strong>of</strong> cut, the<br />

surface roughness is low, at 0.50 mm depth <strong>of</strong> cut there is good surface finish and again as depth <strong>of</strong> cut increases<br />

alternately the quality <strong>of</strong> surface finish also changing.<br />

10. Conclusion<br />

The surface finish is poor as Fe content increases from 1% to 2% in alloy but increasing the Fe content reduces<br />

the variation in surface roughness [Figure 1(b)]. The surface roughness <strong>of</strong> the workpiece was affected by depth<br />

<strong>of</strong> cut. Decrease in feed and an increase in cutting speed improve the surface finish. High speed and low depth <strong>of</strong><br />

cut are recommended for better surface finish.<br />

References<br />

[1] Metal Handbook, (<strong>19</strong>90). 10th Edition, ASM international, the materials information society, Vol.2.<br />

[2] B.N.Pathak, Arvind Kumar, K.L.Sahoo and P.Talukdar, (<strong>20</strong>06). Mater. Sci. Eng. A 433, 310-315.<br />

[3] K.L.Sahoo, C.S.Sivaramakrishnan and A.K.Chakrabarti, (<strong>20</strong>00). Met and Mater. Trans A, Vol.31, 1599-<br />

1610.<br />

[4] R. Noorani, Y. Farooque, T. Ioi,(<strong>20</strong>09). Improving Surface Roughness <strong>of</strong> CNC Milling Machined Aluminum<br />

Samples Due to Process Parameter Variation. International Network for Engineering Education and Research,<br />

ICEE_iCEER- international conference.<br />

[5] John A. Taylor, (<strong>20</strong>04). The Effect <strong>of</strong> Iron in Al-Si Casting Alloys. Australian Foundry Institute (AFI) , 35th<br />

Australian Foundry Institute National Conference, page 148-157.<br />

[6] D K Dwivedi,(<strong>20</strong>02). Indian Foundry Journal, Vol.-48, No.1, pp-32-38.<br />

570


1<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

MACHINING CHARACTERISTICS OF BOROSILLICATE GLASS<br />

USING TRAVELLING WIRE ELECTRO-CHEMICAL SPARK<br />

MACHINING (TW-ESCM) PROCESS<br />

Basanta Kumar Bhuyan 1 , Vinod Yadava 2<br />

Mechanical Engineering Department, Motilal Nehru National Institute <strong>of</strong> <strong>Technology</strong>, Allahabad, India<br />

E-mail: bkbhuyan@mnnit.ac.in<br />

2 Mechanical Engineering Department, Motilal Nehru National Institute <strong>of</strong> <strong>Technology</strong>, Allahabad, India<br />

E-mail: vinody@mnnit.ac.in<br />

Abstract<br />

Machining <strong>of</strong> borosilicate glass is a challenging task for manufacturing engineers from the quality and accuracy<br />

point <strong>of</strong> view. Traveling Wire Electro-Chemical Spark Machining (TW-ECSM) is an emerging technique in the<br />

field <strong>of</strong> non-conventional machining to machine electrically non-conductive materials. It is a hybrid process<br />

which combines features <strong>of</strong> Electro Chemical Machining (ECM) and Wire Electro Discharge Machining<br />

(WEDM). An experimental setup has been developed and employed for machining <strong>of</strong> borosilicate glass which<br />

was used as workpiece. In the present paper only the machining characteristics <strong>of</strong> non-conductive material is<br />

reported. Experiments were also conducted to analysis the effects <strong>of</strong> supply voltage, pulse on-time and<br />

electrolyte concentration on the material removal rate (MRR) and surface roughness (R a ). Material removal<br />

rate and surface roughness are found to increase with increase in supply voltage and pulse on-time. But<br />

MRR and R a increase with increase in electrolyte concentration at certain value (<strong>20</strong>%), beyond that value it<br />

decreases.<br />

Keywords : TW-ECSM, Borosilicate Glass, MRR and R a<br />

1. INTRODUCTION<br />

At the present time, borosilicate glass is gaining increasing importance in precision engineering application<br />

owing to its high strength to weight ratio, heat resisting capacity and high corrosion resistance. The main limiting<br />

factor for growing usage <strong>of</strong> this material is its limited structuring possibility. Chemical etching technologies are<br />

well established, though this process remains very slow and expensive for many industrial applications. Other<br />

processes like ultrasonic machining, abrasive jet machining, laser beam machining and electron beam machining<br />

are some <strong>of</strong> the advanced machining processes that can be used for machining these materials, but dimensional<br />

accuracy and good surface quality <strong>of</strong> the machined surfaces are the major concern. ECM and WEDM are also<br />

being used for electrically conductive materials and failed to machine non-conductive materials. A possible<br />

answer to machine this material with good surface quality is Traveling Wire Electro-Chemical Spark Machining<br />

(TW-ECSM). It is a new and potential process developed to machine non-conductive materials like glass,<br />

ceramic and composite etc. In this process also sparks are generated across the hydrogen bubbles evolved at<br />

cathode. Thermal energy <strong>of</strong> spark is utilized for cutting non-conducting materials such as glasses and ceramics<br />

[1]. TW-ECSM principle is based on electro-chemical spark machining (ECSM) process.<br />

Electro-chemical spark machining (ECSM) which combines the features <strong>of</strong> electro chemical machining and<br />

electro discharge machining, has stemmed from its ability to remove metal at high rates, as much as five and fifty<br />

times faster than ECM and EDM, respectively under the same parameter setting. A simple electro chemical cell<br />

consists <strong>of</strong> two electrodes dipped in the electrolyte. When an external potential is applied between the electrodes,<br />

electric current flows through the cell resulting in electrochemical reactions such as anodic dissolution, cathode<br />

deposition and electrolysis. This is known as Electro-Chemical Discharge (ECD) phenomenon. The electrochemical<br />

spark machining process uses ECD phenomenon for generating heat for the purpose <strong>of</strong> removing work<br />

material by melting and vaporization. This was presented for the first time in <strong>19</strong>68 by Kurafuji as<br />

“Electrochemical Discharge Drilling” for microholes in glass [2]. Several other names <strong>of</strong> ECSM are used in<br />

literature by different researchers, such as Electro chemical arc machining (ECAM), Electro chemical discharge<br />

machining (ECDM) and Spark assisted chemical engraving (SACE) [3]. The diversity <strong>of</strong> name illustrates the<br />

complexity <strong>of</strong> the process. Various researchers have put forth explanations <strong>of</strong> ECD phenomenon based on their<br />

experimental studies.<br />

Bhattacharya et al. [4] conducted experiments on alumina and concluded that the most effective parametric<br />

combination for moderately higher machining rate and dimensional accuracy are 80Vand 25% NaOH<br />

concentration. Tool tip geometry was also found to play an important role in a controlled spark generation in<br />

571


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

ECDM. H<strong>of</strong>y and McGeough [5] carried out experimental studies on the effects <strong>of</strong> mode <strong>of</strong> electrolyte flushing,<br />

wire erosion, machining speed on metal removal rate during TW-ECAM. Their recommendation was to use the<br />

coaxial mode <strong>of</strong> flushing for maintaining the machining action and its accuracy. Peng and Liao [6] verified that<br />

TW-ECDM can be applied for slicing meso-size non-conductive brittle materials <strong>of</strong> several millimeters thick.<br />

They have shown that pulsed DC power shows better spark stability and more spark energy than constant DC<br />

power. Jain et al. [7] carried out experiments on their self developed setup <strong>of</strong> TW-ECSM for cutting Glass epoxy<br />

and Kevlar epoxy composites using NaOH electrolyte. They found that the wire wear rate and the over-cut<br />

follow a similar behavior as the machining rate but the wire wear rate is about two magnitudes smaller than the<br />

MRR. It was also found that there was increase in MRR at higher voltage along with the presence <strong>of</strong> thermal<br />

cracks, large HAZ and irregular machined surfaces. They also tried to study the effect <strong>of</strong> artificially introducing<br />

some bubbles into the process during machining and found that the MRR as well as the over-cut decreases<br />

slightly. Yang et al. [8] carried out experimental study to improve the over-cut quality by adding SiC abrasive to<br />

the electrolyte. They discussed the effects <strong>of</strong> abrasive on expansion, roughness and MRR on the various<br />

machining parameters in Wire Electro-Chemical Discharge Machining (WECDM). Singh et al. [9] attempted to<br />

explore the feasibility <strong>of</strong> using TW-ECSM process for machining <strong>of</strong> electrically partially conductive materials<br />

like lead zirconate titanate and carbon fiber epoxy composites. They found that MRR increases with increase in<br />

supply voltage. MRR also increases with increase in concentration <strong>of</strong> the electrolyte up to around <strong>20</strong> wt. %.<br />

Beyond this concentration, it starts decreasing. They also observed that machined surface shows evidence <strong>of</strong><br />

melting. Large cracks are sometimes observed when the machining is done at higher voltage. However, such<br />

cracking is not seen at lower voltage<br />

In this work, an attempt has been made to develop a prototype model <strong>of</strong> TW-ECSM along with various<br />

indigenous basic components such as machining chamber, wire driving system, electrolyte supply system and<br />

power supply system. Experiments were conducted to machine non-conductive material at different supply<br />

voltage, pulse on-time and electrolyte concentration on material removal rate (MRR) and surface roughness (R a ).<br />

MRR and R a increase with increase in electrolyte concentration at certain value (<strong>20</strong>%), beyond that value it<br />

decreases.<br />

2. DEVELOPED EXPERIMENTAL TW-ECSM SETUP<br />

A tabletop Traveling Wire Electro-Chemical Spark Machining (TW-ECSM) setup has been developed<br />

successfully. Fig. 1 shows a schematic diagram <strong>of</strong> the TW-ECSM and Fig. 2 shows a photographic view <strong>of</strong> the<br />

experimental TW-ECSM setup. The setup has been designed keeping in view the fundamental mechanism <strong>of</strong> the<br />

process and basic functional requirements <strong>of</strong> different parts such as machining chamber, wire driving system,<br />

electrolyte supply system and power supply system.<br />

Wire and<br />

pulley<br />

Workpiece<br />

Stepper<br />

motor<br />

Take up<br />

spool<br />

Ball screw<br />

and slide<br />

Feed spool<br />

Stepper<br />

motor<br />

Ball screw<br />

and slide<br />

Take up<br />

spool<br />

Feed spool<br />

Electrolyte<br />

chamber<br />

Electrolyte<br />

supply<br />

DC Power<br />

supply<br />

Machining<br />

chamber<br />

Graphite<br />

DC power<br />

supply<br />

Fig. 1 Schematic Diagram <strong>of</strong> TW-ECSM<br />

Fig. 2 Photographic view <strong>of</strong> TW-ECSM<br />

572


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2.1. Machining Chamber<br />

The machining chamber <strong>of</strong> size 400mmx250mmx110mm is made <strong>of</strong> Plexiglass holds the electrolyte, as it is an<br />

electrically insulating, transparent and corrosion resistant material. The machining chamber is kept on the lower<br />

platform <strong>of</strong> a wooden table. On the middle wall <strong>of</strong> the machining chamber electrode positioning and job-feeding<br />

unit is fixed. At the bottom <strong>of</strong> machining chamber a hole is provided to drain out electrolyte from the chamber.<br />

Within machining chamber the tool electrode is just touching the non-conducting workpiece such as borosilicate<br />

glass. The auxiliary electrode is a vertical graphite rod and a horizontal scale is attached at the center <strong>of</strong> the top<br />

edge <strong>of</strong> the vertical rod. The horizontal scale is provided in order to measure the horizontal displacement <strong>of</strong> the<br />

auxiliary electrode which in turn helps to measure and control the inter electrode gap. In the base and side wall <strong>of</strong><br />

the machining chamber, pulleys are attached, which helps in movement <strong>of</strong> wire throughout machining chamber.<br />

The electrolyte reservoir is attached with the side wall <strong>of</strong> the machining chamber in order to supply electrolyte.<br />

The workpiece holder is made <strong>of</strong> Plexiglass. It is assembled with a depth control mechanism. A vertical up and<br />

down movement up to 45mm can be made to change the depth <strong>of</strong> the workpiece in the electrolyte by means <strong>of</strong><br />

this mechanism. A stepper motor is coupled to low friction ball screw to provide a very small and accurate feed<br />

movement to the workpiece. The workpiece feed can be changed by varying the speed <strong>of</strong> rotation <strong>of</strong> the stepper<br />

motor.<br />

2.2. Wire Driving System<br />

The wire driving system consists <strong>of</strong> a feed spool, a take-up spool, a set <strong>of</strong> pulleys and a stepper motor. The step<br />

angle <strong>of</strong> the stepper motor is 1.8º. The rpm <strong>of</strong> the stepper motor can be varied from 1 to 80. The programmable<br />

Logic Controller (PLC) is used to rotate the stepper motor smoothly. The input voltage to the stepper motor is<br />

24V and the input current to the stepper motor is 2.8A. The torque <strong>of</strong> the stepper motor is <strong>20</strong>kgcm. The wire<br />

electrode is fed towards the workpiece at a constant rate from a feed spool through a set <strong>of</strong> pulleys to the take-up<br />

spool. The pulley that is submerged in the electrolyte is made <strong>of</strong> Teflon. A stepper motor drives the take-up spool<br />

to pull the wire gently at a constant speed. An anode made <strong>of</strong> graphite is attached to the pulley mount and its<br />

distance from the cathode (wire) can be adjusted. The distance between two electrodes is 30-50mm from each<br />

other.<br />

2.3. Electrolyte Supply System<br />

The electrolyte supply system consists <strong>of</strong> a pump and a flow control valve. The electrolyte is supplied to the<br />

cutting site on the work specimen can be immersed thoroughly in the electrolyte. There are two different modes<br />

<strong>of</strong> electrolyte flushing, such as (a) electrolyte flushing perpendicular to wire and (b) electrolyte flushing coaxial<br />

with wire. The electrolyte is added to the machining chamber from the reservoir in the form <strong>of</strong> drops instead <strong>of</strong><br />

flow from pipe. If electrolyte is fed with high velocity, there will be no formation <strong>of</strong> insulating layer or gas<br />

bubbles. Hence for this thermal consideration the electrolyte should be added drop by drop.<br />

2.4. Power Supply System<br />

The power supply system consists <strong>of</strong> DC power supply and pulsating DC power supply. TW-ECSM demands for<br />

a voltage <strong>of</strong> 5 to 100V and current <strong>of</strong> 0 to 5A and frequency <strong>of</strong> 100 to 1 kHz depending on the rate <strong>of</strong> material<br />

removal and other machining criteria. Keeping the view <strong>of</strong> this need, a pulsed DC power supply has been<br />

developed. In the pulsed TW-ECSM process, a pulse generator is used to supply the voltage pulses across the<br />

electrodes. Pulsing is applied to this D.C by means <strong>of</strong> a timer control. The main 230 volts, 3 phases, AC power<br />

supply are converted to low voltage D.C power supply by a step down transformer and silicon controlled rectifier<br />

unit. The pulse on time varies from 0.2ms to 0.6ms and duty factor varies from <strong>20</strong>% to 60%. A single beam<br />

oscilloscope <strong>of</strong> 10MHz frequencies can observe the electric pulse form features. The voltage is able to maintain<br />

about 40V across the cathode tool-electrode and anodic auxiliary electrode. The positive terminal <strong>of</strong> the power<br />

supply unit is connected with auxiliary electrode and one end <strong>of</strong> the coil heating the electrolyte. The negative<br />

terminal <strong>of</strong> the power supply unit is connected with wire and the other end <strong>of</strong> a heating coil. Thus the<br />

temperature <strong>of</strong> the electrolyte is controlled electrically from <strong>20</strong> o C to 60 o C. The voltage and current can be<br />

recorded with a voltmeter and ammeter.<br />

3. PLANNING FOR EXPERIMENTATION<br />

An exhaustive pilot experiments <strong>of</strong> TW-ECSM have been conducted by varying supply voltage, pulse on-time<br />

and electrolyte concentration. Initial experiments were performed in borosilicate glass with graphite rod<br />

(diameter 8mm, length 55mm) as anode and brass wire <strong>of</strong> diameter 0.25mm as cathode. The size <strong>of</strong> borosilicate<br />

glass as a workpiece was 40mm×35mm×2mm. Workpiece was held at constant distance <strong>of</strong> about 35mm from the<br />

anode. Cathode (wire) was always kept in physical contact with the workpiece which was mounted on the<br />

supporting platform. The wire was broken frequently even at 55 volts because <strong>of</strong> its low current carrying<br />

573


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

capacity. Very low wire speed would lead to the situation similar to the stationary tool resulting in overheating<br />

and finally breaking <strong>of</strong> the wire. Too high wire speed was also not desirable because it would be uneconomical.<br />

Hence, wire was driven by stepper motor at a constant speed <strong>of</strong> 650mm/min. An aqueous solution <strong>of</strong> NaOH with<br />

different electrolyte solution at <strong>20</strong>ºC was used. NaOH has higher specific conductance, reactions take place at<br />

higher rates, so a larger amount <strong>of</strong> gases were evolved. Hence, higher MRR was achieved. Therefore, all the<br />

experiments reported in this paper were carried out using NaOH solution as electrolyte. Each experiment was<br />

tested for about 15 to <strong>20</strong> min, during which voltage and current were recorded on a voltmeter and ammeter,<br />

respectively. The minimum linear feed rate to the workpiece which could be achieved using the present setup<br />

was 0.008mm/s.<br />

The thermo mechanical phenomenon has also been identified as the main mechanism responsible for material<br />

removal and surface roughness in TW-ECSM. Voltage, pulse on-time and electrolyte concentration were<br />

considered as controllable variables and their effects on material removal rate and surface roughness were the<br />

responses <strong>of</strong> the process. For evaluation <strong>of</strong> MRR, the loss in weight <strong>of</strong> the machined specimen was measured on<br />

a weighing digital microbalance (accuracy 10 µg, CAS India Private Limited). After machining, the workpiece<br />

was washed, dried to evaporate any water remaining on the surface and reweighed using a weighing digital micro<br />

balance. The difference between the initial weight and the final weight was given the amount <strong>of</strong> material<br />

removed. The surface roughness characteristic was measured in terms <strong>of</strong> center line average values (R a ) using a<br />

surface texture meter by Taylor Hobson, UK. In this work, material removal rate in millimeter per minute and<br />

surface roughness in micrometer have been taken.<br />

4. RESULTS AND DISCUSSION<br />

The effects <strong>of</strong> major process variables such as supply voltage, pulse on-time and electrolyte concentration on<br />

material removal rate and surface roughness have been analyzed for obtaining the machining characteristics <strong>of</strong><br />

borosilicate glass when using TW-ECSM process.<br />

4.1. Influence <strong>of</strong> voltage on MRR and R<br />

a<br />

The effect <strong>of</strong> applied voltage on MRR in TW-ECSM process, for keeping other parameters constant is shown in<br />

Fig. 3. Here, it is observed that MRR increases with increase in various supplied voltage such as 45V, 50V and<br />

55V. There is no spark below 35V and wire randomly breaks above 55V. An increase in the applied voltage<br />

implies higher discharge energy per spark hence more heat generated resulting in enhanced MRR. However, with<br />

the increase in voltage the electrolysis process is accelerated hence, the rate <strong>of</strong> generation <strong>of</strong> hydrogen gas<br />

bubbles is increased and consequently the rate <strong>of</strong> generation <strong>of</strong> discharge energy increases. At high machining<br />

voltage, micro-cracks form on the work surface has been obtained.<br />

3.4<br />

3.2<br />

0.25mm Dia.<br />

3.0<br />

MRR (mm 3 /min)<br />

2.8<br />

2.6<br />

2.4<br />

2.2<br />

2.0<br />

40 45 50 55 60<br />

Voltage (V)<br />

Fig. 3 Effect <strong>of</strong> applied voltage on the MRR for the 0.25mm brass wire diameter<br />

574


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The effect <strong>of</strong> different applied voltage on surface roughness for keeping other parameter constant is shown in<br />

Fig. 4. The applied voltage considered for the experiments were 45V, 50V and 55V. R a increases with increase<br />

in applied voltage because at higher voltage, higher energy discharge takes place during sparking, which causes a<br />

deeper crater on the machined surface.<br />

15.0<br />

14.5<br />

14.0<br />

0.25mm Dia.<br />

13.5<br />

R a<br />

(µm)<br />

13.0<br />

12.5<br />

12.0<br />

11.5<br />

11.0<br />

40 45 50 55 60<br />

Voltage (V)<br />

Fig. 4 Effect <strong>of</strong> applied voltage on the R a for the 0.25mm brass wire diameter<br />

4.2. Influence <strong>of</strong> pulse on-time on MRR and R<br />

The MRR increases with increase in different pulse on-time for keeping other parameter constant as shown in<br />

Fig. 5. It is clear from the graph that pulse on-time affects the material removal rate, the MRR increases steadily<br />

with the increase in level <strong>of</strong> pulse on-time. The material removal rate is thus a function <strong>of</strong> the pulse on-time. The<br />

value <strong>of</strong> MRR is the lowest with the pulse on-time at 0.<strong>20</strong>ms and the highest with the pulse on-time at 0.40ms.<br />

An increase in the pulse on-time implies that more time has been allowed to machine the workpiece for a fixed<br />

duration, because only during pulse on-time material removal takes place. In alternate way, with an increase <strong>of</strong><br />

pulse on-time, average current density increases which leads to the increase <strong>of</strong> dissolution efficiency. Dissolution<br />

efficiency increases rapidly in the range <strong>of</strong> 0.<strong>20</strong>ms to 0.40ms causing a rapid increment <strong>of</strong> MRR in this zone.<br />

a<br />

1.<strong>20</strong><br />

1.18<br />

0.25mm wire Dia.<br />

1.16<br />

MRR (mm 3 /min)<br />

1.14<br />

1.12<br />

1.10<br />

1.08<br />

1.06<br />

1.04<br />

0.<strong>20</strong> 0.25 0.30 0.35 0.40<br />

T ON<br />

(ms)<br />

Fig. 5 Effect <strong>of</strong> pulse on-time on the MRR for the 0.25mm brass wire diameter<br />

The experiments have been carried out with varying pulse on-time at 0.25mm brass wire diameter. Fig. 6<br />

illustrates that surface roughness increases with increase in pulse on-time. R a increases with increase in pulse on-<br />

575


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

time <strong>of</strong> 0.<strong>20</strong>ms to 0.40ms. Because higher energy discharge takes place during sparking, results more amount <strong>of</strong><br />

heat energy penetrating into the workpiece which causes larger crater on the machined surface. Hence, R a<br />

increases with increase in pulse on-time. The graph clearly shows that the lowest value <strong>of</strong> R a =11.2µm and the<br />

highest value <strong>of</strong> R a =14.8µm.<br />

15.0<br />

14.5<br />

0.25mm wire Dia<br />

14.0<br />

13.5<br />

R a<br />

(µm)<br />

13.0<br />

12.5<br />

12.0<br />

11.5<br />

11.0<br />

4.3. Influence <strong>of</strong> electrolyte concentration on MRR and R<br />

a<br />

MRR increases with an increase in electrolyte concentration up to <strong>20</strong>% i.e. <strong>20</strong>0g/l and then starts decreasing.<br />

This is due to the fact that the specific conductance <strong>of</strong> NaOH solution increases upto <strong>20</strong> percent concentration,<br />

beyond which its start decreasing as shown in Fig. 7. An increase in specific conductance means increased<br />

electrolyte conductivity and consequently more current. An increase in electrolytic current would mean the<br />

accelerated electrolysis process. It would result in a greater rate <strong>of</strong> evolution <strong>of</strong> hydrogen gas bubbles at the<br />

cathode. The increased rate <strong>of</strong> formation <strong>of</strong> gas bubbles at the cathode implies an enhanced rate <strong>of</strong> sparking and<br />

hence higher MRR<br />

2.34<br />

0.<strong>20</strong> 0.25 0.30 0.35 0.40<br />

T ON<br />

(ms)<br />

Fig. 6 Effect <strong>of</strong> pulse on-time on the R a for the 0.25mm brass wire diameter<br />

2.33<br />

2.32<br />

0.25mm Dia.<br />

2.31<br />

MRR (mm 3 /min)<br />

2.30<br />

2.29<br />

2.28<br />

2.27<br />

2.26<br />

2.25<br />

1<strong>20</strong> 140 160 180 <strong>20</strong>0 2<strong>20</strong> 240 260 280<br />

Electrolyte concentration (g/l)<br />

Fig. 7 Effect <strong>of</strong> electrolyte concentration on the MRR for the 0.25mm brass wire diameter<br />

The effect <strong>of</strong> electrolyte concentration on surface roughness in TW-ECSM process, for keeping other parameters<br />

constant is shown in Fig. 8. The electrolyte concentration considered for the experiments were 150g/l, <strong>20</strong>0g/l and<br />

250g/l. The reason for this variation is that the specific conductance <strong>of</strong> NaOH solution increases upto <strong>20</strong>0g/l<br />

electrolyte concentration, beyond which it starts decreasing. An increase in specific conductance means an<br />

increased electrolyte conductivity, which results more circuit current. At higher values <strong>of</strong> circuit current means<br />

more heat energy penetrates into the workpiece and consequently larger value <strong>of</strong> depth <strong>of</strong> crater. But beyond at a<br />

576


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

certain value <strong>of</strong> electrolyte concentration i.e. (<strong>20</strong>0g/l), change in the circuit current decreases. Therefore, heat<br />

energy developed from the spark is proportional to the circuit current and surface roughness will be decreased at<br />

higher values <strong>of</strong> electrolyte concentration<br />

9.2<br />

9.1<br />

0.25mm Dia.<br />

9.0<br />

8.9<br />

R a<br />

(µm)<br />

8.8<br />

8.7<br />

8.6<br />

8.5<br />

140 160 180 <strong>20</strong>0 2<strong>20</strong> 240 260<br />

Electrolyte concentration (g/l)<br />

Fig. 8 Effect <strong>of</strong> electrolyte concentration on the R a for the 0.25mm brass wire diameter<br />

5. CONCLUSIONS<br />

The following conclusions are drawn as listed below,<br />

1. An inhouse TW-ECSM experimental setup has been developed to slice non-conducting hard and brittle<br />

materials.<br />

2. MRR and R a have been found to increase with an increase in supply voltage. It has also been observed<br />

that an increase in MRR at higher voltage and R a is less at lower voltage.<br />

3. With increase in pulse on-time, there is an increase in material removal rate and surface roughness. It has<br />

also been observed that MRR is more at pulse on-time 0.40ms and Ra<br />

is less at pulse on-time 0.<strong>20</strong>ms.<br />

4. MRR also increases with an increase in electrolyte concentration upto around <strong>20</strong> percent. After this it<br />

starts decreasing because <strong>of</strong> higher concentration the specific conductivity <strong>of</strong> NaOH decreases.<br />

ACKNOWLEDGEMENT<br />

Authors thanks to the financial support provided by the Council <strong>of</strong> Scientific and Industrial Research (CSIR),<br />

New Delhi, for the experimental work <strong>of</strong> the project entitled “Experimental and Numerical Study <strong>of</strong> Traveling<br />

Wire Electrochemical Spark Machining <strong>of</strong> Advanced Engineering Materials”.<br />

REFERENCES<br />

[1] H. Tsuchiya, T. Inoue and M. Miyazaiki, (<strong>19</strong>85) Wire electrochemical discharge machining <strong>of</strong> glasses and<br />

ceramics, Bullet. Jap. S. Prec. Eng., <strong>19</strong>: 73-74.<br />

[2] H. Kurafuji and K. Suda, Electrical discharge drilling <strong>of</strong> glass, Ann. CIRP, 16: 415–4<strong>19</strong> <strong>19</strong>68.<br />

[3] R. Wuthrich and V. Fascio, (<strong>20</strong>05) Machining <strong>of</strong> non-conducting materials using electrochemical discharge<br />

phenomenon-an overview, Int. J. Mach. Tools Manuf., 45: 1095-1108.<br />

[4] B. Bhattacharyya, B.N. Doloi and S.K. Sorkhel, (<strong>19</strong>99) Experimental investigations into electrochemical<br />

discharge machining (ECDM) <strong>of</strong> non-conductive ceramic materials, J. Mater. Process. Technol., 95: 145-<br />

154.<br />

[5] H. El. H<strong>of</strong>y and J. A. McGeough, (<strong>19</strong>88) Evaluation <strong>of</strong> an Apparatus for Electrochemical Arc Wire-<br />

Machining, J. Eng. Ind., 110: 1<strong>19</strong>-123.<br />

[6] W. Y. Peng and Y. S. Liao, (<strong>20</strong>04) Study <strong>of</strong> electrochemical discharge machining technology for slicing<br />

non-conductive brittle materials, J. Mater. Process. Technol., 149: 363-369.<br />

[7] V. K. Jain, P. S. Rao, S. K. Choudhury and K. P. Rajurkar, (<strong>19</strong>91) Experimental investigations into traveling<br />

wire electrochemical spark machining (TW-ECSM) <strong>of</strong> composites, ASME Trans., J. Eng. Ind., 113: 75-84.<br />

577


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[8] C.T. Yang, S.L. Song, B.H. Yan and F.Y. Huang, (<strong>20</strong>06) Improving machining performance <strong>of</strong> wire<br />

electrochemical discharge machining by adding SiC abrasive to electrolyte, Int. J. Mach. Tools Manuf., 46:<br />

<strong>20</strong>44-<strong>20</strong>50.<br />

[9] Y.P. Singh, Vijay K. Jain, Prashant Kumar and D.C. Agrawal, (<strong>19</strong>96) Machining piezoelectric (PZT)<br />

ceramics using an electrochemical spark machining (ECSM) process, J. Mater. Process. Technol., 58: 24-31.<br />

578


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

MECHANICAL PROPERTIES OF FRICTION STIR WELDED<br />

DISSIMILAR METALS<br />

Ratnesh Kumar Raj Singh 1 , Rajesh Prasad 2 , Sunil Pandey 3<br />

1 Research Scholar, IIT Delhi, New Delhi, India<br />

2 Associate Pr<strong>of</strong>essor, Department <strong>of</strong> Applied Mechanics, IIT Delhi, New Delhi, India<br />

3 Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, IIT Delhi, New Delhi, India<br />

Abstract<br />

The aim <strong>of</strong> present study was to analyse the influence <strong>of</strong> the microstructures and mechanical properties <strong>of</strong><br />

friction stir welded butt joint <strong>of</strong> 6101 aluminium alloy and pure copper plates in 3 mm thickness. With this aim,<br />

welds were produced using Tungsten Carbide tools, with a cylindrical pin tool having 5 mm and <strong>20</strong> mm diameter<br />

<strong>of</strong> pin and shoulder respectively. Copper plates were kept in advancing side <strong>of</strong> weld. The microstructure <strong>of</strong> weld<br />

were studied by optical microscopy and grain size in different regions were analyze. Vicker’s microhardness test<br />

(as per ASTM E384-89) were done in transverse direction <strong>of</strong> weld to check the hardness distribution in weld<br />

nugget. Transverse tensile test (as per ASTM E8 M) were performed to evaluate the weakest portion <strong>of</strong> weld<br />

joints. Scanning Electron Microscope were used to observe the fracture surfaces. EDAX analysis were done to<br />

find out the mixing characteristic <strong>of</strong> two metals.<br />

Key words: Friction Stir Welding, Aluminium alloy, Pure Copper, Hardness, Tensile testing<br />

1. Introduction<br />

The joints <strong>of</strong> dissimilar materials are widely used in industrial applications due to their technical and beneficial<br />

advantages [1]. Aluminium and copper are two common metals in the electric power industry, and the Al–Cu<br />

transition pieces are widely used to Transmit the electricity. Due to the difficulties in making an electrically<br />

stable bolted joint between these two dissimilar metals, much effort has been focused on welding aluminium to<br />

copper in the last decades [2]. However, the dissimilar combination <strong>of</strong> aluminium and copper is generally<br />

difficult for fusion welding. This is because <strong>of</strong> the wide difference in their physical, chemical and mechanical<br />

properties, and the tendency to form brittle intermetallic compounds (IMCs). Therefore, the solid-state joining<br />

methods, such as friction welding, roll welding, and explosive welding have received much attention [2–7].<br />

These methods, however, have a few drawbacks. Fox example, friction welding and roll welding lack versatility,<br />

and explosive welding involves in the safety problems. In the past decade, much attention has been directed<br />

towards friction stir welding (FSW) [8]. Recently, attempts have been made to join dissimilar materials through<br />

FSW, such as aluminium to steel, aluminium to magnesium, and aluminium to copper [9–16]. It was reported<br />

that sound dissimilar FSW Al–Cu joints were difficult to achieve, and the joints usually failed at the nugget zone<br />

or along the TMAZ.<br />

2. Difficulties in Welding <strong>of</strong> Copper to Aluminium<br />

Copper and aluminium are widely applied in engineering structure due to unique performances such as higher<br />

electric conductivity, heat conductivity, corrosion resistance and mechanical properties. However, the melting<br />

points <strong>of</strong> both materials have a significant difference (nearly 400 °C). This may lead to a large difference in<br />

microstructure and performance <strong>of</strong> Cu–Al joints if copper and aluminium would be joined. Moreover, the Al was<br />

easily oxidized at an elevated temperature, and some welding cracks existed easily in a joint <strong>of</strong> brazed or fusion<br />

welding Cu [1]. Therefore, a high quality weld joint <strong>of</strong> Cu/Al was difficult to obtain by means <strong>of</strong> conventional<br />

welding methods. During fusion welding or pressure welding (brazing, diffusion bonding, etc), the Cu-Al<br />

intermetallics, which resulted in decreased mechanical properties <strong>of</strong> joints, is very difficult to be avoided in<br />

Cu/Al dissimilar materials joint [2,3].<br />

3. Experimental Setup<br />

The plate size <strong>of</strong> aluminium and copper are same and having 150 mm length, 50 mm width and 3 mm thickness.<br />

Tungsten Carbide tool having shoulder diameter <strong>of</strong> <strong>20</strong> mm and pin diameter <strong>of</strong> 7 mm. Detail <strong>of</strong> Tool are given in<br />

Table 1. Two welding sets were taken for welding <strong>of</strong> aluminium-copper plates as given in Table 2.<br />

4. Welding<br />

Prior to welding, joint preparation were used when needed by machining, grinding and cleaning (with acetone)<br />

<strong>of</strong> the surfaces to be weld. The plates were clamped tightly against each other by indigenously designed and<br />

fabricated fixtures and on the backing plate. The axial plunge depth was manually controlled by dial gauge<br />

579


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

indicator. tool tilt angle were kept constant and it is around 1.5 0 . Initially trial welds were conducted with bead<br />

on plate configuration using different welding parameters to set a range <strong>of</strong> suitable welding parameters for our<br />

final welds.<br />

5. Sample preparation<br />

The welded pieces are first cut in the transverse direction <strong>of</strong> weld in required dimensions. Sample for<br />

microstructural analysis were polished with different grades <strong>of</strong> waterpro<strong>of</strong> SiC polishing paper ranging from<br />

grade 2<strong>20</strong> to grade <strong>20</strong>00 and finally polished on s<strong>of</strong>t cloth with alumina paste.<br />

Table 1: Tool Dimension<br />

Tool Material- Tungsten Carbide<br />

Tool Drawing<br />

Shoulder diameter (D)- <strong>20</strong>mm<br />

Pin diameter (d) - 7 mm<br />

Pin length (L)- 2.7 mm<br />

Axial Plunge <strong>of</strong> Shoulder- 0.2 mm<br />

Table 2: Welding Parameter<br />

Weld<br />

Rotation Speed<br />

(rpm)<br />

Welding Speed<br />

(mm/min)<br />

Weld 1<br />

125 50<br />

Weld 2 710 355<br />

6. Optical Microscopy<br />

Optical microscopy was performed using Leica microscope. Samples were first dipped in a polishing solution<br />

containing 55ml orthophosporic acid, 25ml acetic acid and <strong>20</strong> ml nitric acid heated to 70 °C. Then the polished<br />

sample were washed in water and then etched with a solution containing 100 ml water, 50 ml hydrochloric acid<br />

and 5gm ferric chloride.<br />

7. Hardness Measurements<br />

Leica’s Vicker’s micro hardness tester was used to measure the micro hardness <strong>of</strong> welded samples. The hardness<br />

were measured along the transverse direction <strong>of</strong> the weld in centre. Indentation force used was 100 gmf and<br />

indentation time was 10 seconds, step size used was 0.3 mm (as per ASTM E384-89).<br />

580


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

8. Tensile Tests<br />

The transverse tensile tests <strong>of</strong> 3 mm thick Cu/Al FSW welds were performed using an MTS 810 testing machine<br />

according to the standard SFS-EN 895. The standard is for fusion welds, but it is applicable also for friction stir<br />

welds. Subsize transverse test specimens according to ASTM E8M-11 were used. The strain rate was 1.6 x 10 -<br />

3 /s. Three samples were tested in each <strong>of</strong> weld and average is presented. Fig.1 , shows the geometry and<br />

dimensions <strong>of</strong> the sub-size transverse tensile test specimens.<br />

9. Results and Discussion<br />

Fig.1 Sub-size transverse tensile test specimens.<br />

9.1. Welds Obtained<br />

Welds were obtained according to the experimental design. All welds were defect free. The intermixing <strong>of</strong><br />

metals were also found in the welded samples. During the FSW process, the materials were transported from the<br />

retreating side to advancing side behind the pin where the weld was formed. Hardness <strong>of</strong> the cupper was larger<br />

than the aluminium, and due to the pin stirring action the aluminium get displaced in the weld.<br />

9.2. Microstructural Characteristics<br />

Microstructure <strong>of</strong> weld shows distingue feature in different zone (Fig.2). At the weld centre line mix region <strong>of</strong><br />

Aluminium and copper were found. Small particles <strong>of</strong> aluminium and copper were distributed in opposite side by<br />

the stirring forces <strong>of</strong> tool. Thermo mechanically affected zone (TMAZ) is clearly obtain in Copper but it were<br />

not found in aluminium. In both the metals Heat affected zone (HAZ) is not clear.<br />

9.3. Hardness Measurements<br />

Fig.3 shows the horizontal hardness pr<strong>of</strong>iles <strong>of</strong> the Cu/Al FSW welds. In the horizontal hardness pr<strong>of</strong>iles the<br />

hardness values were found to be around 106 for copper base metal & 110 for aluminium base metal. The<br />

hardness value was stable for the both metal in HAZ and tendency to increase in the nugget zone and it may due<br />

to the formation <strong>of</strong> intermatelic compound. Sample 1 showed the highest hardness values for the nugget zone,<br />

which was found to be around 127. Other samples had hardness values <strong>of</strong> around 85-1<strong>20</strong> in nugget zone.<br />

a<br />

581


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

b<br />

Fig.2 Microstructure <strong>of</strong> (a) NZ and (b)TMAZ<br />

Hardness HV 100<br />

125<br />

Weld 1<br />

1<strong>20</strong><br />

115<br />

Weld 2<br />

110<br />

105<br />

100<br />

95<br />

90<br />

85<br />

80<br />

75<br />

-25 -15 -5 5 15 25<br />

Distances from center (mm)<br />

Fig.3 Hardness pr<strong>of</strong>iles horizontally along the centre line <strong>of</strong> the sample<br />

9.4. Tensile Test<br />

Average tensile properties <strong>of</strong> friction stir weld joints <strong>of</strong> Cu/Al are given in Table 3. Sample 1 has the higher<br />

ultimate tensile strength <strong>of</strong> 138.7 MPa than sample 2 (135.5 MPa). Sample 2 had the higher strain <strong>of</strong> 3.1% while<br />

sample 1 have lower strain <strong>of</strong> 2.4%.<br />

Weld<br />

Table 3: Tensile test data<br />

Ultimate<br />

Tensile<br />

Strength (MPa)<br />

Yield<br />

Strength<br />

(MPa)<br />

Strain<br />

(%)<br />

1 138.6 100.31 2.4<br />

2 135.5 91.92 3.1<br />

582


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

10. Conclusions<br />

All welds were defect free and no tool metal inclusions were seen by optical microscopy. Microstructures <strong>of</strong><br />

weld were shown different regions, like TMAZ and Nugget Zone. Microhardness in weld nugget is higher than<br />

base metal and no significant difference found in other regions. Tensile strength <strong>of</strong> weld is very poor as compare<br />

to both <strong>of</strong> the base metals and all welds were fail from nugget zone. The ductility <strong>of</strong> is also very poor and<br />

comparable to the base metals.<br />

References:<br />

[1] Sun Y. F., and Fujii H., <strong>20</strong>10, “Investigation <strong>of</strong> the welding parameter dependent microstructure and<br />

mechanical properties <strong>of</strong> friction stir welded pure copper,” Materials <strong>Science</strong> and Engineering: A, 527(26),<br />

pp. 6879-6886.<br />

[2] Lee W.-bae, and Jung S.-boo, <strong>20</strong>04, “The joint properties <strong>of</strong> copper by friction stir welding,” Materials<br />

Letters, 58, pp. 1041-1046.<br />

[3] Amanci<strong>of</strong>ilho S., Sheikhi S., Dossantos J., and Bolfarini C., <strong>20</strong>08, “Preliminary study on the microstructure<br />

and mechanical properties <strong>of</strong> dissimilar friction stir welds in aircraft aluminium alloys <strong>20</strong>24-T351 and 6056-<br />

T4,” Journal <strong>of</strong> Materials Processing <strong>Technology</strong>, <strong>20</strong>6(1-3), pp. 132-142.<br />

[4] Kati Savolainen, <strong>20</strong>12, “Friction Stir Welding <strong>of</strong> Copper and Microstructure and Properties <strong>of</strong> the Welds,”<br />

DOCTORAL DISSERTATIONS.<br />

[5] Kumar R., Singh K., and Pandey S., <strong>20</strong>12, “Process forces and heat input as function <strong>of</strong> process parameters<br />

in AA5083 friction stir welds,” Transactions <strong>of</strong> Nonferrous Metals Society <strong>of</strong> China, 22(2), pp. 288-298.<br />

[6] Mishra R. S., and Ma Z. Y., <strong>20</strong>05, “Friction stir welding and processing,” Materials <strong>Science</strong> and<br />

Engineering: R: Reports, 50(1-2), pp. 1-78.<br />

[7] Rajakumar S., Muralidharan C., and Balasubramanian V., <strong>20</strong>11, “Predicting tensile strength, hardness and<br />

corrosion rate <strong>of</strong> friction stir welded AA6061-T6 aluminium alloy joints,” Materials & Design, 32(5), pp.<br />

2878-2890.<br />

[8] Shen J. J., Liu H. J., and Cui F., <strong>20</strong>10, “Effect <strong>of</strong> welding speed on microstructure and mechanical properties<br />

<strong>of</strong> friction stir welded copper,” Welding Production, 31, pp. 3937-3942.<br />

[9] Hwang Y. M., Fan P. L., and Lin C. H., <strong>20</strong>10, “Experimental study on Friction Stir Welding <strong>of</strong> copper<br />

metals,” Journal <strong>of</strong> Materials Processing <strong>Technology</strong>, 210(12), pp. 1667-1672.<br />

[10]Colligan K. J., and Mishra R. S., <strong>20</strong>08, “A conceptual model for the process variables related to heat<br />

generation in friction stir welding <strong>of</strong> aluminum,” Scripta Materialia, 58, pp. 327-331.<br />

[11]Sakthivel T., and Mukhopadhyay J., <strong>20</strong>07, “Microstructure and mechanical properties <strong>of</strong> friction stir welded<br />

copper,” Journal <strong>of</strong> Materials <strong>Science</strong>, 42(<strong>19</strong>), pp. 8126-8129.<br />

[12]Cavaliere P., Campanile G., Panella F., and Squillace a., <strong>20</strong>06, “Effect <strong>of</strong> welding parameters on mechanical<br />

and microstructural properties <strong>of</strong> AA6056 joints produced by Friction Stir Welding,” Journal <strong>of</strong> Materials<br />

Processing <strong>Technology</strong>, 180(1-3), pp. 263-270.<br />

[13] Lakshminarayanan A. K., and Balasubramanian V., <strong>20</strong>10, “An assessment <strong>of</strong> microstructure, hardness,<br />

tensile and impact strength <strong>of</strong> friction stir welded ferritic stainless steel joints,” Materials & Design, 31(10),<br />

pp. 4592-4600.<br />

[14] Elangovan K., Balasubramanian V., and Babu S., <strong>20</strong>09, “Predicting tensile strength <strong>of</strong> friction stir welded<br />

AA6061 aluminium alloy joints by a mathematical model,” Materials & Design, 30(1), pp. 188-<strong>19</strong>3.<br />

[15] Sun Y. F., and Fujii H., <strong>20</strong>10, “Investigation <strong>of</strong> the welding parameter dependent microstructure and<br />

mechanical properties <strong>of</strong> friction stir welded pure copper,” Materials <strong>Science</strong> and Engineering: A, 527(26),<br />

pp. 6879-6886.<br />

[16] Avula D., Kumar R., and Singh R., <strong>20</strong>11, “Effect <strong>of</strong> Friction Stir Welding on Microstructural and<br />

Mechanical Properties <strong>of</strong> Copper Alloy,” Scanning Electron Microscopy, pp. 214-223.<br />

583


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

MICROSTRUCTURE AND WELDABILITY EVALUATION OF<br />

DISSIMAILAR METAL JOINT USING PASTE TECHNIQUE FOR<br />

BUTTERING LAYERS<br />

Dinesh Rathod 1 , Hariom Choudhary 2 , Sunil Pandey 3<br />

1. Research Scholar, Department <strong>of</strong> Mechanical Engineering, IIT Delhi; Email:dineshvrathod@gmail.com<br />

2 .Research Scholar, Department <strong>of</strong> Mechanical Engineering, IIT Delhi<br />

3. Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, IIT Delhi<br />

Abstract<br />

The main objective <strong>of</strong> present work was to study the micro-structural changes due to buttering deposit on AISI<br />

10<strong>20</strong> steel for dissimilar metal joint <strong>of</strong> AISI 10<strong>20</strong> steel to SS 304 steel. Dissimilar metal joints are extensively<br />

used in many industrial applications but due to weldability related issues, they cannot perform satisfactory life.<br />

The difference in chemical composition, coefficient <strong>of</strong> thermal expansion and mechanical properties affects the<br />

weldability <strong>of</strong> the joint. For maintaining elemental compatibility, buttering technique is <strong>of</strong>ten used for such joint.<br />

It is quite difficult to select the consumables for the buttering layers, which will satisfy the requirement <strong>of</strong><br />

desirable chemical composition. Carbon migration is one <strong>of</strong> the major causes for buttering layer deposits. Nickel<br />

act as a barrier for carbon migration, so paste technique was used to deposit the buttering layer. The paste was<br />

prepared with Nickel powder, ferro-vanadium and ferro-titanium powders and deposited using Tungsten Inert<br />

Gas (TIG) welding and Shielded Metal Arc (SMAW) welding. Subsequent layer deposit was made using SMAW<br />

using Inconel 182 consumables. Weld joint was prepared between said base metals using SMAW process and<br />

Metal Inert Gas (MIG) welding. Micro-structural analysis and micro-hardness analysis were carried out. Nickel<br />

rich paste layer deposited using TIG observed micro-cracks or solidification cracks. When deposited with<br />

SMAW, due to dilution effect, nickel composition reduced and ferrite content changes in buttering layer hence no<br />

any cracks observed. Nickel paste with controlled parameters with direct deposit using SMAW can be<br />

successfully applied for such dissimilar metal joints.<br />

Keywords: Paste technique, Dissimilar Metal Joint, Buttering, Carbon migration, welding<br />

1. Introduction<br />

The use <strong>of</strong> welding in the world <strong>of</strong> technology is extensive. It has a phenomenal rise since <strong>19</strong>30; this growth<br />

has been faster than the general industrial growth. Practical applications <strong>of</strong> welding include automobile cars,<br />

aircrafts, ships, nuclear power plants, refineries, electronic equipment, machinery, household appliances, etc.<br />

Dissimilar joints between Austenitic Stainless steel and carbon steel are extensively utilized in many applications<br />

in energy conversion systems. In central power stations, in nuclear reactors and in petrochemical plants the<br />

parts <strong>of</strong> the boilers that are subjected to lower temperature are made <strong>of</strong> carbon steel for economic reasons.<br />

The other parts, operating at higher temperatures, are constructed with austenitic stainless steel. Therefore, the<br />

transition welds are needed between the two materials. The various techniques have been developed to join<br />

different materials by welding but still joining <strong>of</strong> dissimilar metals Austenitic Stainless steel with carbon Steel by<br />

welding is the bottleneck. The reason is that the metallurgical factors like Thermal expansion, galvanic<br />

corrosion, Metallurgical stability due to properties <strong>of</strong> alloy phases as well as dilution and design factors must be<br />

viewed in terms <strong>of</strong> how the joint will operate under specific stresses and environments.<br />

Ul-Hamid et. al. investigated the failure mechanism for carbon steel and SS 304 pipe material and reported the<br />

failure due to development <strong>of</strong> high hardness localised region <strong>of</strong> martensite. It was also reported that, the crack<br />

propagation occurs in decarburised region <strong>of</strong> carbon steel.[1] Carbon steel HAZ weakened due to carbon<br />

migration and the low oxidation resistance <strong>of</strong> ferritic/carbon steel at elevated temperature increases the<br />

susceptibility to low ductility failure for oxide notch effect.[2] The Ni base filler metals reduces the thermal<br />

stresses and also reduce the extent <strong>of</strong> carbon migration due to decrease in carbon activity gradient and low<br />

diffusion coefficient <strong>of</strong> carbon in Ni base alloys.[3] The Nickel base filler cannot completely prohibit the<br />

formation <strong>of</strong> s<strong>of</strong>t zone (carbon denuded) but it can greatly decrease the growth rate <strong>of</strong> s<strong>of</strong>t zone.[4]<br />

Carbon migration mainly occurs due to elemental differences, especially due to chromium content in weld and<br />

base metal. Carbon diffusion from low chromium base metal side to high chromium side (filler metal) and<br />

forms chromium carbide adjacent to the weld interface. Lundin reported that, carbon depleted zone appears in<br />

the carbon / ferritic steel material adjacent to fusion line and carbon enriched zone occurs in the stainless steel<br />

or Ni base filler metal. These zones are not present in the as welded conditions (diluted) but appears as after<br />

PWHT or elevated temperature exposure.[5] Carbon migration resulting from the dilution due to welding<br />

584


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

process and the consequent formation <strong>of</strong> an alloy having neither the composition <strong>of</strong> base metal nor that <strong>of</strong><br />

consumable. The Nickel filler barrier reduced but did not prevent carbon migration.[6]<br />

In dissimilar austenitic stainless steel and carbon steel welded joint, weld metal and HAZ were subdivided into<br />

austenitic single phase, austenite and martensite mixture, martensite like structure, ferrite and pearlite like<br />

structure and small grained fine pearlite. This caused due to the convection and stirring effect and the diffusion<br />

process during welding cycle.[7] Taban et. al. was worked on ferritic stainless steel and carbon steel dissimilar<br />

joint. The satisfactory welding was done without any defect despite <strong>of</strong> any buttering layer on carbon steel.[8]<br />

Nickel base filler metals are <strong>of</strong>ten used to prolong the life <strong>of</strong> austenitic / ferritic dissimilar welds. The use <strong>of</strong><br />

nickel base filler metals produces the thinner martensite layer compared to stainless steel filler metals due to<br />

steeper concentration gradient in partially mixed zone compared to Fe- based austenitic alloys.[9] Due to such<br />

various problems encountered in welding <strong>of</strong> carbon steel to stainless steel, this work is carried out to control the<br />

chemical changes in buttered layer as well as in weld metal.<br />

2. Experimental Procedure<br />

AISI 10<strong>20</strong> and SS304 plates <strong>of</strong> size 150mm x 50mm x 10mm were used in this work. The chemical composition<br />

<strong>of</strong> base metals and filler metals are given in Table 1. Weld deposit <strong>of</strong> 6mm thickness was buttered on one <strong>of</strong> the<br />

edge <strong>of</strong> 10mm thick AISI 10<strong>20</strong> plates using Nickel paste as a initial layer on both plates. For both <strong>of</strong> the plates A<br />

and B, the Nickel powder paste composition was kept same as 100gm Ni + 5gm Fe-V + 5gm Fe-Ti with<br />

potassium silicate as binder.<br />

Table 1- Chemical Composition (wt %) <strong>of</strong> materials used<br />

Element / Material AISI 10<strong>20</strong> SS304 Inconel 182 Inconel 82<br />

Fe 98.75 73.65 9.708 7.515<br />

C 0.<strong>20</strong>7 0.101 0.03 0.022<br />

Si 0.141 0.369 0.744 0.582<br />

Mn 0.391 0.30 9.081 2.863<br />

Cr 0.038 14.34 14.26 16.71<br />

Ni 0.023 9.446 62.51 68.35<br />

Mo - 0.025 0.592 -<br />

V - 0.054 - -<br />

Cu 0.102 0.106 0.01 0.013<br />

P 0.035 0.055 0.014 0.003<br />

S 0.0293 0.011 0.01 0.001<br />

Co - - 0.234 0.255<br />

Nb+Ta - - 1.661 2.45<br />

W - - 0.322 0.084<br />

After drying <strong>of</strong> paste, the paste <strong>of</strong> first plate A was melted using GTAW process and subsequent built up was<br />

made by SMAW process using 4mm dia. Inconel 182 electrode. The paste on second plate B was directly melted<br />

by SMAW process using Inconel 182 electrode and the subsequent deposit as well. The process parameters used<br />

for buttering operation are given in Table 2.<br />

Process<br />

Plate A<br />

Table 2- Process Parameters used for Buttering <strong>of</strong> Ni paste and deposit on AISI 10<strong>20</strong><br />

Electrode Layer Current Voltage Welding Polarity<br />

(amps) (Volts) Speed<br />

(mm/sec)<br />

Gas flow<br />

rate<br />

(lit/min)<br />

GTAW - Ni paste 1<strong>20</strong> 10-12 0.887 DCEN 8-9<br />

SMAW Inconel 182 ɸ 1 112 27-32 0.882 DCEP -<br />

4 mm<br />

SMAW - do - 2 109 25-30 0.728 DCEP -<br />

SMAW - do - 3 109 25-30 0.753 DCEP -<br />

SMAW - do - 4 109 25-30 0.778 DCEP -<br />

Process Plate<br />

B<br />

Electrode Layer Current<br />

(amps)<br />

Voltage<br />

(Volts)<br />

Welding<br />

Speed<br />

(mm/sec)<br />

- - Ni paste - - - -<br />

Polarity<br />

585


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

SMAW Inconel 182 ɸ 1 112 27-32 0.886 DCEP<br />

4 mm<br />

SMAW - do - 2 109 25-30 0.756 DCEP<br />

SMAW - do - 3 109 25-30 0.789 DCEP<br />

SMAW - do - 4 109 25-30 0.772 DCEP<br />

The buttered faces were then machined to a square edge. The SS304 plates were machined with 45 o single bevel<br />

edge with 1 mm land. The dissimilar plates <strong>of</strong> SS304 and buttered AISI 10<strong>20</strong> were then setup for 45o single half<br />

V-type groove geometry (Fig.1).<br />

Figure 1- Schematic diagram <strong>of</strong> AISI 10<strong>20</strong> / SS304 weld pad showing Ni paste and Inconel buttering and edge<br />

preparation<br />

The root pass welding was carried out using GTAW process with Inconel 82 filler wires, no any hot cracking and<br />

related defects was observed during root welding <strong>of</strong> both plates. Subsequently fill passes were carried out using<br />

Inconel 182 electrode with SMAW process. The process parameters for root pass and fill pass were same for<br />

both <strong>of</strong> the plate joints and given in Table 3.<br />

After completion <strong>of</strong> welding, non-destructive testing like dye penetrant test was carried out for both plate joints<br />

A and B. The samples for metallographic examination and micro-hardness examination were cut from plates and<br />

prepared. Metallographic examination was carried out using optical microscope LEICA DMLM and the microhardness<br />

measurement was done with LEICA VMHTAUTO.<br />

Type<br />

<strong>of</strong><br />

Pass<br />

Table 3- Process parameters used for welding <strong>of</strong> buttered AISI 10<strong>20</strong> and SS304<br />

Process Consumable No.<br />

passes<br />

Root GTAW Inconel 82<br />

ɸ1.1 mm<br />

Fill SMAW Inconel 182 ɸ<br />

4 mm<br />

Current<br />

(amps)<br />

Voltage<br />

(Volts)<br />

Welding<br />

speed<br />

(mm/sec)<br />

Polarity<br />

Gas flow<br />

rate (lit/min)<br />

1 1<strong>20</strong> 10-12 2.1 DCEN 6-8<br />

2 109 25-30 0.88 DCEP -<br />

3. Results and Discussion<br />

In visual observation no any significant defect has been observed during welding. Dye penetrant testing <strong>of</strong> both<br />

A and B plates was performed for root joint and complete welded joint. No any cracks was observed with root<br />

pass and fill pass. Due to small groove angle, little bit problem was occurred during root pass welding, but it was<br />

rectified by adjusting the arc at root face and land.<br />

586


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 2- Microstructure <strong>of</strong> Ni paste deposited plate<br />

A<br />

Figure 3- Microstructure showing solidification cracks<br />

in Ni paste layer <strong>of</strong> plate A<br />

Figure 4- Microstructure showing mixing and<br />

dilution <strong>of</strong> Ni paste with Inconel 182 <strong>of</strong> Plate B<br />

Figure 5- Microstructure showing mixing <strong>of</strong> Ni paste<br />

with Inconel 182 <strong>of</strong> plate B<br />

Figure 2 shows the microstructure <strong>of</strong> Ni paste deposited with GTAW process on the AISI 10<strong>20</strong> plate A.<br />

Columnar dendrite growth <strong>of</strong> nickel crystals has been clearly observed. The complete austenitic structure is also<br />

seen. Lack <strong>of</strong> ferrite or ferrite content mismatch in the layer causes solidification cracking in the buttered layer.<br />

Due to GTAW process the homogeneous mixing <strong>of</strong> base metal with Ni paste was not possible and high nickel<br />

content causes solidification cracks in the layer and can be seen in figure 3.<br />

The Ni paste deposited directly with Inconel 182 using SMAW process has been observed with complete mixing<br />

<strong>of</strong> Ni paste, Inconel 182 filler and AISI 10<strong>20</strong> base metal. Figure 4 and 5 shows the microstructure in the buttered<br />

layer <strong>of</strong> plate B. Required dilution and Ni paste mixing can be clearly seen in the figures. The austenitic structure<br />

<strong>of</strong> preferred orientation <strong>of</strong> grains with primary ferrite has been clearly revealed. The proper mixing ensures the<br />

ferrite content compatibility and hence no any micro-crack or fissure has been observed in the layer.<br />

587


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 6- Micro-hardness plots for complete plate joint <strong>of</strong> Plate A and Plate B<br />

The complete weldment was then subjected to Vicker’s micro-hardness measurement. The micro-hardness <strong>of</strong><br />

AISI 10<strong>20</strong> base metal, HAZ <strong>of</strong> AISI <strong>20</strong>10, buttering layer, weld metal, HAZ <strong>of</strong> SS 304 and SS 304 base metal<br />

was recorded. For each <strong>of</strong> the zone <strong>of</strong> weldment five indentations were taken. The hardness <strong>of</strong> plate B zone<br />

found to be consistently higher in each zone <strong>of</strong> HAZ od base metals, buttered layers and weld metal. The trend <strong>of</strong><br />

hardness observed with both plate joint A and B can be seen in figure 6. The reason for this hardness change is<br />

that, the homogeneous mixing <strong>of</strong> Inconel with Ni paste. As the Inconel filler having more amount <strong>of</strong> alloying<br />

content, especially chromium than the Ni paste. The dilution and mixing effect as well as the cooling effect<br />

changes the hardness <strong>of</strong> various zone <strong>of</strong> plate B than the hardness <strong>of</strong> plate A joint. Such hardness change was<br />

also recorded by Dupont in the study <strong>of</strong> Austenitic/ferritic dissimilar alloy weld [9].<br />

4. Conclusions<br />

1. High Nickel content in buttered layer can cause the solidification cracks.<br />

2. GTAW process cannot ensure the higher dilution for the dilution and mixing <strong>of</strong> Ni paste.<br />

3. SMAW process ensures the required dilution and homogeneous mixing <strong>of</strong> Ni paste with Inconel 182<br />

filler and with base metal as well.<br />

4. Ferrite content change may take place due to improper dilution and mixing.<br />

5. Improper mixing and dilution affects the hardness <strong>of</strong> buttering layer and the weld metal.<br />

5. References<br />

1. Ul-Hamid, A., H.M. Tawancy, and N.M. Abbas, Failure <strong>of</strong> weld joints between carbon steel pipe and 304<br />

stainless steel elbows. Engineering Failure Analysis, <strong>20</strong>05. 12(2): p. 181-<strong>19</strong>1.<br />

2. Gauzzi, F. and S. Missori, Microstructural transformations in austenitic-ferritic transition joints. Journal <strong>of</strong><br />

Materials <strong>Science</strong>, <strong>19</strong>88. 23(3): p. 782-789.<br />

3. Das, C.R., et al., Selection <strong>of</strong> filler wire for and effect <strong>of</strong> auto tempering on the mechanical properties <strong>of</strong><br />

dissimilar metal joint between 403 and 304L(N) stainless steels. Journal <strong>of</strong> Materials Processing <strong>Technology</strong>,<br />

<strong>20</strong>09. <strong>20</strong>9(3): p. 1428-1435.<br />

4. Ying, Y.Y., et al., The study <strong>of</strong> carbon migration in dissimilar welding <strong>of</strong> the modified 9Cr-1Mo steel. Journal<br />

<strong>of</strong> Materials <strong>Science</strong> Letters, <strong>20</strong>01. <strong>20</strong>(15): p. 1429-1432.<br />

588


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5. Lundin, C.D., Dissimilar Metal welds- Transition joint literature review. Welding Research Supplement,<br />

February <strong>19</strong>82: p. 58s-63s.<br />

6. Eckel, J.F., Diffusion across dissimilar metal joint. Welding Journal, April <strong>19</strong>64: p. 170s-178s.<br />

7. Pan, C., et al., Direct TEM observation <strong>of</strong> microstructures <strong>of</strong> the austenitic-carbon steels welded joint.<br />

Journal <strong>of</strong> Materials <strong>Science</strong>, <strong>19</strong>90. 25: p. 3281-3285.<br />

8. Taban, E., et al., Evaluation <strong>of</strong> Dissimilar Welds between Ferritic Stainless Steel Modified 12% Cr and<br />

Carbon Steel S355. Welding Journal, <strong>20</strong>08. 87(12): p. 291S-297S.<br />

9. Dupont, J.N. and C.S. Kusko, Technical Note: Martensite formation in austenitic/ferritic dissimilar alloy<br />

welds. Welding Journal, February <strong>20</strong>07: p. 51s-54s.<br />

589


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

ELECTRICAL DISCHARGE GRINDING (EDG): A REVIEW<br />

Ravindra Nath Yadav 1 and Vinod Yadava<br />

1. Department <strong>of</strong> Mechanical Engineering, Motilal Nehru National Institute <strong>of</strong> <strong>Technology</strong>, Allahabad, India<br />

Email: rnymnnit@yahoo.com<br />

2. Department <strong>of</strong> Mechanical Engineering, Motilal Nehru National Institute <strong>of</strong> <strong>Technology</strong>, Allahabad, India<br />

vinody@mnnit.ac.in<br />

Abstract<br />

The machining <strong>of</strong> thin and fragile material is very difficult for manufacturing industries and rapid demand <strong>of</strong><br />

requirement could not be achieved. Electrical discharge machining is more acceptable machine tool for<br />

machining hard and brittle electrically conductive materials but its productivity is very slow. In past decade,<br />

researchers are focus on electrical discharge grinding (EDG) for machining these material because there is no<br />

mechanical forces exerted on workpiece during machining and it gives better performances than EDM due to the<br />

rotating speed <strong>of</strong> wheel. The aim <strong>of</strong> this paper is to summarize a review on EDG process along with<br />

developments in same area and also focus on the future research scope in the same area.<br />

Keywords: Electrical discharge Machining (EDM), Electrical discharge grinding (EDG), ED milling<br />

1. INTRODUCTION<br />

Electrical discharge grinding (EDG) is a non-traditional thermal process for machining difficult to machine hard<br />

and brittle electrically conductive materials. EDG has been developed by replacing the stationary electrode used<br />

in electrical discharge machining (EDM) with rotating electrode. In EDG process, material is removed melting<br />

and vaporization as same as EDM process. But there are ample differences with EDM instead <strong>of</strong> mechanism <strong>of</strong><br />

material. In EDG process, an electrically conductive wheel is used as a tool electrode instead <strong>of</strong> stationary tool<br />

electrode used in EDM. There is no contact with workpiece and tool electrode (rotating wheel) except during<br />

electric discharge. Due to the rotational motion <strong>of</strong> wheel electrode, the peripheral speed <strong>of</strong> wheel transmitted to<br />

the stationary dielectric into gap between workpiece and wheel resulting flushing efficiency <strong>of</strong> process is<br />

enhanced. Therefore, the molten material is effectively ejected from gap and no debris accumulation take place<br />

into gap while in EDM debris accumulation is major problem which adverse effect on performances <strong>of</strong> process<br />

[1]. Due to the enhanced in flushing, higher material removal and better surface finish is obtained as compare to<br />

the conventional EDM process [2]. At the same machining condition, EDG gives better performances than EDM<br />

and it is machined extremely hard materials faster (2-3 times) as compare to the conventional grinding [3]. The<br />

high speed <strong>of</strong> wheel is not always beneficial and after a certain value <strong>of</strong> speed, the spark becomes instable and<br />

produces adverse effect on performance [4]. There is no physical contact between workpiece and wheel, so that<br />

the process becomes more advantageous for machining thin and fragile electrically conductive materials [3, 4].<br />

The detail <strong>of</strong> EDG process has been illustrated in Fig 1 and wheel-workpiece interaction is shown in Fig. 2. In<br />

this process, a rotating eclectically conductive metallic wheel is used which is known as grinding wheel. The<br />

grinding wheel used in this process, having no any abrasive particles and rotates its horizontal axis. Due to the<br />

similarities <strong>of</strong> process with conventional grinding and material is removed due to the electrical discharge, it is<br />

known as electrical discharge grinding (EDG). In this process, the spark is generated between rotating wheel and<br />

workpiece. The rotating wheel and workpiece both are separated by dielectric fluid and during machining both<br />

(workpiece and wheel) are continuously deeped into dielectric fluid. The dielectric fluids are mainly Kerosene<br />

oil, Paraffin oil, Transformer oil or de-ionized water. The main purpose <strong>of</strong> dielectric is to make a conductive<br />

channel during ionization when suitable breakdown voltage is applied. The servo control mechanism utilized to<br />

maintain the constant gap between workpiece and wheel in range <strong>of</strong> 0.013-0.075 mm. A pulse generator is used<br />

for maintaining the DC pulse power supply in ranges <strong>of</strong> voltage, current and frequency are 30-400V, 30-100A<br />

and 2-500 kHz respectively [3]. When pulse power supply is applied, the spark takes place into gap due to the<br />

ionization and striking <strong>of</strong> ions and electrons at their respective electrodes. Due to spark, high temperature<br />

generated between ranges <strong>of</strong> 8000°C to 1<strong>20</strong>00°C [5] or as so high upto <strong>20</strong>000 0 c [6] by each spark resulting<br />

material is meted from both the electrodes. Simultaneously DC pulse power supply switch is deactivated<br />

resulting the breakdown <strong>of</strong> spark occurs and fresh dielectric fluid entering into gap. Due to the high flushing<br />

efficiency, the molten materials flush away in form <strong>of</strong> micro debris from gap and formed the crater on work<br />

surface [7].<br />

2. RESEARCH AND DEVELOPMENTS IN EDG<br />

Many research and developments have been done in field <strong>of</strong> EDG for machining difficult to machine materials.<br />

In this process, a rotating electrically conductive wheel is used for spark erosion and simultaneously enhances<br />

2<br />

590


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

the flushing due to the rotational motion <strong>of</strong> wheel. There is many developments are found in particular process,<br />

depending on type <strong>of</strong> wheel and its rotation that are used in EDG process. These developments are implemented<br />

with two types <strong>of</strong> grinding wheels. Firstly, grinding wheel without abrasive particles while others is grinding<br />

wheel with abrasive particles.<br />

Fig. 1 Detail <strong>of</strong> EDG process<br />

Metallic wheel<br />

Pulse power<br />

supply<br />

Dielectric<br />

Workpiece<br />

Fig. 2 Wheel-workpiece interaction in EDG<br />

In EDG without abrasive particle, the wheel is made <strong>of</strong> graphite which rotates on is horizontal axis [3] but<br />

instead <strong>of</strong> graphite wheel, some other materials are used for making wheel for EDG process such as copper, brass<br />

and mild steel. Due to the high wear resistance, the mild steel wheel gives low wheel wear as compare to the<br />

copper and brass wheel. The main developments in EDG without abrasives are: electro-discharge grinding and<br />

electro-discharge milling (ED milling). In EDG process with abrasive particle, the rotating wheel replaced with<br />

metal bonded abrasive wheel or and such types <strong>of</strong> wheel is known as composite wheel. In composite wheel, the<br />

main purposes <strong>of</strong> abrasive particles are: to enhanced the material removal, to achieve better surface finish and<br />

requirement <strong>of</strong> low grinding forces. Electro-discharge abrasive grinding (EDAG) is the main development <strong>of</strong><br />

EDG process with abrasive wheel. It is further developed in three different grinding configurations such as<br />

electro-discharge abrasive cut-<strong>of</strong>f grinding, electro-discharge abrasive face grinding and electro-discharge<br />

abrasive surface grinding.<br />

2.1. RESEARCH IN EDG<br />

In EDG process, a rotating metallic wheel is used in machining which may rotates either its horizontal axis or<br />

vertical axis. Based on the rotation <strong>of</strong> wheel, the EDG process developed in three different configurations. These<br />

are: electro-discharge cut-<strong>of</strong>f grinding, electro-discharge face grinding and electro-discharge surface grinding<br />

[8]. In cut-<strong>of</strong>f grinding configuration, the metallic wheel rotates about its horizontal axis and fed into<br />

perpendicular direction to the machine table. It is used to cut workpiece into pieces or making grooves into<br />

workpiece. In face grinding configuration, the metallic wheel rotates about vertical spindle axis and fed into<br />

perpendicular direction to the machine table. It is more suitable for end machining <strong>of</strong> cylindrical work surface. In<br />

the surface grinding mode, the wheel also rotates its horizontal axis and fed into perpendicular direction to the<br />

machine table. It is mostly applicable for machining <strong>of</strong> the flat surfaces.<br />

591


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Many researchers have made effort to identify the factors that affects the performance <strong>of</strong> EDG process. It has<br />

been experimentally proved that material removal rate (MRR) and surface quality improved by properly<br />

selecting <strong>of</strong> process parameters by Aoyama et al. [9]. Sato et al. [10] have claimed that electrode rotation served<br />

as an effective gap flushing technique resulting better material removal. The edge quality <strong>of</strong> various grades <strong>of</strong><br />

polycrystalline diamond (PCD) cutting tool blanks after EDG on either the face or periphery <strong>of</strong> a rotating<br />

graphite wheel has investigated by Thoe et al. [11] and found that as compare to the coarse grain, the fine grain<br />

blank has higher MRR, grinding ratio and lower roughness <strong>of</strong> surface and edge. To obtain high material removal,<br />

higher peak current and longer pulse duration with positive polarity <strong>of</strong> electrode are suggested by Shih and Shu<br />

[12] as shown in Fig. 3 (a) while the negative tool polarity gives better surface finish as shown in Fig. 3 (b) at<br />

same machining conditions.<br />

Fig. 3 Effect <strong>of</strong> pulse on-time with positive and negative tool polarity [12]<br />

(a) Effect <strong>of</strong> on-time MRR, (b) effect <strong>of</strong> on-time on surface roughness<br />

Soni and Chakraverti [13] developed the orbital motion <strong>of</strong> the electrode for improving the machining rate and the<br />

results were compared with stationary electrode. They have found that orbital motion <strong>of</strong> the electrode enhanced<br />

the performance and MRR increases with rotation <strong>of</strong> electrode due to improved flushing action and sparking<br />

efficiency, however the surface roughness is increased. Guu and Hocheng [14] have been experimentally proved<br />

that rotating workpiece gives two times more MRR as compare to the conventional EDM but this process is most<br />

suitable for axial-symmetrical die and mold work. Koshy et al. [15] have experimentally proved that MRR,<br />

TWR, relative electrode wear, corner reproduction accuracy and surface finish aspects <strong>of</strong> a rotary electrode are<br />

better as compare to stationary electrode. This is because the rotation speed <strong>of</strong> electrode would convey a velocity<br />

to the dielectric in the gap hence more effectively flushing take place in the gap but at higher rotating speeds<br />

result in discharge instability resulting lower MRR with improve in surface roughness.<br />

Chow et al. [16] have been modified the EDG process by locating the rotating electrode below workpiece as<br />

shown in Fig. 4. They have claimed that due to gravitational force debris removal rate was significantly<br />

improved resulting higher MRR with better finish with rotating workpiece below workpiece. The effect <strong>of</strong><br />

vibration-rotary EDM as compare to the vibration EDM on MRR is high with higher surface finish has obtained<br />

by Atkinson and Ghoreishi [17]. They have found that the combination <strong>of</strong> ultrasonic vibration enhanced the<br />

performances <strong>of</strong> rotary EDM and rotation <strong>of</strong> electrode leads to increase the MRR but simultaneously TWR and<br />

Ra values is also increased. For machining <strong>of</strong> non-sphere workpiece with EDG, the Fujun et al. [18] have<br />

introduced the new shaping principle <strong>of</strong> machining these non-sphere materials. They suggested that the angle<br />

speed <strong>of</strong> workpiece and tool electrode should not be too high otherwise working fluid cannot enter into discharge<br />

gap under centrifugal effect <strong>of</strong> rotating wheel which plays adverse effect on the performances.<br />

592


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig. 4 Relative position <strong>of</strong> workpiece; (a) Conventional EDG, (b) Modified EDG [16]<br />

Machining <strong>of</strong> metal matrix composites (MMCs) are very difficult due to the presence <strong>of</strong> hard and brittle ceramic<br />

particles which leads to the rapid tool wear [<strong>19</strong>, <strong>20</strong>]. But the MMCs are effectively machined with EDG due to<br />

the performances <strong>of</strong> EDG is not affected by mechanical or physical properties <strong>of</strong> materials. Yan and Wang [21]<br />

have study on machining characteristics <strong>of</strong> Al 2 O 3 /6061Al composite using with copper tube electrode and they<br />

have found that current and volume fraction <strong>of</strong> Al 2 O 3 were have significant affects the performances but the<br />

flushing pressure and electrode rotational speed have minor effect on performance parameters. Wang and Yan<br />

[22] claimed that the electrical parameters more significant effect on performances as compare to the nonelectrical<br />

parameters. The effects <strong>of</strong> electrode material, electrode rotation, volume percentage <strong>of</strong> SiCp and<br />

electrical parameters have been investigated by Mohan et al. [23]. They compared the performances <strong>of</strong> brass and<br />

copper electrode and found that brass electrode gives higher MRR than copper electrode with positive polarity<br />

electrode. They also claimed that the higher percentage volume <strong>of</strong> SiCp means lower value <strong>of</strong> MRR with good<br />

surface finish due to SiC particles protect the matrix. It has been also found that the rotating tube electrode gives<br />

higher MRR than the rotating solid electrode, when they were tested at same machining conditions.<br />

2.2. RESEARCH IN ED MILLING<br />

Electro-discharge milling is the new development <strong>of</strong> EDG process. In this process, tool electrode rotates and<br />

workpiece fed toward or backward direction as shown in Fig. 5 The performance <strong>of</strong> ED milling in terms <strong>of</strong><br />

MRR and surface quality is much better and machining time reduced up to 50% as compare to the sinking EDM<br />

[24].<br />

Nozzle<br />

Tool<br />

Workpiece<br />

NC Table<br />

Pulse Power<br />

Supply<br />

Fig. 5 ED milling process [24]<br />

Liu et al. [25] have proposed new method for ED milling for machining insulating Al 2 O 3 using a thin copper<br />

sheet as assisting electrode, which fed between insulating ceramic and rotating wheel as shown in Fig. 6. They<br />

have found that process shows high MRR with positive polarity as compare to the negative tool polarity while<br />

negative tool polarity give higher surface finish. The dielectric fluid is a primary factor that affects the<br />

performances <strong>of</strong> process in term <strong>of</strong> MRR and surface quality. It has also found that high velocity flow <strong>of</strong><br />

dielectric fluid resulting MRR increases with a slightly increases in Ra value [26]. But there is no harmful gases<br />

generated during ED milling and the equipment is not corroded while water-based emulsion uses as a dielectric.<br />

The effect <strong>of</strong> toothed steel wheel during ED milling <strong>of</strong> SiC has been also investigated by Liu et al. [27] as shown<br />

in Fig. 7 and they have found that toothed wheel gives high MRR with positive tool polarity. They suggested that<br />

high machining rate and good surface quality is obtained at suitable value <strong>of</strong> pulse on-time, pulse <strong>of</strong>f-time and<br />

peak voltage.<br />

593


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig. 6 Detail <strong>of</strong> ED milling <strong>of</strong> ceramic with assisted electrode [25]<br />

Ji et al. [28] have also proposed a new method for ED milling in which workpiece connected to the servo system<br />

during ED milling <strong>of</strong> silicon carbide ceramic resistivity 500 Ω with steel electrode and it has been found that<br />

smaller high-frequency pulse duration and pulse interval, higher peak voltage and peak current, and positive tool<br />

polarity are suitable for machining the SiC ceramic. Ji et al. [29] have claimed that material is removed by<br />

melting, evaporation and thermal spalling during end milling EDM <strong>of</strong> silicon carbide.<br />

Fig. 7 ED milling with slotted wheel [27]<br />

2.3. RESEARCH IN EDAG<br />

To improve the efficiency <strong>of</strong> the EDG process, the metallic or graphite electrode has been replaced with metal<br />

bond abrasive wheel and the developed is known as electrical discharge abrasive grinding (EDAG) [30-33]. In<br />

this process, the material is removed by the combined effect <strong>of</strong> electro-erosion <strong>of</strong> EDM and micro-cutting <strong>of</strong><br />

grinding process as shown in Fig. 8. Due to the combined effect <strong>of</strong> EDG and grinding, the overall performances<br />

<strong>of</strong> the process have been improved. This process becomes evident when machining super-hard materials,<br />

engineering ceramics, sintered carbides and metal composites [31, 32]. The electrical discharge interactions on<br />

the metal bond abrasive grinding wheel lead to its self dressing in process. The theoretical analysis and<br />

experimental investigation <strong>of</strong> self-dressing mechanism <strong>of</strong> EDAG process has been investigated by Kozak [32].<br />

They have also claimed that electro-erosion process could be applied in pr<strong>of</strong>iling <strong>of</strong> super-hard metal bonded<br />

wheel.<br />

In recent past, several attempts have been carried out for employing the feasibility <strong>of</strong> EDAG process with<br />

different named proposed by researchers such as abrasive electro-discharge grinding (AEDG) and electrodischarge<br />

diamond grinding (EDDG). The enhancement <strong>of</strong> the MRR on introducing abrasion into the process has<br />

been studied in comparison to conventional EDM and EDG with rotating graphite has been done by Rajurkar et<br />

al. [31] during machining <strong>of</strong> Al-SiC composite and titanium alloy with copper bonded diamond wheel. They<br />

have found that MRR obtained by EDAG process is about five times more than EDM and about two times more<br />

than EDG process. Aoyama and Inasaki [33] have found that the normal and tangential grinding forces decrease<br />

with an increased in the applied voltage at the expenses <strong>of</strong> wheel wear. The compound effect <strong>of</strong> electrical<br />

discharge and mechanical grinding process <strong>of</strong> SiC with segmented wheel is developed by Ji et al. [34]. They<br />

have found that the developed process effectively machine the large surface area with higher MRR and good<br />

surface finish.<br />

594


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig. 8 Combined effect <strong>of</strong> EDG and grinding in EDAG process [37]<br />

Koshy et al. [35] have suggested for effectively performance <strong>of</strong> EDAG process, the protrusion height <strong>of</strong> abrasive<br />

particles is approximately 30% <strong>of</strong> the grain size is more suitable. It was found that the spark discharges thermally<br />

s<strong>of</strong>ten the work material in grinding zone, hence s<strong>of</strong>ten material easily removed by grinding action and<br />

consequently decrease the normal forces [35, 36]. Choudhury et al. [37] experimentally investigated that<br />

tangential grinding force decreases with increase in voltage and duty factor for a particular value <strong>of</strong> current. Jain<br />

and Mote [38] claimed that specific energy required in EDAG process is less than EDG. It has been investigated<br />

by Yadav et al. [39] that the wheel speed and current are most significant factors that affecting performances <strong>of</strong><br />

EDAG. Yadav and Yadava [40-43] study the effects <strong>of</strong> parameters on self developed. Singh et al. [44-48]<br />

developed EDAG process in face grinding mode for machining end surface <strong>of</strong> cylindrical workpiece and study<br />

the effects <strong>of</strong> process parameters. Agrawal and Yadava [49, 50], Modi and Agrawal [51] developed EDAG<br />

process in surface grinding mode for machining flat surface <strong>of</strong> workpiece and also study the effects <strong>of</strong> process<br />

parameters on performance measures.<br />

3. PROCESS PARAMETERS AND PERFORMANCE MEASURES<br />

Similar to the EDM process, many parameters affected the performances <strong>of</strong> EDG. These are classified into two<br />

categories: electrical parameters and non-electrical parameters. The electrical parameters are discharge voltage,<br />

pulse current, pulse duration, pulse interval, pulse frequency, duty factor and polarity while non-electrical<br />

parameters are types <strong>of</strong> dielectric and wheel rotational speed while the flushing method and flushing pressure <strong>of</strong><br />

dielectric are not significantly affects the performances <strong>of</strong> EDG. The performance measures are MRR, tool wear<br />

rate (TWR), and average surface roughness (Ra). When the abrasive is added into metallic wheel then size <strong>of</strong><br />

abrasive, types <strong>of</strong> abrasive, bond materials and concentrations also affects the performance measured.<br />

4. SUMMARY<br />

In this paper authors are summarized to the published research papers on EDG process along with the process<br />

parameters and their effects on performances measured. It cleared from the published papers that wheel speed<br />

enhanced the flushing resulting performances <strong>of</strong> process is also enhanced. The ED milling is the unique<br />

development in EDG process for machining insulating materials such as Al 2 O 3 . Adding the abrasive into<br />

metallic wheel means unique changes in performances. This study helpful for researchers and developers, who<br />

works in field <strong>of</strong> advanced manufacturing technology and making efforts for machining difficult to machine<br />

materials at low cost.<br />

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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

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(EDDG), International Journal <strong>of</strong> Advanced Manufacturing <strong>Technology</strong>, 26:56-67, <strong>20</strong>05.<br />

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rd<br />

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on Advances in Manufacturing <strong>Technology</strong>, Chandigarh, pp. 268-273,<strong>20</strong>12.<br />

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597


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

EFFECT OF Ni-<strong>20</strong>Mg TREATMENTOF Al-2Fe-1V-1Si ALLOY ON ITS<br />

MICROSTRUCTURE AND MECHANICAL PROPERTIES<br />

1.<br />

B. N. Pathak 1 , Dr. K. L. Sahoo 2 , Dr. M. N. Mishra 3<br />

Ph.D Scholar at DCRUST Murthal, Sonepat, Haryana<br />

Asstt. Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, IMS Engineering College, NH-24, Adhyatmik Nagar,<br />

Ghaziabad, India Email: bnpathak<strong>20</strong>07@rediffmail.com<br />

2. Senior Scientist, Metal Extraction & Forming Division, National Metallurgical Laboratory, Jamshedpur<br />

831007, Jharkhand, India<br />

3.<br />

Associate Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, DCRUST, Murthal, Haryana, India<br />

Abstract<br />

The paper deals with microstructure and mechanical properties <strong>of</strong> unmodified Al-2Fe-1V-1Si and modification<br />

with 1% (Ni-<strong>20</strong>Mg) Al-2Fe-1V-1Si alloys. The alloys were prepared in a resistance heating furnace and cast in a<br />

permanent mould to prepare the samples. Metallographic sample were prepared and microstructure was<br />

recorded by optical microscope and SEM. The microstructure <strong>of</strong> Al-2Fe-1V-1Si alloy shows primary and<br />

intermetallic inerdendritic phases are present. The melt is treated with Ni-Mg master alloy in order to change<br />

the morphology, size and distribution <strong>of</strong> the primary as well as interdendritic phases. By observing the<br />

microstructure <strong>of</strong> the alloys, it has been seen that with addition <strong>of</strong> Ni-Mg master alloy the grain refinement and<br />

phase modification occurs. In comparison to untreatable alloy, there is an improvement in mechanical<br />

properties on modification by Ni-Mg treatment.<br />

Keywords: Al-2Fe-1V-1Si alloy, Mg treatment, Microstructure, Hardness, Tensile Strength.<br />

1. Introduction<br />

The development <strong>of</strong> any alloys is an evolutionary process rather than a revolutionary process and aluminum<br />

alloys have no exception <strong>of</strong> this [1]. Many aluminum applications are undergoing a reduction in weight as<br />

strength and durability <strong>of</strong> aluminum is improved by alloying. Research in many areas <strong>of</strong> aluminum technology,<br />

such as advanced alloys, rapid solidification, composites and corrosion resistance, is aimed at keeping aluminum<br />

competitive in traditional as well as new applications [2]. Aluminum alloys such as Al-Si, Al-Cu-Si and Al-Mg-<br />

Zn alloys are widely used in aerospace and other engineering industries due to their light weight and high<br />

strength to weight ratio. The use <strong>of</strong> conventionally processed Al alloys is sometimes limited by their low strength<br />

at temperature above <strong>20</strong>0 0 C [1].<br />

Beyond this temperature, the mechanical properties deteriorate with temperature. Al-TM (TM - transition metal)<br />

Systems have the potential for high temperature applications. Among the Al-TM system, Al-Fe-V-Si, Systems<br />

have altered considerable interest due to its high strength at room as well as at elevated temperature [3]. It also<br />

possesses good creep resistance, fatigue and fracture strength. In general Al-Fe-V-Si alloys are produced through<br />

rapid solidification processing (RSP) route because <strong>of</strong> low solubility <strong>of</strong> Fe and V in Al and their wide difference<br />

<strong>of</strong> densities [4,5,6]. Iron is always present in Al alloys. The solid solubility <strong>of</strong> iron in Al is very low (< 0.04 wt.<br />

%) [7]. Therefore most <strong>of</strong> the iron appears as large intermetallic phases in combination with Al and other<br />

elements. Iron reduces the grain size in wrought product [8]. Iron increases the hardness and decreases the<br />

ductility. Iron increases corrosion resistance, creep strength and also improves somewhat the machinability <strong>of</strong> Al.<br />

Al-Si alloys have the potential for excellent cast ability, good weldibility, good thermal conductivity, high<br />

strength at elevated temperature and excellent corrosion resistance. There are, therefore, well suited for<br />

aerospace structural applications, automobile industries, military applications etc.<br />

Grain refinement <strong>of</strong> the casting yields several benefits. A fine grain size results in mechanical properties that are<br />

uniform throughout the material. Also, as the grain size decrease, the distribution <strong>of</strong> secondary phases and<br />

porosity is on a finer scale, and machinability is improved [9]. Therefore V is added to these alloys for its grain<br />

refining effects.<br />

It was reported that the addition <strong>of</strong> vanadium in ternary Al-Fe-Si alloys stabilize the cubic Al 13 (Fe,V) 3 Si phase<br />

[10]. The cubic phase has practically no tendency to transform and has minimal coarsening rate even when held<br />

for 100 hrs, at temperature up to 400 0 C.<br />

598


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

FVS 8009 alloy develop by Allied Signal Company was produced by rapid solidification processing (RSP) route<br />

which contents Al-8Fe-1.5Si-1.7V. But RSP routes have some limitations, as the product size is limited and<br />

product produced is not <strong>of</strong> uniform in size, so difference in microstructure. Recently Al-8.3Fe-0.8V-0.9Si alloy<br />

has produced by melting in casting route, which has ten-armed star shaped structure [11]. In this alloy, both the<br />

strength and ductility are less due to fact that the sharp corner <strong>of</strong> the star shaped clusters acts as a stress raiser.<br />

Therefore, lower Fe (2%), V (1%) and Si (1%) were used for this investigation. The present paper reports the<br />

effect <strong>of</strong> treatment on the properties and modification on microstructure <strong>of</strong> Al- 2 Fe-1V-1Si alloys.<br />

2. EXPERIMENTAL PROCEDURE<br />

For the preparation <strong>of</strong> Al-Fe-V-Si alloys, electrolytic grade Al (99.95% purity), Al-21% Fe, Fe-V (V content<br />

50%) and pure silicon (99.99% purity) were used (all compositions are in wt.%). Master alloys were crushed into<br />

small pieces for easy melting. The compositions <strong>of</strong> different alloys investigated in the present study are shown in<br />

table 1. The experimental alloys were prepared in an electric heating furnace in a clay bonded graphite crucible<br />

under the cover <strong>of</strong> Na-free flux. Na-free flux is used because Na addition increases the pin holing tendency and<br />

reduces fluidity.<br />

First, crucible was preheated to about 600 0 C. At around 600 0 C, weighted quantity <strong>of</strong> master alloys (Al-21%Fe,<br />

Fe-50%V), and 99.9% pure Al and 99.9% pure silicon metallic were charged. Just after melting, the molten alloy<br />

was covered with a Na-free flux (2% <strong>of</strong> melt). After melting, sufficient time was given for complete<br />

homogenization <strong>of</strong> the melt. The melt was frequently agitated with a graphite rod for complete mixing. The<br />

cover flux, in the form <strong>of</strong> scaling and dross etc. were skimmed <strong>of</strong>f before the degassing treatment. The melt was<br />

then degassed with hexachloroethane. Degasser was wrapped in Al foil and plunged into the melt. After<br />

degassing, the melt was cast in different moulds. The object was to vary the cooling rates.<br />

After complete homogenization at desired temperature, the melt was poured in different mould to prepare<br />

different samples. The degassed unmodified as well as modified melts were poured into permanent moulds in the<br />

0<br />

form <strong>of</strong> rods and plates (cooling rate 30 K/s). The pouring temperature was maintained approximately at 880 C.<br />

The fluidity <strong>of</strong> the melt at this temperature was sufficient for casting test pieces. Metallographic samples were<br />

cut from all the heats <strong>of</strong> test pieces and polished using belt polishing, emery paper from coarser ranges to finer<br />

one. After that, cloth polishing was done using fine alumina powder. Finally, the samples were polished with<br />

silvo solution. Silvo polish solution is trade name which contents iso-propyl alchohol, ammonium hydroxide and<br />

silica powder crystalline which is used for cleaning and suspending the turnish on surfaces and also protect from<br />

oxidation<br />

The samples were etched with a modified Keller’s reagent (2ml HF and 3ml HCl in 175ml water) for micro<br />

structural studies in an optical microscope. The microstructures <strong>of</strong> the samples were taken with the help <strong>of</strong> an<br />

image analyzer (LECO) in order to distinguish the shape and size <strong>of</strong> the primary and interdendritic precipitates.<br />

The specimens were also examined in a Scanning Electron Microscope (SEM) fitted with an Energy Dispersive<br />

X-ray analysis (EDX) system.<br />

The hardness from all the samples was measured in Vicker’s hardness testing machine. A load <strong>of</strong> 5Kg was<br />

applied for testing hardness. Average <strong>of</strong> four measurements <strong>of</strong> each as cast samples was taken. The specimens<br />

were tested in a Hounsfield Tensometer (tensile testing machine) at room temperature at a strain rate <strong>of</strong><br />

3mm/min. The Ultimate tensile strength (UTS) and percentage (%) elongation were measured.<br />

Table 1 Composition <strong>of</strong> the alloys prepared<br />

Alloy Designation Chemical Composition (wt %)<br />

Fe V Si Al<br />

1. H2 2 1 1 Balance,<br />

Unmodified<br />

2. H2M 2 1 1 Balance, Modified<br />

with 1% Ni-<strong>20</strong>Mg.<br />

599


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3. Results and discussion<br />

Table 1 reports the chemical compositions <strong>of</strong> the Al-Fe-V-Si alloys and the modification treatment. The samples<br />

were cast in different moulds in order to see the effect <strong>of</strong> cooling rate on the microstructure. But the comparison<br />

<strong>of</strong> Al-2Fe-1Si-1V and Al-2Fe-1Si-1V (treated with 1%Ni-<strong>20</strong>%Mg) alloys has been shown at cooling rate<br />

30 0 C/sec. The two molten metal processing techniques conventionally adopted in order to achieve proper<br />

microstructure, which provides required mechanical and physical properties in the casting, are grain refinement<br />

and modification. In reported literature, the grain refiner and eutectic silicon modified level are usually specified<br />

for sand casting conditions. But practically, the high cooling conditions prevailing in permanent mould casting<br />

and die casting processes require much lower levels <strong>of</strong> grain refiner and modifier compared to sand casting<br />

processes. Therefore in this work, the melts are cast in little higher cooling rates, which normally prevail in<br />

die/chil foundry. Fig 1a. show the optical microstructure <strong>of</strong> Al-2Fe-1Si-1V alloy cast at 12mm diameter<br />

permanent mould, corresponding cooling rate 30 0 C/s. The structure shows the rod type Al 3 Fe (with some V and<br />

Si incorporation) precipitates with interdendritic silicides as well as eutectic Al- Al 3 Fe precipitates with coarser<br />

grais. Fig1b. show the microstructure <strong>of</strong> Al-2Fe-1Si-1V(modified with 1% Ni-<strong>20</strong>Mg) alloy at a cooling rate<br />

30 0 C/s. Magnesium addition in the form <strong>of</strong> Ni-<strong>20</strong>Mg master alloy to the Al-Fe-V-Si alloy melt changed the<br />

morphology <strong>of</strong> both primary and eutectic phases. The solubility <strong>of</strong> Ni in solid Al is low (0.05%) [12]. So, Ni will<br />

strongly segregate to the melt in front <strong>of</strong> growing interface and affect the growth morphology <strong>of</strong> the precipitates.<br />

Both Ni and Mg enter into the lattice <strong>of</strong> the primary phases and change its morphology. This may be due to<br />

understanding that Mg restricts the nucleation and growth <strong>of</strong> Al13Fe4-type precipitates. The gradual<br />

improvement in microstructure has been observed with increasing amount <strong>of</strong> modifier.<br />

(a)<br />

(b)<br />

Figure 1. Optical microphotographs <strong>of</strong> Al- 4Fe-1V-1Si alloys at a cooling rate <strong>of</strong> 30 K/s (a) unmodified, and (b)<br />

modified with 1% <strong>of</strong> Ni-<strong>20</strong>Mg alloy.<br />

600


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

(a)<br />

(b)<br />

Figure 2. SEM <strong>of</strong> Al- 2Fe-1V-1Si alloys at a cooling rate <strong>of</strong> 30 K/s (a) unmodified, and (b) modified with 1% <strong>of</strong><br />

Ni-<strong>20</strong>Mg alloy.<br />

Table 2: Mechanical properties <strong>of</strong> as cast alloys:<br />

Alloy Hardness (VHN) UTS (MPa) % elongation<br />

Al-2Fe-1Si-1V 46 80.91 5<br />

Al-2Fe-1Si-1V 61.25 127.<strong>20</strong> 5<br />

Table 2 show the Hardness, Ultimate tensile strength (UTS) and percentage elongation as cast samples. From the<br />

table, it is clear that the mechanical properties improved considerably after modification with Ni-Mg master<br />

alloy. The tensile strength <strong>of</strong> the 1% <strong>of</strong> Ni-<strong>20</strong>Mg modified Al-2Fe-1V-1Si alloy is 127.<strong>20</strong> MPa with elongation<br />

5%. Modification <strong>of</strong> the alloy results in reduction in microporosity and refinement <strong>of</strong> size and morphology <strong>of</strong> the<br />

particles. The refinement <strong>of</strong> the particles produces dispersion strengthening effect.<br />

4. Conclusions<br />

1. During solidification <strong>of</strong> a quaternary Al-2Fe-V-Si alloy, different phases are formed at different temperatures.<br />

2. The morphology, size and distribution <strong>of</strong> the primary as well as interdendritic phases are considerably<br />

modified with Ni-Mg treatment <strong>of</strong> the molten alloy.<br />

601


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3. The mechanical properties (Hardness, UTS) <strong>of</strong> the Al-2Fe-V-Si alloys are improved after modification with<br />

Ni-<strong>20</strong>Mg master alloy without affected ductility.<br />

Reference<br />

[1] Das.S.K., Gillman.P.S., Raybould.D., <strong>19</strong>89 “Application <strong>of</strong> Rapidly solidified High Temperature Al –<br />

Alloys”, Key Engineering Materials, 367, 437-448.<br />

[2] Edward J.and Kubel Jr., <strong>19</strong>86 “Aluminum alloys: A Push for Excellence”, Advanced Materials and<br />

Processes inc. Metal Progress, 12, 43-49.<br />

[3] Jones, H., Roy, <strong>19</strong>88, In materials in aerospace (London. The Royal Aeronautical Society) 1 97-121, <strong>19</strong>86.<br />

[4] Skinner, D.J., Kim,Y.M., and Griffith, W.M., <strong>19</strong>88, The Physical Metallurgy <strong>of</strong> Dispersion strengthened Al<br />

Alloys”, The Minerals Metals and Materials society, 188-<strong>19</strong>7.<br />

[5] Sanders, R. E., Baumann, Jr. S.F., and Stumpf, H. C., <strong>19</strong>89 “Wrought Non Heat Treated Al- Alloys”,<br />

Treatise on Materials Sc. and Tech; 31, 83-85.<br />

[6] Lavernia,E.J, Ayers,J.D, Srivatsan,T.S., <strong>19</strong>92, International Materials Review, 37, 1.<br />

[7] Mondolfo, L.M., <strong>19</strong>76, “Aluminum Alloys- Structure and Properties”, Butterworths, London, 282-287.<br />

[8] Metal Handbook, <strong>19</strong>90, 10 th Edition, ASM international, The materials information society, 2.<br />

[9] Apelian. D., Sigworth. G.K. and Whaler. K.R., <strong>19</strong>84, “Assessment <strong>of</strong> Grain Refinement and Modification <strong>of</strong><br />

Al-Si Boundary Alloy by Thermal Analysis,” AFS Trans, 92, 297-307.<br />

[10] Srivastava, A.K., Ojha, S.N., and Ranganathan, S., <strong>19</strong>98, “Microstructural Features and Heat Flow<br />

Analysis <strong>of</strong> Automized and Spray-Formed Al-Fe-V-Si Alloys”, Metallurgical and Materials Transactions A, 29<br />

A, 2<strong>20</strong>5-22<strong>19</strong>.<br />

[11] Sahoo, K.L., Sivaramakrishnan, C.S.,& Chakrabarti, A.K., <strong>20</strong>01, “The Effect <strong>of</strong> Mg Treatment on the<br />

Properties <strong>of</strong> Al-8.3Fe-0.8V-0.9Si Alloy”, Journal <strong>of</strong> Mater. Processing Tech.,112, 6-11.<br />

[12] L. M. Mondolfo, Aluminnium alloys- Structure and Properties, Butterworths, London, <strong>19</strong>76.<br />

602


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

IMPACT OF SHOT PEENING AND HOT TREATMENT PROCESS ON<br />

SURFACE HARDENING OF WELDED 304L AUSTENITIC STAINLESS<br />

STEEL<br />

Lakhwinder Singh 1 , R.A. Khan 2 , M.L. Aggarwal 3<br />

1. Associate Pr<strong>of</strong>essor, Deptt. <strong>of</strong> Mechanical Engineering , <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>,<br />

Faridabad-121006, INDIA<br />

2. Pr<strong>of</strong>essor, Deptt. <strong>of</strong> Mechanical Engineering, School <strong>of</strong> Engineering & <strong>Technology</strong>, Galgotias <strong>University</strong>,<br />

Greater Noida, INDIA<br />

3. Pr<strong>of</strong>essor, Deptt. <strong>of</strong> Mechanical Engineering , <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad-<br />

121006, INDIA<br />

Abstract<br />

Heat treatment process like case carburizing & nitriding and cold working process like shot peening are the<br />

most widely used processes for surface hardening <strong>of</strong> welded components used in structures, automobiles, heavy<br />

duty machines, etc. In case carburizing and nitriding <strong>of</strong> steel components the composition <strong>of</strong> the surface changes<br />

by the diffusion <strong>of</strong> carbon and nitrogen respectively and results in a hard outer surface with good wear<br />

resistance properties. Similarly shot peening improves the surface characteristics by deforming the surface layer<br />

by the shots. In the present paper a controlled nitriding, case carburizing and shot peening processes are<br />

discussed for welded 304L austenitic stainless steel. There impact is determined on the surface hardness and<br />

corrosion resistance <strong>of</strong> the welded joint. Vickers’ hardness and salt spray test were carried out for the abovementioned<br />

welded stainless steels before and after diffusion hardening.<br />

Keywords: Shot Peening, Nitriding, Case carburizing, Austenitic stainless steel.<br />

1. Introduction<br />

Austenitic stainless steels are iron-chromium-nickel alloys having a face-centered cubic (FCC) crystal structure.<br />

It is non magnetic in nature. It is seen experimentally that solid case carburizing adversely effects on surface<br />

hardness and tensile strength <strong>of</strong> austenitic stainless steel [1]. There are limited surface hardening treatments<br />

which are applicable to the stainless steels. The strength <strong>of</strong> austenitic stainless steels can be increased by solid<br />

solution hardening with nitrogen, fine grain hardening and by cold work [2]. It is possible to surface harden the<br />

austenitic stainless steels by nitriding. In nitriding as <strong>of</strong> other steels the surface layer is hard and thin.<br />

Carburizing is an example <strong>of</strong> chemical – thermal process, it adds carbon to the surface layer, together with<br />

appropriate heat treatment. It is a surface hardening process widely used in number <strong>of</strong> industrial applications. In<br />

most instances hardening <strong>of</strong> carbon and low alloy steels is due to the martensitic transformation, in which the<br />

achievable hardness is related to the carbon content - as most austenitic stainless steels have carbon contents<br />

ranging from fairly low to extremely low.<br />

Turpin et al. [3] did gas carburizing at atmospheric pressure. They observed that the growth <strong>of</strong> chromium-rich<br />

carbides during carbon transfer into the steel was responsible for an important depletion <strong>of</strong> the metallic<br />

chromium content in the austenitic solid solution all around the carbides. At the end <strong>of</strong> the carburizing process,<br />

the corrosion resistance <strong>of</strong> the steel strongly depended on the carbon content at the surface. To obtain the best<br />

compromise between hardness level and corrosion resistance in the carburized layer, the carbon pr<strong>of</strong>ile in the<br />

steel must be controlled carefully.<br />

Cold working is used to increase strength, especially in higher alloyed austenitic stainless steels [4]. The<br />

improvement in mechanical properties such as surface hardness, fatigue strength, tensile strength, damping etc.<br />

are due to the induction <strong>of</strong> compressive residual stress in the metal parts [5]. The residual compressive stress<br />

induced by shot peening is the function <strong>of</strong> material and mechanical conditions. Shot peening process is impacting<br />

a surface with shot (round metallic cast steel, glass, ceramic particles) with force sufficient to create plastic<br />

deformation. It operates by the mechanism <strong>of</strong> plasticity, each particle functions as a ball-peen hammer.<br />

The magnitude <strong>of</strong> the compressive stress induced and the depth <strong>of</strong> the induced layer depend considerably on the<br />

peening intensity [6, 7]. Peening intensity can be defined as a measure <strong>of</strong> the kinetic energy within a stream <strong>of</strong><br />

peening media. Peening intensity attained can vary with shot size, shot hardness, shot speed, shot flow rate,<br />

impact angle, coverage, etc.<br />

603


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. Experimental Set – up<br />

The chemical composition <strong>of</strong> AISI 304L austenitic stainless steel used is shown in Table 1. The mechanical<br />

properties <strong>of</strong> parent material are: yield strength 256MPa, ultimate tensile strength 564MPa, surface hardness<br />

265VHN and elongation 67.24%.<br />

Table 1: Chemical composition <strong>of</strong> AISI 304L (wt %)<br />

Steel C Si Mn P S Ni Cr Mo V<br />

AISI 304L 0.025 0.485 1.4 0.025 0.011 9.46 18.21 0.241 0.05<br />

2.1. Welding procedure<br />

For various tests a flat plate <strong>of</strong> AISI 304L having thickness 10 mm was taken. The plate was divided in to two<br />

parts with the help <strong>of</strong> Power Hacksaw Machine. After that these pieces were welded as shown in Fig. 1(a) and<br />

(b). Edge preparation was done before welding shown in Fig. 2 as per standards. Single V joint was prepared<br />

because it was used for the sheet thickness 8 ~ 16mm for GMAW (Gas Metal Arc Welding). “FRONIUS-Type<br />

Trans Plus Synergic 4000” welding machine was used to join these pieces. E308-16 electrodes <strong>of</strong> ESAB make<br />

were used for welding. The welding parameters were set as:<br />

• Electrode Size : 1.6mm<br />

• Pass : 2<br />

• Current DC (+) : 300amp<br />

• Arc Voltage : 25V<br />

• Wire feed rate : 85mm/sec<br />

• Arc Speed : 6.5mm/sec<br />

• Electrode required : 0.405Kg/m<br />

• Shielding Gas : 98% Argon + 2% Oxygen<br />

• Gas Flow Rate : 16.5 l/min<br />

The specimens were prepared for tests surface hardness and corrosion test after welding and cleaning. The<br />

material was cut in different pieces with the help <strong>of</strong> Power Hacksaw Machine. The first part and the last part was<br />

scrap because the initiation and stoppage <strong>of</strong> welding may have defects.<br />

Vickers hardness tests were carried on the welded specimens. The surface hardness measurements were<br />

performed using “WOLPERT Universal hardness testing machine dia tester – 2, model 2RC”. The average<br />

values <strong>of</strong> three readings <strong>of</strong> surface hardness were taken.<br />

Air blast machine was used for shot peening <strong>of</strong> welded AISI 304L austenitic stainless steel. The cast steel<br />

spherical shots <strong>of</strong> 1 mm diameter were used. The nozzle angle was kept as 90 0 . The hardness <strong>of</strong> the shots was<br />

56HRC to 60HRC. The coverage <strong>of</strong> shot peening was 100%.<br />

450mm<br />

110mm<br />

110mm<br />

(a)<br />

604


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

(b)<br />

(b)<br />

Fig. 1: (a) Dimensions <strong>of</strong> two plates used for welding (b) Actual picture <strong>of</strong> welded plates.<br />

60 0<br />

1.6mm<br />

10mm<br />

110mm<br />

110mm<br />

Fig. 2: Edge preparation (all dimensions in mm).<br />

2.2. Nitriding<br />

Initially the specimens was pickled or chemically descaled in a solution <strong>of</strong> nitric and hydr<strong>of</strong>luoric acid. The<br />

process was done to remove the tightly adherent oxide layer from the surface <strong>of</strong> the specimen. Electrically heated<br />

furnace with stainless steel pot was used to carry out the processing. Base salt was filled up in the pot and heated<br />

to 560 - 570°C. After the aging <strong>of</strong> 24 hours to saturate the pot, the bath chemistry was checked and brought to<br />

normal by the addition <strong>of</strong> regenerator salt. Then the bath was ready to use. The components were pre heated for 1<br />

hour at 300 – 400 0 C, degreased and soaked in the furnace for required time durations. Then the specimens were<br />

kept in salt bath for required soaking time. Afterward the specimens were quenched in oxynit. After quenching,<br />

the components were washed in hot water. The specifications <strong>of</strong> liquid nitriding are shown in Table 2.<br />

Table 2: Specifications <strong>of</strong> liquid nitriding.<br />

Pre-heating temperature<br />

300-400 o C for 1 hour<br />

Loading temperature<br />

560-570 o C<br />

Soaking time<br />

55-65 mins<br />

Quenching media<br />

Oxynit<br />

Total time<br />

2.5 hours approx.<br />

Tempering temperature<br />

145-155 o C<br />

Soaking time<br />

115-125 mins<br />

2.3. Carburizing<br />

The chief carburizer (Table 3) for solid case carburizing were activated charcoal grains <strong>of</strong> 3.5mm to 10 mm in<br />

diameter, coal semi-coke and peat coke. Carbonates were added to the charcoal to accelerate the carburizing<br />

process. They included barium carbonate (BaCO 3 ) and soda ash (Na 2 CO 3 ) that was added in an amount from 10<br />

to 40 percent <strong>of</strong> weight <strong>of</strong> the charcoal.<br />

Table 3: Composition <strong>of</strong> solid carburizers.<br />

Barium Calcium Sulphur Silica Moisture Volatile Charcoal<br />

Carbonate Carbonate<br />

matter<br />

<strong>20</strong> to 25% 3.5% 0.06 (max.) 0.5% 5.0% 10.09 (min.)% Remainder<br />

605


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

A working mixture was consisting <strong>of</strong> 25 to 35 percent fresh carburizer and 65 to 75 percent used material. Work<br />

pieces were cleaned <strong>of</strong> dirt, scale, and rust for solid carburizing. They were then placed in a box. Welded boxes<br />

<strong>of</strong> cast heat resistant alloys were used.<br />

Packing the work was accomplished by first covering the bottom <strong>of</strong> the box with a 40mm to 45 mm layer <strong>of</strong><br />

carburizer. The work pieces to be carburized were placed on this layer with spaces <strong>20</strong>mm to 25 mm between<br />

them and the box walls. Then they were covered with a dense layer <strong>of</strong> carburizer, <strong>20</strong> to 25 mm thick, which was<br />

rammed before laying the next row <strong>of</strong> work pieces. The upper row was covered with a layer <strong>of</strong> carburizer 40mm<br />

to 50 mm thick. The box was closed with a cover. The packed box was placed in the furnace for different time<br />

periods.<br />

3. Results and Discussion<br />

3.1. Surface hardness<br />

The surface hardness <strong>of</strong> different specimens was measured by Vicker hardness tester. The hardness was checked<br />

three times at different positions and mean <strong>of</strong> them is shown in table 4. It was seen that for a solid case<br />

carburized component, hardness depends on holding time. It is clear from the table 4 that solid case carburizing<br />

s<strong>of</strong>tens the austenitic stainless steel. The surface hardness is found to be increased with shot peening and<br />

nitriding <strong>of</strong> welded joint.<br />

The surface hardness <strong>of</strong> the welded joint was enhanced after shot peening due to closing <strong>of</strong> crests and valleys on<br />

the surface. The average surface hardness <strong>of</strong> welded joint before shot peening was 235VHN. It is enhanced to<br />

351VHN after shot peening at 5A<br />

S. No.<br />

Table 4: Surface hardness <strong>of</strong> un-treated, shot peened, nitride carburized specimens and.<br />

Un-treated<br />

specimen<br />

(VHN)<br />

Shot peened<br />

at 5A<br />

(VHN)<br />

Liquid<br />

nitrided<br />

specimen<br />

(VHN)<br />

Carburized specimen<br />

Holding Surface<br />

Time Hardness<br />

(hrs) (VHN)<br />

1 238 352 691 6 210<br />

2 229 347 659 8 2<strong>19</strong><br />

3 242 362 678 10 225<br />

4 230 341 682 12 228<br />

Average 235 351 678 - 221<br />

The surface hardness <strong>of</strong> the un-treated, shot peened, nitrided and carburized specimens are listed in Table 4. For<br />

an easy comparison Fig. 3 shows the surface hardness <strong>of</strong> the different specimens <strong>of</strong> welded 304L austenitic<br />

stainless steel. It is evident that nitriding causes a high increase in the surface hardness as compared to shot<br />

peening and carburizing process (table 4 and fig 3). The percentage increase in surface hardness with nitiding is<br />

approximately 188%.<br />

Fig 3. Hardness variation for un-treated, shot peened, nitride and carburized specimens.<br />

606


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 5: Corossion rate for un-treated, shot peened and nitrided specimen.<br />

S. No. Un-treated specimen<br />

(mpy)<br />

Shot peened<br />

specimen at 5A<br />

(mpy)<br />

Nitrided<br />

specimen (mpy)<br />

Carburized<br />

specimen (mpy)<br />

1 0.928 0.855 0.521 1.421<br />

2 0.956 0.862 0.484 1.736<br />

3 0.992 0.846 0.498 1.3<strong>19</strong><br />

4 0.908 0.843 0.501 1.901<br />

Average 0.946 0.852 0.501 1.594<br />

3.2. Corossion Rate<br />

Corrosion test was conducted under salt spray chamber at 40-45 0 C for 48 hours under 5% NaCl mist. Un-treated<br />

specimen & nitrided specimen showed no corrosion but red rust was observed in shot peened specimen. This<br />

shows that shot peening & nitriding improves surface hardness and corrosion resistance however carburizing<br />

decreases the surface hardness as well as corrosion resistance (table 5 and fig 4).<br />

Fig 4. Corossion rate for un-treated, shot peened and nitrided specimen.<br />

4. Conclusion<br />

It is seen experimentally that shot peening, nitriding and carburizing effects on surface hardness and corrosion<br />

rate <strong>of</strong> welded 304L austenitic stainless steel. The following conclusions were made:<br />

1. Surface hardness <strong>of</strong> welded 304L austenitic stainless steel specimen improves with shot- peening and<br />

nitriding.<br />

2. Increase in surface hardness is more after nitrding as compared to that with shot-peening.<br />

3. The shot peening & nitriding improves surface hardness and corrosion resistance however carburizing<br />

decreases the surface hardness as well as corrosion resistance.<br />

4. Carburizing s<strong>of</strong>tens the welded joint <strong>of</strong> 304L austenitic stainless steel.<br />

References<br />

1. Lakhwinder Singh, Khan R.A., Aggarwal M.L., “S<strong>of</strong>tening due to case carburizing <strong>of</strong> austenitic stainless<br />

steel”, National conference, NCFTME-<strong>20</strong>07, SUS College <strong>of</strong> Engineering and <strong>Technology</strong>, Tangori<br />

(Mohali), pp 147-150.<br />

2. Speidel, M.O., Zheng-Cui, M., “High-nitrogen austenitic stainless steels”, HNS <strong>20</strong>03 High Nitrogen Steels,<br />

ISBN 3728128910, VDF-Hochschulverlag AG, <strong>20</strong>03; pp 63–75.<br />

3. Turpin T., Dulcy J., and Gantois M., “Carbon Diffusion and Phase Transformations during Gas Carburizing<br />

<strong>of</strong> High-Alloyed Stainless Steels: Experimental Study and Theoretical Modeling”, Metallurgical and<br />

materials transactions, volume 36A, October <strong>20</strong>05, pp 2751-2762.<br />

4. Norton R.L., “Machine Design – An Integrated Approach”, Pearson Education Asia, 2 nd ed., pp 59-60.<br />

5. Sharma. M.C., Shot Peening and Blasting, International Conf. on shot peening and sand blasting, <strong>20</strong>01, pp<br />

<strong>19</strong>0-<strong>19</strong>5.<br />

6. George P.M., Pillai N. and Shah N., “Optimization <strong>of</strong> shot peening parameters using Taguchi technique”,<br />

Journal <strong>of</strong> Materials Processing <strong>Technology</strong> (<strong>20</strong>04) 925–930.<br />

7. Aggarwal M.L, Khan R.A and Agrawal V.P., “Investigation into the effects <strong>of</strong> shot peening on the fretting<br />

fatigue behaviour <strong>of</strong> 65Si7 spring steel leaf springs”, Journal <strong>of</strong> Materials: Design and Applications,<br />

Institution <strong>of</strong> Mech. Engineers., U.K., Vol 2<strong>19</strong>(3), <strong>20</strong>05, pp139-147.<br />

607


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

SENSITIVE ANALYSIS OF EDM PROCESS USING DIAGRAPH<br />

APPROACH<br />

1. Research Scholar <strong>YMCA</strong>UST,Faridabad(Hr.)<br />

2.Workshop Supdtt. <strong>YMCA</strong>UST,Faridabad(Hr.)<br />

3. Asst.Pr<strong>of</strong>essor <strong>YMCA</strong>UST,Faridabad(Hr.)<br />

Madan Gopal 1 , Naresh Yadav 2 , Bhupender Singh<br />

Abstract<br />

A number <strong>of</strong> computationally efficient optimization tools are being developed now a day, but the numerical tools<br />

for multi-criterion optimization problems have their own significance. The present work aims beyond the<br />

approaches use for such optimization problems. In order to justify the related work, the author has chosen a<br />

machining method, known as Electric Discharge Machining process. This paper, in particular, shows the<br />

potentiality <strong>of</strong> graph theory and matrix approach for the analysis, evaluation, selection and optimization <strong>of</strong><br />

manufacturing systems and processes The work contained relationships establishment between the various input<br />

variables and parameters for the EDM machine.The results have been obtained for the given set <strong>of</strong> constraints<br />

and the individual objective functions and are compared to those obtained by using Graph theory.<br />

1. Introduction<br />

The use <strong>of</strong> thermoelectric source <strong>of</strong> energy in developing the non-traditional techniques has greatly helped in<br />

achieving an economic machining <strong>of</strong> the extremely low mach inability materials and difficult jobs. The process<br />

<strong>of</strong> material removal by a controlled erosion through a series <strong>of</strong> electric sparks, commonly known as EDM, was<br />

first started in <strong>19</strong>43 in USSR. When a discharge takes place between two points <strong>of</strong> the anode and cathode, the<br />

intense heat generated near the zone melts and evaporates the materials in the sparking zone. For improving the<br />

effectiveness, the work piece and the tool are submerged in the Dielectric fluid. The basic EDM process has been<br />

shown in Fig. 1.1. it has been observed that if both the electrodes are made <strong>of</strong> the same material, the electrode<br />

connected to the positive terminal generally erodes at faster rate. For this reason, the work piece is generally<br />

made the anode. A suitable gap, known as the spark gap, is maintained between the tool and the work piece<br />

surfaces. The sparks are made to discharge at a high frequency with a suitable source. Since the spark occurs at<br />

the spot where the tool and the work piece surfaces are the closest and, since, the spot changes after each spark,<br />

the spark ravel all over the surface. . The spark gap ranges from 0.005 mm to 0.05mmdepending upon the<br />

cutting action required and the current density, this spark gap is either flooded or immersed in a dielectric fluid,<br />

the spark discharge is produced by the controlled pulsing and direct current.. The spark causes a focused stream<br />

<strong>of</strong> electrons to move with a high velocity and acceleration from the cathode toward the anode ,thus creating high<br />

compression shock waves .such shock waves result in local rise in temperature to the order <strong>of</strong> about 10,000 c and<br />

cause melting <strong>of</strong> the metal. The forces <strong>of</strong> electric and magnetic fields caused by the spark produced a tensile<br />

force and tear <strong>of</strong>f particles <strong>of</strong> molten and s<strong>of</strong>ten metal from the work piece, Thereby resulting in the metal and<br />

carried away by the flowing dielectric fluid.<br />

The dielectric breaks down when a proper DC voltage (50-450) V is applied across the anode and the cathode,<br />

and electrons are emitted from the cathode and the gap is ionized, there by causing electrical discharge and<br />

machining operation. The electro-magnetic field cause compressive forces to act on the cathode thus metal<br />

removal from the tool is much slower than the work piece .the duration <strong>of</strong> the electric pulse is about 0.001<br />

seconds, hence the whole cycle <strong>of</strong> sparking and metal removal take place in a few microseconds. The particles <strong>of</strong><br />

the metal so removed are driven away by the flowing dielectric fluid .the current density and the power density<br />

used is the order <strong>of</strong> 10,000a/cm2 and 500mw/cm2 respectively.<br />

The few variables / parameters which are useful in analyzing the EDM process accuracy and efficiency are as<br />

below:<br />

(i). Metal removal rate, (ii). Electrode wear,(iii). Surface Roughness,(iv). Power consumption<br />

1.1. Metal removal rate<br />

Metal removal rate it is direct proportional to the current density used. it is defined as the volume <strong>of</strong> metal<br />

removed per unit time per ampere. The metal removal rate in roughening operations <strong>of</strong> steel with a graphite<br />

electrode 50 A current is about 400mm3/min and with 400A current it is about 4800mm 3 /min . But for high<br />

precision works with use <strong>of</strong> high frequency (500-1000) kHz and low current (1-2A), metal removal rate is as low<br />

as 2mm3/min.<br />

3<br />

608


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

1.2. Accuracy<br />

The smaller the gap the higher is the accuracy, but a smaller gaps leads to a lower working voltage and hence a<br />

slow metal removal rate. Thus an optimum gap is necessary for higher accuracies tolerances <strong>of</strong> +-0.05 mm can<br />

be obtained in normal EDM operations. In precision operations, with close control <strong>of</strong> process variables, tolerance<br />

up to +-0.003 mm can be achieved. EDM also produces taper, overcut and corner radii, which are not desirable.<br />

The taper is <strong>of</strong> the order <strong>of</strong> 0.005 to 0.05mm per 10 mm depth. The taper effect reduces gradually to zero after<br />

about 75mm penetration .taper effect can be eliminated by the use <strong>of</strong> vacuum flushing <strong>of</strong> dielectric fluid. The<br />

range <strong>of</strong> overcut is 5 to 100 microns and depth on the roughening operations .the effect <strong>of</strong> corner radii is equal to<br />

the spark gap.<br />

1.3. Surface finish<br />

In EDM operations, each electrical spark discharge develops a spherical crater in the work piece, as well as in the<br />

electrode. Thus the depth <strong>of</strong> the crater is proportional to the energy in the spark. the electrode material. usually<br />

high frequency and low current density give better surface finish, the best surface finish on steel is <strong>of</strong> the order <strong>of</strong><br />

0.4 micron (at 1000khz &1A).in a typical no-wear EDM ,the surface finish is about 3.2microngenerally roughing<br />

operations.<br />

1.4. Heat effected zone (HAZ)<br />

The instant heating and vaporization <strong>of</strong> metal due to spark, leaves behind a small amount <strong>of</strong> molten metal on the<br />

machined surface which re-solidifies and due to fast cooling action <strong>of</strong> the dielectric fluid forms a hard surface.<br />

This becomes the heat affected zone. In EDM operations .the HAZ is about 2 to 10micron 10 micron deep on the<br />

work surface and its hardness is about 60HRC.the hard surface is a source for thermal stresses ,plastic<br />

deformation and fine cracks at the grain boundaries .the depth <strong>of</strong> HAZ is small in finishing operations which can<br />

be removed by producing after EDM operations.<br />

2. Methodology Adopted<br />

A methodology for the proposed operational- economics based evaluation <strong>of</strong> the Electric Discharge Machining is<br />

suggested on the basis <strong>of</strong> digraph and matrix methods. The Graph theoretic approach (digraph) evaluates the<br />

performance Index <strong>of</strong> the Electric Discharge Machining in terms <strong>of</strong> single numerical index. This takes into<br />

consideration the effects <strong>of</strong> various factors, sub-factors and their inter-dependencies. Various steps <strong>of</strong> the<br />

proposed approach are presented below, which will be helpful in evaluating the Electric Discharge Machining<br />

with stated objectives in this paper.<br />

(a). The entire Electric Discharge Machining is assumed as a system and all the operational features are critically<br />

reviewed (b). Identify the various attributes affecting the operational economics <strong>of</strong> the Electric Discharge<br />

Machining. In order to analyze complex systems, the system as a whole may be divided into sub-systems and<br />

further sub-subsystems up to the component level in order to analyze the dependency and affect <strong>of</strong> one variable<br />

at the sub-system levels up to the component level and its cumulative effect at the system level.(c ). Obtain the<br />

values <strong>of</strong> the attributes and analyze their level <strong>of</strong> inter-dependencies on a normalized scale <strong>of</strong> 0-10. The inherent<br />

attribute value ( i.e. Di’s) are generally calculated from the standard tests or retrieving the experimental data.<br />

Whenever, the quantitative data is not available, then a criteria <strong>of</strong> ranked values by judgments over a scale <strong>of</strong> 0-<br />

10 is generally adopted.. Table 1 shown below suggests the equivalent value over a scale <strong>of</strong> 0-10 for the<br />

qualitative measure <strong>of</strong> an attribute.<br />

Table 1<br />

Value <strong>of</strong> the attributes (Di)<br />

Qualitative measure <strong>of</strong> attributes Assigned value <strong>of</strong> the attributes<br />

(Di)<br />

Exceptionally low 0<br />

Extremely low 1<br />

Very low 2<br />

Low 3<br />

Below normal 4<br />

Normal 5<br />

Above normal 6<br />

High 7<br />

Very high 8<br />

Extremely high 9<br />

Exceptionally high 10<br />

609


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Further, the response <strong>of</strong> the attribute contributing to system performance evaluation index is initially categorized<br />

as benefit type attributes or the cost type attributes so that all the attributes can be ranked and evaluated on a<br />

standard scale 0-10 in similar fashion, such as, if the higher attribute value contributes to increased value <strong>of</strong><br />

performance evaluation index <strong>of</strong> the system, then the attribute is called as <strong>of</strong> benefit type and its higher values<br />

are ranked near to 10 on a scale <strong>of</strong> 0-10 whereas the attributes whose higher values leads to lowering <strong>of</strong> the<br />

system performance index values are called cost type attributes and its higher values are generally ranked in the<br />

proximity <strong>of</strong> 0 on a scale <strong>of</strong> 0-10. since most <strong>of</strong> the attributes are dissimilar in sense, operating units and<br />

measured value ranges, the attribute values can not be directly used in the per(A) function. The values <strong>of</strong> all<br />

such attributes are to be normalized using suitable normalizing functions on a scale 0-10 also for their variation<br />

limits keeping benefit type criteria and cost type criteria into consideration. It helps in evaluating the generic<br />

effect <strong>of</strong> each inter-dependency contributing towards the overall index measures and sensitivity index evaluation<br />

for such attributes which will be helpful for critical analysis <strong>of</strong> the system as a whole. The relative importance<br />

between the two attributes is also assigned a value on a scale <strong>of</strong> 0-10 and is arranged into classes as mentioned in<br />

Table 2. Due to complexity <strong>of</strong> the system as a whole, it becomes infeasible to calculate the relative interdependency<br />

<strong>of</strong> one attribute over the other. However, for simplicity, a relationship has been suggested in the<br />

literature for such cases which assigns the relative importance <strong>of</strong> ‘i’th attribute over ‘j”th attribute and vice-versa<br />

as under:<br />

a ij = 1-a ji, a jj = 1-a ji<br />

Table 2<br />

Relative importance <strong>of</strong> attributes (aij)<br />

Class description<br />

Relative importance <strong>of</strong> attributes<br />

Aij<br />

aji = 10- aij<br />

Two attributes are <strong>of</strong> equal importance 5 5<br />

One attribute is slightly more important than the other 6 4<br />

One attribute is more important than the other 7 3<br />

One attribute is much more important than the other 8 2<br />

One attribute is extremely more important than the 9 1<br />

other<br />

One attribute is exceptionally more important than the<br />

other<br />

10 0<br />

Since various attributes affects the permanent function over class intervals or operating ranges, normalization <strong>of</strong><br />

values over the operating ranges <strong>of</strong> the attributes are to be done using standard algorithms.<br />

(d). identify the nature <strong>of</strong> the attributes as Benefit type or the cost type. Also identify the sense <strong>of</strong> the desired<br />

outcome index as benefit type or the cost type. Normalization <strong>of</strong> all the values <strong>of</strong> the attributes must be in<br />

conformance to the nature <strong>of</strong> the outcome Index. Modifications, if required, can be made accordingly. For<br />

example, if an attribute is <strong>of</strong> benefit type i.e. increase or decrease in the attribute value contributes in the same<br />

sense as that <strong>of</strong> the objective or index <strong>of</strong> the problem then the assigned values (Di’s) within the limits <strong>of</strong> 0-10 are<br />

normalized using the relation:<br />

Di = (10/Diu)*Diifor Dii=0, Di= {10/(Diu-Dil)}*(Dii-Dil) for Dii>0 Where Dil= lowest range value <strong>of</strong> the<br />

attribute,Diu : highest range value <strong>of</strong> the attribute Dii: value <strong>of</strong> the attribute (diagonal value in the matrix<br />

representation D(MxM),M is the order <strong>of</strong> the Matrix.However, if the attribute is <strong>of</strong> cost type i.e. increase or<br />

decrease in the attribute value contributes to the decrease or increase in the value <strong>of</strong> the objective or the index<br />

variable respectively, then the normalization <strong>of</strong> the attribute value is generally done between range <strong>of</strong> 0-10 by<br />

sing the following relation:Di = 10(1-Dii/Diu)for Dii=0,Di= {10/(Diu-Dil)}*(Diu-Dii) for Dii>0and notations<br />

have their usual meanings<br />

(e).Logically, develop a digraph between the factors or attributes depending on their inter-dependencies. A<br />

logical digraph <strong>of</strong> seven attributes having interdependencies with in the systems and each contributing to the<br />

overall system evaluation index or the objectives is shown as figure-1 below:<br />

Figure-1 Digraph showing seven attributes and their interdependencies for a system<br />

610


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Here ‘V1, V2,…..V6’ are the attributes <strong>of</strong> the system represented with interconnections thus reflecting the<br />

interdependencies with in the system.<br />

(f). Develop a universal performance based attributes based matrix which will be <strong>of</strong> order MxM, where ‘M’ is<br />

the total number <strong>of</strong> attributes affecting the system desired outcome. The matrix representation <strong>of</strong> the digraph as<br />

given in Figure 1 is represented as below:<br />

Attributes V1 V2 V3 V4 V5 V6<br />

V1 D1 a12 a13 a14 a15 a16<br />

V2 a21 D2 a23 a24 a25 a26<br />

V3 a31 a32 D3 a34 a35 a36<br />

A= V4 a41 a42 a43 D4 a45 a46<br />

V5 a51 a52 a53 a54 D5 a56<br />

V6 a61 a62 a63 a64 a65 D6<br />

(g). Obtain the permanent function for the attribute matrix as in step (f). Both digraph and matrix representation<br />

are not unique as they change by changing the labeling <strong>of</strong> nodes represented for the attributes considered. In<br />

order to have a unique representation independent <strong>of</strong> the labeling behaviour <strong>of</strong> the nodes, the permanent <strong>of</strong> the<br />

matrix (i.e. per(A)) is calculated which is a standard matrix function and is generally used in combinatorial<br />

mathematics. The permanent <strong>of</strong> the matrix ‘A’ is calculated in similar manner as determinant. However, during<br />

the calculation <strong>of</strong> permanent, per(A), , all negative signs introduced as in case <strong>of</strong> determinant are to be replaced<br />

by positive signs. This computation results in multinomial whose every term has a significance related to the<br />

overall evaluation <strong>of</strong> the system and no term significance is lost due to negative signs. This multinomial<br />

representation <strong>of</strong> the permanent, per(A) includes all the information regarding all critical factors or attributes and<br />

their interdependencies with in the system as a whole.<br />

The permanent function <strong>of</strong> the matrix form as represented above is given as :<br />

6<br />

per(A)= Vi<br />

∏ + ∑∑∑∑∑∑ (a ij.a ji ).V k .V l .V m .Vn<br />

i j k l m n<br />

1<br />

+<br />

∑∑∑∑∑∑ (a ij.a jk. a ki ).V l .V m .V n<br />

i j k l m n<br />

.<br />

+ {<br />

∑∑∑∑∑∑ (a ij.a jk. a kl. a li ).V m .V<br />

i j k l m n<br />

n<br />

+<br />

∑∑∑∑∑∑ (a ij.a ji).( a kl. a lk) ).V m .V n<br />

i j k l m n<br />

}<br />

+ {<br />

∑∑∑∑∑∑ (a ij.a jk. a kl. a lm. a mi ).V<br />

i j k l m n<br />

n<br />

+<br />

∑∑∑∑∑∑ (a ij.a kl. a ki).( a lm. a ml ).V n<br />

i j k l m n<br />

}<br />

+ {<br />

∑∑∑∑∑∑ (a ij.a jk. a kl. a lm. a mn. a ni<br />

i j k l m n<br />

)<br />

+<br />

∑∑∑∑∑∑ (a ij.a jk. a kl. a li).( a mn. a nm<br />

i j k l m n<br />

)<br />

+<br />

∑∑∑∑∑∑ (a ij.a ji).( a kl. a lk).( a mn. a nm ) }<br />

i j k l m n<br />

611


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The permanent <strong>of</strong> the matrix (i.e. equation 2) represented is a mathematical expression in symbolic form. It<br />

ensures an estimate <strong>of</strong> the system as a whole. The above equation (2) contains 6! terms. Each term is useful for<br />

system assessors as each term serves as a test <strong>of</strong> the effectiveness <strong>of</strong> the relevant group in permanent <strong>of</strong> the<br />

matrix A, i.e. per(A). Equation (2) contains terms arranged in N+ 1 groups, where N is the number <strong>of</strong><br />

elements..In the permanent, per(A) various groupings have their own physical significance. The first term<br />

(grouping) represents a set <strong>of</strong> seven independent subsystem characteristics as V 1 , V 2 , V 3 ,….V 6 . As there are no<br />

self loops with in the system itself, second groupings are absent. Each term <strong>of</strong> the third grouping represents a set<br />

<strong>of</strong> two elements attribute loops (i.e. a ij .a ji ) and is the resultant dependence <strong>of</strong> attribute i and j and the evaluation<br />

measure <strong>of</strong> N-2 connected terms. Each term <strong>of</strong> the fourth grouping represents a set <strong>of</strong> three element attribute<br />

loops (a ij .a jk .a ki or its pair a ik .a kj .a ji ) and the evaluation measure <strong>of</strong> N-3 unconnected elements or attributes with<br />

in the system. The fifth grouping contains two subgroups. The terms <strong>of</strong> first subgrouping consists <strong>of</strong> four element<br />

attribute loops (i.e. a ij .a jk. a kl. a li ) and the 3- subsystem evaluation index component (Dm.Dn.Dp). The terms <strong>of</strong> the<br />

second grouping are the product <strong>of</strong> two element attributes loops (a ij .a ji) ( a kl. a lk) ) and the index evaluation<br />

component (i.e. Dm.Dn.Dp). The terms <strong>of</strong> the sixth grouping are also arranged in two subgroupings. The terms<br />

<strong>of</strong> the first subgroupings are <strong>of</strong> five element attribute loop (i.e. a ij .a jk .a kl .a lm .a mi ) or its pair (a im .a ml .a lk .a kj .a ji ). the<br />

second subgrouping consists <strong>of</strong> a product <strong>of</strong> two attributes loops (i.e. a ij .a ji ) and a three attribute loop (i.e.<br />

a kl .a lm .a mk ) or its pair (i.e. a km .a ml .a lk ) and the index evaluation component (i.e. D n D p ). The terms <strong>of</strong> seventh<br />

groupings are also arranged in three subgrouping. The terms <strong>of</strong> first subgrouping <strong>of</strong> seventh subgrouping are <strong>of</strong><br />

six elemental attribute loop (i.e. a ij .a jk .a kl .a lm .a mn. .a ni ). the terms <strong>of</strong> second subgrouping <strong>of</strong> seventh grouping are<br />

<strong>of</strong> four element attribute loop (i.e. a ij .a jk .a kl .a li ) and two element attribute loop (i.e. a mn .a nm) with one - subsystem<br />

evaluation index component (Dp). The third subgrouping <strong>of</strong> the seventh grouping is a set <strong>of</strong> 3- two element<br />

attribute loops (i.e. a ij .a ji , a kl .a lk , a mn .a nm ) and a one - subsystem evaluation index component (Dp). Thus the<br />

permanent function characterizes a system for selected number <strong>of</strong> attributes as it contains all possible<br />

components <strong>of</strong> attributes and their relative importance.(h). Arrange the type <strong>of</strong> systems in descending order <strong>of</strong><br />

the evaluation index. The system having the highest value <strong>of</strong> the calculated index is the best choice for the given<br />

set <strong>of</strong> attributes over their prescribed operating ranges. (i). perform the sensitivity analysis for the attributes over<br />

the domains <strong>of</strong> influence for a few cases.<br />

3. Formulation <strong>of</strong> The EDM process problem and its Solution<br />

In the present work, the Electric Discharge Machining process is modeled as a process Graph Model where in the<br />

attributes have been considered which affect the material removal rate significantly under constrained<br />

operational conditions <strong>of</strong> the process. It has been observed that even though there are a number <strong>of</strong> controlling<br />

factors including ambient conditions as well as related to MCU (i.e. Machine Control Unit <strong>of</strong> Electric Discharge<br />

Machine- conventional or CNC type), but when operation is performed on a work piece with some <strong>of</strong> the desired<br />

outcomes like surface finish, tool wear with in the prescribed limits, then several controlling variables or the<br />

attributes are almost constant and becomes the inherent but constant attributes for a given process conditions.<br />

Desired outcomes <strong>of</strong> the Electric Discharge machining process:<br />

Material removal rate , MRR, Absolute wear <strong>of</strong> Tool electrode, Ua,Productivity <strong>of</strong> the machined surface, Qp,.<br />

Wear <strong>of</strong> the Tool electrode, γ ES, ,Roughness <strong>of</strong> the machined surface, Ra,. Power consumption, P. Working<br />

Speed, Vp, Gap Size, S<br />

Following input parameters are considered for analyzing any <strong>of</strong> the above mentioned desired output:<br />

(a). Current intensity, I,. Pulse time, Ta,. Pulse Interval, Tb, Working depth, h,. Polarity <strong>of</strong> the Tool electrode P(-<br />

), Polarity <strong>of</strong> the Tool-Piece P(+)As per the technical recommendations <strong>of</strong> the Electric discharge Machine tools,<br />

while testing generally, following considerations are generally taken into account for further process analysis:<br />

(i). The working depth is generally kept constant and is recommended as equal to 2 mm for testing purposes.<br />

However, once the data analysis has been carried out through the theory <strong>of</strong> experiments, higher order working<br />

depths may be considered.<br />

(ii). The polarity <strong>of</strong> the Tool electrode P(-) and the polarity <strong>of</strong> the Tool Piece P(+) are kept as constant and the<br />

entire experimental data is collected and analyzed for a constant vale <strong>of</strong> P(-) and P(+), however, these variables<br />

are not <strong>of</strong> fixed type and their variation affect the Material removal rate and the surface finish parameters<br />

significantly..At present, in this work, a particular case <strong>of</strong> EDM process has been analyzed. It is granted that<br />

cylindrical copper electrode is to be used as a tool and tool steel as the machining material. It is assumed to have<br />

constant dielectric pressure and average working voltage while taking the experimental readings which are to be<br />

used further for regression analysis. After analyzing the experimental data, as available in the literature,<br />

following attributes or the system variables, which affect the performance parameters <strong>of</strong> the Electric Discharge<br />

machining Model, are listed as below in their increasing order using<br />

612


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 3<br />

Sr. No.<br />

Name <strong>of</strong> the attribute for<br />

EDM process<br />

Significance as per the order <strong>of</strong> its influence on<br />

process objectives<br />

1 Pulse time, Ta Very very critical ( rated 8 on a scale <strong>of</strong> 10)<br />

2 Current intensity, I, Very critical ( rated 7 on a scale <strong>of</strong> 10)<br />

3 Pulse Interval, Tb critical ( rated 6.5 on a scale <strong>of</strong> 10)<br />

4 Polarity <strong>of</strong> the Tool electrode Significant but not critical ( rated 5 on a scale <strong>of</strong><br />

P(-)<br />

10)<br />

5 Polarity <strong>of</strong> the Tool-Piece Significant but not critical ( rated 5 on a scale <strong>of</strong><br />

P(+)<br />

10)<br />

6 Working depth, h significant ( rated 4 on a scale <strong>of</strong> 10)<br />

From various graphs <strong>of</strong> the process variables for Electric Discharge Machining process, the interactions between<br />

the various attributes have been analyzed as below table :<br />

Dependency <strong>of</strong><br />

attributes<br />

Table 4<br />

Dependency on attributes<br />

I Ta Tb P(-) P(+) h<br />

I --- <strong>20</strong>% 35% 25% 30% 40%<br />

Ta 40% --- 35% --- 55% ---<br />

Tb 35% 60% --- 50% 40% 50%<br />

P(-) --- 30% 60% --- 60% ---<br />

P(+) 40% --- <strong>20</strong>% 15% --- 40%<br />

h --- 25% --- 40% 50% ---<br />

The combined matrix as used for the permanent calculation <strong>of</strong> the inheritance effect <strong>of</strong> the attributes and their<br />

interdependencies is further represented in below table:<br />

Dependency <strong>of</strong><br />

attributes<br />

Table 5<br />

Dependency on attributes<br />

I Ta Tb P(-) P(+) h<br />

I 0.70 0.<strong>20</strong> 0.35 0.25 0.30 0.40<br />

Ta 0.40 0.80 0.35 --- 0.55 ---<br />

Tb 0.35 0.60 0.65 0.50 0.40 0.50<br />

P(-) --- 0.30 0.60 0.50 0.60 ---<br />

P(+) 0.40 --- 0.<strong>20</strong> 0.15 0.50 0.40<br />

h --- 0.25 --- 0.40 0.50 0.40<br />

In order to calculate the Permanent <strong>of</strong> the Matrix [P] as shown below, the number <strong>of</strong> terms has been represented<br />

in Micros<strong>of</strong>t EXCEL and computations have been done in EXCEL which can be easily used for the sensitivity<br />

analysis <strong>of</strong> the attributes on the Electrical Discharge Machining process.<br />

Table 6<br />

I Ta Tb P(-) P(+) h<br />

0.70 0.<strong>20</strong> 0.35 0.25 0.30 0.40<br />

0.40 0.80 0.35 --- 0.55 ---<br />

[P] = 0.35 0.60 0.65 0.50 0.40 0.50<br />

--- 0.30 0.60 0.50 0.60 ---<br />

0.40 --- 0.<strong>20</strong> 0.15 0.50 0.40<br />

--- 0.25 --- 0.40 0.50 0.40<br />

Since the Micros<strong>of</strong>t EXCEL worksheet is dynamic enough to explore the effect <strong>of</strong> changes in the<br />

interdependency factor in the Matrix [P] in particular constructed for the EDM process. For the present<br />

computation, the effect <strong>of</strong> present state <strong>of</strong> the Interdependencies <strong>of</strong> the attributes, the pictorial representation <strong>of</strong><br />

the computations for the Subgrouping under various groupings is shown in below table:<br />

613


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 7<br />

0.7 0.2 0.35 0.25 0.3 0.4<br />

0.4 0.8 0.35 0 0.55 0<br />

0.35 0.6 0.65 0.5 0.4 0.5<br />

0 0.3 0.6 0.5 0.6 0<br />

0.4 0 0.2 0.15 0.5 0.4<br />

0 0.25 0 0.4 0.5 0.4<br />

After analyzing the experimental data as contained in the literature, it is logically pointed out that the variation in<br />

the level <strong>of</strong> interdependencies is as under for a given set <strong>of</strong> experimental work and test measurements in the<br />

below tables:<br />

Table 8<br />

The terms as contained in the permanent calculations for the various subgrouping under various grouping are represented as result Table Total<br />

Groupings Group-1 group- group- group-<br />

group-5 group-6 group-7<br />

2 3 4<br />

subgroup Subgroup- Total(5) subgroup-I Subgroup- Total(6) subgroup-I Subgroup Total(7)<br />

-I II<br />

II<br />

-II<br />

No. <strong>of</strong><br />

Terms<br />

1 0 15 40 45 90 135 1<strong>20</strong> 144 264 145 1<strong>20</strong> 265 7<strong>20</strong>.00<br />

Value <strong>of</strong><br />

the<br />

Groupings<br />

0.0364 0 0.3174<br />

1<br />

0.2262<br />

81<br />

0.096632 0.23139 0.328022 0.157163 0.<strong>19</strong>4081 0.351244 0.08381 0.079664 0.1635 1.42<br />

Table 9<br />

Variation <strong>of</strong><br />

interdependency<br />

<strong>of</strong> attributes<br />

Variation in interdependencies on attributes<br />

I Ta Tb P(-) P(+) h<br />

I --- <strong>20</strong>%-30% 35%-40% 25% 30% 40%<br />

Ta 40% --- 35% --- 55% ---<br />

Tb 35%-45% 60% --- 50%-55% 40% 50%<br />

P(-) --- 30% 60% --- 60% ---<br />

P(+) 40% --- <strong>20</strong>% 15% --- 40%-50%<br />

h --- 25% --- 40% 50% ---<br />

For the sensitivity analysis, the effect <strong>of</strong> variation in the . Effect <strong>of</strong> variation <strong>of</strong> ‘Tb’ on ‘P(-Interdependencies is<br />

considered:<br />

.<br />

Table 10<br />

Effect <strong>of</strong> variation <strong>of</strong> ‘I’ on ‘Tb’<br />

Total<br />

Groupings<br />

Group-<br />

1<br />

group-<br />

2<br />

group-<br />

3<br />

group-4 group-5 group-6 group-7<br />

subgroup-<br />

I<br />

Subgroup-<br />

II<br />

Total(5) subgroup-<br />

I<br />

Subgroup-<br />

II<br />

Total(6)<br />

Subgroup-<br />

II<br />

Total(7)<br />

Variation<br />

factor<br />

0.35<br />

0.375<br />

0.40<br />

No. <strong>of</strong> Terms 1 0 15 40 45 90 135 1<strong>20</strong> 144 264 145 1<strong>20</strong> 265 7<strong>20</strong>.00<br />

Value <strong>of</strong> the<br />

Groupings<br />

Value <strong>of</strong> the<br />

Groupings<br />

Value <strong>of</strong> the<br />

Groupings<br />

0.0364 0 0.31391 0.224251 0.094728 0.226838 0.321566 0.153488 0.<strong>19</strong>0026 0.343514 0.082179 0.077952 0.1601 1.40<br />

0.0364 0 0.31541 0.225491 0.095544 0.23007 0.325614 0.155161 0.<strong>19</strong>2232 0.347393 0.083366 0.078887 0.1623 1.41<br />

0.0364 0 0.31691 0.226731 0.09636 0.233303 0.329663 0.156833 0.<strong>19</strong>4438 0.351271 0.084552 0.079821 0.1644 1.43<br />

614


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4. Result and Discussion<br />

In the present work, the permanent index have been calculated for the standard operating conditions <strong>of</strong> the<br />

process parameters or the attributes for the desired objectives like increase in the metal removal rate. It has been<br />

observed that the permanent <strong>of</strong> the sub-groupings for the attributes gives the informative knowledge related to<br />

the Electric Discharge Machining process. The subgrouping permanent function gives information related to its<br />

effect on the overall permanent functional value for an attribute variation. Since, various graphs as available in<br />

the technical documents <strong>of</strong> the EDMs as well as experimental data for the Electric Discharge Machining process<br />

are used for developing and analyzing the logical interdependencies <strong>of</strong> the attributes along with their inheritance<br />

factors on the machining process, so the results during the sensitivity analysis as carried out in previous chapter<br />

is an alternate representation <strong>of</strong> the Electric Discharge Machining Process which can be used ahead for<br />

simulating the process under the extended limits <strong>of</strong> the process constraints or the attributes.<br />

The variation in the process index i.e. the permanent <strong>of</strong> the logical matrix developed also gives the same effect<br />

on the desired objective <strong>of</strong> material removal rate for the Electric Discharge Machining process. Hence, the efforts<br />

done for the logical representation <strong>of</strong> the process is found to be satisfactory in terms <strong>of</strong> usage <strong>of</strong> graph theoretic<br />

approach as a tool for simulating such process constraints and further benchmarking <strong>of</strong> the process.<br />

5. References<br />

1. Bhattacharyya S.K., Menshawy, “ A correlation between machining parameters and machineability in<br />

EDM”, International Journal <strong>of</strong> Production Research, Volume <strong>19</strong>, Issue 2, Pages 111-122, <strong>19</strong>81<br />

2. Cogun C, Ilhan C, “ The Process Parameter Dependence <strong>of</strong> the Occurrence <strong>of</strong> Discharge Pulses in<br />

EDM”, Australian Journal <strong>of</strong> Electrical & Electronics Engineering, Vol. 21 No. 2 , <strong>20</strong>09<br />

3. Dixon L.C. , “ Non Linear Optimization”, The English <strong>University</strong> Press, London<br />

4. Iuras E., “ Experimental contributions regarding numerical modeling <strong>of</strong> the relative wear <strong>of</strong> the tool<br />

electrode at EDM process”, proceedings <strong>of</strong> ESAFORM <strong>20</strong>08, Romania<br />

5. Ivanov A. et. el“, Micro EDM process Modeling and Process capabilities”, Journal <strong>of</strong> materials and<br />

Machining” Volume 47, <strong>20</strong>08<br />

6. Gandhi O.P., Venkata Rao R., “ Digraph and matrix methods for the machineability evaluation <strong>of</strong> work<br />

materials”, International Journal <strong>of</strong> Machine Tools and manufacture, Volume 42, Pages 321-330, <strong>20</strong>02<br />

7. Gao Q.,Zhang Q.H.,Su S.P., Zhang J.H.,” Parameter optimization model in Electrical discharge<br />

machining process”, Journal <strong>of</strong> Zheiiang <strong>University</strong>- <strong>Science</strong> A, Volume 9, Number 1,Pages 104-108,<br />

January <strong>20</strong>08,<br />

8. Grover S., Agrawal V.P., Khan I.A.,“Human resource performance Index in TQM environment”<br />

International Journal <strong>of</strong> management Practice, Volume 1, Number 2, <strong>20</strong>05<br />

9. Guu Y. H. , Deng C.S., “ Effect <strong>of</strong> electrical discharge machining on surface characteristics and<br />

machining damage <strong>of</strong> AISI D2 Tool steel”, Journal <strong>of</strong> Material science and Engineering, <strong>20</strong>03, Volume<br />

A358, pages 37-43.<br />

10. Jain, V. K., "Multi-Objective Optimization <strong>of</strong> Electro discharge Machining Process," Microtechnic<br />

journal issue, Vol. 2, <strong>19</strong>90, pp. 33-37.<br />

11. Junker M. at el., “Comparison <strong>of</strong> Material removal in micro and conventional EDM”, Journal <strong>of</strong><br />

material processing technology, Volume 24, <strong>20</strong>07<br />

12. Kalyanmoy Deb “Optimization Techniques in Engineering with examples”, PHI, <strong>20</strong>04<br />

13. Kusur D., Valenticic J., “Machining parameters selection for varying surface in EDM”, International<br />

Journal <strong>of</strong> Materials and product technology, Volume 29, Number 1, Pages 344-357, <strong>20</strong>07<br />

14. Lajis M. A., Nurul Amin A. K. M.,”The implementation <strong>of</strong> TAGUCHI method on EDM procees <strong>of</strong><br />

Tungston carbine”, Europian Journal <strong>of</strong> Scientific Research, Volume 26, No.-4, Pages 609-617, <strong>20</strong>09<br />

15. L.C. Lim, H.H. Lu," Towards a Better Understanding <strong>of</strong> the Surface Features <strong>of</strong> Electro-discharge”,<br />

Journal <strong>of</strong> Materials Processing <strong>Technology</strong>, Vol. 24,pp.513-523, <strong>19</strong>90<br />

16. Mahdavinejad R.A., “Optimization <strong>of</strong> Electro discharge Machining parameters,” Journal <strong>of</strong><br />

achievements in materials and Manufacturing Engineering, Volume 27, issue 2, April <strong>20</strong>08<br />

615


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

MATHEMATICAL MODELING OF HAZ IN SUBMERGED ARC<br />

WELDING PROCESS USING FACTORIAL DESIGN TECHNIQUE<br />

Hari Om 1 , Sunil Pandey 2 , Dinesh Rathod 3<br />

1 Deptt. <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong>UST, Faridabad, Haryana -121006. email: hariohm<strong>20</strong>01@gmail.com<br />

2 Department <strong>of</strong> Mechanical Engineering, Indian Institute <strong>of</strong> <strong>Technology</strong> Delhi, New Delhi-110016<br />

(Presently Director, Sant Longowal Institute <strong>of</strong> Engineering &<strong>Technology</strong>, Sangrur, Punjab)<br />

3 Department <strong>of</strong> Mechanical Engineering, Indian Institute <strong>of</strong> <strong>Technology</strong> Delhi, New Delhi-110016<br />

Abstract<br />

Submerged arc welding (SAW), a fusion joining process is known for its high deposition capabilities. This<br />

process is useful in joining thick sections used in various industries. High deposition rates are obtained because<br />

high welding current level can be used with this process. Besides joining, SAW is also used for surfacing applications.<br />

Heat Affected Zone (HAZ) produced within the base metal and around the fused metal as a result <strong>of</strong><br />

large heat input is <strong>of</strong> big concern since it affects the performance <strong>of</strong> welded/surfaced structure in service due to<br />

metallurgical changes in the base metal /substrate. This work was carried out to investigate the effect <strong>of</strong> polarity<br />

and other SAW parameters on HAZ size. Empirical models have been developed using fractional factorial design<br />

technique.<br />

Keywords: Submerged arc welding, Weld Dilution, Electrode Polarity. Heat Affected Zone<br />

1. Introduction<br />

Submerged Arc Welding (SAW) is primarily used in shipbuilding, pipe fabrication, pressure vessels, and structural<br />

components for bridges and buildings due to its high deposition rate (Chandel, Seow et al. <strong>19</strong>97). Other<br />

than joining, SAW is used to build up parts and overlay with stainless or wear-resistant steel for example, rolls<br />

for continuous casting steel, pressure vessels, rail car wheels, and equipment for mining, mineral processing,<br />

construction, and agriculture SAW normally uses constant-voltage power supply and is self-regulating, so it can<br />

be used with a constant-speed wire feeder. The current is controlled by the wire diameter, the electrical stick-out,<br />

and the wire-feed speed, while the voltage is controlled by the power supply.(Olson, Siewert et al. <strong>19</strong>93).No<br />

shielding gas is needed because arc is submerged and the molten metal is separated from the air by the molten<br />

slag and granular flux. Direct-current electrode positive is most <strong>of</strong>ten used. However, at very high welding currents,<br />

AC is preferred in order to minimize arc blow (Kou <strong>20</strong>03).<br />

The knowledge <strong>of</strong> how welding process parameters affect weld bead geometry is important because it can be<br />

applied in automatic and semiautomatic control <strong>of</strong> arc welding processes where optimal selection <strong>of</strong> input parameters<br />

is required for high productivity and cost effectiveness (Shen, Oguocha et al. <strong>20</strong>12). The welding current<br />

direction also affects the weld bead pr<strong>of</strong>ile. The current may be direct with the electrode positive (reverse polarity),<br />

electrode negative (straight polarity), or alternating (Olson, Siewert et al. <strong>19</strong>93). As reported by various researchers,<br />

electrode positive polarity produces wider beads usually with more penetration depth and Electrode<br />

negative yields narrower beads with low penetration. (Chandel <strong>19</strong>87, May; Yang, Chandel et al. <strong>19</strong>93, Jan).<br />

Mechanical properties <strong>of</strong> a welded joint are dictated mainly by weld bead contour, HAZ area, precipitation<br />

process and heat input during welding (Lancaster <strong>19</strong>93). Base metal in the vicinity <strong>of</strong> deposited weld metal undergoes<br />

a considerable change metallurgically and mechanically due to weld thermal cycle. Size <strong>of</strong> this heat affected<br />

zone (HAZ) depends on the heat input and is to be predicted for better analysis and understanding <strong>of</strong> the<br />

characteristics <strong>of</strong> HAZ affecting the microstructure and properties <strong>of</strong> the welded steel (Gunaraj and Murugan<br />

<strong>19</strong>99). The most intriguing issue is about HAZ s<strong>of</strong>tening that imparts some uncertainties in the welded quality. It<br />

increases the probability <strong>of</strong> fatigue failures at the weakest zones caused by the heating and cooling cycle <strong>of</strong> the<br />

weld zone(Ghosh, Chattopadhyaya et al. <strong>20</strong>11).<br />

2. Literature Survey<br />

Extensive work has been done by many researchers in the field <strong>of</strong> submerged arc welding and various aspects <strong>of</strong><br />

this fusion joining process have been discussed. Some <strong>of</strong> these researches have been highlighted.<br />

(Pandey, Bharti et al. <strong>19</strong>94) showed in their work that welding current and voltage have an appreciable influence<br />

on element transfer, as well as on weld composition. Weldment properties such as strength, toughness and solidification<br />

cracking behaviour are affected by chemical composition <strong>of</strong> the weld. (Chandel, Seow et al. <strong>19</strong>97)<br />

through their research, presented theoretical predictions <strong>of</strong> the effect <strong>of</strong> current, electrode polarity, electrode<br />

616


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

diameter and electrode extension on the melting rate, bead height, bead width and weld penetration, in submerged-arc<br />

welding.<br />

(Gunaraj and Murugan <strong>19</strong>99) studied the effect <strong>of</strong> controllable process variables on the heat input and the area <strong>of</strong><br />

the heat-affected zone (HAZ) for bead-on-plate and bead-on joint welding using mathematical models developed<br />

for the submerged arc welding <strong>of</strong> pipes (SAW). A comparative study <strong>of</strong> the area <strong>of</strong> the heat-effected zone between<br />

bead-on-plate and bead-on-joint welding was then carried out.(Gunaraj and Murugan <strong>19</strong>99; Murugan and<br />

Gunaraj <strong>20</strong>05) again addressed the main problem faced in the manufacture <strong>of</strong> pipes by the SAW process regarding<br />

the selection <strong>of</strong> the optimum combination <strong>of</strong> input variables for achieving the required qualities <strong>of</strong> weld using<br />

response surface methodology.<br />

(Pandey <strong>20</strong>04) proposed a relationship between welding current and direct SAW process parameters using two<br />

level half factorial design. Interactive effects <strong>of</strong> direct parameters were also studied. The study performed by<br />

(Karaoğlu and Seçgin <strong>20</strong>08) focused on the sensitivity analysis <strong>of</strong> parameters and fine tuning requirements <strong>of</strong> the<br />

parameters for optimum weld bead geometry. Effects <strong>of</strong> design parameters on the bead width and bead height<br />

showed that even small changes in these parameters play an important role in the quality <strong>of</strong> welding operation.<br />

(Dhas and Kumanan <strong>20</strong>11) used Taguchi’s Design <strong>of</strong> Experiments and regression analysis to establish input–<br />

output relationships <strong>of</strong> the process. By this relationship, an attempt was made to minimize weld bead width, a<br />

good indicator <strong>of</strong> bead geometry, using optimization procedures based on the genetic algorithm (GA) and particle<br />

swarm optimization (PSO) algorithm to determine optimal weld parameters.<br />

(Ghosh, Chattopadhyaya et al. <strong>20</strong>11) addressed the issue associated the uncertainties involved with the heat affected<br />

zone (HAZ) in and around the weldment produced by SAW process. They assessed the heat affected zone<br />

<strong>of</strong> submerged arc welding <strong>of</strong> structural steel plates through the analysis <strong>of</strong> the grain structure by means <strong>of</strong> digital<br />

image processing techniques. It was concluded that the grains are predominantly <strong>of</strong> smaller variety and the<br />

counts for larger grain are almost negligible.<br />

A series <strong>of</strong> measurements was carried out by (Shen, Oguocha et al. <strong>20</strong>12) on specimens <strong>of</strong> submerged arc welded<br />

plates <strong>of</strong> ASTM A709 Grade 50 steel. The bead reinforcement, bead width, penetration depth, HAZ size, deposition<br />

area and penetration area increased with increasing heat input, but the bead contact angle decreased with it.<br />

The electrode melting efficiency increased initially and then decreased with increasing heat input, but the plate<br />

melting efficiency and percentage dilution changed only slightly with it. Cooling time exhibited a very good linear<br />

relationship with the total nugget area, heat transfer boundary length, and nugget parameter.<br />

3. Motivation for the present work<br />

A lot <strong>of</strong> work has been done in past years for the modeling <strong>of</strong> bead geometry & shape relationships in terms <strong>of</strong><br />

submerged arc welding process parameters. Various statistical and modeling technique have used by different<br />

authors. Heat Affected Zone, which is a critical region in any weldment, had been modeled by Gunaraj and Murugan<br />

years back in <strong>19</strong>99. They correlated HAZ area with the heat input and other welding parameters and comparison<br />

was done between HAZ produced in bead on plate welds and pipe joint welds. It was concluded that for<br />

the same heat input the area <strong>of</strong> the HAZ is greater on the plate than on the joint.<br />

No studies in the past, however been done to find the effect <strong>of</strong> polarity on the size <strong>of</strong> heat affected zone in submerged<br />

arc welding. In the present work an attempt is made to fill this gap by modeling HAZ width and area for<br />

electrode positive and electrode negative polarity using factorial design technique.<br />

4. Scheme <strong>of</strong> Investigation<br />

4.1. Identification <strong>of</strong> parameters and determination <strong>of</strong> working limits<br />

Based on available literature, four predominant parameters i.e. wire feed rate (WFR), open circuit voltage<br />

(OCV), welding speed (WS) and electrode polarity (PO), which can be varied independently were selected for<br />

the stud (Om and Pandey <strong>20</strong>10). The working limits <strong>of</strong> selected parameters were finalized on the basis <strong>of</strong> a large<br />

number <strong>of</strong> trial runs. Minimum and maximum levels <strong>of</strong> each parameter were decided by inspecting the resulting<br />

bead on plate carefully during trial experiments. Only those parameter limits were selected, which resulted free<br />

<strong>of</strong> any visible welding defect like surface porosity, undercut, overlap, excessive convexity, cracks and showed<br />

smooth and uniform appearance throughout the length. The high and low levels <strong>of</strong> the parameters were coded as<br />

+1 and -1 respectively. The actual values <strong>of</strong> parameters corresponding to the coded values are given in<br />

Table 1<br />

617


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 1: Parameters and their values at two levels<br />

Process parameter Units Notation Type <strong>of</strong> parameter Low Level (-1) High Level (+1)<br />

Open Circuit Voltage Volts OCV Numeric 33 42<br />

Wire Feed mm/sec WFR Numeric 16 28<br />

Welding Speed mm/sec WS Numeric 5.5 10<br />

Polarity PO Categorical Electrode Negative ( EN) Electrode Positive (EP)<br />

Coded value for any intermediate actual value <strong>of</strong> given variable can be calculated from the following relationship:<br />

X = [2x - (x max + x min )] / (x max - x min )<br />

…(1)<br />

Where X is the required coded value <strong>of</strong> a variable, x is any actual value <strong>of</strong> variable lying between x min to x max ,<br />

x min and x max are the actual values <strong>of</strong> variable at low and high levels respectively (Murugan and Parmar <strong>19</strong>93;<br />

Pandey <strong>20</strong>04).<br />

4.2. Developing the design matrix<br />

Statistical design <strong>of</strong> experiment is the process <strong>of</strong> planning the experiment so that the appropriate data that can be<br />

analyzed by statistical methods will be collected, resulting in valid and objective conclusions (Montgomery<br />

<strong>20</strong>01). This approach is necessary if we wish to draw any meaningful conclusions from the data. Factorial designs<br />

are the most efficient experimental design methods since all possible combinations <strong>of</strong> the levels <strong>of</strong> the factors<br />

are investigated in each trial <strong>of</strong> the experiment (Anderson and McLean <strong>19</strong>74).The numbers <strong>of</strong> trials in a factorial<br />

experiment increase considerably with increase in the number <strong>of</strong> factors (Adler <strong>19</strong>75). Fractional factorial<br />

experiments are important alternatives to complete factorial experiments when budgetary, time, or experimental<br />

constraints preclude the execution <strong>of</strong> complete factorial experiments (Mason, Gunst et al. <strong>20</strong>03). In this work, a<br />

half fractional factorial design was adopted to cut down the number <strong>of</strong> runs needed.<br />

Regression<br />

Coefficient<br />

Table 2. Design matrix for calculating coefficients.<br />

WFR OCV WS PO WFR*OCV=<br />

WS*PO<br />

WFR*WS=<br />

OCV*PO<br />

WFR*PO=<br />

OCV*WS<br />

1 2 3 4 12 =34 13=24 14=23<br />

b o b 1 b 2 b 3 b 4 b 5 b 6 b 7<br />

1 1 1 1 1 1 1 1<br />

1 -1 1 1 -1 -1 -1 1<br />

1 1 -1 1 -1 -1 1 -1<br />

1 -1 -1 1 1 1 -1 -1<br />

1 1 1 -1 -1 1 -1 -1<br />

1 -1 1 -1 1 -1 1 -1<br />

1 1 -1 -1 1 -1 -1 1<br />

1 -1 -1 -1 -1 1 1 1<br />

The design matrix considering four independent welding parameters was developed as per 2 k-1 fractional factorial<br />

design to conduct a total <strong>of</strong> eight runs (2 4-1 = 8) as shown in Table 2. Three numeric parameters WFR, OCV, WS<br />

and a categorical parameter PO have been represented by the numbers 1, 2, 3 and 4 respectively. The main effect<br />

<strong>of</strong> electrode polarity (PO) was confounded with the other three parameters (WFR, OCV, WS) interaction effect.<br />

The forth column <strong>of</strong> the matrix was generated using the confounding pattern. The signs under the column 1, 2, 3<br />

were arranged in standard Yate’s method (Adler <strong>19</strong>75), while those under the column 4 were obtained by selecting<br />

a generating relation 4 =123. This means, defining contrast for the design was I=1234. Three parameters and<br />

higher order interactions were assumed to be negligible; the half fractional factorial design <strong>of</strong> eight runs provided<br />

eight estimates for the effect <strong>of</strong> four welding parameters on a particular response. Out <strong>of</strong> these estimates, one<br />

estimate was for the mean effect <strong>of</strong> all the parameters on response, four estimates for the main effects and the<br />

remaining three confounded estimates for two parameter interactions (Adler <strong>19</strong>75; Pandey <strong>20</strong>04).<br />

618


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4.3. Experimental Procedure<br />

A direct current constant voltage power source and mechanized Submerged Arc Welding equipment with a current<br />

capacity <strong>of</strong> 600 amperes was used for the experimentation. The equipment could be used for an open circuit<br />

voltage range <strong>of</strong> 12-48 volts. A ‘single bead on plate’ technique was used to deposit beads on 250mm x 75mm x<br />

10mm mild steel plates. A general purpose agglomerated acidic flux (AWS SFA A-5.17) with a basicity index <strong>of</strong><br />

0.6 was used along with a compatible mild steel electrode <strong>of</strong> 3.15 mm. The plates were cleaned chemically and<br />

mechanically to remove rusting and possible sources <strong>of</strong> hydrogen such as grease and oil etc. The bead was deposited<br />

along the longitudinal centre line <strong>of</strong> each plate carefully so that the heat distribution on both sides <strong>of</strong> bead<br />

remained same. The plates were then left to cool at room temperature.<br />

Three replicates for each <strong>of</strong> eight experimental runs (total runs 8x3 =24) were conducted as per the design matrix.<br />

The nozzle to plate distance was kept constant throughout the experiment at 30 mm. These runs were performed<br />

randomly as the randomization protects against unknown biases, including any unanticipated or unobservable<br />

“break-in” effects due to greater or lesser care in conducting the experiment (Mason, Gunst et al. <strong>20</strong>03).<br />

4.4. Recording <strong>of</strong> responses<br />

Welding current and welding voltage were recorded during welding for each experimental run. After cooling at<br />

room temperature each plate was cut at the centre transverse to the welding direction in order to obtain the specimen<br />

<strong>of</strong> about 10 mm thickness. The sized specimens were molded with Bakelite and then polished using fine<br />

grade emery papers. Molded specimens were then etched with 2% Nital solution in order to reveal different<br />

zones <strong>of</strong> deposited weld bead. Well etched specimens were then scanned using high resolution scanner and bead<br />

pr<strong>of</strong>iles and area <strong>of</strong> HAZ were measured carefully using adobe acrobat measuring tools.<br />

Table 3 Experimental design matrix and measured responses<br />

Design Matrix (SAW Parameters)<br />

Coded Values<br />

Actual values<br />

S.No. WFR OCV WS PO WFR OCV WS PO<br />

6<strong>19</strong><br />

Responses<br />

HAZ Width<br />

(mm)<br />

HAZ Area<br />

(sq. mm)<br />

1 -1 -1 -1 (-1) 16 33 5.5 EN 1.34 29.60<br />

2 -1 -1 -1 (-1) 16 33 5.5 EN 1.48 26.70<br />

3 -1 -1 -1 (-1) 16 33 5.5 EN 1.68 26.30<br />

4 1 -1 -1 (1) 28 33 5.5 EP 2.<strong>20</strong> 36.<strong>20</strong><br />

5 1 -1 -1 (1) 28 33 5.5 EP 2.90 39.70<br />

6 1 -1 -1 (1) 28 33 5.5 EP 2.50 34.50<br />

7 -1 1 -1 (1) 16 42 5.5 EP 4.<strong>20</strong> 55.60<br />

8 -1 1 -1 (1) 16 42 5.5 EP 4.40 71.90<br />

9 -1 1 -1 (1) 16 42 5.5 EP 4.10 68.90<br />

10 1 1 -1 (-1) 28 42 5.5 EN 6.35 69.52<br />

11 1 1 -1 (-1) 28 42 5.5 EN 5.66 75.27<br />

12 1 1 -1 (-1) 28 42 5.5 EN 6.05 73.85<br />

13 -1 -1 1 (1) 16 33 10 EP 1.06 10.40<br />

14 -1 -1 1 (1) 16 33 10 EP 1.00 10.60<br />

15 -1 -1 1 (1) 16 33 10 EP 1.<strong>20</strong> 10.80<br />

16 1 -1 1 (-1) 28 33 10 EN 1.27 16.65<br />

17 1 -1 1 (-1) 28 33 10 EN 1.33 13.86<br />

18 1 -1 1 (-1) 28 33 10 EN 1.53 15.56<br />

<strong>19</strong> -1 1 1 (-1) 16 42 10 EN 1.35 14.85<br />

<strong>20</strong> -1 1 1 (-1) 16 42 10 EN 1.35 21.60<br />

21 -1 1 1 (-1) 16 42 10 EN 1.59 23.66<br />

22 1 1 1 (1) 28 42 10 EP 3.50 42.70<br />

23 1 1 1 (1) 28 42 10 EP 2.71 34.60<br />

24 1 1 1 (1) 28 42 10 EP 3.50 44.90<br />

4.5. Development <strong>of</strong> model<br />

Table 3 shows the experimental design matrix and measured responses. The functional relationship<br />

R = f(WFR, OCV, WS, PO) was considered, where R is one <strong>of</strong> the responses. This relation can be expressed<br />

as shown in Eq. (2).<br />

R=b 0 + b 1 WFR + b 2 OCV + b 3 WS + b 4 PO + b 12 WFR*OCV + b 13 WFR*WS + b 14 WFR*PO + b 23 OCV*WS +<br />

b 24 OCV*PO + b 34 PO*WS . …(2)


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

According to confounding pattern, 12=34, 13=24 and 14=23, shown in<br />

given in Eq. (3).<br />

Table 2, the above relation can be modified by incorporating the confounding parameters as<br />

R = b 0 + b 1 WFR + b 2 OCV + b 3 WS + b 4 PO + b 5 WFR*OCV + b 6 WFR*WS + b 7 WFR*PO<br />

Where, b 5 = (b 12 + b 34 ), b 6 = (b 13 + b 24 ), & b 7 = (b 14 + b 23 )<br />

…(3)<br />

Checking the adequacy <strong>of</strong> developed model<br />

The significance <strong>of</strong> the model was tested by using Analysis <strong>of</strong> Variance (ANOVA) technique. The results <strong>of</strong><br />

ANOVA for responses are shown in Table 4 & Table 5. These tables show details <strong>of</strong> sum <strong>of</strong> squares (SS), degrees<br />

<strong>of</strong> freedom (DF), mean square (MS), F-Ratio (F- VALUE) and Probability <strong>of</strong> larger F- value (P- VALUE)<br />

along with the percentage contribution (CONTR%) <strong>of</strong> each <strong>of</strong> the factors and their interactions in the model<br />

(Fnides, Yallese et al. <strong>20</strong>11). The F value in the ANOVA table, also known as the ratio <strong>of</strong> variances, is the ratio<br />

<strong>of</strong> model mean square (MS) to the appropriate error mean square. Larger F-values show that the variance contributed<br />

by the model is significantly larger than random error. If the F ratio lies near the tail <strong>of</strong> the F-distribution<br />

then the probability <strong>of</strong> a larger F is small and the variance ratio is judged to be significant. Usually, a probability<br />

value less than 0.05 is considered significant at 95% confidence level, thus justifying the use <strong>of</strong> the assumed polynomial.<br />

Coefficient <strong>of</strong> multiple determination R 2 and adjusted R 2 are the measures <strong>of</strong> the amount <strong>of</strong> reduction<br />

in the variability <strong>of</strong> particular response. For a model to be adequate, R 2 and adjusted R 2 values must approach<br />

unity and be close to each other. If they differ considerably, there is a good chance that non-significant terms<br />

have been included in the model (Montgomery <strong>20</strong>01).<br />

Significance <strong>of</strong> coefficients <strong>of</strong> the model<br />

It is quite important to determine whether the coefficients are statistically significant or not. The statistical significance<br />

<strong>of</strong> the coefficients was tested by applying the‘t’ test. Coefficients having ‘t’ values less than or equal to<br />

the listed ‘t’ value from tables at 95% confidence level, are considered insignificant and can be dropped along<br />

with the responses with which they are associated without affecting much the accuracy <strong>of</strong> the proposed model<br />

(Gunaraj and Murugan <strong>19</strong>99; Pandey <strong>20</strong>04). Only the significant coefficients and associated parameters were<br />

considered in the developed mathematical model. The model should consist <strong>of</strong> the factors and interactions that<br />

are significant, plus any terms that are needed to maintain hierarchy. For the present 2-level factorial design, the<br />

half-normal probability plot and Pareto chart was used to choose an appropriate model for each response. Normal<br />

probability plots and predicted vs. actual responses plots are shown in Figure 1 Figure 4. Modeling s<strong>of</strong>tware<br />

‘Design Expert’ was used for Analysis <strong>of</strong> Variance.<br />

Table 4 ANOVA for HAZ Width<br />

Source SS DF MS F-VALUE P-VALUE % CONTR<br />

Model 5.298 6 0.883 152.401 < 0.0001<br />

WFR 0.836 1 0.836 144.263 < 0.0001 15.777<br />

OCV 2.296 1 2.296 396.259 < 0.0001 43.335<br />

WS 1.682 1 1.682 290.258 < 0.0001 31.743<br />

PO 0.073 1 0.073 12.552 0.0025 1.373<br />

WFR*OCV 0.094 1 0.094 16.<strong>19</strong>6 0.0009 1.771<br />

WFR*PO 0.318 1 0.318 54.874 < 0.0001 6.001<br />

Residual 0.099 17 0.006<br />

Lack <strong>of</strong> Fit 0.000 1 0.000 0.053 0.8<strong>20</strong>3<br />

Pure Error 0.098 16 0.006<br />

Cor Total 5.397 23 100<br />

Std. Dev. 0.076 R 2 0.982<br />

Mean 1.566 Adj -R 2 0.975<br />

C.V. % 4.861 Pred- R 2 0.964<br />

PRESS 0.<strong>19</strong>6 S/N Ratio 34.328<br />

Table 5 ANOVA for HAZ Area<br />

Source SS DF MS F-VALUE P-VALUE % CONTR<br />

Model 10843.830 5 2168.766 98.172 < 0.0001<br />

WFR 665.707 1 665.707 30.134 < 0.0001 6.139<br />

OCV 4441.216 1 4441.216 <strong>20</strong>1.037 < 0.0001 40.956<br />

WS 5041.941 1 5041.941 228.229 < 0.0001 46.496<br />

PO 118.726 1 118.726 5.374 0.0324 1.095<br />

WFR*PO 576.240 1 576.240 26.084 < 0.0001 5.314<br />

Residual 397.648 18 22.092<br />

Lack <strong>of</strong> Fit 103.277 2 51.639 2.807 0.0902<br />

Pure Error 294.371 16 18.398<br />

6<strong>20</strong>


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Cor Total 11241.478 23 100<br />

Std. Dev. 4.700 R 2 0.965<br />

Mean 36.176 Adj -R 2 0.955<br />

C.V. % 12.993 Pred- R 2 0.937<br />

PRESS 706.929 S/N Ratio 26.501<br />

Figure 1 Normal probability plot <strong>of</strong> the studentized<br />

residuals to check for normality <strong>of</strong> residuals<br />

for HAZ width<br />

Figure 2 Normal probability plot <strong>of</strong> the studentized<br />

residuals to check for normality <strong>of</strong> residuals<br />

for HAZ area<br />

Figure 3 Predicted HAZ width vs. actual HAZ<br />

width<br />

Figure 4 predicted HAZ area vs. actual HAZ<br />

area<br />

4.6. Final models<br />

After carefully analyzing the measured responses by statistical techniques, final models comprised <strong>of</strong> significant<br />

factors only were developed as follows;<br />

Final Equation in Terms <strong>of</strong> Coded Factors:<br />

HAZ Width = [+ 1.57 + 0.<strong>19</strong>*WFR + 0.31*OCV - 0.26*WS + 0.055*PO + 0.063*WFR*OCV - 0.12*WFR<br />

*PO] 2<br />

……..4<br />

HAZ Area = + 36.18 + 5.27*WFR + 13.60*OCV - 14.49*WS + 2.22*PO - 4.90*WFR*PO<br />

….….5<br />

Final Equation in Terms <strong>of</strong> Actual Factors with electrode posive:<br />

621


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

HAZ Width = [+ 1.604 - 0.075*WFR + 0.018*OCV - 0.118*WS + 2.316×10 -03 *WFR*OCV] 2<br />

….….6<br />

HAZ Area = - 26.381 + 0.061*WFR + 3.023*OCV - 6.442*WS<br />

……..7<br />

Final Equation in Terms <strong>of</strong> Actual Factors with electrode negative:<br />

HAZ Width = [+ 0.649 - 0.037*WFR + 0.018*OCV - 0.118*WS + 2.316×10 -03 *WFR*OCV] 2<br />

HAZ Area = - 66.763+ 1.694*WFR + 3.023*OCV - 6.442*WS<br />

……..8<br />

……..9<br />

5. Results<br />

Mathematical models represented by Eqs. 4-9 may be used to predict both responses i.e. HAZ width and HAZ<br />

area. Predicted values can be found by substituting parameter values either in the coded form (Eqs. 4 & 5) or<br />

actual parameter values can be used in Eqs. 6-9 for direct results.<br />

Figure 5Figure 10 depict the variation <strong>of</strong> responses in the form <strong>of</strong> graphical representation. The advantage <strong>of</strong><br />

using cube plots is that, for a given response, main effects and interaction effects <strong>of</strong> three parameters can be studied<br />

simultaneously in a single illustration.<br />

6. Discussion<br />

6.1. Direct effect <strong>of</strong> processes parameters on responses<br />

Eqs. 4 & 5 shows that direct effect <strong>of</strong> process parameters is the same on both HAZ width and area. Wire feed rate<br />

and open circuit voltage have positive effect and welding speed is seen oppositely related. In other words, both<br />

increase with an increase in wire feed rate and open circuit voltage. A reduction is noted as there is an increase in<br />

welding speed. This can be explained as following; Heat affected zone is influenced by amount <strong>of</strong> heat input per<br />

unit length <strong>of</strong> the weld. Heat input is calculated as<br />

Heat Input, J/m = η × (welding current, Amp × welding voltage, Volt) / welding speed, m/s<br />

Where, η is arc efficiency<br />

…..10<br />

It is indicated from the Eq. 10 that increase in welding current and voltage and decrease in welding speed will<br />

increase the amount <strong>of</strong> heat input per unit length and in turn HAZ size will increase. From ANOVA (tables 4 &<br />

5, it is found that open circuit voltage and welding speed with 43 and 31% contribution respectively are the most<br />

effective parameters for HAZ width, while contribution <strong>of</strong> same parameters for HAZ area was calculated as 40%<br />

and 46%. Main effect <strong>of</strong> polarity is not so significant in both the cases, but the relationship is positive.<br />

6.2. Interaction effect <strong>of</strong> process parameters on HAZ width<br />

From Error! Reference source not found., it can be noted that at low open circuit voltage apparently there<br />

is no change in HAZ width with increase in wire feed rates, but at higher open circuit voltage, an increase is seen<br />

under electrode positive polarity. On the other hand, even at low open circuit voltage, HAZ width increases significantly<br />

with the increase in wire feed rates but rate <strong>of</strong> increase is not influenced by high open circuit voltage<br />

under electrode negative. Main effect <strong>of</strong> polarity is not so significant as compared to other variables. It has interactive<br />

influence with wire feed rate as can be seen in<br />

Figure 6 &Figure 7. Low wire feed rates under electrode positive produced wider HAZ as compared to electrode<br />

negative, while at high wire feed rates wider HAZ is obtained with electrode negative. In other words, HAZ<br />

width can be said more sensitive to wire feed rates under electrode negative conditions. No interactions <strong>of</strong> welding<br />

speed are present with wire feed rates, open circuit voltage or polarity, but from the model equation 4 it is<br />

eminent that a slight positive interaction effect between open circuit voltage and wire feed rate is present. As a<br />

result <strong>of</strong> this interaction, higher heat affected zone width is produced when both the parameters are at their high<br />

levels.<br />

622


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 5 Interaction effects <strong>of</strong> process parameters on HAZ width, mm<br />

Figure 6 3D and contour plot for HAZ width (WFR= 7.8 mm/s, Electrode Negative)<br />

6.3. Interaction effect <strong>of</strong> process parameters on HAZ area<br />

Mathematical model for HAZ area in coded form indicates that a reduction in HAZ area is favoured by decrease<br />

in wire feed rates and open circuit voltage.<br />

623


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 8<br />

Figure 7 3D and contour plot for HAZ width (WS= 7.8 mm/s, Electrode Positive)<br />

Figure 9 Figure 10 show that, the main effect <strong>of</strong> polarity is not influential but it has interaction with the wire<br />

feed rates similar to HAZ width. One can notice that at low wire feed rates HAZ area is higher at electrode positive<br />

under all similar variable combinations, while at high wire feed rates electrode negative polarity provides<br />

larger HAZ area. Hardly any effect <strong>of</strong> wire feed rates is observed on HAZ area with electrode positive but wire<br />

feed rates become more effective under electrode negative. In other words, electrode negative polarity with lower<br />

wire feed rates should be favoured to achieve small HAZ area during submerged arc welding. Like HAZ width,<br />

welding speed and open circuit voltage are most significant parameters which influence HAZ area.<br />

Figure 8 Interaction effects <strong>of</strong> process parameters on HAZ are<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

6.4. Electrode polarity and HAZ Size<br />

Electrode polarity is influential to both HAZ width and area as discussed in section 0 & 0 can be explained as<br />

follows; with electrode positive, the amount <strong>of</strong> welding current available during welding is higher than that<br />

available with electrode negative. Reason behind this is the working principle <strong>of</strong> a submerged arc welding<br />

process, where a bare solid electrode wire is used as filler metal. In electrode negative polarity, though welding<br />

current is less, generally higher voltages are used to maintain arc stability. Welding voltage alongwith welding<br />

current affect the heat input to the base metal according to Equation 10. At high level <strong>of</strong> wire feed rate, a combination<br />

<strong>of</strong> high welding current and voltage is created that increases the heat input and thus the HAZ size.<br />

Figure 9 3D and contour plot for HAZ width (WFR= 22 mm/s, Electrode Negative)<br />

Figure 10 3D and contour plot for HAZ width (WFR= 22 mm/s, Electrode Positive)<br />

625


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

7. Conclusions<br />

The present work was the effort to quantify the effect <strong>of</strong> SAW parameters on heat input, and HAZ size and dilution.<br />

Following conclusions can be drawn from the study;<br />

1. Two level factorial design techniques can be used to develop mathematical models for HAZ size in submerged<br />

arc welding and cladding process.<br />

2. HAZ width varies more effectively with wire feed rate at all the levels <strong>of</strong> open circuit voltage under electrode<br />

negative condition.<br />

3. Influence <strong>of</strong> process variables on HAZ area are found similar to that on HAZ Width.<br />

4. Electrode negative polarity produces lesser HAZ under all conditions, in general, except at higher wire feed<br />

rates.<br />

8. References<br />

Adler, Y. P. (<strong>19</strong>75). The design <strong>of</strong> experiments to find optimal conditions, Mir Publishers, Moscow.<br />

Anderson, V. L. and R. A. McLean (<strong>19</strong>74). Design <strong>of</strong> experiments-a realistic approach, Marcel Dekker, Inc.,<br />

New York.<br />

Chandel, R. S. (<strong>19</strong>87, May). "Mathematical modeling <strong>of</strong> melting rates for submerged arc welding." Welding<br />

Journal, Welding Research Supplements: 135s-140s.<br />

Chandel, R. S., H. P. Seow, et al. (<strong>19</strong>97). "Effect <strong>of</strong> increasing deposition rate on the bead geometry <strong>of</strong> submerged<br />

arc welds." Journal <strong>of</strong> Materials Processing <strong>Technology</strong> 72(1): 124-128.<br />

Dhas, J. E. R. and S. Kumanan (<strong>20</strong>11). "Optimization <strong>of</strong> parameters <strong>of</strong> submerged arc weld using non conventional<br />

techniques." Applied S<strong>of</strong>t Computing 11(8): 5<strong>19</strong>8-5<strong>20</strong>4.<br />

Fnides, B., M. A. Yallese, et al. (<strong>20</strong>11). "Application <strong>of</strong> response surface methodology for determining cutting<br />

force model in turning hardened AISI H11 hot work tool steel." Sadhana Vol. 36, Part 1,(February ): pp. 109-<br />

123.<br />

Ghosh, A., S. Chattopadhyaya, et al. (<strong>20</strong>11). "Assessment <strong>of</strong> Heat Affected Zone <strong>of</strong> Submerged Arc Welding<br />

Process through Digital Image Processing." Procedia Engineering 10: 2782-2785.<br />

Gunaraj, V. and N. Murugan (<strong>19</strong>99). "Application <strong>of</strong> response surface methodology for predicting weld bead<br />

quality in submerged arc welding <strong>of</strong> pipes." Journal <strong>of</strong> Materials Processing <strong>Technology</strong> 88(1-3): 266-275.<br />

Gunaraj, V. and N. Murugan (<strong>19</strong>99). "Prediction and comparison <strong>of</strong> the area <strong>of</strong> the heat-affected zone for the<br />

bead-on-plate and bead-on-joint in submerged arc welding <strong>of</strong> pipes." Journal <strong>of</strong> Materials Processing <strong>Technology</strong><br />

95(1-3): 246-261.<br />

Karaoğlu, S. and A. Seçgin (<strong>20</strong>08). "Sensitivity analysis <strong>of</strong> submerged arc welding process parameters." Journal<br />

<strong>of</strong> Materials Processing <strong>Technology</strong> <strong>20</strong>2(1-3): 500-507.<br />

Kou, S. (<strong>20</strong>03). Welding metallurgy, John Wiley & Sons, Inc., USA.<br />

Lancaster, J. F. (<strong>19</strong>93). Metallurgy <strong>of</strong> Welding. London, Chapman & Hall.<br />

Mason, R. L., R. F. Gunst, et al. (<strong>20</strong>03). Statistical Design and Analysis <strong>of</strong> Experiments New Jersey, John Wiley<br />

& Sons, Inc.<br />

Montgomery, D. C. (<strong>20</strong>01). Design and Analysis <strong>of</strong> Experiments, John Wiley & sons Inc, Singapore.<br />

Murugan, N. and V. Gunaraj (<strong>20</strong>05). "Prediction and control <strong>of</strong> weld bead geometry and shape relationships in<br />

submerged arc welding <strong>of</strong> pipes." Journal <strong>of</strong> Materials Processing <strong>Technology</strong> 168(3): 478-487.<br />

Murugan, N. and R. S. Parmar (<strong>19</strong>93). "Effect <strong>of</strong> submerged arc process variables on dilution and bead geometry<br />

in single wire surfacing." Journal <strong>of</strong> Materials Processing <strong>Technology</strong> Vol. 37: 767-780.<br />

Olson, D. L., T. A. Siewert, et al. (<strong>19</strong>93). Welding , Brazing and soldering, ASM International.<br />

Om, H. and S. Pandey (<strong>20</strong>10). Effect <strong>of</strong> electrode polarity in submerged arc welding process. Twenty fourth Indian<br />

Engineering Congress. NIT Surathkal, Mangalore, India.<br />

Pandey, N. D., A. Bharti, et al. (<strong>19</strong>94). "Effect <strong>of</strong> submerged arc welding parameters and fluxes on element<br />

transfer behaviour and weld-metal chemistry." Journal <strong>of</strong> Materials Processing <strong>Technology</strong> 40(1-2): <strong>19</strong>5-211.<br />

Pandey, S. (<strong>20</strong>04). "Welding current and melting rate in submerged arc welding: a new approach." Australasian<br />

Welding Journal Supplements Vol. 49(Second Quarter): 33 - 42.<br />

Shen, S., I. N. A. Oguocha, et al. (<strong>20</strong>12). "Effect <strong>of</strong> heat input on weld bead geometry <strong>of</strong> submerged arc welded<br />

ASTM A709 Grade 50 steel joints." Journal <strong>of</strong> Materials Processing <strong>Technology</strong> 212(1): 286-294.<br />

Yang, L. J., R. S. Chandel, et al. (<strong>19</strong>93, Jan). "The effects <strong>of</strong> process variables on the weld deposit area <strong>of</strong> submerged<br />

arc welds." Welding Journal Welding Research Supplements: 11s-18s.<br />

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1<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

CONSUMPTION AND MANUFACTURING FOR THE FUTURE<br />

CHALLENGES – “THE SUSTAINABLE WAY”<br />

Subrata Kumar Patra 1 , Tilak Raj 2<br />

Research Scholar ,<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong> ,Sector-6, Mathura Road,<br />

Faridabad – 121 006, India, E-mail: patrask<strong>20</strong>05@yahoo.co.in<br />

2 Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong> , Sector-6, Mathura<br />

Road, Faridabad – 121 006, India, E-mail: tilakraj64@rediffmail.com<br />

Abstract<br />

From the dawn <strong>of</strong> creation, mankind has struggled and competed with other species on this planet for its<br />

existence. By relentless efforts and innovations, the human population has moved to the present arena <strong>of</strong> luxuries<br />

and comforts. Of late, it has been realized that one <strong>of</strong> the worst problems faced by us is that <strong>of</strong> the “population<br />

explosion” and its “by-products”. In this context one <strong>of</strong> the biggest challenges that we are facing now, is the<br />

exponential but quantitative increase <strong>of</strong> the necessity <strong>of</strong> various products for fulfilling our requirements.<br />

Fulfillment <strong>of</strong> these requirements can only be achieved through the efficient use <strong>of</strong> energy. This requires an indepth<br />

analysis <strong>of</strong> the process <strong>of</strong> degradation <strong>of</strong> energy. This paper stresses the importance <strong>of</strong> ‘sustainable’<br />

processes and delves into the scary future lest we do not act today. An abridged historical review <strong>of</strong> the<br />

importance <strong>of</strong> ‘sustainability’ is also provided. Immediate but pro-active steps have to be taken to reduce the<br />

intense stress on the existing resources which is being aggravated due to increased demand being met by<br />

mindless development for short term gains.<br />

1. Introduction<br />

The guidelines <strong>of</strong> OECD (<strong>20</strong>01) highlighted that the development progress over the past thirty years was<br />

unprecedented and the life expectancy in developing countries has risen by more than <strong>20</strong> years; infant mortality<br />

rates have been halved and primary school enrolment rates had doubled. Also food production and consumption<br />

has increased dramatically. The pace <strong>of</strong> improvements in income levels, as well as in health and education, has<br />

exceeded that <strong>of</strong> the industrialized countries.<br />

With the rapid growth <strong>of</strong> human population and industrialization, the consumption <strong>of</strong> natural resources has gone<br />

up exponentially. Energy obtained from the natural resources through various processes is used for meeting the<br />

various everyday needs besides running plants and machineries. The manufacturing processes result in increased<br />

level <strong>of</strong> pollution and generate a lot <strong>of</strong> waste that further degrades the environment. Continuance <strong>of</strong> unscientific<br />

and thoughtless activities for exploration and use <strong>of</strong> energy for manufacturing operations may jeopardize our<br />

environment to the extent <strong>of</strong> threatening our own very existence. As per R K Mudgal, Ravi Shankar, P Talib and<br />

Tilak Raj (<strong>20</strong>08) environmental degradation is a growing global problem. Increased production and consumption<br />

has resulted in increased use <strong>of</strong> raw materials and energy, which has led to the depletion <strong>of</strong> natural resources. As<br />

per Askiner Gungor, et al. (<strong>19</strong>99) our environment has limited resources <strong>of</strong> raw material, energy, water and air<br />

supply. Also the places where we dispose <strong>of</strong> old products are limited. He emphasized that there was an urgent<br />

need for a sustainable environment for the next generation.<br />

The present day problems have arisen out <strong>of</strong> the ‘past’ and the ‘future’ problems will arise out <strong>of</strong> the ‘present’.<br />

And yes, the future problems would be exponentially compounded. For decades, mankind has focused on the<br />

‘end’ without being conscious about the ‘means’. The modern day ‘energy’ system is non-sustainable. Some <strong>of</strong><br />

the major problems as a result <strong>of</strong> such indiscriminate use <strong>of</strong> natural resources which may occur in the foreseeable<br />

future are:<br />

●Acute energy shortage<br />

●Acute water shortage<br />

●Global warming<br />

●Global unrest<br />

●Spread <strong>of</strong> chronic diseases<br />

This list is by no means comprehensive and can be termed as ‘the tip <strong>of</strong> the iceberg’. It is evident from the above<br />

that the very existence <strong>of</strong> mankind is under the threat <strong>of</strong> extinction.<br />

2. Importance <strong>of</strong> sustainability<br />

The World Commission on Environment and Development (The Brundtland Commission,<strong>19</strong>87) defined<br />

sustainable development as “development that meets the needs <strong>of</strong> the present without compromising the ability <strong>of</strong><br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

future generations to meet their own needs”. This is only possible by maintaining a dynamic equilibrium<br />

between ecological, economical and social dimensions. It has been felt that only the increase <strong>of</strong> manufactured<br />

products and goods are not sufficient to deliver sustainable development. In fact many a times, increase in such<br />

parameters are directly responsible for a reduced ‘sustainability index’ (index <strong>of</strong> ‘sustainability’ measurement).<br />

Launched in <strong>19</strong>99, the Dow Jones Sustainability Index (DJSI) was the first global benchmark for sustainability.<br />

The main priority <strong>of</strong> the DJSI is to rank “sustainability-driven” companies based on how viable <strong>of</strong> an investment<br />

option they are, according to their long-term fiscally sustainable growth (Chelsea Amaio, <strong>20</strong>12). 'Dow Jones<br />

STOXX Sustainability Index' aims to capture companies on the leading edge <strong>of</strong> sustainability practice/reform;<br />

the sustainability score that each company receives is based on an intricate weighting system that examines<br />

company actions regarding things such as corporate governance, environmental performance, energy efficiency<br />

and climate change strategies (www.investopedia.com/....).<br />

The consumption patterns, the changes in consumer habits and lifestyles are only a few <strong>of</strong> the many factors<br />

which should be taken into consideration in order to achieve development which is truly sustainable. True<br />

sustainability needs us to revamp our entire thought process and deeds. Environment and growth are two separate<br />

chapters <strong>of</strong> the same book. Both are linked to each other and compliment each other. The concept <strong>of</strong> thinking for<br />

tomorrow is one single, and probably, the most important characteristic which have to be built in our genes.<br />

Once we achieve this, the rest <strong>of</strong> the parameters can be programmed accordingly. As per Westkamper E., et al.<br />

(<strong>20</strong>01) there is five typical drivers for sustainability. These are (i) the shortage <strong>of</strong> natural resources (ii) the<br />

dramatic increase <strong>of</strong> world population (iii) global warming (iv) pollution and (v) an unstoppable global<br />

economy. Since then the list <strong>of</strong> these drivers has gone up to alarming levels. The need <strong>of</strong> the hour is to enshrine<br />

environmental concerns within the ambit <strong>of</strong> ‘growth’. This fact should lead us to strongly differentiate between<br />

‘growth’ and ‘sustainable growth’. Thus we need to have a paradigm shift in understanding the true meaning <strong>of</strong><br />

‘growth’ or ‘development’. Any development which is bereft <strong>of</strong> sustainability culture should not be termed as<br />

‘growth’ at all. However, the ‘sustainability index’ <strong>of</strong> the ‘development’ could be a subject <strong>of</strong> other parameters.<br />

2.1. Sustainable consumption and manufacturing<br />

The human population is dangerously dependent on natural resources like raw materials, water, soil and air.<br />

These resources are haphazardly being utilized for fulfilling our needs to improve our living standards. There are<br />

substances or products that are eco-friendly during their useful life but may promote a reduced sustainability<br />

index during their manufacturing stage. On the contrary some might be eco friendly during their use but may<br />

cause environmental damage while they are disposed <strong>of</strong>f after their useful life.<br />

As per Tim Jackson (<strong>20</strong>03) there is an increased realization <strong>of</strong> the fact that mere increase in resource productivity<br />

will be not be sufficient to deliver sustainable development. Shifts in the scale and pattern <strong>of</strong> consumption, apart<br />

from other factors, are also likely to be essential. We need to give a serious thought to the product ‘Life Cycle<br />

Analysis’ (LCA) or the more recently coined ‘Life Cycle Exergy Analysis’ (LCEA) which involves a detailed<br />

study <strong>of</strong> the various sustainability parameters at different stages <strong>of</strong> the product. Of course there is also an urgent<br />

need <strong>of</strong> changing our consumption levels, consumption habits and consumption patterns in such a manner that<br />

the consumption can be sustained by the earth’s natural resources.<br />

The population is increasing at a rapid pace and with it the consumption <strong>of</strong> natural resources are also increasing.<br />

Products are being manufactured by using energy in various forms which again require the use <strong>of</strong> various natural<br />

resources without any consideration <strong>of</strong> their depletion. More and more use <strong>of</strong> these resources for manufacturing<br />

various goods has resulted in an increase <strong>of</strong> pollution and non-biodegradable waste at an alarming rate. The<br />

space and site where the scrap, waste and toxic substances can be safely disposed <strong>of</strong>f are also decreasing. The<br />

modern day needs have resulted in an unplanned exploitation <strong>of</strong> the limited natural resources. If the pace with<br />

which these scarce resources are being exploited, their depletion is sure to happen and, that too with a predictable<br />

time frame.<br />

The manufacturing sectors play an important role in the growth <strong>of</strong> a country. Manufacturing <strong>of</strong> goods and<br />

services are dependent on the consumer driven market conditions. Sustainable manufacturing can be considered<br />

as a part <strong>of</strong> sustainable production related to the transformation <strong>of</strong> input materials and energy into finished goods<br />

for economic trade (Center for integrated manufacturing studies, <strong>20</strong>09). The U.S. Department <strong>of</strong> Commerce<br />

(www.trade.gov/....) defined Sustainable manufacturing as the creation <strong>of</strong> manufactured products that use<br />

processes that are non-polluting, conserve energy and natural resources and are economically sound and safe for<br />

employees, communities and consumers. Sustainable manufacturing can promote a good standard <strong>of</strong> living in a<br />

healthy environment and can contribute towards a sustainable development. Thus, the importance <strong>of</strong> sustainable<br />

manufacturing cannot be undermined and is a critical component for any development which is rated high on the<br />

‘Sustainability Index’. Sustainable manufacturing is possible through the active participation <strong>of</strong> the Government<br />

628


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

and the manufacturing organizations. In this context the PPP (Public Private Partnership) model can make a<br />

tremendous contribution to the cause <strong>of</strong> sustainability. The incorporation <strong>of</strong> advanced and innovative<br />

manufacturing technologies can help in promoting sustainable growth. Energy saving and emission reduction<br />

technologies can help in conserving our natural resources and thereby help in building a sustainable society. Use<br />

<strong>of</strong> alternative materials, clean and energy efficient technologies, mass and batch production concepts, better<br />

plant layout, use <strong>of</strong> CNC and machining centers, automated control and material handling systems, recycling and<br />

reuse technologies, research and development etc. can go a long way in helping the cause <strong>of</strong> sustainability. The<br />

MSA(<strong>20</strong>08) mentions that the new world <strong>of</strong> sustainable technologies and work practices is undoubtedly a<br />

challenging and exciting emerging reality for the manufacturing industries and the role that they will play in<br />

creating and shaping this world might be significant. This will require steadfast commitment and effective<br />

strategies that embrace the full extent <strong>of</strong> sustainable possibilities. The sustainable development through<br />

sustainable consumption and manufacturing practices will ensure a balanced and efficient use <strong>of</strong> natural<br />

resources and prevent the undesirable degradation <strong>of</strong> the environment.<br />

2.1.1 Economic Drivers for Sustainable Manufacturing:<br />

As per Center for Integrated Manufacturing Studies (<strong>20</strong>09) companies and organizations that have adopted<br />

sustainability practices have <strong>of</strong>ten reported improved pr<strong>of</strong>itability as a result <strong>of</strong> reduction in the use <strong>of</strong> energy,<br />

water and the release <strong>of</strong> hazardous substances. It has mentioned the followings as the key drivers for engaging<br />

sustainable manufacturing practices. These are:<br />

• Customer demands among OEMs (Original Equipment Manufacturers), major retailers, distributors, and end<br />

consumers<br />

• Increased pr<strong>of</strong>it and competitive advantages for manufacturers<br />

• Emerging international regulations<br />

• CSR( Corporate Social Responsibility) activities<br />

• Education<br />

Many OEM’s such as Motorola and Texas Instruments are beginning programs that require their suppliers to<br />

meet their prescribed sustainability metrics. In India companies like NTPC, Tata Steel, Tata BP, JSW Steel,<br />

Suzlon, ACC, Coir Atlas, Orchid Ecotels, ITC and many more are already working to increase the<br />

‘sustainability index’ <strong>of</strong> their factories.<br />

2.2. Role <strong>of</strong> stakeholders in Sustainable Development<br />

The stakeholders <strong>of</strong> Sustainable development are the consumers in the society, the government and the<br />

manufacturing organizations. Environmental issues are gaining justifiable popularity among society, government<br />

and industry due to negative environmental developments (Askiner Gungor and Surendra M. Gupta, <strong>19</strong>99). A<br />

coordinated and active participation by all stakeholders may lead them towards the path <strong>of</strong> sustainable<br />

development. The concept <strong>of</strong> ‘sustainability’ can be marketed by propagating the fact that ALL the stakeholders<br />

stand to benefit from it.<br />

The consumers in the society are the end users who use the goods and finished products produced by<br />

manufacturing firms. The role <strong>of</strong> the consumers and the society as a whole is therefore crucial for sustainable<br />

development. With the rapid growth <strong>of</strong> information technology and the access <strong>of</strong> electronic media, consumers<br />

are becoming more and more conscious <strong>of</strong> their environment and the problems associated with its degradation.<br />

The demand for environmentally safe products by the consumers will force the manufacturers in designing and<br />

manufacturing sustainable products. Consequently, the market demand for the sustainable products will give a<br />

competitive edge to the manufacturers as compared to their “not so sustainable” competitors. This will act as a<br />

catalyst for all manufacturers who will then willfully adopt sustainable practices.<br />

The government can play a pro-active role in educating the consumers on the issues <strong>of</strong> sustainability and<br />

environmental implications. The involvement and active participation <strong>of</strong> the media, NGO (Non Government<br />

Organizations) and the educational institutions in this regard can be highly motivational. The education,<br />

knowledge and awareness can help the consumers in distinguishing between sustainable and non-sustainable<br />

products and practices. The government can frame various policies, regulations, standards and norms with regard<br />

to environmental protection that are to be complied by the manufacturers. Legislation is seen to have had<br />

negative effects on cost <strong>of</strong> production but positive effects on new product development and business<br />

opportunities (Hartmut Kaebernick, et al. <strong>20</strong>06).<br />

To motivate the manufacturers in perceiving the importance <strong>of</strong> sustainable growth, the government may extend<br />

various financial and non-financial incentives as the incorporation <strong>of</strong> sustainable practices generally involve high<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

initial costs. Moreover the government has to develop a proper monitoring framework including regular auditing<br />

and Environmental Impact Assessment (EIA) for various industrial and other operations. The manufacturers<br />

causing environmental damages have to be penalized while those using clean and sustainable practices may be<br />

rewarded. Some <strong>of</strong> these steps adopted and implemented on the part <strong>of</strong> the government will help in attaining the<br />

goals <strong>of</strong> sustainable manufacturing in the near future. The concept <strong>of</strong> ‘carbon credits’ has already started having<br />

a huge positive impact on the ‘sustainability index’ <strong>of</strong> many processes.<br />

Manufacturers are under tremendous pressure to improve productivity and quality while reducing costs (Ge<strong>of</strong>f<br />

Miller, et al. <strong>20</strong>10). The manufacturers can make use <strong>of</strong> advanced and sophisticated manufacturing technologies<br />

and processes so as to comply with the various environmental regulations framed by the governments from time<br />

to time. However, the compliance <strong>of</strong> these regulations generally involve high initial cost burden. Stringent<br />

environmental laws and consumer awareness are forcing the manufacturers to look for innovative ways <strong>of</strong><br />

recycling the waste for reuse. In some parts <strong>of</strong> the world dumping or burying the waste is not allowed anymore.<br />

By redesigning the products and systems, and using clean and improved technologies involving recycling,<br />

reducing waste, emission and pollution, the cost <strong>of</strong> goods and products can be substantially reduced. The<br />

manufacturing sectors in such a scenario shall be willing to design and develop products that are cheap, green,<br />

recyclable, sustainable and environment friendly. This will help them to survive in the highly competitive market<br />

(national and global) by earning goodwill in the market and by earning more pr<strong>of</strong>its because <strong>of</strong> reduced<br />

manufacturing cost. The manufacturers may look at the environmental challenges as opportunities for their<br />

economic growth. This will help to improve the overall environmental performance <strong>of</strong> products throughout their<br />

entire life-cycle. Paul R. Kleindorfer, et al. (<strong>20</strong>05) was <strong>of</strong> the opinion that companies are most likely to improve<br />

their environmental performance when public pressure results in strong regulations. They also highlighted that<br />

sometimes companies themselves lobby for regulations if they have developed an environmentally friendly<br />

technology and believe that regulations requiring their technology would give them a competitive advantage.<br />

It can be concluded that for sustainable development to be meaningful, the government should formulate various<br />

strategies in close collaboration with the various stakeholders and should extend all possible help in this<br />

direction.<br />

2.3. Energy consumption and sustainability<br />

The demand for energy is rapidly increasing. At the same time the conventional resources <strong>of</strong> energy are<br />

depleting very fast. The efficient use <strong>of</strong> energy for the industrial and other applications has assumed a great<br />

importance. This thought gave birth to the concept <strong>of</strong> “exergy” (Goran Wall, et al. <strong>20</strong>11) which deals not only<br />

with the quantitative aspect <strong>of</strong> “energy” but also its “qualitative” aspect. The importance <strong>of</strong> designing more<br />

energy efficient (exergetic aspect) machines and equipments have to be understood at length. Apart from the<br />

technological improvements the energy consumption may also be reduced by recycling waste and by designing<br />

alternate materials. The stakeholders must be made to realize that “Small Steps = Big Difference”. Research<br />

shows that even small steps like doing away with cut flowers (for decoration) has a big positive impact on the<br />

environment. Metal industries use scrap to manufacture products with much lesser energy and cost. Even<br />

changes in lifestyle practices like using public transport instead <strong>of</strong> private cars may cause a huge saving <strong>of</strong><br />

energy. Educating the children early about the significance <strong>of</strong> energy management will also lead towards a long<br />

term saving <strong>of</strong> energy. There is an urgent need for research and development in the field <strong>of</strong> harnessing energy<br />

from renewable sources both economically and safely. At the same time there is an urgent need to promote<br />

technologies for saving energy (increased exergetic efficiency) and reducing emissions.<br />

3. Sustainable development and the future<br />

The vision <strong>of</strong> a sustainable growth for the future will help in promoting economical, ecological, technological<br />

and societal development. This will only be possible through an efficient utilization <strong>of</strong> our limited resources and<br />

infrastructures. Alternate sources with a greater “exergy” level should also be continuously explored. The design<br />

<strong>of</strong> machineries and equipments should be such that they will not only consume less energy but will use energy<br />

from renewable sources. Innovative technological design and optimization will help in reducing the waste and<br />

the dependence on conventional sources <strong>of</strong> energy. Investments in technological innovations will lead to better<br />

product quality at the lower price because <strong>of</strong> process efficiency, higher productivity, reduced consumption <strong>of</strong><br />

resources and cheap but efficient pollution control systems. Sustainable consumption and manufacturing will<br />

help in minimizing the use <strong>of</strong> raw materials obtained from nature leading to growth that will be sustainable. In<br />

this context J. Kopac (<strong>20</strong>09) showed that sustainable machining provides the followings benefits:<br />

• Enhanced environmental friendliness<br />

• Reduced cost<br />

• Reduced power consumption<br />

• Reduced waste and more effective waste management<br />

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• Enhanced operational safety<br />

• Improved personnel health<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

From various studies related to sustainable issues it can be concluded that the Sustainable development has the<br />

potential <strong>of</strong> changing our future environment and life in a variety <strong>of</strong> ways. This is given in Figure1.<br />

Fig.1. Sustainable development and the future<br />

4. Conclusion<br />

Rapid industrialization and economic growth is taking place in almost all the countries <strong>of</strong> the world. The world<br />

economy has opened up with globalization, liberalization and open market competiveness. The tough global<br />

competition is forcing the producers to sell high quality products on competitive pricing. Many <strong>of</strong> the<br />

environmental problems have emerged that can pose big threat to the very existence <strong>of</strong> mankind. Corrective<br />

measures need to be initiated immediately. Sustainable manufacturing is about designing and manufacturing<br />

products that will meet the expectations <strong>of</strong> the consumers in terms <strong>of</strong> quality, price, increased lifespan, safety,<br />

aesthetic value, repair and maintenance and so on. At the same time it should not give any adverse consequences<br />

on the environment during its entire “product life cycle”.<br />

This paper highlights the importance <strong>of</strong> future challenges as a result <strong>of</strong> consumption and manufacturing on the<br />

“sustainability index” primarily due to the limited natural resources and the increase in the level <strong>of</strong><br />

environmental degradation. It can be concluded that we, as a member <strong>of</strong> the global community, should<br />

immediately respond to the sustainability issues in order to sustain our future generations. This will only be<br />

possible by adopting sustainable consumption and manufacturing practices. No nation can face the challenge <strong>of</strong><br />

environmental degradation alone. The issue needs to be addressed globally. India has made an extremely<br />

responsible choice <strong>of</strong> not exceeding the per capita emissions <strong>of</strong> any developed country. The developing countries<br />

need space for their industries to develop. Hence these countries need technology and other enablers to switch<br />

over to ‘sustainable’ manufacturing or green techniques. Ironically the developing countries face greater adverse<br />

consequences <strong>of</strong> ‘growth’. This is because, to alleviate poverty, and enhance growth, these countries tend to over<br />

consume and stretch their resources.<br />

There is no escape from development. But unless it is sustainable, the future <strong>of</strong> our planet is uncertain. We have<br />

to cherish and nourish our resources to enable us to enjoy the nature’s bounty and hand over a healthy planet to<br />

the future generations. The road to sustainability is embedded in Gandhi’s quote “Earth provides enough to<br />

satisfy every man’s need, but not every man’s greed”. Furthering this apt saying, we all need to understand that<br />

“there’s only one earth” and we all need to protect it.<br />

631


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

References<br />

1. Askiner Gungor, Surendra M. Gupta (<strong>19</strong>99) “Issues in environmentally conscious manufacturing and<br />

product recovery: a survey”, Computers & Industrial Engineering, Vol. 36, pp. 811-853.<br />

2. Center for integrated manufacturing studies (<strong>20</strong>09), “Sustainable Manufacturing”, Rochester Institute <strong>of</strong><br />

<strong>Technology</strong>, pp. 1-22.<br />

3. Chelsea Amaio ( <strong>20</strong>12), “Does the Dow Jones Sustainability Index Really Measure Sustainability”, Revolt.<br />

4. Ge<strong>of</strong>f Miller, Janice Pawloski, Charles Standridge (<strong>20</strong>10), “A case study <strong>of</strong> lean, sustainable<br />

manufacturing”, Journal Of Industrial Engineering and Management, Vol. 3, No.1, pp. 11-32.<br />

5. Goran Wall, Tsatsaronis (June <strong>20</strong>11), “ Life Cycle Exergy Analysis <strong>of</strong> Wind Power”, 2 nd Int Exergy Life<br />

Cycle Assessment, and Sustainability Workshop Symposium, Greece.<br />

6. Hartmut Kaebernick, Sami Kara (<strong>20</strong>06), “Environmentally Sustainable Manufacturing: A Survey on<br />

Industry Practices”, 13th CIRP INTERNATIONAL CONFERENCE ON LIFE CYCLE ENGINEERING.<br />

7. J. Kopac (<strong>20</strong>09), “Achievements <strong>of</strong> sustainable manufacturing by machining”, Journal <strong>of</strong> Achievements in<br />

Materials and Manufacturing Engineering, Volume 34, Issue 2.<br />

8. Manufacturing skills Australia (MSA) (<strong>20</strong>08), “sustainable Manufacturing”, Manufacturing for<br />

Sustainability.<br />

9. OECD (<strong>20</strong>01), “The DAC Guidelines Strategies for Sustainable Development: Guidance for Development<br />

Co-operation”.<br />

10. Paul R. Kleindorfer, Kalyan Singhal, Luk N. Van Wassenhove (<strong>20</strong>05), “Sustainable Operations<br />

Management”, PRODUCTION AND OPERATIONS MANAGEMENT, Vol. 14, No. 4, pp. 482–492.<br />

11. Rakesh K. Mudgal, Ravi Shankar, Parvaiz Talib and Tilak Raj (<strong>19</strong>98), “Modelling the barriers <strong>of</strong> green<br />

supply chain practices: an Indian perspective”, Int. J. Logistics Systems and Management, Vol. x, No. x,<br />

xxxx<br />

12. Tim Jackson (<strong>20</strong>03), “Policies for Sustainable Consumption: A report to the Sustainable Development<br />

Commission”.<br />

13. Westkamper E, Alting L., Arndt G. (<strong>20</strong>01), “Life cycle management and assessment: approaches and<br />

visions towards sustainable manufacturing”, CIRP Ann. Manuf. Technol., 215, 599-626.<br />

14. World Commission on Environment and Development (<strong>19</strong>87), “Our common future”, Oxford <strong>University</strong><br />

Press, New York.<br />

15. www.investopedia.com/terms/d/djones-stoxx-sustainability.asp#axzz274El0kmA .<br />

16. www.trade.gov/competitiveness/sustainablemanufacturing/how_doc_defines_SM.asp .<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

FINITE ELEMENT MODELLING OF TUBE HYDROFORMING<br />

PROCESS USING PURE ALUMINIUM (Al 99)<br />

Dhairya Pratap Singh 1 , Dilip Johari 2 , Jitendra Kumar Verma 3<br />

1 PhD Scholar ,Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad,<br />

Haryana, India, Email: d.psingh2<strong>20</strong>785@gmail.com<br />

2 M.Tech Student, Department <strong>of</strong> Mechanical Engineering, Dayalbagh Educational <strong>University</strong>,, Agra, U.P.,<br />

India, Email: jkverma14@gmail.com<br />

3<br />

M.Tech Student ,Department <strong>of</strong> Mechanical Engineering, Dayalbagh Educational <strong>University</strong>, Agra, U.P., India<br />

Email: dilipjohari@gmail.com<br />

Abstract<br />

Hydr<strong>of</strong>orming process may be defined as a metal forming technology using hydraulic or fluid pressure to<br />

deform the tubes and sheet. Increasing use <strong>of</strong> hydr<strong>of</strong>orming in automotive applications requires intensive<br />

research and development on all aspects <strong>of</strong> this relatively new technology to satisfy an ever-increasing demand<br />

by the industry. Tube hydr<strong>of</strong>orming process and sheet hydr<strong>of</strong>orming process are some variations <strong>of</strong><br />

hydr<strong>of</strong>orming process. Tube hydr<strong>of</strong>orming is one <strong>of</strong> the most popular unconventional metal forming processes<br />

which is widely used to form various tubular components. By this process, tubes are formed into different shapes<br />

using internal pressure and axial compressive loads simultaneously to force a tubular blank to conform to the<br />

shape <strong>of</strong> a given die cavity. Initially, Factors affecting the output <strong>of</strong> the process are reviewed in the paper.<br />

Moreover, common types <strong>of</strong> failure <strong>of</strong> the process are introduced and improvements to avoid them are also<br />

mentioned. Review <strong>of</strong> sheet hydr<strong>of</strong>orming process is also done. Comparison <strong>of</strong> conventional deep drawing<br />

process and deep drawing process with hydr<strong>of</strong>orming process is done. S-shape rail is simulated in FORGE<br />

<strong>20</strong>11.Pure Aluminium is used as tube material to form double T-joint under different friction conditions is<br />

simulated using Forge <strong>20</strong>11 and results are analysed.<br />

Keywords: Hydr<strong>of</strong>orming Process, Tube Hydr<strong>of</strong>orming Process, Sheet Hydr<strong>of</strong>orming Process, Finite Element<br />

Modeling (FEM), Deformation behaviour, Friction.<br />

1. Introduction<br />

Hydr<strong>of</strong>orming processes have become popular in recent years, due to the increasing demands for lightweight<br />

parts in various fields, such as bicycle, automotive, aircraft and aerospace industries [01]. This technology is<br />

relatively new as compared with rolling, forging or stamping, therefore there is not much knowledge available<br />

for the product or process designers. Compared to conventional manufacturing like stamping and welding, Tube<br />

Hydr<strong>of</strong>orming Process (THF) and Sheet Hydr<strong>of</strong>orming Process (SHF) <strong>of</strong>fers several advantages, such as<br />

decrease in work piece cost, tool cost and product weight, improvement <strong>of</strong> structural stability and increase <strong>of</strong> the<br />

strength and stiffness <strong>of</strong> the formed parts, more uniform thickness distribution, fewer secondary operations,<br />

better surface finish etc. [01].<br />

Hydr<strong>of</strong>orming process uses fluid pressure in place <strong>of</strong> the punch as comparing with a conventional tool set to<br />

form the component into the desired shape <strong>of</strong> the die. Generally, hydr<strong>of</strong>orming processes can be classified as<br />

tube or sheet hydr<strong>of</strong>orming depending on the initial shape <strong>of</strong> workpiece. In the tube hydr<strong>of</strong>orming process<br />

(THP), the initial workpiece is placed into a die cavity, which corresponds to the final shape <strong>of</strong> the component.<br />

Next, the dies are closed under the force and the tube is internally pressurized by a liquid medium to effect<br />

the expansion <strong>of</strong> the component (internal pressure, p i ) and axially compressed by sealing punches to force<br />

material into the die cavity (axial force). Hence the component is formed under the simultaneously controlled<br />

action <strong>of</strong> internal pressure p i and axial force. [01]<br />

In the present work finite element method has been applied to analyse the equivalent strain obtained, formability<br />

achieved and shape achieved by using 'FORGE <strong>20</strong>11' aiming to investigate the effect <strong>of</strong> friction between die<br />

channel and specimen on the equivalent strain distribution and shape achieved. Moreover FEM analysis indicates<br />

that higher equivalent strain means the higher yield strength and higher hardness.<br />

FORGE <strong>20</strong>11, based on the finite element method, is s<strong>of</strong>tware package used to simulate hot, warm and cold<br />

forging <strong>of</strong> both 3D parts and 2D geometry parts (such as long products where a cross section is studied or such as<br />

products with a revolution axis when a radial section is studied). The s<strong>of</strong>tware uses thermo-viscoplastic laws for<br />

hot forging. For warm and cold forging, a thermo-elasto-plastic model enables the prediction <strong>of</strong> residual stresses<br />

and geometrical dimensions at the end <strong>of</strong> the forming.<br />

633


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. Tube Hydr<strong>of</strong>orming<br />

Tube hydr<strong>of</strong>orming is one <strong>of</strong> the most popular unconventional metal forming processes which is widely used to<br />

form various tubular components. By this process, tubes are formed into different shapes using internal pressure<br />

and axial compressive loads simultaneously to force a tubular blank to conform to the shape <strong>of</strong> a given die<br />

cavity. Tube hydr<strong>of</strong>orming is one <strong>of</strong> the unconventional metal forming processes which is widely used in order<br />

to form complex shapes. Tube Hydr<strong>of</strong>orming (THF) has been called by many other names such as:<br />

• Bulge forming <strong>of</strong> tubes (BFT)<br />

• Liquid bulge forming (LBF)<br />

• Hydraulic pressure forming (HPF)<br />

• Internal high pressure forming (IHPF)<br />

• Unconventional Tee Forming (UTF), depending on the time and country in which it was used.<br />

Establishment <strong>of</strong> process goes back to <strong>19</strong>39 when Grey et al. investigated manufacturing <strong>of</strong> seamless copper<br />

fittings with T protrusions using a combination <strong>of</strong> internal pressure and axial load. The investigation was<br />

considered as a US patent in the <strong>19</strong>40, which gave an indication <strong>of</strong> the coming period <strong>of</strong> tube hydr<strong>of</strong>orming.<br />

2.1. Tube Hydr<strong>of</strong>orming Setup<br />

Design <strong>of</strong> the THF system is <strong>of</strong> special importance since high hydraulic pressures and complex shaped parts<br />

involved.<br />

The system needed for THF consists <strong>of</strong> the followings:<br />

• Presses or clamping devices for closing the dies,<br />

• Tooling,<br />

• Pressure system; intensifier,<br />

• Hydraulic cylinders and punches; for sealing the tube and move the material,<br />

• Process control systems; computers, data acquisition, transducers, etc.<br />

2.2. Principle <strong>of</strong> Tube Hydr<strong>of</strong>orming<br />

The principle <strong>of</strong> tube hydr<strong>of</strong>orming is shown in Fig 1.The tubular blank is firstly placed between the two die<br />

halves and then filled with high-pressure liquid through holes in the plungers to remove any air bubbles trapped<br />

inside. The tube is then forced to adopt the inner contour <strong>of</strong> the tool by application <strong>of</strong> internal pressure (via high<br />

pressure liquid) and two axial forces (via plungers) simultaneously. In many cases, internal pressure can be<br />

transmitted via an elastomer (e.g. rubber or polyurethane), or a s<strong>of</strong>t metal (e.g. lead) [9] or limited applications,<br />

the tube can be formed by the increasing internal pressure only. This means that the axial plungers do not feed<br />

more material into the expansion zone. However, the axial forces acting on the tube ends must exceed a certain<br />

level to prevent leakage. This limit is known as sealing [4].<br />

Figure 1. Schematic diagram <strong>of</strong> Tube Hydr<strong>of</strong>orming System<br />

(a) Initial setup<br />

634


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

(b)Intermediate stage<br />

(c) Final Stage<br />

Figure 2. Various Stages during Tube Hydr<strong>of</strong>orming Process<br />

The overall success <strong>of</strong> hydr<strong>of</strong>orming product heavily depends on the incoming tubular material properties.<br />

Material properties such as composition, weld type, yield and tensile strength, ductility, anisotropy must be<br />

determined for tubes [3,5]. Some <strong>of</strong> the important characteristics tubular materials for quality THF applications<br />

are high and uniform elongation, high strain-hardening exponent and low anisotropy [7]. There are certain<br />

limitations on the degree <strong>of</strong> deformation achievable in tube hydr<strong>of</strong>orming (THF) process such that parts with<br />

desired specifications (like expansions) may not be formed without any defects. THF process defects can be<br />

grouped as wrinkling, buckling and bursting (Necking, Fracture) [11,13].<br />

Aluminium has poor drawing capability with conventional forming processes. But with hydr<strong>of</strong>orming process its<br />

formability can be increased by 30-40%.The higher draw ratio <strong>of</strong> sheet hydro formed aluminium makes it a<br />

replacing element to steel sheets as it has same strength with light weight. In order to develop double-T shape<br />

joint, aluminium can be material with hydr<strong>of</strong>orming process. So in this report, Aluminium tube is used for<br />

forming double T joint with THF process [8].<br />

The Tube Hydr<strong>of</strong>orming process parameters, viz., die geometry, internal fillet angle at corners, internal hydraulic<br />

pressure variation, velocity <strong>of</strong> pistons, and temperature greatly influence the final microstructure and thus the<br />

properties <strong>of</strong> the final product. In this investigation pure aluminium is processed by THF process and studied the<br />

formability <strong>of</strong> aluminium.<br />

3. Literature Review<br />

The history <strong>of</strong> hydr<strong>of</strong>orming process is not very old. Its application in automobile sector field began in Europe<br />

and North America and has been showing rapid expansion in these countries. In Japan, on the other hand, the<br />

application <strong>of</strong> Hydr<strong>of</strong>orming Process to the manufacture <strong>of</strong> car components began in <strong>19</strong>99. THF process has<br />

been in practical industrial use only more than a decade, the development <strong>of</strong> the techniques and establishment <strong>of</strong><br />

the theory started in <strong>19</strong>40s. Manufacturing <strong>of</strong> seamless copper fittings with T branches was investigated using<br />

internal pressure and axial load by Grey et al [14].<br />

Davis tested tubes <strong>of</strong> medium carbon steel under internal pressure and tensile axial load in order to determine<br />

their yield and fracture characteristics [15]. Experimental and numerical studies were conducted to find the<br />

bursting pressure <strong>of</strong> thick-walled cylinders by Faupel, Crossland and Dietmann during <strong>19</strong>50s and <strong>19</strong>60s [16].<br />

635


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

In<strong>19</strong>60s, experimental and theoretical investigations on instability <strong>of</strong> thin- walled cylinders were performed by<br />

many researchers at different countries [17]. Fundamental investigations on thin-and thick-walled cylinders<br />

helped theoretical improvements in THF operations. Use <strong>of</strong> hydrostatic pressure in metal forming processes, in<br />

particular, for bulging <strong>of</strong> tubular parts was first reported by Fuchs [18]. In this paper, he reported experimental<br />

studies on expansion and flanging <strong>of</strong> copper tubes using hydraulic pressure.<br />

Ogura and Ueda [<strong>19</strong>] presented their experimental results on THF <strong>of</strong> Tee shapes from low and medium carbon<br />

steel. Different configurations and number <strong>of</strong> Tee protrusions were formed using internal pressure and axial<br />

compressive loading. Al-Qureshi and his team [<strong>20</strong>] performed bulging and piercing experiments <strong>of</strong> different<br />

materials including copper, steel and aluminium using polyurethane to provide internal pressure [21]. They did<br />

not report use <strong>of</strong> axial loading in their experiments.<br />

In <strong>19</strong>70s, research on different aspects <strong>of</strong> bulge forming continued both experimentally and theoretically by<br />

various authors. New shapes, materials, different tooling configurations and new machine concepts were<br />

introduced, whereas the fundamentals remained the same. For illustration, instead <strong>of</strong> polyurethane, rubber and<br />

elastomer were used to provide internal pressure [21].<br />

Limb and his team [22] performed THF <strong>of</strong> different materials with changing wall thickness. They reported that<br />

increasing the internal pressure gradually during the application <strong>of</strong> axial load gives the best results on thinning<br />

and complete filling. Thickening <strong>of</strong> tube wall at feeding zone was also mentioned due to the friction between<br />

tube and die surface.<br />

Woo [23] reported experimental and analytical results for tubes bulged under internal pressure and axial<br />

compressive loading. He carried out a numerical study assuming that the entire length <strong>of</strong> the bulged tube was in<br />

tension, and thus, free bulging took place.<br />

Limb et al. used oil as pressurizing medium in their experiments to investigate the forming <strong>of</strong> copper,<br />

aluminium, low carbon steel and brass Tee-shaped tubular parts. Results <strong>of</strong> lubricant and material evaluations<br />

were reported in terms <strong>of</strong> protrusion height attainable. Sauer et al. presented their theoretical and experimental<br />

work on necking criterion <strong>of</strong> bulged tubes. Assuming a constant ratio <strong>of</strong> hoop and longitudinal stresses in tube<br />

wall during expansion, numerical and experimental results were found to be in agreement. Effective strain at<br />

necking was also explained in terms <strong>of</strong> pre-strain, strain-hardening exponent and stress ratio.<br />

Woo and Lua [24] described their experimental tooling for THF process, and presented a theoretical analysis <strong>of</strong><br />

stresses and strains taking into account the anisotropy effect <strong>of</strong> the sheet metals in two separate papers. They<br />

utilized Hill's theory <strong>of</strong> plastic anisotropy in their work.<br />

Starting from <strong>19</strong>80s, researchers in Japan concentrated on determining the material properties and their effects<br />

on tube bulging operations. Manabe and Nishimura investigated influence <strong>of</strong> the strain hardening exponent and<br />

anisotropy on forming <strong>of</strong> tubes in hydraulic bulging and nosing processes [25]. They briefly presented the<br />

maximum internal pressure as a function <strong>of</strong> tube radius, thickness, strain hardening exponent, and strength<br />

coefficient assuming that there was no axial loading.<br />

Manabe et al. [26] published their work on examination <strong>of</strong> deformation behaviour and limits <strong>of</strong> forming for<br />

aluminium tubes under both internal pressure and axial force. Axial cylinders and internal pressure were<br />

controlled by a computer-control-system to obtain pre-defined stress ratio during their experiments. They utilized<br />

fundamental analysis <strong>of</strong> thin-walled cylinders in their predictions for internal pressure and axial force.<br />

Fuchizawa [27] analyzed bulge forming <strong>of</strong> finite-length, thin-walled cylinders under internal pressure using<br />

incremental plasticity theory. He presented the influence <strong>of</strong> strain-hardening exponent on limits <strong>of</strong> bulge height.<br />

Internal pressure and maximum expansion radius were expressed in terms <strong>of</strong> length, diameter, strength<br />

coefficient (k) and strain-hardening exponent (n). He based his analysis on deformation theory and Hill's theory<br />

<strong>of</strong> plastic anisotropy.<br />

Thiruvarudchelvan [28] and his team have worked on experimental and theoretical aspects <strong>of</strong> tube bulging<br />

process using both polyurethane and liquid as pressurizing medium Ueda presented forming <strong>of</strong> differential gear<br />

casings with hydr<strong>of</strong>orming techniques after a series <strong>of</strong> experimentations in <strong>19</strong>80s. Hashimi and his team<br />

investigated the bulge forming <strong>of</strong> axi-symmetric and asymmetric components via experiments, analytical<br />

techniques and FEA.<br />

636


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4. Finite element analysis <strong>of</strong> Double T-Shape Tube Hydr<strong>of</strong>orming Process<br />

The Double T-Shape Tube Hydr<strong>of</strong>orming Process is simulated by using the commercial metal forming finite<br />

element code 'FORGE <strong>20</strong>11'. The initial tube sample having 10 mm in external diameter, 1mm thickness and 50<br />

mm in length, made <strong>of</strong> pure copper Al-99 is used. Our goal is to focus on the average equivalent strain obtained.<br />

In this investigation each geometrical combination with a particular velocity is studied under oil, low, medium<br />

and high friction conditions respectively. The punches moved with velocities 1mm/s in opposite directions. The<br />

counter punches remained fixed at 10mm from centreline so that proper material flow can be achieved at<br />

protrusion area. The internal pressure was varied linearly from 0 to 100 MPa during the process.<br />

4.1 Arrangement for Double T-shape hydr<strong>of</strong>orming process<br />

Tube Parameters<br />

Figure.3 Schematic illustration Double T- shape Die.<br />

Figure 4. Tube Parameters<br />

Table 1.Process Parameters for Double T-joint hydr<strong>of</strong>orming process<br />

Tube Type<br />

Tube Dimensions<br />

Tube Material<br />

Temperature<br />

Friction<br />

Press type<br />

Velocity<br />

Punch 1<br />

Punch 2<br />

Counter Punches 1,2<br />

Circular<br />

Length=50mm<br />

External Diameter=10mm<br />

Tube Thickness=1mm<br />

Aluminium (99% pure)<br />

Ambient (<strong>20</strong>°C)<br />

High (μ=0.2)<br />

Medium(μ=0.05)<br />

Low(μ=0.02)<br />

Oil(μ=0.01)<br />

Hydraulic<br />

1 mm/s<br />

Stationary<br />

637


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The equivalent strain contours during tube hydr<strong>of</strong>orming process on Al99.97 under different friction conditions<br />

and ram velocity <strong>of</strong> 1mm/sec using FORGE are depicted in figure 5.<br />

(a) High Friction<br />

(c).Low Friction<br />

(b).Medium Friction<br />

(d) Under Oil Condition<br />

Figure 5. Variation <strong>of</strong> strain during Double T-Shape THF process on Al99.97 under different friction conditions<br />

using FORGE.<br />

Figure6. indicated the variation <strong>of</strong> temperature over the tube during THF process. It is observed that with<br />

increase friction equivalent strain decreases for all considered friction values.<br />

(a) High Friction<br />

(b) Medium Friction<br />

638


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

(c) Low Friction<br />

(d) Under Oil Condition<br />

Figure 6. Variation <strong>of</strong> temperature during Double T-Shape THF process on Al99.97 under different friction<br />

conditions using FORGE.<br />

5. Results and Discussion<br />

Results obtained by FE modelling are shown in following table.<br />

Table 2.Simulation Results <strong>of</strong> Double T-joint hydr<strong>of</strong>orming process<br />

Parameters<br />

Equivalent<br />

Strain<br />

Generated<br />

Max.<br />

Temperature<br />

Reached(in °C)<br />

Punch<br />

Force<br />

(in<br />

Tonnes)<br />

Internal<br />

Hydraulic<br />

Pressure<br />

Friction<br />

conditions<br />

High Friction(0.2) 1.71 43.8 0.745 100 MPa<br />

(Linearly<br />

Increasing)<br />

Medium<br />

Friction(0.05)<br />

Low<br />

Friction(0.02)<br />

Under Oil<br />

Condition(0.01)<br />

1.3 43.1 0.639 100 MPa<br />

(Linearly<br />

Increasing)<br />

1.05 42.6 0.626 100 MPa<br />

(Linearly<br />

Increasing)<br />

1.08 43.5 0.624 100 MPa<br />

(Linearly<br />

Increasing)<br />

6. Conclusion<br />

From the experiment it is concluded that under different friction conditions the equivalent strain generated in the<br />

Al billet increased tremendously with different rates. High strain is obtained with high friction and with<br />

decreasing friction strain gets reduced. Also the shape achieved also effected with friction conditions.The current<br />

FE study greatly helps to understand THF parameters to design experimental facilities. FEM analysis <strong>of</strong> double<br />

T-shape hydr<strong>of</strong>orming process is done with Aluminium under different conditions <strong>of</strong> friction. The strain<br />

generated, and hence deformation achieve in the process is studied. The protrusion height achieved during the<br />

deformation process is also studied.<br />

References<br />

1. Ahmetoglu M., Sutter K., Li X.J., and Altan T., "Tube hydr<strong>of</strong>orming: current research, applications and<br />

need for training." J Mater Process <strong>Technology</strong> Vol. 98, pp 224–31, <strong>20</strong>00.<br />

2. Ahmed M., and Hashmi M. S. J.," Three dimensional finite element simulation <strong>of</strong> axi-symmetric tube<br />

bulging. In: Proc pacific congress on manufacturing and management. Brisbane, Australia, pp. 515–21,<br />

<strong>19</strong>98.<br />

639


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3. Back C., Miyagawa M." The plastic deformation and strength <strong>of</strong> circular cylindrical shells under<br />

internal pressure and/or axial force (1st report, experiment)." Trans Jpn Soc Mech Eng Vol 32(235),<br />

pp.447–56, <strong>19</strong>66<br />

4. Birkert A., "Tool and part design for hydr<strong>of</strong>orming."Proceedings <strong>of</strong> the International Conference on<br />

Hydr<strong>of</strong>orming, Stuttgart, Germany, October 12-13, <strong>19</strong>99.<br />

5. Breckner M.," Hydraulic systems for hydr<strong>of</strong>orming." Proceedings <strong>of</strong> the International Conference on<br />

Hydr<strong>of</strong>orming, Stuttgart, Germany, October 12-13, <strong>19</strong>99.<br />

6. Chen F., Wang S., and Lin R. "A study <strong>of</strong> forming pressure in the tube hydr<strong>of</strong>orming process." J Mater<br />

Process <strong>Technology</strong> <strong>19</strong>2–<strong>19</strong>3, pp.404–409, <strong>20</strong>07.<br />

7. Fuchizawa S., “Influence <strong>of</strong> strain hardening exponent on the deformation <strong>of</strong> thin-walled tube <strong>of</strong> finite<br />

length subjected to hydrostatic external pressure.” Adv. Technol. Plasticity, vol.1, pp. 297–302, <strong>19</strong>84.<br />

8. Hama T., Ohkubo T., Kurisu K., Fujimoto H., and Takuda H.," Formability <strong>of</strong> tube hydr<strong>of</strong>orming under<br />

various loading paths." J Mater Process <strong>Technology</strong> Vol. 177, pp.676–9, <strong>20</strong>06.<br />

9. Jeong K., Sang-Woo K., Hoon-Jae P., and Kang B. S., “A prediction <strong>of</strong> bursting failure in tube<br />

hydr<strong>of</strong>orming process based on plastic instability”. Int. J Adv. Manufacturing <strong>Technology</strong> vol.27,<br />

pp.518–524, <strong>20</strong>06.<br />

10. Kang S. J., Kim H.K., Kang B. S. “Tube size effect on hydr<strong>of</strong>orming formability” J Mater Process<br />

<strong>Technology</strong>, Vol. 160, pp 24–33, <strong>20</strong>05.<br />

11. Klaas F., "Innovations in high pressure hydr<strong>of</strong>orming." Proceedings <strong>of</strong> the Second International<br />

Conference on Innovations in Hydr<strong>of</strong>orming <strong>Technology</strong>, Columbus, OH, September 17, <strong>19</strong>99.<br />

12. Koç M., Allen T., Jiratheranat S., and Altan T. “The use <strong>of</strong> FEA and design <strong>of</strong> experiments to establish<br />

design guidelines for simple hydr<strong>of</strong>ormed parts” Int. J Mach Tools Manufacturing, Vol. 40, pp.2249–<br />

2266, <strong>20</strong>00.<br />

13. Altan T., Muammer Koc "Prediction <strong>of</strong> forming limits and parameters in the tube hydr<strong>of</strong>orming<br />

process", International Journal <strong>of</strong> Machine Tools & Manufacture 42 pp.123–138, <strong>20</strong>02.<br />

14. Grey J. E., Devereaux A.P., Parker W.N.," Apparatus for making wrought metal T's", US Patent<br />

2,<strong>20</strong>3,868 June (<strong>19</strong>39).<br />

15. Davis E.A.," Yield and fracture <strong>of</strong> medium-carbon steel under combined stress,."J. Appl. Mech.pp.13-<br />

24, <strong>19</strong>45.<br />

16. H. Dietmann, ”The Flow behaviour <strong>of</strong> thick-walled cylinders under internal pressure." Bander Bleche<br />

Rohre 8(3), pp.143-149, <strong>19</strong>67.<br />

17. Woo D.M., "The analysis <strong>of</strong> axi-symmetric forming <strong>of</strong> sheet metal and the hydrostatic bulging process."<br />

Int. J. Mech. Sci. 6, pp. 303-317, <strong>19</strong>64.<br />

18. Fuchs F.J., "Hydrostatic pressure Ð its role in metal forming."Mech. Eng. pp. 34-40, <strong>19</strong>66.<br />

<strong>19</strong>. Ogura T and Ueda T. "Liquid bulge forming" Metalwork Prod, pp.73–81, <strong>19</strong>68.<br />

<strong>20</strong>. Al-Qureshi H.A., Mellor P.B., Garber S., "Application <strong>of</strong> polyurethane to the bulging and piercing <strong>of</strong><br />

thin-walled tubes."Proceedings <strong>of</strong> the Ninth International MTDR Conference, Birmingham, UK, pp.<br />

3<strong>19</strong>-338, <strong>19</strong>68.<br />

21. Al-Qureshi H.A.," Comparison between the bulging <strong>of</strong> thin-walled tubes using rubber forming<br />

technique and hydraulic forming process." Sheet Metal Ind. pp.607 612, <strong>19</strong>70.<br />

22. Limb M.E., Chakrabarty J., Garber S., and Mellor P.B.," The forming <strong>of</strong> axi-symmetric and asymmetric<br />

components from tube." In Proc 14th international MTDR conference, pp. 799–805, <strong>19</strong>73.<br />

23. Woo D.M.," Tube-bulging under internal pressure and axial force." J. Eng. Mater. Technol. pp.2<strong>19</strong>-223,<br />

<strong>19</strong>73.<br />

24. Woo D.M.," Development <strong>of</strong> a bulge forming process,." Sheet Metal Ind., pp.623-625, <strong>19</strong>78.<br />

25. Manabe K., Nishimura H.," Influence <strong>of</strong> material properties in forming <strong>of</strong> tubes." Bander Bleche Rohre<br />

9, <strong>19</strong>83.<br />

26. Manabe K., Mori S., Suzuki K., Nishimura H.," Bulge forming <strong>of</strong> thin-walled tubes by micro-computer<br />

controlled hydraulic press." Adv. Technol. Plasticity pp.279- 284, <strong>19</strong>84.<br />

27. Fuchizawa S., “Influence <strong>of</strong> strain hardening exponent on the deformation <strong>of</strong> thin-walled tube <strong>of</strong> finite<br />

length subjected to hydrostatic external pressure.” Adv. Technol. Plasticity, vol.1, pp. 297–302, <strong>19</strong>84.<br />

28. Thiruvarudchelvan S.,"A theory for the bulging <strong>of</strong> aluminium tubes using urethane rod." J. Eng.<br />

Technol. <strong>19</strong>89.<br />

640


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

NANOMATERIALS SYNTHESIS, CHARACTERISATION AND<br />

PHOTOLUMINESCENT PROPERTIES OF Ca 2 V 2 O 7 : EU<br />

NANOMATERIALS<br />

Avni Khatkar 1 , S.P. Khatkar 2<br />

1 UIET, Maharshi Dayanand <strong>University</strong>, Rohtak – 124001, India<br />

2<br />

UIET, Maharshi Dayanand <strong>University</strong>, Rohtak – 124001, India Tel: +91 9813805666<br />

E-mail address: s_khatkar@rediffmail.com<br />

Abstract<br />

A solution combustion route for the synthesis <strong>of</strong> Eu 3+ -activated Ca 2 V 2 O 7 nanomaterials using carbohydrazide<br />

fuel and their photoluminescent properties have been investigated. Structure and luminescent characteristics <strong>of</strong><br />

as prepared and post heat-treated at different temperatures with different mole % <strong>of</strong> Eu 3+ doped Ca 2 V 2 O 7<br />

nanomaterials have been studied by x-ray diffraction (XRD), fluorescence spectrometry (PL) and scanning<br />

electron microscopy (SEM). The incorporation <strong>of</strong> Eu 3+ activator in these nanoparticles has been checked by<br />

luminescence characteristics. These particles have displayed excellent red color under a UV source which is due<br />

to characteristics transition <strong>of</strong> Eu 3+ from 5 D 0 → 7 F 2 transition. The excitation spectra shows a dominant broad<br />

band corresponding to CT transitions from Eu 3+ -O 2- group and sharp peaks in the higher wavelength range due<br />

to the intrinsic excitation bands <strong>of</strong> Eu 3+ . These materials have potential applications in optics, optoelectronics<br />

technology and display panels.<br />

Keywords: Nanomaterials; Carbohydrazide; Ca 2 V 2 O 7 : Eu<br />

1. Introduction<br />

Rare-earth oxides are a new class <strong>of</strong> materials which introduce advantages compared to bulk crystals due to their<br />

enhanced physical properties with potential applications in optics, optoelectronics technology and advanced<br />

ceramics [1-2]. Accordingly, the host has only a weak influence on the RE 3+ energy levels and the radiative<br />

emission resemble those <strong>of</strong> the free ion in terms <strong>of</strong> their narrow spectral width (5-<strong>20</strong> cm -1 in crystalline host) [3-<br />

5], long excited state lifetimes (milliseconds) and relatively low oscillator strengths (~ 10 -5 -10 -8 ) [6]. Rare earth<br />

doped yttrium vanadates are widely used in a variety <strong>of</strong> applications such as CRTs, fluorescent lamps,<br />

scintillators in medical image detectors and in plasma display panels [7-10]. The recent research demonstrated<br />

that the red emission <strong>of</strong> the Eu- doped phosphors arises from the 5 D 0 → 7 Fj (j= 0, 1, 2, 3, 4) transitions. Ca 2 V 2 O 7<br />

is member <strong>of</strong> a series <strong>of</strong> luminescent materials with general formula M 2 V 2 O 7 (M=Mg, Ca, Sr, Ba, Zn, Cd, Hg).<br />

Many polycrystalline pyrovanadates M 2 V 2 O 7 (M =Ca, Sr, Ba) having triclinic structures [11-12] have been<br />

investigated to have a rare luminescent property and these compounds showed a quite broad band luminescence<br />

in the visible range from 400nm to 800 nm derived from the CT transition in the VO 4 tetrahedra. The broad band<br />

luminescence in the visible region is effective to obtain a good color rendering property for the light devices.<br />

Although, fluorescence studies on M 2 V 2 O 7 (M =Ca, Sr, Ba) have been reported by Nakajima [13] and<br />

luminescent color <strong>of</strong> these new vanadate phosphor system varied from green (M: Ba) to yellowish orange (M:<br />

Ca) with internal quantum efficiency (η) 25%, 8% and 0.9% respectively, but to our knowledge there are very<br />

few reports on Ca 2 V 2 O 7 : Eu 3+ phosphors synthesis. Red emitting Ca 2 V 2 O 7 :Eu 3+ phosphors were prepared by<br />

hydrothermal method, using CaO, Eu 2 O 3 , NH 4 VO 3 as the raw materials [14].<br />

Solution combustion synthesis (SCS) has emerged as an attractive technique for the synthesis <strong>of</strong> high purity<br />

homogeneous and crystalline oxide powders at significantly lower temperatures than the conventional synthesis<br />

method because the starting raw materials are homogeneously mixed in liquid phase and the high temperature<br />

generated instantly by the exothermic radiation can volatilize low boiling point impurities [15-17]. The attractive<br />

features <strong>of</strong> SCS are its ability to synthesize materials with high purity, better homogeneity and high surface area<br />

in a single step. As a part <strong>of</strong> our programme on luminescent materials [18-<strong>19</strong>], here we report the use <strong>of</strong> solution<br />

combustion synthesis (SCS) for the preparation <strong>of</strong> Eu 3+ -doped Ca 2 V 2 O 7 nanomaterials.<br />

2. Experiment<br />

The starting reagents were high purity Ca(NO 3 ) 2 .2H 2 O, NH 4 VO 3 , Eu(NO 3 ) 3 .5H 2 O and carbohydrazide.<br />

According to nominal composition <strong>of</strong> Ca 2(1-x) V 2 O 7 :2xEu 3+ (x=0.01, 0.02, 0.03, 0.04, 0.05), a stoichiometric<br />

amount <strong>of</strong> metal nitrates were dissolved in minimum quantity <strong>of</strong> deionized water in <strong>20</strong>0 mL capacity pyrex<br />

beakers. Then carbohydrazide was added in this solution with molar ratio <strong>of</strong> fuel to nitrates based on total<br />

oxidizing and reducing valencies <strong>of</strong> oxidizer and the fuel according to concept used in propellant chemistry [<strong>20</strong>].<br />

Finally the beaker containing the solution was placed into a preheated furnace at 500°C. The material undergoes<br />

641


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

rapid dehydration and foaming followed by decomposition, generating combustible gases. These volatile<br />

combustible gases ignite and burn with a flame yielding voluminous solid. Carbohydrazide was oxidized by<br />

nitrate ions and served as a fuel for propellant reaction. Combustion synthesized nanoparticles were annealed at<br />

different temperatures from 700°C to 900°C in order to know the effect <strong>of</strong> annealing on the particle size/shape<br />

and luminescence properties.<br />

3. Characterization<br />

The crystal phase <strong>of</strong> Ca 2 V 2 O 7 :Eu 3+ nanoparticles prepared was characterized by Rigaku Miniflex-II X-ray<br />

powder diffraction with CuKα radiation at 30 kV tube voltage and 15 µA tube current. The particle size and<br />

morphology were evaluated using Jeol JSM-6510 scanning electron microscope (SEM). The excitation and<br />

emission spectra <strong>of</strong> nanoparticles in the ultraviolet-visible region were obtained by using a Hitachi F-7000<br />

fluorescence spectrophotometer with Xe- lamp at room temperature.<br />

4. Results and discussion<br />

The XRD patterns <strong>of</strong> Ca 2(1-x) Eu 2x V 2 O 7 (Eu =4 mol %) particles, both as synthesized and annealed at<br />

temperatures 700° and 900°C for 3h are shown in fig.1(a). Calcium pyrovanadate crystallizes in the triclinic<br />

space group P1 and has a structure with two distinct V 5+ sites and a V-O-V bond angle <strong>of</strong> 124.0°. This resembles<br />

the “dichromate” pyrovanadate structure. The V(1) site in Ca 2 V 2 O 7 includes four V-O bonds (dV-O) (1.70-1.74<br />

Å) in a fairly symmetric tetrahedron, whereas the V(2) site may be considered pentacoordinated with five V-O<br />

distances in the range 1.65- 2.05 Å [21]. All diffraction peaks are in good agreement with the JCPDS data (no.<br />

36-0155) [5]. Ca 2 V 2 O 7 phase formation is initiated in the as-synthesized powder by combustion, which increases<br />

with increasing annealing temperature. No peak corresponding to any <strong>of</strong> the source materials or allotropic forms<br />

was found after annealing at 900°C (Fig.1) suggesting that a pure compound with the same structure as Ca 2 V 2 O 7<br />

exists. Fig. 1(b) shows the XRD pattern <strong>of</strong> the sample Ca 2(1-x) Eu 2x V 2 O 7 nanoparticles (Eu =1, 2, 3, 4 mol %)<br />

annealed at 900°C for 3h. From the analysis <strong>of</strong> XRD, it was revealed that the introduction <strong>of</strong> an activator (Eu 3+ )<br />

did not influence the crystal structure <strong>of</strong> the phosphor matrix. The XRD pattern <strong>of</strong> the Ca 2 V 2 O 7 :Eu 3+ showed the<br />

presence <strong>of</strong> broad peaks. The broad peaks either indicate particles <strong>of</strong> very small crystalline size or particles are<br />

semicrystalline in nature.<br />

Fig.2 depicts the typical red photoluminescence from Eu 3+ ions in the Ca 2 V 2 O 7 :Eu 3+ nanoparticles when rooting<br />

the excitation wavelength at 394 nm. It is clear that the PL intensity <strong>of</strong> the as–synthesized nanomaterials at<br />

500°C, increased rapidly with increase <strong>of</strong> annealing temperature. This is mainly due to the improvement in<br />

doping and crystallinity. In particular, the most intense emission peak at 613 nm corresponds to 5 D 0 → 7 F 2 and<br />

occurs through the forced electric dipole, while the 5 D 0 → 7 F 1 band at 588 nm is the magnetic dipole transition<br />

[14].The emission spectrum is dominated by 5 D 0 → 7 F 2 hypersensitive transition (∆ J=2), which is because the<br />

Eu 3+ is located at a low symmetry local site in the Ca 2 V 2 O 7 host lattice. Moreover, the splitting number <strong>of</strong><br />

5 D 0 → 7 F j transitions can provide information <strong>of</strong> the surroundings <strong>of</strong> the Eu 3+ ions and the site symmetry <strong>of</strong> Eu 3+<br />

ion with a maximum number <strong>of</strong> lines “2J+1” for each lattice site [22]. Unique 5 D 0 → 7 F 0 (581 nm) transition<br />

indicates that the Eu 3+ ions occupy single site in Ca 2 V 2 O 7 lattice.<br />

Generally, the luminescence properties <strong>of</strong> nanomaterials depend on the activator concentration and crystallinity.<br />

Dependence <strong>of</strong> the emission intensity <strong>of</strong> europium ions upon the doping concentration (x) in the crystalline Ca 2(1-<br />

x)Eu 2x V 2 O 7 (900°C annealed) excited by 394 nm is shown in fig. 2(b). It is found that the PL emission intensity<br />

increased with the increase in the concentration <strong>of</strong> Eu 3+ , reaching a maximum value with 4 mol % doping <strong>of</strong><br />

Eu 3+ . Usually, an over-doping concentration results in the enhancement <strong>of</strong> non-radiative relaxation between the<br />

neighboring Eu 3+ ions which indicates the concentration quenching.<br />

Photoluminescence excitation spectrum <strong>of</strong> Ca2V 2 O 7 : Eu 3+ sample (fig.2c), include a broad peak centered at 305<br />

nm followed by a series <strong>of</strong> peaks beyond 390 nm. The dominant broad peak is ascribed to charge transfer band<br />

(CTB) which corresponds to an electron transfer from an oxygen 2p orbital to an empty 4f orbital <strong>of</strong> europium<br />

ions ( O 2- → Eu 3+ ). The sharp lines in the range above 390 nm are intra-configurational 4f-4f transitions <strong>of</strong> Eu 3+<br />

in the host lattices, peak with maxima at ~ 395 nm ( 7 F 0 → 5 L 6 ) being the dominating.<br />

The morphology and particle size <strong>of</strong> the Ca 2 V 2 O 7 : Eu 3+ nanoparticles with 4 mol % doping <strong>of</strong> both as prepared<br />

and annealed at 900°C have been investigated by SEM images as shown in Fig.3. The as-synthesized products by<br />

the combustion process show an unusual morphology i.e. forming cracks and porous network due to rapid release<br />

<strong>of</strong> gases by-products during the combustion. This type <strong>of</strong> porous network is typical <strong>of</strong> combustion synthesized<br />

powders. For the powders synthesized at 500°C, the particle size was very small and the particles tend to<br />

agglomerate. With an increase <strong>of</strong> temperature, particle size increased and agglomeration decreased.<br />

642


5. Conclusion<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Ca 2 V 2 O 7 : Eu 3+ nanomaterials have been synthesized by the carbohydrazide-assisted solution combustion<br />

synthesis. XRD analysis shows that the prepared composition retains the triclinic structure <strong>of</strong> Ca 2 V 2 O 7 . The<br />

results from SEM and XRD studies show that Ca 2 V 2 O 7 doped with Eu has a mean particle size <strong>of</strong> about 25 nm<br />

with spherical like morphology. The emission spectra were recorded under λ ex =394 nm and exhibited the<br />

strongest peak at 613 nm. The Ca 2 V 2 O 7 : Eu 3+ nanomaterials thus prepared were shown to possess red-emitting<br />

property attractive to a wide range <strong>of</strong> potential applications in displays.<br />

References<br />

[1] S.H. Dai, Y.F. Liu, Y.N. Lu, H.H. Min, “Microwave solvothermal synthesis <strong>of</strong> Eu 3+ -doped (Y,Gd) 2 O 3<br />

microsheets”, Powder Technol. <strong>20</strong>2 (<strong>20</strong>10) 178.<br />

[2] Y. Ying, A.P. Alivisatos, “Colloidal nanocrystal synthesis and the organic-inorganic interface” , Nature 437<br />

(<strong>20</strong>05) 664.<br />

[3] S. Strite, in : H.J. Queisser (Ed.), Advances in Solid State Physics, Springer, <strong>19</strong>94.<br />

[4] J. Ballato, J.S. Lewis, P.H. Holloway, “Bridgman-stockbarger growth and spectral characteristics <strong>of</strong><br />

vanadium-doped yttrium-aluminium garnet (YAG) single crystals”, Mater. Res. Bull. 24 (<strong>19</strong>99) 51.<br />

[5] G. Blasse, B.C. Grabmeier, Luminescent Material, Springer, Berlin, <strong>19</strong>94.<br />

[6] A. Bao, H. Yang, C. Tao, Y. Zhang, L. Han, “ Luminescent properties <strong>of</strong> nanoparticles YP x V 1-x O 4 :Dy<br />

phosphors”, J. Lumin. 128 (<strong>20</strong>08) 60.<br />

[7] A.K. Levine, F.C. Papilla, “A new, highly efficient red-emitting cathodoluminescent phosphor (YVO 4 :Eu)<br />

for color television”, Appl. Phys. Lett. 5 (<strong>19</strong>66) 118.<br />

[8] A.S. Osvaldo, A.C. Simone, R.I. Renata, “ A new procedure to obtain Eu 3+ doped oxide and oxosalt<br />

phosphors”, J. Alloys Compd. 303 (<strong>20</strong>00) 316.<br />

[9] G. P. Anayiotakis, D. Cavouras, I. Kandarakis, C. Nomicos, “A study <strong>of</strong> X-ray luminescence and spectral<br />

compatibility <strong>of</strong> europium-activated yttrium-vanadate (YVO 4 : Eu) screens for medical imaging applications”,<br />

Appl. Phys. A 62 (<strong>19</strong>96) 483.<br />

[10] K.S. Sohn, W. Zeon, H. Chang, S.K. Lee, H.D. Park, “Combinatorial search for new red phosphors <strong>of</strong> high<br />

efficiency at VUV excitation based on the YRO 4 (R = As, Nb, P, V) system”, Chem. Mater. 14 (<strong>20</strong>02) 2140.<br />

[11] F.C. Hawthorne, C. Calvo, “The crystal structure <strong>of</strong> Ba 2 V 2 O 7 ”, J. Solid State Chem. 26 (<strong>19</strong>78) 345.<br />

[12] J. Huang, A.W. Sleight, “Crystal structure <strong>of</strong> high temperature strontium pyrovanadate”, Mater. Res. Bull.<br />

27 (<strong>19</strong>92) 581.<br />

[13] T. Nakajima, M. Isobe, T. Tsuchiya, Y. Ueda, T. Manabe, “Photoluminescence property <strong>of</strong> vanadates<br />

M 2 V 2 O 7 (M: Ba, Sr and Ca)”, Opt. Mater. 32 (<strong>20</strong>10) 1618.<br />

[14] J. Gu, B. Yan, “Hydrothermal synthesis and luminescent properties <strong>of</strong> Ca2V 2 O 7 :Eu 3+ phosphors”, J. Alloys<br />

Compd. 476 (<strong>20</strong>09) 6<strong>19</strong>.<br />

[15] V. Singh, V.K. Rai, K.A. Shamery, J. Nordmann , M. Haase, “ NIR to visible upconversion in Er 3+ /Yb 3+ codoped<br />

CaYAl 3 O 7 phosphor obtained by solution combustion process”, J. Lumin. 131 (<strong>20</strong>11) 2679.<br />

[16] J.R. Jayaramaiah, B.N. Lakshminarasappaa, B.M. Nagabhushana, “Thermoluminescence studies <strong>of</strong> solution<br />

combustion synthesized Y 2 O 3 :Nd 3+ nanophosphor”, Mater. Chem. Phys. 130 (<strong>20</strong>11) 175.<br />

[17] I. Pekgozlu, E. Erdomu, B. Demirel, M.S. Gok, H. Karabulut, A.S. Baak, “A novel UV-emitting phosphor<br />

Li 6 CaB 3 O 8.5 :Pb 2+ ”, J. Lumin. 131 (<strong>20</strong>11) 2290.<br />

[18] V.B. Taxak, S.P. Khatkar, S.D. Han, R. Kumar, M. Kumar, “ Tartaric acid-assisted sol–gel synthesis <strong>of</strong><br />

Y 2 O 3 :Eu 3+ nanoparticles”, J. Alloys Compd. 469 (<strong>20</strong>09) 224.<br />

[<strong>19</strong>] B. Mari, K.C. Singh, M. Sahal, S.P. Khatkar, V.B. Taxak, M. Kumar, “Characterization and<br />

photoluminescence properties <strong>of</strong> some MLn 2(1−x) O 4 :2xEu 3+ or 2xTb 3+ systems (M=Ba or Sr, Ln=Gd or La) ”, J.<br />

Lumin. 131 (<strong>20</strong>11) 587.<br />

[<strong>20</strong>] S. Ekambaram, K.C. Patil, “Synthesis and properties <strong>of</strong> Eu 2+ activated blue phosphors”, J. Alloys Compds.<br />

248 (<strong>19</strong>97) (7).<br />

[21] V. K. Trunov, Y. A. Velikodnyi, E.V. Murasheva, V. D. Zhuravlev, “ Crystal Structure <strong>of</strong> Calcium<br />

Pyrovanadate”, Doklady Akademii Nauk SSSR 270 (<strong>19</strong>83) 886.<br />

[22] G.P. Thim, H.F. Brito, S.A. Silva, M.A.S. Oliveira, M.C.F.C. Felintoc, “ Preparation and optical properties<br />

<strong>of</strong> trivalent europium doped into cordierite using the sol-gel process”, J. Solid State Chem. 171 (<strong>20</strong>03) 375.<br />

643


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig.1. XRD patterns <strong>of</strong> (a) Ca 2 V 2 O 7 (Eu=4 mol %) (b) Ca 2(1-x) Eu 2x V 2 O 7 (Eu =1, 2, 3 and 4 mol %), annealed<br />

at 900°C.<br />

644


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig.2. Emission spectra <strong>of</strong> (a) Ca 2(1-x) Eu 2x V 2 O 7 (Eu=4 mol %) at different temperatures, (b) Ca 2(1-x) Eu 2x V 2 O 7<br />

with different mol % doping <strong>of</strong> Eu 3+ annealed at 900°C; (c) excitation spectrum <strong>of</strong> Ca 2 V 2 O 7 :Eu 3+ (Eu=4 mol %)<br />

.<br />

Fig.3. SEM images <strong>of</strong> Ca 2 V 2 O 7 : Eu 3+ nanomaterials prepared by the solution combustion method (a) asprepared<br />

(b) annealed at 900°C.<br />

645


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

A STUDY OF RECENT TRENDS IN FRICTION STIR WELDING<br />

Rajan 1 , Shailesh S. Sengar 2 , Jitender Kumar<br />

1. Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong>UST Faridabad<br />

2. Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong>UST Faridabad<br />

3. Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong>UST Faridabad<br />

Abstract<br />

This paper deals with the fundamental understanding <strong>of</strong> friction stir welding process. Friction stir welding is<br />

one <strong>of</strong> the most economical and highly efficient methods in joining similar and dissimilar metals. Most<br />

commercial FSW applications use simple butt joint like circular cross section and alternative designs such as<br />

T-sections, ɪ-section, triangular Geometry and corner welds are very rarely welded. The focus <strong>of</strong> this paper is on<br />

mechanism <strong>of</strong> FSW, influence <strong>of</strong> parameters, heat generation in the process, understanding the deformation,<br />

microstructure and the properties <strong>of</strong> similar and dissimilar welded materials. This review paper will cover<br />

relevant published work conducted to date on FSW.<br />

3<br />

Keywords: FSW, LSW, FSSW, ERHAFW<br />

1. Introduction<br />

Friction stir welding (FSW) is a solid state process for joining materials, especially dissimilar materials, which<br />

involves generation <strong>of</strong> heat by the conversion <strong>of</strong> mechanical energy into thermal energy at the interface <strong>of</strong> the<br />

work pieces without using electrical energy or heat from other sources during rotation under pressure.As a highquality,<br />

precise, high-efficiency, energy-saving and environmental- friendly technique, FW has been widely used<br />

in the aerospace, shipbuilding, automobile industries and in many applications <strong>of</strong> commercial importance. Some<br />

<strong>of</strong> the advantages over the conventional welding techniques are very low distortion, no fumes, porosity or<br />

spatter, no consumables, no special surface treatment and no shielding gas requirements. Two important types <strong>of</strong><br />

friction welding is explained as follows:<br />

2. Spin welding<br />

Spin welding systems consist <strong>of</strong> two chucks for holding the materials to be welded, one <strong>of</strong> which is fixed and the<br />

other rotating. Before welding one <strong>of</strong> the work pieces is attached to the rotating chuck along with a flywheel <strong>of</strong> a<br />

given weight. The piece is then spun up to a high rate <strong>of</strong> rotation to store the required energy in the flywheel.<br />

Once spinning at the proper speed, the motor is removed and the pieces forced together under pressure. The force<br />

is kept on the pieces after the spinning stops to allow the weld to "set". This technique is also known as inertia<br />

welding, rotational welding or inertial friction welding.<br />

3. Linear friction welding<br />

Linear friction welding (LFW) is similar to spin welding except that the moving chuck oscillates laterally instead<br />

<strong>of</strong> spinning. The speeds are much lower in general, which requires the pieces to be kept under pressure at all<br />

times. This also requires the parts to have a high shear strength. Linear friction welding requires more complex<br />

machinery than spin welding, but has the advantage that parts <strong>of</strong> any shape can be joined, as opposed to parts<br />

with a circular meeting point.<br />

4. Mechanism <strong>of</strong> joint formation<br />

In most <strong>of</strong> cases three stages are identified in friction welding. First stage occurs as the surface contact is made<br />

at localized regions especially at surface irregularities and asperities. Due to the high local pressure during<br />

rotation, surface films are broken down to reveal the parent metal and local hot spots are continuously formed<br />

and destroyed. The second stage is characterized by steadily increasing power demand. At the start <strong>of</strong> this stage,<br />

the temperature reaches its operating value and plastic deformation begins at the interface as indicated by ‘burn<br />

<strong>of</strong>f’ at the joint area. The third stage <strong>of</strong> the process begins when the rotating component is brought to rest and the<br />

applied pressure is maintained or decreased to consolidate the weld. Rapid material displacement in joint region<br />

causes diffusion at the interface, recrystallization and grain growth. During deceleration stage, the interface<br />

undergoes hot working as identified by the rise in torque. This continues until such a point when the shear<br />

strength <strong>of</strong> the interface equals to that <strong>of</strong> the material adjacent to it. The absolute value <strong>of</strong> the torque developed is<br />

governed by the adjacent material, applied pressure and the speed <strong>of</strong> rotation.<br />

646


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig 1 A setup <strong>of</strong> friction welding [8]<br />

5. Influence <strong>of</strong> process parameters<br />

The important parameters associated with friction welding are 1) Rotational speed 2) Friction pressure 3)<br />

Friction time. High axial pressure and low rotational speed produces a high rate <strong>of</strong> deformation and this results in<br />

a short weld time. Low friction pressure or high rotational speed produces a relatively low rate <strong>of</strong> deformation.<br />

The friction time is selected so as to ensure that the faying surfaces are cleaned by friction and the weld zone.<br />

The optimum friction time for a given combination depends on material composition, dimensions, friction<br />

pressure and rotational speed. When the friction time is too short, the heating effect could become irregular and<br />

this results in lower bonding strength in some regions. Any heating time in excess <strong>of</strong> the optimum time will<br />

reduce productivity and increases material consumption which leads to coarse grain structure.<br />

6. Literature review<br />

Electric-resistance-heat-aided friction welding (ERHAFW) [1] was introduced by Wen-Ya Li, Min Yu. This<br />

technique is a combination <strong>of</strong> electric resistance welding with the conventional continuous-drive friction welding<br />

and this employment helped in improving the joint quality and energy-saving. In this work, 21-4N (austenitic<br />

stainless steel) and 4Cr9Si2 (martensitic stainless steel) valve steel rods <strong>of</strong> 4 mm diameter were used as base<br />

metals. The results show that electric-resistance-heat-aided friction welding can be applied to join thin rods<br />

within a relatively short time, which is very difficult for conventional friction welding (FW). The ERHAFW is<br />

suitable for joining the thin rods <strong>of</strong> 4 mm diameter.<br />

Experimental investigations on joint properties <strong>of</strong> brass plates by friction stir welding [2] was studied by Cemal<br />

Meran. It is difficult to fusion welding <strong>of</strong> brasses. The main problem <strong>of</strong> these alloys in fusion welding is the<br />

evaporation <strong>of</strong> the zinc during the welding process. The solution to this problem as investigated by him, lies in<br />

recent methodology <strong>of</strong> friction stir welding. In this research, it was pointed out friction stir welding is capable <strong>of</strong><br />

especially brass plates which are 3 mm in thickness. He concluded that evaporation <strong>of</strong> zinc and copper which<br />

makes welding more difficult disappears in friction stir welding because <strong>of</strong> not reaching to melting point <strong>of</strong> metal<br />

during welding. In addition, mechanical properties <strong>of</strong> obtained weld joints were reach to base metal strength<br />

level if suitable welding parameters are determined. Fractures usually occur either in heat affected zone or in<br />

weld joint.<br />

Investigations on the linear friction welding process through numerical simulations [3] was done by Livan<br />

Fratini. LFW is a solid-state joining process applied to non-axis symmetric components and involves joining <strong>of</strong><br />

materials through the relative motion <strong>of</strong> two components undergoing an axial force. The force <strong>of</strong> friction<br />

transformed into heat which cause local s<strong>of</strong>tening <strong>of</strong> material and the bonding occurs. In this paper process<br />

conditions allowing effective bonding conditions were highlighted and local conditions <strong>of</strong> pressure and<br />

temperature determining effective bonding <strong>of</strong> the specimens were determined. A dedicated prototype machine<br />

has been designed and assembled in order to produce experimental test welds. Such conditions can be obtained<br />

acting on the process parameters, namely the oscillation frequency <strong>of</strong> the specimens and the acted pressure. The<br />

numerical model is able to effectively reproduce the process conditions. The subsequent stages and process<br />

647


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

mechanics <strong>of</strong> the LFW operations were highlighted and effective bonding conditions were determined. Future<br />

developments include the definition <strong>of</strong> a bonding criterion, taking into account the combined effects <strong>of</strong><br />

temperature and pressure, to be used for LFW processes.<br />

A study on automatic gap detection in friction stir butt welding operations [4] was done by Yu Yang . A<br />

common problem that arises when welding two sheets is the presence <strong>of</strong> a gap between the sheets. When the<br />

FSW tool encounters a gap, material can possibly escape from the processing zone and the welded part’s<br />

effective cross-sectional area around the gap will decrease. A monitoring algorithm was developed to detect gaps<br />

in friction stir butt welding operations in real time. Experimental studies were conducted to determine the<br />

process parameters (like tool rotation rate and tool traverse speed) and the gap width affect the welding process;<br />

particularly, the plunge force. This paper will be useful in monitoring friction stir butt welding operations and in<br />

performing intelligent control, where process parameters are varied when defects such as gaps are encountered. It<br />

can also be used as a non-destructive evaluation technique that provides the operator with the location <strong>of</strong> a<br />

possible defect. The monitoring algorithm developed in this paper can be modified for the detection <strong>of</strong> other<br />

defects in FSW processes. One example is the initiation <strong>of</strong> wormholes that result in a sudden change in the<br />

plunge force in the tool traverse direction.<br />

An experimental study on friction welding <strong>of</strong> plastically deformed steel by [5] Mümin Sahin. An experimental set<br />

up was designed and realized in order to achieve the friction welding <strong>of</strong> plastically deformed steel bars. The parts<br />

<strong>of</strong> same and different diameters deformed plastically, but same material was welded with different process<br />

parameters. The strengths <strong>of</strong> the joints were determined by tension tests. Variations in hardness and<br />

microstructures in the welding zone were obtained and the effects <strong>of</strong> welding parameters on the welding zone<br />

were investigated. This paper concluded that optimum welding parameters obtained from equal diameter parts<br />

could not be used in welding <strong>of</strong> parts having different diameters and widths. The tensile strength <strong>of</strong> the joints<br />

decreases with the increase in width. Increasing hardness due to rapid cooling decreases the strength because <strong>of</strong><br />

affecting notch. This was due to martensite structure that is a hard and brittle phase. Therefore, welded parts will<br />

not be stronger. The weld strength <strong>of</strong> the joints is not affected prior plastic deformation due to two reasons. First,<br />

plastic deformation in friction welding process is larger than the degree <strong>of</strong> prior plastic deformation. Secondly,<br />

the effect <strong>of</strong> prior plastic deformation is removed in the welding zone due to high temperature in the welding<br />

zone. As a result, plastically deformed steels can easily be applied by friction welding method.<br />

A study on friction Stir Spot Welding <strong>of</strong> polymeric material [6] was done by Saeid Hoseinpour Dashatan. In<br />

this paper the feasibility <strong>of</strong> friction Stir Spot Welding (FSSW) for two dissimilar polymers; polymethyl<br />

methacrylate (PMMA) and acrylonitrile butadiene styrene (ABS) was investigated. An improved tool equipped<br />

with two additional plates was used to make lap joint welded specimens. The effect <strong>of</strong> FSSW parameters on<br />

mechanical properties <strong>of</strong> welded specimens was also studied. The process parameters were tool rotational speed,<br />

tool plunge rate and dwell time. Signal-to-noise ratio and analysis <strong>of</strong> variance were utilized to obtain the<br />

influence <strong>of</strong> process parameters on weld strength as a mechanical property. The study demonstrates that welding<br />

<strong>of</strong> PMMA to ABS by friction stir spot welding was feasible and process parameters had a significant effect on<br />

weld strength. The most effective parameter was found to be tool plunge rate. Main effect diagrams obtained by<br />

statistical analysis had shown that weld strength was enhanced by increasing the dwell time while increasing the<br />

tool plunge rate decreases weld strength. For tool rotational parameter, there was an optimum rotation speed at<br />

which the joint strength reached a maximum value. As a result <strong>of</strong> macrostructure observations, three different<br />

fracture modes were recognized through failure <strong>of</strong> lap-shear tests.<br />

The joining with friction welding <strong>of</strong> high-speed steel and medium-carbon steel [7] was studied by Mumin Sahin.<br />

In the experiments, high-speed steel and medium-carbon steel were used. Post-weld annealing was applied to the<br />

joints . First, the optimum welding parameters for the joints were obtained. Later, the strengths <strong>of</strong> the joints were<br />

determined by tension, fatigue and notch-impact tests, and results were compared with the tensile strengths <strong>of</strong><br />

materials. Then, hardness variations and microstructures in the post-weld <strong>of</strong> the joints were obtained and<br />

examined. Then, obtained results were compared with those <strong>of</strong> previous studies. The tensile strength <strong>of</strong> the joints<br />

increases together with the friction time and pressure, and it rises to maximum, but it decreases for more friction<br />

time and pressure. The fatigue strength <strong>of</strong> the welded joints shows similar behavior like the tensile properties.<br />

The impact properties <strong>of</strong> the welded joints that were obtained in the study were a little bit different from static or<br />

fatigue loadings. In macro and microstructure examinations, decarburization zone in the welding <strong>of</strong> high-speed<br />

steel and medium carbon steel occurs in the medium-carbon steel next to the weld during welding. Therefore,<br />

this zone is the weakest link in the joint. But, its tensile strength is still comparable with that <strong>of</strong> the mediumcarbon<br />

steel parent metal.<br />

648


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

7. Conclusion<br />

From the study <strong>of</strong> notable works on friction stir welding following conclusions can be drawn. The drawback <strong>of</strong><br />

fusion welding is evaporation <strong>of</strong> zinc and copper which makes welding more difficult disappears in friction stir<br />

welding because <strong>of</strong> not reaching to melting point <strong>of</strong> metal during welding. Tool geometry is very important<br />

factor for producing sound welds Welding parameters, including tool rotation rate, traverse speed, spindle tilt<br />

angle, and target depth, are crucial to produce sound and defect-free weld. In FSW the stirring and mixing <strong>of</strong><br />

material occurred only at the surface layer <strong>of</strong> the weld adjacent to the rotating shoulder Compared to the<br />

traditional fusion welding, friction stir welding exhibits a considerable improvement in strength, ductility, fatigue<br />

and fracture toughness Fatigue life <strong>of</strong> friction stir welds are lower than that <strong>of</strong> the base material,.<br />

References<br />

[1] Wen-Ya Li, Min Yu, Jinglong Li, Guifeng Zhang, Shiyuan Wang-Characterizations <strong>of</strong> 21-4N to 4Cr9Si2<br />

stainless steel dissimilar joint bonded by electric-resistance-heat-aided friction welding, Materials and<br />

Design 30 (<strong>20</strong>09) 4230–4235.<br />

[2] Cemal Meran-The joint properties <strong>of</strong> brass plates by friction stir welding, Materials and Design 27 (<strong>20</strong>06)<br />

7<strong>19</strong>–726.<br />

[3] Livan Fratini, Gianluca Buffa, Davide Campanella, Dario La Spisa-Investigations on the linear friction<br />

welding process through numerical simulations and experiments, Materials and Design 40 (<strong>20</strong>12) 285–291<br />

[4] Yu Yang, Prabhanjana Kalya, Robert G. Landers, K. Krishnamurthy-Automatic gap detection in friction stir<br />

butt welding operations, International Journal <strong>of</strong> Machine Tools & Manufacture 48 (<strong>20</strong>08) 1161–1169.<br />

[5] Mümin Sahin, H. Erol Akata- Joining with friction welding <strong>of</strong> plastically deformed steel, Journal <strong>of</strong><br />

Materials Processing <strong>Technology</strong> 142 (<strong>20</strong>03) 239–246.<br />

[6] Saeid Hoseinpour Dashatan, Taher Azdast, Samrand Rash Ahmadi, Arvin Bagheri- Friction Stir Spot<br />

Welding <strong>of</strong> Dissimilar polymethyl methacrylate and acrylonitrile butadiene Styrene Sheets, Materials and<br />

Design(<strong>20</strong>12).<br />

[7] Mumin Sahin, Joining with friction welding <strong>of</strong> high-speed steel and medium-carbon steel, Journal <strong>of</strong><br />

Materials Processing <strong>Technology</strong> 168 (<strong>20</strong>05) <strong>20</strong>2–210.<br />

[8] M.N. Ahmad Fauzi , M.B. Uday, H. Zuhailawati, A.B. Ismail-Microstructure and mechanical properties <strong>of</strong><br />

alumina-6061 aluminum alloy joined by friction welding, Materials and Design 31 (<strong>20</strong>10) 670–676.<br />

649


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

THERMAL MODELING AND FINITE ELEMENT ANALYSIS OF<br />

ELECTRO-CHEMICAL SPARK MACHINING (ECSM)<br />

Gaurav Kumar Sharma 1 , Audhesh Narayan 2<br />

1 Department <strong>of</strong> Mechanical Engineering, MNNIT, Allahabad-211004. email: shagaurav11@gmail.com<br />

2 Department <strong>of</strong> Mechanical Engineering, MNNIT, Allahabad-211004, email: anarayan@mnnit.ac.in<br />

Abstract<br />

The key to achieve good surface integrity in the workpiece due to Electro-chemical spark machining (ECSM )<br />

process, which is hybrid <strong>of</strong> ECM and EDM, is by preventing the excessive temperature and thermal stress<br />

generated during the process. The present work involves in the development <strong>of</strong> a simulation model to simulate<br />

the complex ECSM process which consists <strong>of</strong> simulation <strong>of</strong> each constituent process namely EDM and ECM for<br />

temperature and thermal stress distribution. In order to simulate the realistic complex conditions the three<br />

dimensional FEM is used in the process <strong>of</strong> development <strong>of</strong> the simulation model accounting the random<br />

occurrence <strong>of</strong> the spark during EDM. It is observed that the spark contributes primarily to the temperature and<br />

tensile thermal stresses are created near the top surface <strong>of</strong> the workpiece. Thermal stress distribution holds the<br />

vital information about the surface integrity and surface quality.<br />

Keywords: Electro-chemical spark machining (ECSM), EDM, Hybrid machining, FEM<br />

1. Introduction<br />

Advanced ceramics and composite materials have high potential for their applications in various fields <strong>of</strong><br />

engineering due to the superior properties such as high compressive strength, good thermal shock resistance,<br />

high wear resistance, high hardness, high strength to weight ratio, etc. Such improved material properties,<br />

however, pose new challenges to manufacturing engineers to shape and size these electrically non-conductive<br />

materials economically and efficiently.<br />

For realistic progress in industries, advancements in materials should go hand in hand with the advancement <strong>of</strong><br />

the machining processes. To machine the advanced difficult-to-machine materials, newer machining processes<br />

have come forward[1-4]. Recently, a new trend has been introduced to combine the features <strong>of</strong> different<br />

machining processes. Such machining processes are called as hybrid machining processes (HMPs). HMPs are<br />

developed to exploit the advantages <strong>of</strong> each <strong>of</strong> the constituent machining process and diminish the disadvantages<br />

<strong>of</strong> each constituent process. It has been observed that sometimes, hybrid machining process enhances the<br />

material removal rate (MRR), increases the capabilities <strong>of</strong> the constituent processes, and widen the area <strong>of</strong><br />

application <strong>of</strong> the constituent processes. HMPs also reduce some adverse effects <strong>of</strong> the constituent processes<br />

when they are applied individually[4-5]. Electrochemical spark machining (ECSM) is one <strong>of</strong> the HMPs, which<br />

combines the features <strong>of</strong> electrochemical machining (ECM) and electrodischarge machining (EDM).<br />

ECSM has successfully overcome the limitation <strong>of</strong> electrical conductivity requirement <strong>of</strong> the workpiece material<br />

to be machined by EDM or ECM. Also, the material removal rate by ECSM has been found five and 50 times<br />

faster than that <strong>of</strong> ECM and EDM, respectively, under the same parameter setting [1]. The ECSM process uses<br />

electrochemical discharge (ECD) phenomenon for generating heat for the purpose <strong>of</strong> removing work material by<br />

melting and vaporization[2]. This was presented for the first time in <strong>19</strong>68 by Kurafuji as “Electrochemical<br />

Discharge Drilling” for micro holes in glass .<br />

Figure 1 – Schematic diagram <strong>of</strong> basic electrochemical cell in ECSM process.<br />

650


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. Finite Element Modeling<br />

Configuration <strong>of</strong> the ECSM in machining mode is showing in the Fig. 1. The spark machining zone is the region<br />

<strong>of</strong> mirror contact <strong>of</strong> tool and workpiece.<br />

The workpiece is simultaneously subjected to heating due to electrical sparks generated between the electrode<br />

and workpiece, and the chemical reaction occurs between the electrodes. Hence the transient temperature is<br />

determined by EDM heat source.<br />

2.1 Assumptions<br />

1. The workpiece material is homogeneous and isotropic.<br />

2. The heat transfer to the workpiece is by conduction and convection takes place at workpiece top surface.<br />

3. Only a fraction discharge power is dissipated as heat into the workpiece.<br />

4. The protrusion height <strong>of</strong> all the grains is equal and remains constant throughout the operation.<br />

2.2 Thermal Modeling <strong>of</strong> ECSM<br />

The general transient three dimensional heat conduction equations within a homogeneous material without heat<br />

generation can be used to describe the temperature variation in the workpiece. Hence governing equation can be<br />

written as<br />

∂ ⎛ ∂T<br />

⎞ ∂ ⎛ ∂T<br />

⎞ ∂ ⎛ ∂T<br />

⎞ ∂T<br />

⎜ k ⎟ + ⎜ k ⎟ + ⎜ k ⎟ = ρC<br />

∂X<br />

∂X<br />

∂Y<br />

∂Y<br />

∂Z<br />

∂Z<br />

S<br />

∂t<br />

(1)<br />

⎝ ⎠ ⎝ ⎠ ⎝ ⎠<br />

In the present case the domain is considered as 3-D solid workpiece as shown in Fig. 2. Where, ρ is density<br />

(Kg/m 3 ), C S is a specific heat (J/Kg K), k is the thermal conductivity <strong>of</strong> the workpiece material (W/m K), t is the<br />

time in seconds. The workpiece is having length L, Width W and thickness T w. The required boundary<br />

conditions have been applied and simulated in the APDL.<br />

Figure.2 Thermal Model for ECSM<br />

2.2.1 Boundary Conditions<br />

Energy transfer to the workpiece as heat input serves as the thermal boundary condition on the top surface. The<br />

heat loss to the coolant on the top surface and four face <strong>of</strong> the workpiece is modeled using the convective<br />

boundary condition having convection coefficient hc, when t > 0. The bottom <strong>of</strong> the workpiece is assumed to be<br />

sufficiently far from the top surface and remains at its initial temperature throughout the process. The heat flux<br />

q wg supplied to the workpiece due to spark [4] is given by<br />

E ws U o V w d<br />

q ws =<br />

(2)<br />

Lc<br />

where E ws is energy partition fraction due to spark. V w is feed <strong>of</strong> the workpiece and U o is specific energy <strong>of</strong> the<br />

workpiece material. The parameters such as contact length, heat flux, energy partition, and specific spark energy,<br />

thermal properties <strong>of</strong> workpiece and depth <strong>of</strong> cut and convective heat transfer coefficient are important for<br />

determining temperature distribution in the workpiece.<br />

2.3 Thermal Modeling <strong>of</strong> ECSM process<br />

The thermal diffusion differential equation in cylindrical coordinate system governs the temperature field during<br />

the EDM process,<br />

∂T<br />

1 ∂ ∂T<br />

∂ ∂T<br />

ρ C s = ( k ) + ( k ) Where r and Z are cylindrical coordinate axes (3)<br />

∂t<br />

r ∂r<br />

∂r<br />

∂Z<br />

∂Z<br />

651


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure.3 Thermal model <strong>of</strong> EDM<br />

2.4 Boundary Conditions<br />

A small cylindrical portion <strong>of</strong> the workpiece around the spark is taken and the axis symmetric nature <strong>of</strong> the<br />

cylindrical portion is used in the modeling <strong>of</strong> domain (Fig. 3). Energy transferred to the workpiece as heat input<br />

serves as the thermal boundary condition on the top surface (г 1 ). The heat loss to the on the top surface is<br />

modeled using the convective boundary condition. The bottom surface (г 2 ) <strong>of</strong> the domain and circumferential<br />

surface (г 3 ) <strong>of</strong> the domain is at such distance that there is no heat transfer across them.<br />

The boundary condition is given by,<br />

⎧<br />

⎪<br />

⎨<br />

⎪<br />

⎩<br />

hc<br />

( T − T o ) for r > R<br />

∂T<br />

,<br />

k = q ws for r ≤ R,<br />

∂n<br />

0 for <strong>of</strong>ftime<br />

(4)<br />

∂T<br />

k = 0 on Γ Γ<br />

∂n<br />

2 3<br />

(5)<br />

Where q ws is quantity <strong>of</strong> heat flux entering in to the workpiece, given by (6) and R is the Spark radius in μm [5].<br />

q ws<br />

=<br />

4.45R ws U<br />

2<br />

πR<br />

I<br />

b<br />

( −4.5(<br />

r<br />

) 2 )<br />

e R<br />

If r ≤ R (6)<br />

0.43 0.44<br />

R = ( 2.04e<br />

− 3) I ton<br />

(7)<br />

Where h c is the convective heat transfer coefficient, T o is the room temperature and n is the normal to the<br />

boundary.<br />

3. Result and discussion<br />

The program for simulation <strong>of</strong> ECSM is developed in the ANSYS APDL programming tool. The program is<br />

solved in ANSYS SOLVER v10. The programs for temperature distribution due EDM has been developed<br />

separately and the results were superimposed to determine the total temperature rise due to ECSM. Many<br />

researchers [6-10] have taken the temperature independent property for the analysis <strong>of</strong> EDM, but during EDM,<br />

due to high heat input, temperature goes well beyond melting point near the spark. This makes the proper<br />

justification to consider the temperature dependent material property (Table. I) for the analysis.<br />

Table. I Temperature Dependent thermal properties<br />

S.no Temperature (K) k(W/mK) C p (J/KgK)<br />

1. 293.15 39.54 414.56<br />

2. 393.15 38.37 440.58<br />

3. 493.15 37.21 480.23<br />

4. 593.15 36.05 515.23<br />

5. 693.15 34.89 550.36<br />

6. 793.15 33.72 610.23<br />

7. 893.15 33.12 640.23<br />

The simulation <strong>of</strong> the surface grinding in ANSYS APDL was carried out in the workpiece having dimension<br />

<strong>20</strong>mm×15mm×5mm. The convective boundary condition simulates the cooling effect <strong>of</strong> dielectric (kerosene)<br />

652


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

with a convective coefficient <strong>of</strong> 10,000 W/m 2 K. The domain is discretized using 8 – noded brick element (Fig.<br />

4). In order to capture more information in the grinding zone, the mesh was made very fine. Convergence test<br />

revealed that the mesh <strong>of</strong> 7904 elements and 9477 nodes is adequate for the problem<br />

Figure 4 Discretized workpiece used in the simulation <strong>of</strong> surface grinding<br />

The small cylindrical domain is considered to have diameter 3 times the spark radius and height in such a way<br />

that there is no heat transfer from the bottom surface as shown in the Fig. 5. It is assumed the sparks are far away<br />

from each other and interaction <strong>of</strong> sparks in the process <strong>of</strong> determination <strong>of</strong> temperature in the EDM operation is<br />

neglected. The domain <strong>of</strong> EDM exhibits the axis symmetry so it has to be properly captured in the meshing.<br />

Convergence test revealed the mesh <strong>of</strong> 50700 elements and 54106 nodes are adequate to capture the symmetric<br />

nature <strong>of</strong> the domain<br />

Figure 5 Discretized cylindrical domain used for the simulation <strong>of</strong> EDM process<br />

(a)<br />

(b)<br />

Figure 6 3-D top surface temperature distribution in the grinding zone <strong>of</strong> the HSS workpiece due to (a) EDM<br />

only (b) ECSM<br />

Fig. 7 shows the top surface <strong>of</strong> the domain. Here the certain lines are taken to study the temperature distribution<br />

due to EDDG. The line AA is parallel to X–axis is at Z = 5.7 mm and the line BB is parallel to Z-axis is at X = 8<br />

mm. the Fig. 8 shows the depth distribution <strong>of</strong> temperature (at X = 11.5 mm, Z =5.6 mm) and it is observed that<br />

the high temperature gradient exist which primarily induces the thermal stress.<br />

653


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure7 Top surface <strong>of</strong> the workpiece<br />

3.1 Effect <strong>of</strong> Energy Partition (R ws )<br />

Figure 8 Depthwise temperature distribution over the HSS workpiece<br />

Fig. 11 shows the temperature distribution <strong>of</strong> workpiece top surface due to the ECSM process along the line BB.<br />

The prediction <strong>of</strong> temperature is governed by one <strong>of</strong> the important parameters namely, Energy Partition (R WS ).<br />

The same value <strong>of</strong> energy partition is used for EDM. Among tool and workpiece the one having lower value <strong>of</strong><br />

thermal diffusivity has a lower share <strong>of</strong> heat energy than the one having the higher value. Fig. 11 shows for<br />

higher value <strong>of</strong> energy partition, the temperature is more than the lesser value <strong>of</strong> energy partition.<br />

The random variation <strong>of</strong> temperature in the Fig. 11 is due to random occurrence <strong>of</strong> spark in EDM. The increase<br />

in temperature <strong>of</strong> the workpiece is mainly contributed by the EDM process which results in thermal s<strong>of</strong>tening <strong>of</strong><br />

the material and increase MRR through chemical reaction. The EDM involves in assisting the material removal<br />

while ECM action involves in the surface finishing.<br />

Figure 10 Top surface temperature distribution after different time due to ECSM along BB for E WS = 0.08<br />

654


3.2 Effect <strong>of</strong> Different Dielectric Fluid<br />

Proceedings <strong>of</strong> the National Conference on<br />

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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The effect <strong>of</strong> the use <strong>of</strong> different dielectric also affects the top surface temperature distribution <strong>of</strong> the workpiece.<br />

The change <strong>of</strong> dielectric results in change in breakdown voltage. The published machining handbook [9] were<br />

chosen for the present analysis .The two different values <strong>of</strong> dielectric, 30V, 40V and 50V were taken for the<br />

present study. Increase in breakdown voltage results in increase in top surface temperature since the more heat<br />

flux enters the workpiece compared to lesser breakdown voltage. Fig. 13 has shown the effect <strong>of</strong> breakdown<br />

voltage on top surface temperature distribution in workpiece.<br />

Figure 11 Top surface temperature along AA for different breakdown voltage<br />

Figure 12 Top surface temperature along AA for different breakdown voltage<br />

4. Conclusion<br />

The main objective <strong>of</strong> this present work is to simulate the ECSM process to determine the temperature<br />

distribution and thermal stress distribution induced in the workpiece. The simulation code is developed in APDL<br />

and the result presented here would be useful for the prediction <strong>of</strong> temperature distribution in the workpiece<br />

before going for an actual time consuming experimental procedure. Major contribution to the temperature<br />

distribution was by the EDM process. The result shows that the node which had more sparks was in high<br />

temperature than the other nodes with less number <strong>of</strong> sparks. The following points have been concluded for the<br />

present simulation work.<br />

1. EDM contributes primarily to the temperature distribution due to its high heat input.<br />

2. The EDM assist the ECM in material removal by thermally s<strong>of</strong>tening the material and result in<br />

increasing chemical reaction.<br />

3. High thermal gradient exist near the top surface which primarily contribute the thermal stress.<br />

5. References<br />

1. Mcgeough, J.A., <strong>19</strong>84. Principles <strong>of</strong> Electrochemical Machining. Chapman and Hall, London.<br />

2. Basak, I., Ghosh, A., <strong>19</strong>97. Mechanism <strong>of</strong> material removal in electrochemical discharge machining: a<br />

theoretical model and experimental verification. J. Mater. Process. Technol. 71, 350–359.<br />

655


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3. Bhattacharya, B., Doloi, B.N., Sorkel, S.K., <strong>19</strong>99. Experimental investigations into electrochemical<br />

discharge machining (ECDM) <strong>of</strong> non-conductive ceramic materials. J. Mater. Process. Technol. 95,<br />

145–154.<br />

4. Jain, V.K., <strong>20</strong>02. Advanced Machining Processes. Allied Publishers, New Delhi.<br />

5. Jain, V.K., Dixit, P.M., Pandey, P.M., <strong>19</strong>99. On the analysis <strong>of</strong> the electrochemical spark machining<br />

process. Int. J. Mach. Tool. Manuf. 39, 165–186.<br />

6. Withrich, R., Fascio, V., <strong>20</strong>05. Machining <strong>of</strong> non-conductive materials using electrochemical discharge<br />

phenomenon: an overview. Int. J. Mach. Tool Manuf. 45, 1095–1108.<br />

7. Singh, Y.P., Jain, V.K., Kumar, P., Agarwal, D.C., <strong>19</strong>96. Machining piezoelectric (PZT) ceramics using<br />

an electrochemical spark machining (ECSM) process. J. Mater. Process. Technol. 58, 24–31.<br />

8. S.N.Joshi, S.S.Pande, “Thermo-physical modeling <strong>of</strong> die-sinking EDM process” Journal <strong>of</strong><br />

Manufacturing Processes, 12, 45-56, <strong>20</strong>10<br />

9. Machiningdata Handbook,V2 Machiniability data centre,Mercut Research Associaates inc USA,<strong>19</strong>81.<br />

656


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

A DETAILED REVIEW OF THE CURRENT RESEARCH TRENDS IN<br />

ELECTRICAL DISCHARGE MACHINING (EDM)<br />

Sumit Ganguly<br />

Assistant Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering,Lingayas <strong>University</strong>, Faridabad, Nachauli, Jasana, Old<br />

Faridabad Road, Faridabad – 121002, Haryana, India; Email: sumitgang@rediffmail.com ,Mobile Phone No:<br />

9899677962, 9211891433<br />

Abstract - Electrical discharge machining (EDM) is a non-traditional concept <strong>of</strong> machining<br />

which has been widely used to produce dies and molds. It is also used for finishing parts for<br />

aerospace and automotive industry and surgical components Electrical discharge machining<br />

(EDM) is one <strong>of</strong> the earliest non-traditional machining processes. EDM process is based on<br />

thermoelectric energy between the work piece and an electrode. A pulse discharge occurs in a<br />

small gap between the work piece and the electrode and removes the unwanted material from<br />

the parent metal through melting and vaporising. The electrode and the work piece must have<br />

electrical conductivity in order to generate the spark.<br />

The detailed study presented in this paper is on current EDM research trends carried out by<br />

researchers on machining techniques viz. sinker EDM machining, dry EDM machining, wire<br />

EDM, EDM for small hole drilling and EDM in water and modeling techniques in predicting<br />

EDM performances. The areas are selected because <strong>of</strong> the novel techniques employed, the<br />

environmental aspect and effort towards validating and predicting EDM performance. Each<br />

topic will present the activities carried out by the researchers and the development <strong>of</strong> the area<br />

that brings it to the current trends.<br />

Keywords— sinker EDM, dry EDM machining, wire EDM, EDM in water, modeling techniques<br />

1. Introduction<br />

Electrical Discharge Machining (EDM) process involved removal <strong>of</strong> material by erosion. Series<br />

<strong>of</strong> persistent electrical discharges emerge between the tool and the work piece in dielectric fluid<br />

and remove the unwanted material. Metal erosion by spark discharges was first observed by Sir<br />

Joseph Priestly as early as 1768. In <strong>19</strong>43 two Russians B.R. and N.I Lazarenko discovered that<br />

precision machining can be achieved by EDM. Since then, exploration were done globally and<br />

locally to expand EDM potentials. It is an alternative machining method which is not defeated<br />

by the mechanical strength <strong>of</strong> materials. With the emerging <strong>of</strong> harder, tougher and stronger<br />

materials in manufacturing together with the needs <strong>of</strong> ultra-precision machining, EDM has been<br />

one <strong>of</strong> the important methods in machining. Basic EDM process consists <strong>of</strong> electrode, work<br />

piece materials, dielectric and the range <strong>of</strong> pulse rate, current and voltage. The functions <strong>of</strong> the<br />

dielectric are: transportation <strong>of</strong> removal particles, to increase the energy density in plasma<br />

channel, recondition <strong>of</strong> the dielectric strength and cooling <strong>of</strong> the electrode. Dielectric fluid is<br />

pumped through the arc gap to flush away the eroded particles between the work piece and the<br />

electrode. Most common dielectric fluids are mineral oil, kerosene, paraffin, distilled water and<br />

deionised water. Recent trends involve the use <strong>of</strong> clear and low viscosity fluids to make cleaning<br />

easier. After cycles <strong>of</strong> usage, dielectric performance will reduce and must be replaced. Hence<br />

this situation draws interest in investigating the consumption <strong>of</strong> dielectric in EDM process.<br />

Ideally, EDM can be seen as a series <strong>of</strong> breakdown and restoration <strong>of</strong> the liquid dielectric inbetween<br />

the electrodes. However, caution should be exerted in considering such a statement<br />

because it is an idealized model <strong>of</strong> the process, introduced to describe the fundamental ideas<br />

underlying the process. Yet, any practical application involves many aspects that may also need<br />

to be considered. For instance, the removal <strong>of</strong> the debris from the inter-electrode volume is<br />

likely to be always partial. Thus the electrical proprieties <strong>of</strong> the dielectric in the inter-electrodes<br />

volume can be different from their nominal values and can even vary with time. The interelectrode<br />

distance, <strong>of</strong>ten also referred to as spark-gap, is the end result <strong>of</strong> the control algorithms<br />

<strong>of</strong> the specific machine used. The control <strong>of</strong> such a distance appears logically to be central to this<br />

process. Also, not all <strong>of</strong> the current between the dielectric is <strong>of</strong> the ideal type described above:<br />

657


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

the spark-gap can be short-circuited by the debris. The control system <strong>of</strong> the electrode may fail<br />

to react quickly enough to prevent the two electrodes (tool and workpiece) from coming into<br />

contact, with a consequent short circuit. This is unwanted because a short circuit contributes to<br />

material removal differently from the ideal case. The flushing action can be inadequate to restore<br />

the insulating properties <strong>of</strong> the dielectric so that the current always happens in the point <strong>of</strong> the<br />

inter-electrode volume (this is referred to as arcing), with a consequent unwanted change <strong>of</strong><br />

shape (damage) <strong>of</strong> the tool-electrode and workpiece. Ultimately, a description <strong>of</strong> this process in<br />

a suitable way for the specific purpose at hand is what makes the EDM area such a rich field for<br />

further investigation and research.<br />

To obtain a specific geometry, the EDM tool is guided along the desired path very close to the<br />

work; ideally it should not touch the workpiece, although in reality this may happen due to the<br />

performance <strong>of</strong> the specific motion control in use. In this way, a large number <strong>of</strong> current<br />

discharges (colloquially also called sparks) happen, each contributing to the removal <strong>of</strong> material<br />

from both tool and workpiece, where small craters are formed. The size <strong>of</strong> the craters is a<br />

function <strong>of</strong> the technological parameters set for the specific job at hand. They can be with typical<br />

dimensions ranging from the nanoscale to some hundreds <strong>of</strong> micrometers in roughing<br />

conditions.<br />

A further strategy consists in using a set <strong>of</strong> electrodes with different sizes and shapes during the same EDM<br />

operation. This is <strong>of</strong>ten referred to as multiple electrode strategy, and is most common when the tool electrode<br />

replicates in negative the wanted shape and is advanced towards the blank along a single direction, usually the<br />

vertical direction (i.e. z-axis). This resembles the sink <strong>of</strong> the tool into the dielectric liquid in which the workpiece is<br />

immersed, so, not surprisingly, it is <strong>of</strong>ten referred to as die-sinking EDM (also called conventional EDM and ram<br />

EDM). The corresponding machines are <strong>of</strong>ten called sinker EDM. Usually, the electrodes <strong>of</strong> this type have quite<br />

complex forms. If the final geometry is obtained using a usually simple-shaped electrode which is moved along<br />

several directions and is possibly also subject to rotations, <strong>of</strong>ten the term EDM milling is used.<br />

2. Process<br />

In EDM, a potential difference is applied between the tool and workpiece. Both the tool and the<br />

work material are to be conductors <strong>of</strong> electricity. The tool and the work material are immersed in<br />

a dielectric medium. Generally kerosene or deionised water is used as the dielectric medium. A<br />

gap is maintained between the tool and the workpiece. Depending upon the applied potential<br />

difference and the gap between the tool and workpiece, an electric field would be established.<br />

Generally the tool is connected to the negative terminal <strong>of</strong> the generator and the workpiece is<br />

connected to positive terminal. As the electric field is established between the tool and the job,<br />

the free electrons on the tool are subjected to electrostatic forces. If the work function or the<br />

bonding energy <strong>of</strong> the electrons is less, electrons would be emitted from the tool (assuming it to<br />

be connected to the negative terminal). Such emission <strong>of</strong> electrons are called or termed as cold<br />

emission. The “cold emitted” electrons are then accelerated towards the job through the<br />

dielectric medium. As they gain velocity and energy, and start moving towards the job, there<br />

would be collisions between the electrons and dielectric molecules. Such collision may result in<br />

ionization <strong>of</strong> the dielectric molecule depending upon the work function or ionization energy <strong>of</strong><br />

the dielectric molecule and the energy <strong>of</strong> the electron. Thus, as the electrons get accelerated,<br />

more positive ions and electrons would get generated due to collisions. This cyclic process<br />

would increase the concentration <strong>of</strong> electrons and ions in the dielectric medium between the tool<br />

and the job at the spark gap. The concentration would be so high that the matter existing in that<br />

channel could be characterized as “plasma”. The electrical resistance <strong>of</strong> such plasma channel<br />

would be very less. Thus all <strong>of</strong> a sudden, a large number <strong>of</strong> electrons will flow from the tool to<br />

the job and ions from the job to the tool. This is called avalanche motion <strong>of</strong> electrons. Such<br />

movement <strong>of</strong> electrons and ions can be visually seen as a spark. Thus the electrical energy is<br />

dissipated as the thermal energy <strong>of</strong> the spark.<br />

The high speed electrons then impinge on the job and ions on the tool. The kinetic energy <strong>of</strong> the<br />

electrons and ions on impact with the surface <strong>of</strong> the job and tool respectively would be<br />

658


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

converted into thermal energy or heat flux. Such intense localized heat flux leads to extreme<br />

instantaneous confined rise in temperature which would be in excess <strong>of</strong> 10,000 o C. Such<br />

localized extreme rise in temperature leads to material removal. Material removal occurs due to<br />

instant vaporization <strong>of</strong> the material as well as due to melting. The molten metal is not removed<br />

completely but only partially. As the potential difference is withdrawn as shown in Fig. 1, the<br />

plasma channel is no longer sustained. As the plasma channel collapse, it generates pressure or<br />

shock waves, which evacuates the molten material forming a crater <strong>of</strong> removed material around<br />

the site <strong>of</strong> the spark.<br />

Thus to summarize, the material removal in EDM mainly occurs due to formation <strong>of</strong> shock<br />

waves as the plasma channel collapse owing to discontinuation <strong>of</strong> applied potential difference.<br />

Generally the work piece is made positive and the tool negative. Hence, the electrons strike the<br />

job leading to crater formation due to high temperature and melting and material removal.<br />

Similarly, the positive ions impinge on the tool leading to tool wear. In EDM, the generator is<br />

used to apply voltage pulses between the tool and the job. A constant voltage is not applied.<br />

Only sparking is desired in EDM rather than arcing. Arcing leads to localised material removal<br />

at a particular point whereas sparks get distributed all over the tool surface leading to uniformly<br />

distributed material removal under the tool.<br />

Fig.1 Schematic representation <strong>of</strong> the basic working principle <strong>of</strong> EDM process.<br />

3. Process parameters<br />

This section discusses the process parameters <strong>of</strong> EDM. This section focuses on the effects <strong>of</strong><br />

process parameters such as electrical (pulse waveform <strong>of</strong> a controlled pulse generator) and nonelectrical<br />

parameters on the various performance measures.<br />

3.1 Electrical Parameters<br />

Pulse Duration (Ton): It is the duration <strong>of</strong> time measured in micro seconds. During this time<br />

period the current is allowed to through the electrode towards the work material within a short<br />

gap known as spark gap. Metal removal is directly proportional to the amount <strong>of</strong> energy applied<br />

during the on time period. Pulse duration is also known as pulse on time and the sparks are<br />

generated at certain frequency. Material removal rate depends on longer or shorter pulse on time<br />

period. Longer pulse duration improves removal rate <strong>of</strong> debris from the machined area which<br />

also effects on the wear behavior <strong>of</strong> electrode. As in EDM process erosion takes place in the<br />

form <strong>of</strong> melting and vaporization <strong>of</strong> both the tool and work material at the same time period, so<br />

with longer pulse duration more material has to be melt and vaporize. The resulting crater<br />

produced will be broader as comparison to the shorter pulse on time. But, in some experimental<br />

research work it has been proved that optimal pulse duration gives higher performance<br />

measures. It conclude all that MRR can not be increased by increasing the Pulse on time, a<br />

suitable combination <strong>of</strong> peak current is also needed for increasing rate <strong>of</strong> removing unwanted<br />

material from the work piece. At constant current and constant duty factor, the MRR is<br />

decreased with increase in pulse on time. This is due to the reason because <strong>of</strong> short pulses cause<br />

less vaporization, where as long pulse duration causes the plasma channel to expand rapidly.<br />

659


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

This expansion <strong>of</strong> plasma channel cause less energy density on the work material, which is not<br />

sufficient to melt and vaporize the work material. It was also concluded by the researchers that<br />

with increase <strong>of</strong> pulse duration, surface roughness decreased, hardness <strong>of</strong> work material, crack<br />

length, crack width and the thickness <strong>of</strong> recast layer increased.<br />

Pulse Interval (T<strong>of</strong>f):<br />

It is the waiting interval time period during two pulses on time periods. This parameter is to<br />

affect the speed and the stability <strong>of</strong> the cut. If the <strong>of</strong>f-time is too short, it improves MRR but it<br />

will because more sparks to be unstable in the machining zone .Kansal et al. result out that<br />

increase in pulse interval time decreases the MRR. Saha et al. reported out that for small value <strong>of</strong><br />

pulse interval time period, the MRR was low, but with further increase MRR increases. MRR<br />

was dropped slowly with increase in pulse interval time. This is due to very short pulse interval<br />

the probability <strong>of</strong> arcing is larger because dielectric in the gap does not recover its dielectric<br />

strength. O.A. Abu Zeid investigated the role <strong>of</strong> voltage, pulse <strong>of</strong>f time in the electro discharge<br />

machined AISI T1 high speed steel. The researcher concluded that the MRR is not so much<br />

sensitive to pulse interval time changes at low pulse on time in finish machining.<br />

Electrode gap (spark gap):<br />

It is the distance between the electrode and the part during the process <strong>of</strong> EDM. An electromechanical<br />

and hydraulic systems are used to respond to average gap voltage. To obtain good<br />

performance and gap stability a suitable gap should be maintained. For the reaction speed, it<br />

must obtain a high speed so that it can respond to short circuits or even open gap circuits. Gap<br />

width is not measured directly, but can be inferred from the average gap voltage.<br />

Fig.2 Pulse wave form <strong>of</strong> pulse generator<br />

3.2 Non Electrical Parameters<br />

Non-electrical parameters such as the Rotational movement <strong>of</strong> electrode, flushing <strong>of</strong> dielectric<br />

fluid and aspect ratio ( tool shape) together play a significant role in delivering optimal<br />

performance measures. This section discusses the effects <strong>of</strong> non-electrical parameters on the<br />

various performance measures.<br />

Rotation <strong>of</strong> Tool Electrode:<br />

It is the rotational effect <strong>of</strong> cylindrical (pin shaped) or disc shaped electrode tool measured in<br />

revolution/minute. The rotational movement <strong>of</strong> electrode is normal to the work surface and with<br />

increasing the speed, a centrifugal force is generated causes more debris to remove faster from<br />

the machining zone. According to Mohan et al., the centrifugal force generated throws a layer <strong>of</strong><br />

dielectric in to the machining gap, induces an atmosphere for better surface finish, prevent<br />

arching and improves MRR. Soni and Chakraverti compared the various performance measures<br />

<strong>of</strong> rotating electrode with the stationary electrode. The results concluded an improvement in<br />

660


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

MRR due to the better flushing action and sparking efficiency with little tool wear but the<br />

surface finish was improved.<br />

Injection flushing:<br />

Flushing removes eroded particles from the gap for efficient cutting and improved surface finish<br />

<strong>of</strong> machined material. Flushing also enables fresh dielectric oil flow into the gap and cools both<br />

the electrode and the work piece. Basic characteristics required for dielectric used in EDM are<br />

high dielectric strength and quick recovery after breakdown. There variations <strong>of</strong> EDM processes<br />

can be classified according to the type <strong>of</strong> dielectric fluid used. Most dielectric media are<br />

hydrocarbon compounds and water. The hydrocarbon compounds are in the form <strong>of</strong> refined oil;<br />

better known as kerosene. While the fluid properties are essential, the correct fluid circulating<br />

methodology is also important. The dielectric fluid not only forms a dielectric barrier for the<br />

spark between the work piece and the electrode but also cools the eroded particles between the<br />

work piece and the electrode. The pressurized fluid flushes out the eroded gap particles and<br />

remove the debris from the fluid medium by causing the fluid to pass through a filter system.<br />

During the investigation <strong>of</strong> EDM <strong>of</strong> Ti 6Al 4V, Chen et al. found that the MRR was greater and<br />

the relative EWR is lower, when using 16 distilled water as dielectric solution.<br />

Tool Geometry:<br />

Tool geometry is concerned with the shape <strong>of</strong> the tool electrodes.ie. Square, rectangle,<br />

cylindrical, circular.etc. The ratio <strong>of</strong> length /diameter <strong>of</strong> any shaped feature <strong>of</strong> material. In case<br />

<strong>of</strong> rotating disk electrode the ratio becomes thickness/diameter. Murali et al used graphite foil<br />

for straight grooving operation instead <strong>of</strong> pin shaped electrode. An aspect ratio <strong>of</strong> 2.3 was<br />

achieved by using FAST technique (Foil as tool electrode) which was improved to 8 by<br />

implementing GAME (Gravity assisted Micro EDM). Singh et al. uses square and rectangular<br />

shaped electrodes having aspect ratio <strong>of</strong> 1.0 and 0.6 for machining 6061Al/Al2O3P composite .It<br />

concluded that shape <strong>of</strong> the electrode effects EWR. The tool having less aspect ratio gave higher<br />

value <strong>of</strong> EWR. Thus with increasing the size <strong>of</strong> electrode more good performance <strong>of</strong> ED<br />

Machining takes place.<br />

Tool Material (Electrode):<br />

Engineering materials having higher thermal conductivity and melting point are used as a tool<br />

material for EDM process <strong>of</strong> machining . Copper, graphite, copper-tungsten, silver tungsten,<br />

copper graphite and brass are used as a tool material (electrode) in EDM. They all have good<br />

wear characteristics, better conductivity, and better sparking conditions for machining. Copper<br />

with 5% tellurium, added for better machining properties. Tungsten resist wear better than<br />

copper and brass .Brass ensures stable sparking conditions and is normally used for specialized<br />

applications such as drilling <strong>of</strong> small holes where the high electrode wear is acceptable (Metals<br />

Handbook, <strong>19</strong>89). The factors that effect selection <strong>of</strong> electrode material include metal removal<br />

rate, wear resistance, desired surface finish, cost <strong>of</strong> electrode material manufacture and material<br />

and characteristics <strong>of</strong> work material to be machined.<br />

4. Characteristics <strong>of</strong> EDM<br />

(a) The process can be used to machine any work material if it is electrically conductive<br />

(b) Material removal depends on mainly thermal properties <strong>of</strong> the work material rather than its<br />

strength, hardness etc<br />

(c) In EDM there is a physical tool and geometry <strong>of</strong> the tool is the positive impression <strong>of</strong> the<br />

hole or geometric feature machined<br />

(d) The tool has to be electrically conductive as well. The tool wear once again depends on the<br />

thermal properties <strong>of</strong> the tool material<br />

(e) Though the local temperature rise is rather high, still due to very small pulse on time, there is<br />

not enough time for the heat to diffuse and thus almost no increase in bulk temperature takes<br />

place. Thus the heat affected zone is limited to 2 – 4 μm <strong>of</strong> the spark crater<br />

661


5. Dielectric<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

In EDM, as has been discussed earlier, material removal mainly occurs due to thermal<br />

evaporation and melting. As thermal processing is required to be carried out in absence <strong>of</strong><br />

oxygen so that the process can be controlled and oxidation avoided. Oxidation <strong>of</strong>ten leads to<br />

poor surface conductivity (electrical) <strong>of</strong> the work piece hindering further machining. Hence,<br />

dielectric fluid should provide an oxygen free machining environment. Further it should have<br />

enough strong dielectric resistance so that it does not breakdown electrically too easily but at the<br />

same time ionize when electrons collide with its molecule. Moreover, during sparking it should<br />

be thermally resistant as well.<br />

Generally kerosene and de-ionized water is used as dielectric fluid in EDM. Tap water cannot be<br />

used as it ionizes too early and thus breakdown due to presence <strong>of</strong> salts as impurities occur.<br />

Dielectric medium is generally flushed around the spark zone. It is also applied through the tool<br />

to achieve efficient removal <strong>of</strong> molten material.<br />

6. Electrode material<br />

Electrode material should be such that it would not undergo much tool wear when it is impinged<br />

by positive ions. Thus the localized temperature rise has to be less by tailoring or properly<br />

choosing its properties or even when temperature increases, there would be less melting. Further,<br />

the tool should be easily workable as intricate shaped geometric features are machined in EDM.<br />

Thus the basic characteristics <strong>of</strong> electrode materials are:<br />

• High electrical conductivity – electrons are cold emitted more easily and there is less bulk<br />

electrical heating<br />

• High thermal conductivity – for the same heat load, the local temperature rise would be less<br />

due to faster heat conducted to the bulk <strong>of</strong> the tool and thus less tool wear<br />

• Higher density – for the same heat load and same tool wear by weight there would be less<br />

volume removal or tool wear and thus less dimensional loss or inaccuracy<br />

• High melting point – high melting point leads to less tool wear due to less tool material melting<br />

for the same heat load<br />

• Easy manufacturability<br />

• Cost – cheap<br />

The followings are the different electrode materials which are used commonly in the industry:<br />

• Graphite<br />

• Electrolytic oxygen free copper<br />

• Tellurium copper – 99% Cu + 0.5% tellurium<br />

• Brass<br />

7. Types oF EDM<br />

7.1 Sinker EDM<br />

Sinker EDM, also called cavity type EDM or volume EDM, consists <strong>of</strong> an electrode and<br />

workpiece submerged in an insulating liquid such as, more typically, oil or, less frequently, other<br />

dielectric fluids. The electrode and workpiece are connected to a suitable power supply. The<br />

power supply generates an electrical potential between the two parts. As the electrode<br />

approaches the workpiece, dielectric breakdown occurs in the fluid, forming a plasma channel,<br />

and a small spark jumps.<br />

These sparks usually strike one at a time because it is very unlikely that different locations in the<br />

inter-electrode space have the identical local electrical characteristics which would enable a<br />

662


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

spark to occur simultaneously in all such locations. These sparks happen in huge numbers at<br />

seemingly random locations between the electrode and the workpiece. As the base metal is<br />

eroded, and the spark gap subsequently increased, the electrode is lowered automatically by the<br />

machine so that the process can continue uninterrupted. Several hundred thousand sparks occur<br />

per second, with the actual duty cycle carefully controlled by the setup parameters. These<br />

controlling cycles are sometimes known as "on time" and "<strong>of</strong>f time", which are more formally<br />

defined in the literature.<br />

The on time setting determines the length or duration <strong>of</strong> the spark. Hence, a longer on time<br />

produces a deeper cavity for that spark and all subsequent sparks for that cycle, creating a<br />

rougher finish on the workpiece. The reverse is true for a shorter on time. Off time is the period<br />

<strong>of</strong> time that one spark is replaced by another. A longer <strong>of</strong>f time, for example, allows the flushing<br />

<strong>of</strong> dielectric fluid through a nozzle to clean out the eroded debris, thereby avoiding a short<br />

circuit. These settings can be maintained in micro seconds. The typical part geometry is a<br />

complex 3D shape, <strong>of</strong>ten with small or odd shaped angles. Vertical, orbital, vectorial,<br />

directional, helical, conical, rotational, spin and indexing machining cycles are also used.<br />

7.2 Wire EDM<br />

In wire electrical discharge machining (WEDM) a thin single-strand metal wire, usually brass,<br />

is fed through the workpiece, submerged in a tank <strong>of</strong> dielectric fluid, typically deionized water.<br />

Wire-cut EDM is typically used to cut plates as thick as 300mm and to make punches, tools, and<br />

dies from hard metals that are difficult to machine with other methods.<br />

The wire, which is constantly fed from a spool, is held between upper and lower diamond<br />

guides. The guides, usually CNC-controlled, move in the x–y plane. On most machines, the<br />

upper guide can also move independently in the z–u–v axis, giving rise to the ability to cut<br />

tapered and transitioning shapes (circle on the bottom square at the top for example). The upper<br />

guide can control axis movements in x–y–u–v–i–j–k–l–. This allows the wire-cut EDM to be<br />

programmed to cut very intricate and delicate shapes.<br />

The upper and lower diamond guides are usually accurate to 0.004 mm, and can have a cutting<br />

path or kerf as small as 0.021 mm using Ø 0.02 mm wire, though the average cutting kerf that<br />

achieves the best economic cost and machining time is 0.335 mm using Ø 0.25 brass wire. The<br />

reason that the cutting width is greater than the width <strong>of</strong> the wire is because sparking occurs<br />

from the sides <strong>of</strong> the wire to the work piece, causing erosion. This "overcut" is necessary, for<br />

many applications it is adequately predictable and therefore can be compensated for (for instance<br />

in micro-EDM this is not <strong>of</strong>ten the case). Spools <strong>of</strong> wire are long—an 8 kg spool <strong>of</strong> 0.25 mm<br />

wire is just over <strong>19</strong> kilometers in length. Wire diameter can be as small as <strong>20</strong> micrometres and<br />

the geometry precision is not far from +/- 1 micrometre.<br />

The wire-cut process uses water as its dielectric fluid, controlling its resistivity and other<br />

electrical properties with filters and de-ionizer units. The water flushes the cut debris away from<br />

the cutting zone. Flushing is an important factor in determining the maximum feed rate for a<br />

given material thickness.<br />

7.3 EDM With Water<br />

F.N. Leao and I.R. Pashby [15] published a review paper on dielectric fluid which is safe for the<br />

environment. Deionized/distilled water is having the ability to be used as dielectric and can<br />

achieve higher MRR in several condition even though hydrocarbon oil is proven to be more<br />

competent. Norliana Mohd Abbas et al. [11] revealed the advantages <strong>of</strong> machining with water.<br />

Information is presented in chronological order according to the year <strong>of</strong> published manuscript.<br />

Some <strong>of</strong> the benefits are 1) promote high MRR and low TWR, 2) harmless machining<br />

operations, 3) cost effective, 4) less microcracks and 5) no crack breeding.<br />

663


7.4 Dry EDM<br />

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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Dry machining was introduced by M. Kunieda et al. where by supplying gas into gap between<br />

the electrode and work piece. It resulted to repeated rate <strong>of</strong> discharge happened thus enhance the<br />

MRR. MRR is six times greater and TWR only one-third than machining in oil. Some other<br />

advantages are low residual stress and no need <strong>of</strong> working basin, fluid tank and fluid circulation<br />

system. Development on dry EDM research can be obtained from Norliana Mohd Abbas et al.<br />

where until <strong>20</strong>05 hybrid activity viz. combination dry EDM with ultrasonic vibration has taken<br />

place.<br />

7.5 Small Hole EDM<br />

Small Hole EDM drilling uses the same spark erosion principle as Sinker or Ram EDM. Small<br />

Hole EDM drilling is ideal for putting ejector holes in hardened punches, coolant holes in<br />

cutting tools, vent holes in molds, and start holes for Wire EDM. Small Hole EDM machines use<br />

the EDM process to blast through hardened materials that cannot be conventionally machined.<br />

Small Hole EDM machines ideally complement our Wire EDM machines with the ability to<br />

quickly blast Wire EDM start holes in our work pieces for minimal material preparation times,<br />

which gives the fastest turnarounds possible to our customers. Small Hole EDM Diameters<br />

range from .155mm to 3.0mm. Part Heights up to 12” can be Small Hole EDM Drilled.<br />

7.6 Advantages <strong>of</strong> EDM<br />

• Complex shapes that would otherwise be difficult to produce with conventional cutting tools<br />

• Extremely hard material to very close tolerances<br />

• Very small work pieces where conventional cutting tools may damage the part from excess cutting tool<br />

pressure.<br />

• There is no direct contact between tool and work piece. Therefore delicate sections and weak materials can<br />

be machined without any distortion.<br />

• A good surface finish can be obtained.<br />

• Very fine holes can be easily drilled.<br />

7.7 Disadvantages <strong>of</strong> EDM<br />

• The slow rate <strong>of</strong> material removal.<br />

• The additional time and cost used for creating electrodes for ram/sinker EDM.<br />

• Reproducing sharp corners on the workpiece is difficult due to electrode wear.<br />

• Specific power consumption is very high.<br />

• Power consumption is high.<br />

• "Overcut" is formed.<br />

• Excessive tool wear occurs during machining.<br />

• Electrically non-conductive materials can be machined only with specific set-up <strong>of</strong> the process<br />

8. Hybrid EDM Processes<br />

Hybrid machining process in EDM make use <strong>of</strong> the combined advantages and to reduce some negative effects the<br />

combined processes produce better performance as compared to individual process machining. In EDM process the<br />

electrical energy is converted to thermal energy, the combined effect <strong>of</strong> powder suspension and ultrasonic motion <strong>of</strong><br />

tool or work piece as been reported in this section.<br />

8.1 Powder mixed EDM (PMEDM)<br />

EDM process in pure kerosene shows instability resulting to the arcing effect. In order to improve the machining<br />

efficiency, the addition <strong>of</strong> abrasives and metallic powders is done to dielectric fluid. Erden et al. research out the<br />

effect <strong>of</strong> suspended powder particles (Al, Cu, Fe, and carbon) on the mach inability <strong>of</strong> mild steel. It was observed<br />

664


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

that the added powder increases the breakdown characteristics <strong>of</strong> the dielectric fluid, and the machining rate<br />

increases with an increase in the concentration <strong>of</strong> the added powder. It was also observed that the machining<br />

becomes Unstable and difficult at an excessive powder concentration due to the occurrence <strong>of</strong> short-circuiting.<br />

Jeswani et al. carried out the research by the addition <strong>of</strong> fine graphite powder into kerosene oil on the machining <strong>of</strong><br />

tool steels. It was resulted out that the addition <strong>of</strong> 4 g/l <strong>of</strong> graphite powder increases the interspace for electric<br />

discharge initiation and lowered the breakdown voltage. Narumiya et al. studied the addition aluminum and graphite<br />

powders in dielectric fluid which results in better surface finish than the silicon powder. The best results are obtained<br />

for aluminum and graphite powder particles having diameters less than 15 μm and concentration ranges from 2 to 15<br />

g/l.<br />

8.2 Ultrasonic Assisted EDM (USEDM)<br />

The hybrid effect ultrasonic vibration <strong>of</strong> the electrode with EDM has been undertaken since mid <strong>19</strong>80s. Ultrasonic is<br />

concerned with the vibratory wave <strong>of</strong> frequency above 16 Kc/s. Ultrasonic machining combined with Electrical<br />

discharge machining can improve material removal rate as high as possible on account <strong>of</strong> decreasing surface finish.<br />

It can be used to machine high strength materials i.e. composites and super alloys. In USEDM process the abrasive<br />

slurry is replaced by suitable dielectric fluid (kerosene, distilled water,). The Ultrasonic vibration <strong>of</strong> tool or work<br />

piece in combination with electrical discharges produced by the electrode removes material effectively. The motion<br />

<strong>of</strong> direction <strong>of</strong> tool is generally normal to the work surface. The vibrating movement <strong>of</strong> the tool electrode or the work<br />

piece improves the slurry circulation and the pumping action, by pushing the debris away and sucking new fresh<br />

dielectric and which provides ideal condition for discharges, their efficiency and gives higher removal rate.<br />

8.3 Tool Vibration in EDM<br />

Murti and Philip added that with the combination <strong>of</strong> ultrasonic vibration in EDM the MRR and surface finish<br />

improved significantly and the tool wear rate increased. Zhixin et al. has produced an ultrasonic vibration pulse<br />

electro-discharge machining (UVPEDM) to produce holes in ceramics material. High material removal rate (MRR)<br />

was confirmed during the experimental work. Ogawa et al. reported out that the depth <strong>of</strong> micro holes by the<br />

combined effect <strong>of</strong> EDM with ultrasonic vibration becomes almost two times as that without ultrasonic vibration and<br />

machining rate was increased. Yan et al. result out that with combined effect <strong>of</strong> micro electrical discharge machining<br />

(MEDM) and micro ultrasonic vibration machining (MUSM) , the diameter variation between the entrance and exit<br />

(DVEE) could obtained about 2 mm in micro holes with diameters <strong>of</strong> about 150 mm and depth <strong>of</strong> 500 mm.<br />

8.4 Work piece Vibration in EDM<br />

Egashira et al. adopted to vibrate the work piece during machining. Micro holes as small as 5 m in diameter in quartz<br />

glass and silicon was machined by EDM with combined effect vibration. In the machining range, high tool wear<br />

occurs and sintered diamond tool was used to make machining effective. Prihandana et al. work out the effect <strong>of</strong><br />

vibratory work piece. It was result out that work piece vibration increases the flushing effect and high amplitude<br />

combined with high frequency increase the MRR. Till less research work has been reported with work piece<br />

vibratory motion by EDM process.<br />

Fig.3 Schematic diagram <strong>of</strong> PMEDM<br />

665


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig.4 Schematic diagram <strong>of</strong> USEDM<br />

9. EDM Research<br />

Electrical discharge machining is one <strong>of</strong> the pr<strong>of</strong>itable machining processes used for accurate and high precision<br />

geometry <strong>of</strong> the work piece. EDM can become more reliable by doing the research on performances to be obtained<br />

by it. Some <strong>of</strong> the research areas in EDM are shown in Fig.5.<br />

Fig.5 Classification <strong>of</strong> EDM research<br />

Throughout the paper references have been taken <strong>of</strong> several researchers in different areas <strong>of</strong><br />

EDM research whose study has been published in different proceedings <strong>of</strong> conferences or in<br />

journals till current times. Their findings have been published in various papers as mentioned in<br />

the references and have contributed enormously to the development <strong>of</strong> EDM. A few more<br />

current research work are mentioned below.<br />

STarng et al. formulated a neural network model and simulated annealing algorithm in order to<br />

predict and optimize the surface roughness and cutting velocity <strong>of</strong> the WEDM process when<br />

machining <strong>of</strong> SUS-304 stainless steel materials. T.A. Spedding and Z.Q.Wang attempted to<br />

model the cutting speed and surface roughness <strong>of</strong> WEDM process through the response-surface<br />

methodology and artificial neural networks (ANNs) and have found that the model accuracy <strong>of</strong><br />

both the approaches were better. Lok et al. presented the finding <strong>of</strong> processing two advanced<br />

666


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

materials Sialon and Al2O3-TiC by using WEDM. The author has taken MRR and surface finish<br />

as output parameters. Ghoreishi and Atkinson compared the effects <strong>of</strong> high and low frequency forced axial<br />

vibration <strong>of</strong> the electrode, rotation <strong>of</strong> the electrode and combinations <strong>of</strong> the methods in respect <strong>of</strong> MRR, tool wear<br />

ratio (TWR) and surface quality in EDM die sinking process. They concluded that vibro-rotary increases MRR by up<br />

to 35% compared with vibration EDM and by up to 100% compared with rotary EDM in semi finishing.<br />

10. References<br />

[1] J.A. McGeough, <strong>19</strong>98, Advanced Methods <strong>of</strong> Machining. London: Chapman and Hall.<br />

[2] M. Kunieda, B. Lauwers, K.P. rajurkar, B.M Schumacher, <strong>20</strong>05, Advancing EDM through Fundamental Insight<br />

into the Process, CIRP Annals -Manufacturing <strong>Technology</strong>, vol. 54 (2), pg. 64-87.<br />

[3] Norliana Mohd. Abbas, Darius G. Solomon, Md. Fuad Bahari, <strong>20</strong>06, EDM: Global Techniques and Local<br />

Scenario, 1st International Conference & 7 th AUN/SEED-Net Fieldwise Seminar on Manufacturing and Material<br />

Processing (ICMM<strong>20</strong>06), Kuala Lumpur, 14-15 March <strong>20</strong>06, pg 71-76.<br />

[4] W. Rehbein, H.P. Schulze, K. Mecke, G. Wollenberg, M. Storr, <strong>20</strong>04, Influence <strong>of</strong> Selected Groups <strong>of</strong> Additives<br />

on Breakdown in EDM Sinking, Journal <strong>of</strong> Materials Processing <strong>Technology</strong>, vol. 149, pp. 58–64.<br />

[5] Serope Kalpakjian, Steven Schmid, <strong>20</strong>06, Manufacturing Engineering and <strong>Technology</strong>, Fifth Edition, Prentice<br />

Hall, Singapore.<br />

[6] Federation <strong>of</strong> Malaysian Manufacturer [www.fmm.org.my/retrieved on 25 January <strong>20</strong>10]<br />

[7] Li Li, Y. S. Wong, J.Y.H. Fuh, L. Lu, <strong>20</strong>01, EDM Performance <strong>of</strong> TiC Copper-based Sintered Electrodes,<br />

Materials and Design, vol. 22, pp. 669-678.<br />

[8] Shankar Singh, S. Maheshwari, P.C. Pandey, <strong>20</strong>04, Some Investigations into the Electric Discharge Machining <strong>of</strong><br />

Hardened Tool Steel using Different Electrode Materials, Journal <strong>of</strong> Materials Processing <strong>Technology</strong>, vol. 149, pp.<br />

272–277.<br />

[9] Marin Gostimirovic, Pavel Kovac, Milenko Sekulic, Branko Skoric, <strong>20</strong>12, Influence <strong>of</strong> Discharge Energy<br />

Characteristics in EDM, Journal <strong>of</strong> Mechanical <strong>Science</strong> and <strong>Technology</strong>, vol. 26 (1),pg 173-179.<br />

[10] Sanjeev Kumar and Uma Batra, <strong>20</strong>12, Surface Modification <strong>of</strong> Die Steel Materials by EDM Method using<br />

Tungsten Powder-mixed Dielectric, Journal <strong>of</strong> Manufacturing Processes, vol. 14 (1),pg 35-40.<br />

[11] Norliana Mohd. Abbas, Darius G. Solomon, Md. Fuad Bahari, <strong>20</strong>07, A Review on Current Research Trends in<br />

Electrical Discharge Machining (EDM), International Journal <strong>of</strong> Machine Tools and Manufacture, vol. 47 (7-8), pg<br />

1214-1228<br />

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[12] Norliana Mohd. Abbas, Darius G. Solomon, Md. Fuad Bahari, <strong>20</strong>06, Additives in EDM Dielectric, Regional<br />

Postgraduate Conference on Engineering and <strong>Science</strong> (RPCES <strong>20</strong>06), pg 343-348.<br />

[13] M. Kunieda, S. furuoya, N. Taniguchi, <strong>19</strong>91, Improvement <strong>of</strong> EDM Efficiency by Supplying Oxygen gas into<br />

Gap, CIRP Annals – Manufacturing <strong>Technology</strong>, vol. 40, pg. 215-218.<br />

[14] Z.B. Yu, T. Jun, K. Masanori, <strong>20</strong>04, Dry Electrical Discharge Machining <strong>of</strong> Cemented Carbide, Journal <strong>of</strong><br />

Materials Processing <strong>Technology</strong>, volume 149, pg. 353-357.<br />

[15] Y. Zhanbo, J. Takahashi, N. Nakajima, S. Sano, K. Karato, M. Kunieda, Feasibility <strong>of</strong> 3-D surface machining<br />

by dry EDM<br />

[16] Singh, S.; Kansal, H.K.; Kumar, P. (<strong>20</strong>05): Parametric optimization <strong>of</strong> powder mixed Electrical discharge<br />

machining by response surface methodology, Journal <strong>of</strong> Materials Processing <strong>Technology</strong>, 169, 3, pp. 427-436.<br />

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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[17] Mohan, B.; Rajadurai, A.; Satyanarayana, K.G. (<strong>20</strong>04): Electric discharge machining <strong>of</strong> Al–Sic metal matrix<br />

composites using rotary tube electrode”, Journal <strong>of</strong> Materials Processing <strong>Technology</strong>, 153–154, pp.978–985.<br />

[18] Krishna Mohan Rao, G.; Satyanarayana, S.; Praveen, M.(<strong>20</strong>08):Influence <strong>of</strong> machining parameters on electric<br />

discharge machining <strong>of</strong> maraging steels-An experimental investigation, Proceeding <strong>of</strong> the world congress on Eng.,<br />

Vol. II.<br />

[<strong>19</strong>] Kansal,H.K.; Singh,S.; Kumar,P.(<strong>20</strong>07):Effect <strong>of</strong> Silicon Powder Mixed EDM on Machining Rate <strong>of</strong> AISI D2<br />

Die Steel, Journal <strong>of</strong> Manufacturing Processes, Volume9, No.1, pp.13-22.<br />

[<strong>20</strong>] Saha, S.K.; Chaudhary, S.K. (<strong>20</strong>09): Experimental investigation and empirical modeling <strong>of</strong> the dry electrical<br />

discharge machining process, International Journal <strong>of</strong> machine tools and manufacturing, vol.49, 297-308.<br />

[21] Abu Zied,O.A.(<strong>19</strong>96): The role <strong>of</strong> voltage pulse <strong>of</strong>f time in the electro discharge machined AISI T1 high speed<br />

steel, Journal <strong>of</strong> Material process <strong>Technology</strong>,61,pp.287-291.<br />

[22] Crookall, J.R.; Heuvelman, C.J. (<strong>19</strong>71): Electro-discharge machining-the state <strong>of</strong> the art”, Annual <strong>of</strong> the CIRP,<br />

<strong>20</strong>, pp.113-1<strong>20</strong>.<br />

[23] Soni,J.S.; Chakraverti,G.(<strong>19</strong>97):Performance evaluation <strong>of</strong> rotary EDM by experimental design technique,<br />

Defense <strong>Science</strong> journal, Vol. 47, No.1, pp. 65-73.<br />

[24] Wong, Y.S.; Lim, L.C.; Lee, L.C. (<strong>19</strong>95): Effect <strong>of</strong> Flushing on Electro Discharge Machined Surface, Journal <strong>of</strong><br />

Materials Processing <strong>Technology</strong>’. 48, pp. 299-305.<br />

[25] Sommer, C. (<strong>20</strong>00):Non-traditional machining handbook, First edition, Advance Publishing. Houston.<br />

[26] Chen, S.L.; Yan, B.H.; Huang, F.Y. (<strong>19</strong>99): Influence <strong>of</strong> kerosene and distilled water as dielectric on electric<br />

discharge machining characteristics <strong>of</strong> Ti 6Al 4V, Journal <strong>of</strong> Materials Processing <strong>Technology</strong>, 876, pp. 107-111.<br />

[27] Murali, M.; Yeo, S.H. (<strong>20</strong>04): A novel sparks erosion technique for the fabrication <strong>of</strong> high aspect ratio microgrooves,<br />

Microsystems Technologies, 10, pp. 628–632.<br />

[28] Singh, S.; Maheswari, S.; Pandey, P.C. (<strong>20</strong>07): Optimization <strong>of</strong> multiperformance characteristics in electrical<br />

discharge machining <strong>of</strong> Aluminium matrix composites (AMCs) using Taguchi DOE methodology, International<br />

Journal <strong>of</strong> Manufacturing Research, vol.2, No.2, pp.138-163.<br />

[29] Lok, Y.K.; Lee, T.C. (<strong>19</strong>99): Processing <strong>of</strong> Advanced Ceramics Using the Wire-Cut EDM process, Journal <strong>of</strong><br />

Materials Processing <strong>Technology</strong> 63, pp. 839-843.<br />

[30] Tarng, Y.S.; Ma, S.C.; Chung, L.K. (<strong>19</strong>95): Determination <strong>of</strong> optimal cutting parameters in wire electrical<br />

discharge machining, International Journal <strong>of</strong> Machine Tools Manufacturing, 35, 129, pp.1693–1700.<br />

[31] Spedding, T.A.; Wang, Z.G. (<strong>19</strong>97): Parametric optimization and surface characteristic <strong>of</strong> wire electrical<br />

discharge machining process, Precision Engineering <strong>20</strong>, pp.5–15.<br />

[32] Chow, H.M.; Yan, B.H.; Huang, F.Y. (<strong>19</strong>99): Micro slit machining using electro-discharge machining with a<br />

modified rotary disk electrode (RDE), Journal <strong>of</strong> Materials Processing <strong>Technology</strong>, 91, pp. 161–166.<br />

[33] Erden, A.; Bilgin,S.(<strong>19</strong>80): Role <strong>of</strong> impurities in electric discharge machining, Proceeding <strong>of</strong> 21st International<br />

Machine Tool Design and Research Conference, pp.345-350.<br />

[34] Jeswani, M.L. (<strong>19</strong>81): Effects <strong>of</strong> the addition <strong>of</strong> graphite powder to kerosene used as the dielectric fluid in<br />

electrical discharge machining. Journal <strong>of</strong> Wear, Volume 70, pp.133-139.<br />

668


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[35] Narumiya,H.; Mohri,N.; Saito,N.; Otake,H.; Tsnekawa,Y.; Takawashi,T.; Kobayashi,K.(<strong>19</strong>89):EDM by powder<br />

suspended working fluid”, Proceeding <strong>of</strong> 9th ISEM, pp.5-8.<br />

[36] Pandey, P.C.; Shan, H.S (<strong>20</strong>03): Modern Machining Process, Tata McGraw Hill publishing, pp.7.<br />

[37] Kozak, J.; Rajurkar, K.P. (<strong>20</strong>01): Hybrid machining process evaluation and development, Proceedings <strong>of</strong> the<br />

2nd International Conference on Machining and Measurement <strong>of</strong> Sculptured Surfaces, Krakow, pp.501–536.<br />

[38] Murti,V.S.; Philip,P.K.(<strong>19</strong>87): A Comparative Analysis <strong>of</strong> Machining Characteristics in Ultrasonic Assisted<br />

EDM by Response Surface Methodology, International Journal <strong>of</strong> Product Research, 25, 2, pp.259–272.<br />

[39] Zhixin, J. (<strong>19</strong>95): Study on Mechanical Pulse Electro discharge Machining,” Precision Engineering, 17, 2,<br />

pp.89–93.<br />

[40] Hitoshi, O.; Teruo, N.; .Iwao, M. (<strong>20</strong>01): Study <strong>of</strong> Micro Machining <strong>of</strong> Metals by EDM with High Frequency<br />

Vibration”, Takushima Prefectual Industrial <strong>Technology</strong> Center.<br />

[41] Yan,B.H.; Wang,A.C.; Huang,C.Y.; Huang,F.Y.(<strong>20</strong>02): Study <strong>of</strong> precision micro-holes in borosilicate glass<br />

using micro EDM combined with micro ultrasonic vibration machining, International Journal <strong>of</strong> Machine Tools &<br />

Manufacture, 42,pp. 1105–1112.<br />

[42] Egashira, T. (<strong>19</strong>99): Micro ultrasonic machining by the application <strong>of</strong> work piece vibration”, CIRP Annals—<br />

Manufacturing <strong>Technology</strong>, 48, pp. 131–134.<br />

[43] Prihandana,G.S.; Hamdi,M.; Wong,Y.S.;Kimiyuki,M.(<strong>20</strong>06): Effect <strong>of</strong> vibrated electrode in electrical discharge<br />

machining, Proceedings <strong>of</strong> the First International Conference and Seventh AUN/SEED-Net Field wise Seminar on<br />

Manufacturing and Material Processing, Kuala Lumpur, pp. 133–138.<br />

669


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

HARDNESS IMPROVEMENT OF DISSIMILAR METAL STAINLESS<br />

STEEL (A304) AND MILD STEEL BY TIG WELDING<br />

1 Rakesh Kumar # and 2 Manmeet Shergill<br />

Department <strong>of</strong> Mechanical Engineering, SLIET, Longowal, India.<br />

#<br />

Corresponding Author, E-mail address: rakeshsliet@yahoo.co.in<br />

Tel.:+91-1672-256349; Fax: +91-1672-280057<br />

Abstract<br />

Recently more stress is given on welding <strong>of</strong> dissimilar metals. In this study joining <strong>of</strong> stainless steel A304 with<br />

low alloy steel has been optimized by using TIG Welding process. The electrode diameter, Filler Wire electrode<br />

diameter, Welding current & Argon gas flow rate were identified as most important control factors for manual<br />

TIG welding. The orthogonal arrays L18 (2)¹. (3)7 were selected for optimizing weld bead Hardness. It has been<br />

found that these parameters affect the weld quality significantly and their levels have been optimized after doing<br />

confirmation experimentation. The increase in hardness was found by 36.4 %.<br />

Keywords: Dissimilar metals welding, TIG welding <strong>of</strong> M.S & AISI 304 Stainless steel, Taguchi method, optimal<br />

parameters, Hardness<br />

1. Introduction<br />

The experimental work was planned to cut sheet in size <strong>of</strong> 150mm×50mm×3mm before TIG welding <strong>of</strong> M.S<br />

&S.S. The “V” shape groove was developed at 45˚. The length <strong>of</strong> butt gap was 2–3mm. In figure 1.0 shown<br />

TIG welding joint for mild steel and stainless steel.<br />

Fig1.0: TIG welding joint for mild steel and stainless steel<br />

Chemical composition <strong>of</strong> filler wire as given below<br />

C% Si% Mn% S% P% Cu% Cr% Ni% Mo%<br />

0.078 0.3 1.28 0.025 0.041 0.54 16.81 10.17 2.02<br />

Chemical composition <strong>of</strong> M.S as given below<br />

C% Si% Mn% P% S% Cu% Cr% Ni% Mo%<br />

0.0905 0.0564 0.4410.015 0.266 0.00599 0.0143 0.0052


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. Methodology and Experimentation<br />

In the present work three levels were chosen for three parameters and two levels were chosen for one parameter.<br />

The interaction effect between electrode diameter and wire diameter was studied.<br />

TABLE 1.1: Process Parameters Level<br />

Symbol Process Parameters Unit Level 1 Level 2 Level 3<br />

A Electrode Diameter (mm) 2.4 1.6 ---<br />

B Wire Diameter (mm) 1.8 2.6 2.9<br />

C Welding Current (Amp) 100 115 130<br />

D Argon Flow (Litre/min) 6 7 8<br />

FIXED PARAMETERS: Gap between plates 2 mm, Bevel Angle= 45 o (Noise Factor) and Material <strong>of</strong> Job AISI<br />

304 and Mild steel plates (3 mm).<br />

The experiment layout was set up with L18 orthogonal array.in the layout 18 trial run and 4 process parameters<br />

A, B, C and D and their Levels were presented in table 1.2<br />

TABLE 1.2: Experimental Layout Using L18 Orthogonal Array<br />

Trial No.<br />

Process Parameters and their Levels<br />

- A B C D<br />

1 1 1 1 1<br />

2 1 1 2 2<br />

3 1 1 3 3<br />

4 1 2 2 3<br />

5 1 2 3 1<br />

6 1 2 1 2<br />

7 1 3 1 3<br />

8 1 3 2 1<br />

9 1 3 3 2<br />

10 2 1 3 1<br />

11 2 1 1 2<br />

12 2 1 2 3<br />

13 2 2 3 2<br />

14 2 2 1 3<br />

15 2 2 2 1<br />

16 2 3 2 2<br />

17 2 3 3 3<br />

18 2 3 1 1<br />

TABLE 1.3: Experimental Data for Hardness Measurements<br />

(A)<br />

(B)<br />

(C)<br />

(D)<br />

Hardness<br />

Expt.<br />

No.<br />

Electrode<br />

Diameter<br />

(mm.)<br />

Wire<br />

Diameter<br />

(mm.)<br />

Welding<br />

Current (Amp.)<br />

Argon Flow<br />

(L/min.)<br />

(V.H.N.)<br />

1 2.4 1.8 100 6 257 259<br />

2 2.4 1.8 115 7 383 390<br />

3 2.4 1.8 130 8 254 248<br />

4 2.4 2.6 100 6 238 244<br />

5 2.4 2.6 115 7 212 <strong>20</strong>6<br />

6 2.4 2.6 130 8 238 244<br />

7 2.4 2.9 100 7 <strong>19</strong>8 <strong>19</strong>8<br />

8 2.4 2.9 115 8 <strong>20</strong>4 212<br />

671


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

9 2.4 2.9 130 6 222 222<br />

10 1.6 1.8 100 8 280 293<br />

11 1.6 1.8 115 6 400 402<br />

12 1.6 1.8 130 7 258 260<br />

13 1.6 2.6 100 7 353 360<br />

14 1.6 2.6 115 8 314 321<br />

15 1.6 2.6 130 6 302 310<br />

16 1.6 2.9 100 8 299 306<br />

17 1.6 2.9 115 6 400 402<br />

18<br />

1.6 2.9 130 7 258 260<br />

Trial No.<br />

Process Parameters and their<br />

Levels<br />

A B C D<br />

TABLE 1.4: Hardness SN Ratio (smaller-the-Better)<br />

Hardness<br />

Mean Sum <strong>of</strong><br />

Squares<br />

SN Ratio<br />

(smallerthe-Better)<br />

(V.H.N.)<br />

1 1 1 1 1 257 259 4.4E+04 -46.47<br />

2 1 1 2 2 383 390 1.0E+05 -49.98<br />

3 1 1 3 3 254 248 4.2E+04 -46.23<br />

4 1 2 2 3 238 244 3.9E+04 -45.88<br />

5 1 2 3 1 212 <strong>20</strong>6 2.9E+04 -44.64<br />

6 1 2 1 2 238 244 3.9E+04 -45.88<br />

7 1 3 1 3 <strong>19</strong>8 <strong>19</strong>8 2.6E+04 -44.17<br />

8 1 3 2 1 <strong>20</strong>4 212 2.9E+04 -44.60<br />

9 1 3 3 2 222 222 3.3E+04 -45.17<br />

10 2 1 3 1 280 293 5.5E+04 -47.38<br />

11 2 1 1 2 400 402 1.1E+05 -50.30<br />

12 2 1 2 3 258 260 4.5E+04 -46.51<br />

13 2 2 3 2 353 360 8.5E+04 -49.28<br />

14 2 2 1 3 314 321 6.7E+04 -48.27<br />

15 2 2 2 1 302 310 6.2E+04 -47.95<br />

16 2 3 2 2 299 306 6.1E+04 -47.85<br />

17 2 3 3 3 400 402 1.1E+05 -50.30<br />

18 2 3 1 1 258 260 4.5E+04 -46.51<br />

Table 1.5: Raw Data S/N Response for Main Factors for Hardness<br />

CONTROL<br />

FACTORS /<br />

LEVELS<br />

CONTROL FACTOR NAME<br />

1 2 3<br />

A electrode diameter (mm) -45.89 -48.26 -----<br />

B wire diameter (mm) -47.81 -46.99 -46.43<br />

A1X B<br />

A2xB<br />

electrode diameter (mm) (1) x wire diameter (mm)<br />

(1,2,3)<br />

electrode diameter (mm) (2) x b wire diameter<br />

(mm) (1,2,3)<br />

-0.93 0.33 0.60<br />

0.93 -0.33 -0.60<br />

C welding current (amp) -46.84 -48.02 -46.37<br />

D Argon volume (litre/min.) -47.68 -46.85 -46.70<br />

TABLE 1.6: The Pooled Version <strong>of</strong> ANOVAS<br />

672


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

SOURCE<br />

SUM OF<br />

SQUARE<br />

DOF<br />

MEAN OF<br />

SQUARE(V)<br />

F RATIO<br />

A 25 1 25 164 38<br />

B 6 2 3 <strong>19</strong> 9<br />

A1X B<br />

A2xB<br />

8 2 4 26 12<br />

C 9 2 4.5 28 13<br />

D 3 2 1.5 11 5<br />

ERROR 15 8 1.875 23<br />

SST 66 17 100<br />

P%<br />

(a)<br />

(b)<br />

(c)<br />

673


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

(d)<br />

(e)<br />

FIG. (A), (B) (C) & (D) SHOWS EFFECTS OF FACTORS A, B, C, D, A1×B & A2× B ON PROCESS AVERAGE<br />

AND S/N DATA.<br />

Figure 1.1: Response Plots for Hardness.<br />

(f)<br />

TABLE 1.7: The Summary <strong>of</strong> Optimum Levels for Hardness<br />

The average hardness <strong>of</strong> confirmation experiment must lie: 167


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3. Confirmation test results:<br />

As a result five samples have been welded at the optimum condition as above with<br />

HARDNESS are 176,178; 166, 174; 187, 182; <strong>19</strong>4, <strong>19</strong>0 and 177, 179. The samples have been<br />

evaluated following the same criteria used for the original experiments. The average <strong>of</strong> the<br />

Control Factor Names Optimum Level Optimum Value<br />

Electrode Diameter A1 2.4 mm<br />

Wire Diameter B3 2.9 mm<br />

Welding Current C3 130 Amp<br />

Argon Flow D3 9 L/min<br />

sample has been found to be 180.3 V.H.N. which is within the confidence interval. The<br />

increase in hardness has been found to be 36.4 %<br />

4. References<br />

1. San-bao Lin , Jian-ling Song, Guang-chao MA, Chun-li YANG Dissimilar metals TIG welding-brazing <strong>of</strong><br />

aluminum alloy to galvanized steel<br />

2. Lenin N., Sivakumar M. and Vigneshkumar .Process Parameter Optimization in ARC Welding <strong>of</strong> Dissimilar<br />

Metals.<br />

3. A. Kumar & S. Sundarrajan .Effect <strong>of</strong> welding parameters on mechanical properties and optimization <strong>of</strong><br />

pulsed TIG welding <strong>of</strong> Al-Mg-Si alloy.<br />

4. Rajesh Manti & D. K. Dwivedi & A. Agarwal, Microstructure and hardness <strong>of</strong> Al-Mg-Si weldments produced<br />

by pulse GTA welding.<br />

5. Ahmad J. I. Akhter M. Akhtar M. Iqbal, Microstructure and characterization <strong>of</strong> phases in TIG welded joints <strong>of</strong><br />

Zircaloy-4 and stainless steel 304L M.<br />

6. Padmanaban, V. Balasubramanian, and J.K. Sarin Sundar Influences <strong>of</strong> Welding Processes on Microstructure,<br />

Hardness, and Tensile Properties <strong>of</strong> AZ31B Magnesium Alloy G.<br />

7. J Nayak, K R Udupa, K R Hebbar and H V S Nayak. Estimation <strong>of</strong> embrittlement during aging <strong>of</strong> AISI 316<br />

stainless steel TIG welds.<br />

8. Jing Wang, Min-xu Lu, Lei Zhang, Wei Chang, Li-ning Xu, and Li-hua Hu. Effect <strong>of</strong> welding process on the<br />

microstructure and properties <strong>of</strong> dissimilar weld joints between low alloy steel and duplex stainless steel.<br />

9. Liming Liu, Xiaodong Qi. Effects <strong>of</strong> copper addition on microstructure and strength <strong>of</strong> the hybrid laser-TIG<br />

welded joints between magnesium alloy and mild steel<br />

10.Rattana Borrisutthekul, Pusit Mitsomwang, Sirirat Rattanachan and Yoshiharu Mutoh Feasibility <strong>of</strong> Using<br />

TIG Welding in Dissimilar Metals between Steel/Aluminum Alloy<br />

11. J.L. Song, S.B. Lin, C.L. Yang, G.C. Ma, H. Liu Spreading behavior and microstructure characteristics <strong>of</strong><br />

dissimilar metals TIG welding–brazing <strong>of</strong> aluminum alloy to stainless steel.<br />

675


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

CONCURRENT ENGINEERING<br />

S.P.Tayal<br />

Pr<strong>of</strong>essor, M.M.<strong>University</strong>,Mullana- 133<strong>20</strong>3, Distt.Ambala (Haryana)<br />

M: 08059930976, E-Mail: sptayal@gmail.com<br />

Abstract<br />

It is a work methodology based on the parallelization <strong>of</strong> tasks (i.e. performing tasks concurrently). It refers to an<br />

approach used in product development in which functions <strong>of</strong> design engineering, manufacturing engineering and<br />

other functions are integrated to reduce the elapsed time required to bring a new product to the market. As<br />

mentioned above, part <strong>of</strong> the design process is to ensure that the entire product's life cycle is taken into<br />

consideration. This includes establishing user requirements, propagating early conceptual designs, running<br />

computational models, creating physical prototypes and eventually manufacturing the product. Included in the<br />

process is taking into full account funding, work force capability and time, subject areas that are extremely<br />

important factors in the success <strong>of</strong> a concurrent engineering system. As before, the extensive use <strong>of</strong> forward<br />

planning allows for unforeseen design problems to be caught early so that the basic conceptual design can be<br />

altered before actual physical production commences. The amount <strong>of</strong> money that can be saved by doing this<br />

correctly has proven to be significant and is generally the deciding factor for companies moving to a concurrent<br />

design framework.<br />

Keywords: product development, design engineering, manufacturing, conceptual designs, design cycles, design<br />

phases<br />

1. Introduction<br />

As mentioned above, part <strong>of</strong> the design process is to ensure that the entire product's life cycle is taken into<br />

consideration. This includes establishing user requirements, propagating early conceptual designs, running<br />

computational models, creating physical prototypes and eventually manufacturing the product. Included in the<br />

process is taking into full account funding, work force capability and time, subject areas that are extremely<br />

important factors in the success <strong>of</strong> a concurrent engineering system. As before, the extensive use <strong>of</strong> forward<br />

planning allows for unforeseen design problems to be caught early so that the basic conceptual design can be<br />

altered before actual physical production commences. The amount <strong>of</strong> money that can be saved by doing this<br />

correctly has proven to be significant and is generally the deciding factor for companies moving to a concurrent<br />

design framework.<br />

The concurrent engineering method is a still a relatively new design management system, but has had the<br />

opportunity to mature in recent years to become a well-defined systems approach towards optimizing<br />

engineering design cycles[1]. Because <strong>of</strong> this, concurrent engineering has gathered much attention from industry<br />

and has been implemented in a multitude <strong>of</strong> companies, organizations and universities, most notably in the<br />

aerospace industry.<br />

The basic premise for concurrent engineering revolves around two concepts. The first is the idea that all elements<br />

<strong>of</strong> a product’s life-cycle, from functionality, producibility, assembly, testability, maintenance issues,<br />

environmental impact and finally disposal and recycling, should be taken into careful consideration in the early<br />

design phases[2].<br />

The second concept is that the preceding design activities should all be occurring at the same time, or<br />

concurrently. The overall goal being that the concurrent nature <strong>of</strong> these processes significantly increases<br />

productivity and product quality, aspects that are obviously important in today's fast-paced market[3]. This<br />

philosophy is key to the success <strong>of</strong> concurrent engineering because it allows for errors and redesigns to be<br />

discovered early in the design process when the project is still in a more abstract and possibly digital realm. By<br />

locating and fixing these issues early, the design team can avoid what <strong>of</strong>ten become costly errors as the project<br />

moves to more complicated computational models and eventually into the physical realm [4].<br />

As mentioned above, part <strong>of</strong> the design process is to ensure that the entire product's life cycle is taken into<br />

consideration. This includes establishing user requirements, propagating early conceptual designs, running<br />

computational models, creating physical prototypes and eventually manufacturing the product. Included in the<br />

process is taking into full account funding, work force capability and time, subject areas that are extremely<br />

important factors in the success <strong>of</strong> a concurrent engineering system. As before, the extensive use <strong>of</strong> forward<br />

planning allows for unforeseen design problems to be caught early so that the basic conceptual design can be<br />

676


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

altered before actual physical production commences. The amount <strong>of</strong> money that can be saved by doing this<br />

correctly has proven to be significant and is generally the deciding factor for companies moving to a concurrent<br />

design framework.<br />

One <strong>of</strong> the most important reasons for the huge success <strong>of</strong> concurrent engineering is that by definition it<br />

redefines the basic design process structure that was common place for decades. This was a structure based on a<br />

sequential design flow, sometimes called the ‘Waterfall Model’ [5,6]. Concurrent engineering significantly<br />

modifies this outdated method and instead opts to use what has been termed an iterative or integrated<br />

development method[7]. The difference between these two methods is that the ‘Waterfall’ method moves in a<br />

completely linear fashion by starting with user requirements and sequentially moving forward to design,<br />

implementation and additional steps until you have a finished product. The problem here is that the design<br />

system does not look backwards or forwards from the step it is on to fix possible problems. In the case that<br />

something does go wrong, the design usually must be scrapped or heavily altered. On the other hand, the iterative<br />

design process is more cyclic in that, as mentioned before, all aspects <strong>of</strong> the life cycle <strong>of</strong> the product are taken<br />

into account, allowing for a more evolutionary approach to design [8]. The difference between the two design<br />

processes can be seen graphically in Figure 1.<br />

Figure 1. “Waterfall” or Sequential Development Method vs. Iterative Development Method<br />

A significant part <strong>of</strong> this new method is that the individual engineer is given much more say in the overall design<br />

process due to the collaborative nature <strong>of</strong> concurrent engineering. Giving the designer ownership plays a large<br />

role in the productivity <strong>of</strong> the employee and quality <strong>of</strong> the product that is being produced. This stems from the<br />

fact that people given a sense <strong>of</strong> gratification and ownership over their work tend to work harder and design a<br />

more robust product, as opposed to an employee that is assigned a task with little say in the general process.<br />

By making this sweeping change, many organizational and managerial challenges arise that must be taken into<br />

special consideration when companies and organizations move towards such a system. From this standpoint,<br />

issues such as the implementation <strong>of</strong> early design reviews, enabling communication between engineers, s<strong>of</strong>tware<br />

compatibility and opening the design process up to allow for concurrency creates problems <strong>of</strong> its own[9].<br />

Similarly, there must be a strong basis for teamwork since the overall success <strong>of</strong> the method relies on the ability<br />

<strong>of</strong> engineers to effectively work together. Often this can be a difficult obstacle, but is something that must be<br />

tackled early to avoid later problems [10].<br />

Similarly, now more than ever, s<strong>of</strong>tware is playing a huge role in the engineering design process. Be it from<br />

CAD packages to finite element analysis tools, the ability to quickly and easily modify digital models to predict<br />

future design problems is hugely important no matter what design process you are using. However, in concurrent<br />

engineering s<strong>of</strong>tware’s role becomes much more significant as the collaborative nature must take into the<br />

account that each engineer's design models must be able to ‘talk’ to each other in order to successfully utilize the<br />

concepts <strong>of</strong> concurrent engineering.<br />

677


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. Need for concurrent engineering<br />

Intoday's business world, corporations must be able to react to the changing market needs rapidly, effectively,<br />

and responsively. They must be able to reduce their time to market and adapt to the changing environments.<br />

Decisions must be made quickly and they must be done right the first time out. Corporations can no longer waits<br />

time repeating tasks, thereby prolonging the time it takes to bring new products to market. Therefore, concurrent<br />

engineering has emerged as way <strong>of</strong> bringing rapid solutions to product design and development process.<br />

Concurrent engineering is indisputably the wave <strong>of</strong> the future for new product development for all companies<br />

regardless <strong>of</strong> their size, sophistication, or product portfolio. In order to be competitive, corporations must alter<br />

their product and process development cycle to be able to complete diverse tasks concurrently. This new process<br />

will benefit the company, although it will require a large amount <strong>of</strong> refinement in its implementation. This is<br />

because; concurrent engineering is a process that must be reviewed and adjusted for continuous improvements <strong>of</strong><br />

engineering and business operations.<br />

2.1 Theconcurrent engineering approach<br />

Concurrent engineering is a business strategy which replaces the traditional product development process with<br />

one in which tasks are done in parallel and there is an early consideration for ever y aspect <strong>of</strong> a product's<br />

development process. This strategy focuses on the optimization and distribution <strong>of</strong> a firm's resources in the<br />

design and development process to ensure an effective and efficient product development process. It mandates<br />

major changes within the organizations and firms that use it, due to the people and process integration<br />

requirements. Collaboration is a must for individuals, groups, departments, and separate organizations within the<br />

firm. Therefore, it cannot be applied at leisure. A firm must be dedicated to the long term implementation,<br />

appraisal, and continuous revision <strong>of</strong> a concurrent engineering process.<br />

2.2 Strategic plan <strong>of</strong> concurrent engineering<br />

Concurrent engineering is recognized as a strategic weapon that businesses must use for effective and efficient<br />

product development. It is not a trivial task, but a complex strategic plan that demands full corporate<br />

commitment, therefore strong leadership and teamwork go hand and hand with successful concurrent<br />

engineering programs.<br />

3. How to apply concurrent engineering<br />

3.1 Commitment, planning, and leadership<br />

Concurrent engineering is not a trivial process to apply. If firms are going to commit to concurrent engineering<br />

then they must first devise a plan. This plan must create organizational change throughout the entire company or<br />

firm. There must be a strong commitment from the firm's leadership in order to mandate the required<br />

organizational changes from the top down. Concurrent engineering without leadership will have no clear<br />

direction or goal. On the other hand, concurrent engineering with leadership, management support, and proper<br />

planning will bring success in today's challenging market place.<br />

3.2 Continuousimprovement process<br />

Concurrent engineering is not a one size fits all solution to a firm's development processes. There are many<br />

different aspects <strong>of</strong> concurrent engineering which may or may not fit in a corporation's development process.<br />

Concurrent engineering is only a set <strong>of</strong> process objectives and goals that have a variety <strong>of</strong> implementation<br />

strategies. Therefore, concurrent engineering is an evolving process that requires continuous improvement and<br />

refinement. This continuous improvement cycle consist <strong>of</strong> planning, implementing, reviewing, and revising. The<br />

process must be updated and revised on a regular basis to optimize the effectiveness and benefits in the<br />

concurrent engineering development process.<br />

3.3 Communication and collaboration<br />

The implementation <strong>of</strong> concurrent engineering begins by creating a corporate environment that facilitates<br />

communication and collaboration not just between individuals, but also between separate organizations and<br />

departments within the firm. This may entail major structural changes, re-education <strong>of</strong> the existing work-force,<br />

and/or restructuring <strong>of</strong> the development process.<br />

4. Basic principles <strong>of</strong> concurrent engineering<br />

• Get a strong commitment to from senior management.<br />

• Establish unified project goals and a clear business mission.<br />

678


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

• Develop a detailed plan early in the process.<br />

• Continually review your progress and revise your plan.<br />

• Develop project leaders that have an overall vision <strong>of</strong> the project and goals.<br />

• Analyze your market and know your customers.<br />

• Suppress individualism and foster a team concept.<br />

• Establish and cultivate cross-functional integration and collaboration.<br />

• Transfer technology between individuals and departments.<br />

• Break project into its natural phases.<br />

• Develop metrics.<br />

• Set milestones throughout the development process.<br />

• Collectively work on all parts <strong>of</strong> project.<br />

• Reduce costs and time to market.<br />

• Complete tasks in parallel.<br />

5. When is concurrent engineering used<br />

The majority <strong>of</strong> a product's costs are committed very early in the design and development process. Therefore,<br />

companies must apply concurrent engineering at the onset <strong>of</strong> a project. This makes concurrent engineering a<br />

powerful development tool that can be implemented early in the conceptual design phase where the majority <strong>of</strong><br />

the a products costs are committed. There are several application in which concurrent engineering may be used.<br />

Some primary applications include product research, design, development, re-engineering, manufacturing, and<br />

redesigning <strong>of</strong> existing and new products. In these applications, concurrent engineering is applied throughout the<br />

design and development process to enable the firm to reap the full benefits <strong>of</strong> this process.<br />

6. Why do companies use concurrent engineering<br />

6.1 Competitiveadvantage<br />

The reasons that companies choose to use concurrent engineering is for the clear cut benefits and competitive<br />

advantage that concurrent engineering can give them. Concurrent engineering can benefit companies <strong>of</strong> any size,<br />

large or small. While there are several obstacles to initially implementing concurrent engineering, these obstacles<br />

are minimal when compared to the long term benefits that concurrent engineering <strong>of</strong>fers.<br />

6.2 Increasedperformance<br />

Companies recognize that concurrent engineering is a key factor in improving the quality, dev elopement cycle,<br />

production cost, and delivery time <strong>of</strong> their products. It enables the early discovery <strong>of</strong> design problems, thereby<br />

enabling them to be addressed up front rather than later in the development process. Concurrent engineering can<br />

eliminate multiple design revisions, prototypes, and re-engineering efforts and create an environment for<br />

designing right the first time.<br />

6.3 Reduceddesign and development times<br />

Companies that use concurrent engineering are able to transfer technology to their markets and customers more<br />

effectively, rapidly and predictably. They will be able to respond to customers’ needs and desires, to produce<br />

quality products that meet or exceed the consumer's expectations. They will also be able to introduce more<br />

products and bring quicker upgrades to their existing products through concurrent engineering practices.<br />

Therefore companies use concurrent engineering to produce better quality products, developed in less time, at<br />

lower cost, that meets the customer's needs.<br />

7. Conclusions<br />

There are several benefits that concurrent engineering can bring, although it is difficult to quantify many <strong>of</strong> these<br />

benefits by using spreadsheets and numbers. These are not only benefits which the participating company will<br />

experience, but ultimately the end users or customers also will reap these benefits by having a quality product<br />

which fits their needs and in many case, costs them less to purchase. Therefore, concurrent engineering produces<br />

a unified pr<strong>of</strong>itable corporation and a satisfied consumer.<br />

Regardless <strong>of</strong> the type <strong>of</strong> application, there are significant benefits to the firms or organizations that use cross<br />

functional teams.<br />

679


References<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[1] Ma, Y., Chen, G. &Thimm, G.; "Paradigm Shift: Unified and Associative Feature-based Concurrent<br />

Engineering and Collaborative Engineering", Journal <strong>of</strong> Intelligent Manufacturing, DOI 10.1007/s10845-<br />

008-0128-y<br />

[2] Kusiak, Andrew; Concurrent Engineering: Automation, Tools and Techniques<br />

[3] Quan, W. &Jianmin, H., A Study on Collaborative Mechanism for Product Design in Distributed Concurrent<br />

Engineering IEEE<br />

[4] Kusiak, Andrew, Concurrent Engineering: Automation, Tools and Techniques<br />

[5] “The standard waterfall model for systems development”, NASA Webpage, November 14, <strong>20</strong>08<br />

[6] Kock, N. and Nosek, J., “Expanding the Boundaries <strong>of</strong> E-Collaboration”, IEEE Transactions on<br />

Pr<strong>of</strong>essional Communication, Vol 48 No 1, March <strong>20</strong>05.<br />

[7] Ma, Y., Chen, G., Thimm, G., "Paradigm Shift: Unified and Associative Feature-based Concurrent<br />

Engineering and Collaborative Engineering", Journal <strong>of</strong> Intelligent Manufacturing, DOI 10.1007/s10845-<br />

008-0128-y<br />

[8] Royce, Winston, "Managing the Development <strong>of</strong> Large S<strong>of</strong>tware Systems", Proceedings <strong>of</strong> IEEE WESCON<br />

26 (August <strong>19</strong>70): 1-9.<br />

[9] Kusiak, Andrew, "Concurrent Engineering: Automation, Tools and Techniques"<br />

[10] Rosenblatt, A. and Watson, G. (<strong>19</strong>91). "Concurrent Engineering", IEEE Spectrum, July, pp 22-37.<br />

680


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

IMPLEMENTATION OF NSGA-II TO REDUCE THE OCCUPATIONAL<br />

HEALTH HAZARDS OF WORKERS IN GLASS MAKING INDUSTRY<br />

RuchiChaudhary 1 , Ajit 1 , Manisha Verma 1 , RK Srivastava 2<br />

1 Manav Rachna College <strong>of</strong> Engineering, Faridabad -121001<br />

2<br />

BIT SINDRI<br />

Phone: +9<strong>19</strong>953546282, e-mail: ruchi_chaudhary88@yaho.com<br />

Abstract<br />

Glass making industry is a very hazardous industry in which fatal and non-fatal occupational injuries occur<br />

most frequently due to its unique nature. It is characterised by continual changes, use <strong>of</strong> many different<br />

resources, poor working conditions, tough environments (ex-noise, direct exposure to heat, vibration, dust etc.).<br />

The GMI is plagued by occupational risky situations and poor working conditions. Occupational health is<br />

concerned with those factors in the work environment which can give rise to ill-health in exposed workers. The<br />

study <strong>of</strong> Ergonomics provides the information <strong>of</strong> matching the man – machine interaction and work place<br />

design. This study aimed to present an overview <strong>of</strong> the situation <strong>of</strong> occupational health in glass making industry<br />

to gain information related to welfare and health facilities, health education, accident statistics, occupational<br />

health and safety activities.<br />

The paper is structured as follows- The first section introduces the objective <strong>of</strong> this work. The second section<br />

represents the work methodology carried out in the Glass Making Industry. The third presents the Literature<br />

Survey. The fourth presents an overview <strong>of</strong> the problem formulation <strong>of</strong> traditional glass making method. The<br />

fifth section gives the Data Analysis. Finally, the sixth section presents the conclusions.<br />

The Earnings <strong>of</strong> the glass making workers is calculated as per the jobs specified to them. In particular eight<br />

types <strong>of</strong> jobs, usually done by glass making workers, are considered. Each job has its specific earnings. Usually<br />

high earning jobs are very tedious to perform. Combining jobs is found to be a way <strong>of</strong> reducing OHH and yet<br />

maintaining the good earnings. One severe job (firing-work) is combined with the rest <strong>of</strong> three jobs sequentially<br />

resulting in three job combinations Workers performing such jobs suffer from severe stresses and other health<br />

problems. NSGA-II is used to search for those solution points which would simultaneously minimize the<br />

occupational health hazards and maximize the earnings.<br />

Keywords: Ergonomics, Human Factors and Work Place Design, Glass Manufacturing, Small Scale Industry,<br />

ANN.<br />

1. Introduction<br />

Ergonomic design and comfort <strong>of</strong> handling objects and operating <strong>of</strong> equipment are <strong>of</strong>ten linked to the activity <strong>of</strong><br />

the human body, expressed in muscle action, depending on the arrangement and interaction <strong>of</strong> man and machine.<br />

Ergonomics design and comfort <strong>of</strong> handling objects and operating <strong>of</strong> equipment are <strong>of</strong>ten linked to the activity <strong>of</strong><br />

the human body, expressed in muscle action, depending on the arrangement and interaction <strong>of</strong> man and machine<br />

.Muscles plays a major role when mechanical factors are involved. Psychological fatigue also plays an important<br />

role in the actions <strong>of</strong> daily life and work.<br />

Working in glass industries may leads towards many occupational health hazards. Managing such hazards in an<br />

optimum manner for workers <strong>of</strong> OKAY Glass Industries is a challenging job. These workers are subjected to<br />

high heat stress owing to high temperature <strong>of</strong> the furnace. The worker aims at maximizing his earnings and job<br />

growth by subjecting themselves to extreme work conditions.<br />

Factors like long working hours, improper rest breaks etc. Severely affect worker’s health and depending upon<br />

the type <strong>of</strong> job, they suffer from various disorders when working beyond prescribed limits.<br />

The molten mixture prepared with the above method is glass. Molten glass is then taken out from the furnace<br />

with the help <strong>of</strong> iron pipes. The glass worker then blows air through their mouth from the other end <strong>of</strong> pipe and<br />

the molten glass, which is on the second end <strong>of</strong> the pipe, blows like balloon. Before this blown glass cools, it is<br />

quickly placed in the dyes <strong>of</strong> desired size and shape. In the glassware industry the temp goes up to 30000C.<br />

High temperature and harmful vapours in glassware manufacturing causes health disorders to workers, such as<br />

Heat Stroke, T.B., Dehydration, Heat crams, Heat rashes, Fainting, Heat Exhaustion etc.<br />

681


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. Work Methodology<br />

2.1. Visit the glass making industry to explore the real life scenario <strong>of</strong> glass making workers.<br />

2.2. Questionnaire development-<br />

A questionnaire was developed comprising check-box questions and open-ended questions.<br />

The questionnaire was divided into four sections that covered: information about the Health Risk<br />

(b) Occupation History, (c) Health Risk questions for employer side and (d) Health Risk questions at<br />

the working conditions.<br />

2.2.1 Sample:<br />

The targeted employees were 10-12, producing various glass-ware products.<br />

2.2.2 Taking feedback from the workers <strong>of</strong> ‘OKAY GLASS INDUSTRIES’ through questionnaire regarding<br />

their:<br />

2.2.2.1 Heat exposure limits<br />

2.2.2.2 Health disorders they are suffering from<br />

2.2.2.3 Anthropological data <strong>of</strong> workers<br />

2.3. Analysing the perceived discomforts <strong>of</strong> ‘OKAY GLASS INDUSTRIES’ with respect to variation in the<br />

following factors on the site itself:<br />

2.3.1 Rest break<br />

2.3.2 Working hours<br />

2.3.3 Working hour between two consecutive rest breaks<br />

2.3.4 Switching the job with in same industry so as to reduce OHH<br />

2.4. Data Analysis:<br />

Data from the questionnaire were coded and analysis.<br />

2.5. Finding the range <strong>of</strong> optimal parameters using some optimization techniques so as to minimize health<br />

disorders and maximize earnings <strong>of</strong> firers.<br />

3. Literature Survey<br />

According to human psychological nature study a person start giving low performance in his duty assigned if<br />

conditions are not favourable with his body requirement in both physically and mentally. Ruchi et al. (<strong>20</strong>12)<br />

stated the combined study <strong>of</strong> HEERAP with its implementation which helps in giving proper working<br />

atmosphere in which a worker can do his best without any fear or fatigue in mental and physical type [1]. Ajit et<br />

al. (<strong>20</strong>12) investigated the extent to which OHH can be minimized in glass making industry [2]. Adel et al.<br />

(<strong>20</strong>11) examined the extent to which OHS risks are taken into account in the project management and industrial<br />

safety practices with special focus on the construction industry [3]. Iman et al. (<strong>20</strong>11) investigated the effects <strong>of</strong><br />

wearing typical industrial gloves on hand performance capabilities & subjective assessments for an extended<br />

duration <strong>of</strong> performing a common assembly task, wire tying with pliers, which requires a combination <strong>of</strong><br />

manipulation & force exertion. Results showed that wearing gloves significantly increased the muscle activity,<br />

wrist deviation & discomfort whilst reducing hand grip strength, forearm torque strength & touch sensitivity.<br />

Combined results also showed that the length <strong>of</strong> time for which gloves are worn does affect hand performance<br />

capabilities & that gloves need to be evaluated in a realistic working context [4]. Qiang et al. Proposes a Genetic<br />

Algorithm approach to assessing work zone casualty risk defined as the likelihood <strong>of</strong> a vehicle occupant being<br />

killed or injured in a work zone crash and demonstrates that the GA approach is a good alternative for the work<br />

zone casualty risk assessment [6]. Magne et al. (<strong>20</strong>11) study stated that the pain levels in different body areas<br />

were significantly correlated with subjective assessment <strong>of</strong> reduced work capacity in small <strong>of</strong>fices and in the<br />

<strong>of</strong>fice landscape. Moving into an <strong>of</strong>fice landscape might be problematic due to high luminance from the<br />

windows giving glare & increased contrast reduction in the work area [7]. N.Louis et al. (<strong>20</strong>09) study indicates<br />

that upper limb muscles forces augment with distance [9]. Y.Lan.Noy et al. (<strong>20</strong>09) study will inspire & motivate<br />

new research efforts that will lead to dramatic reduction in loss & human suffering [10]. A.M.Makin et al. (<strong>20</strong>08)<br />

study utilising a systematic approach to safety, OHS MS optimise the overall co-ordination <strong>of</strong> prevention &<br />

control measures [13]. Sanjay et al. (<strong>20</strong>08) done a analysis to reduce OHH <strong>of</strong> brick kiln workers [12].Hal<br />

W.Hendric (<strong>20</strong>08) study stated that how to achieve the potential <strong>of</strong> ergonomics for practical engineering design<br />

use .Ergonomics pr<strong>of</strong>essional education programs will need to be continuously updated to provide the necessary<br />

knowledge, methods & skills to meet those challenges[11]. Dahlberg et al. (<strong>20</strong>04) compared the work technique<br />

and self-reported musculoskeletal symptoms between men and women performing the same type <strong>of</strong> work tasks<br />

within a metal industry [16]. Lipscomb et al. (<strong>20</strong>04) studied musculoskeletal symptoms among commercial<br />

fishers in North Carolina.Salvendy, G (<strong>20</strong>06) investigated the extent to which process, barriers and outcomes are<br />

accommodated by current ergonomics consultancy practices [15]. Hyung-Yun Choi (<strong>20</strong>01) presents a short<br />

overview on the emerging ESI Group comfort and ergonomics models <strong>of</strong> the human body, that are developed to<br />

study the activation levels <strong>of</strong> the skeletal muscles, needed to sustain various load conditions[17].<br />

682


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4. Problem Formulation<br />

Workers can have number <strong>of</strong> problems in glass industries .Basically we can divide these problem in three<br />

parts:<br />

‣ Glass formation (heat effect)<br />

‣ Coloring (chemical effect)<br />

‣ Posture (sitting and working)<br />

In this work we intend to reduce the OHH <strong>of</strong> different workers in OKAY Glass Industries. For this purpose we<br />

will take the following parameters:<br />

‣ RB (Rest break) : Defined as time interval between continuous works. It is taken by workers<br />

when they get tired after doing continuous work.<br />

‣ WH (Working Hours) : Time taken by the worker during the whole day.<br />

‣ SOAJ (Switching Over for Alternate Jobs) : This is done in order to reduce health hazards<br />

pertaining to one type <strong>of</strong> job for long working hours.<br />

‣ WHBTCB (Working hours between two consecutive breaks) : It means that after how much<br />

time rest break should be provided.<br />

We also intend to find the range <strong>of</strong> optimal parameters using some optimization<br />

technique so as to minimize health disorders and maximize earnings <strong>of</strong> firers.<br />

5. Data Analysis<br />

Basically we can divide the work <strong>of</strong> the Glass-ware products formation in the following eight jobs.<br />

1. Firer (A) 5. Sorter (E)<br />

2. Mixer (B) 6. Packager (F)<br />

3. Firer polisher (C) 7. Decorator (G)<br />

4. Annealer (D) 8. Lifter (H)<br />

Out <strong>of</strong> these jobs the Firer job is complex one. So, result shows that a person which doing the job <strong>of</strong> firer will<br />

face more health problems as compared to the person which doing the other jobs. But at the same time a person<br />

doing the job <strong>of</strong> firer can earn more money as compared to a person doing the other jobs.<br />

5.1 Working Parameters<br />

Here we assume that a worker will do two types <strong>of</strong> jobs in a day. Out <strong>of</strong> these two jobs one job will Firer job<br />

and second can be any one out <strong>of</strong> rest available seven jobs.<br />

Rest breaks matrices in minutes = [0 10 15 <strong>20</strong> 25 30] for each type <strong>of</strong> job.<br />

WHBTRB matrices in hours = [0 1 2 3].<br />

Working hours in a day (combined hours <strong>of</strong> two jobs) = Between 7-9 hours.<br />

5.2 Earning Details<br />

Average earning <strong>of</strong> a worker - ‘Firer job’<br />

Average earning <strong>of</strong> a worker - ‘Mixer job’<br />

Average earning <strong>of</strong> a worker - ‘Firer Polisher job’<br />

Average earning <strong>of</strong> a worker - ‘Annealer job’<br />

Average earning <strong>of</strong> a worker - ‘Sorter job’<br />

Average earning <strong>of</strong> a worker - ‘Packager job’<br />

Average earning <strong>of</strong> a worker - ‘Decorator job’<br />

Average earning <strong>of</strong> a worker - ‘Lifter job’<br />

40 Rs. /hours<br />

25 Rs. /hours<br />

35 Rs. /hours<br />

15 Rs. /hours<br />

25 Rs. /hours<br />

18.7 Rs. /hours<br />

22.5 Rs. /hours<br />

25 Rs. /hours<br />

5.3 Occupational Health Hazard Scale<br />

Here we take the range <strong>of</strong> O.H.H from 100 to 0 with the assumption <strong>of</strong> that when the value <strong>of</strong> O.H.H is 0 i.e.<br />

Negligible, and when the value <strong>of</strong> O.H.H is 100 i.e. Extremely high.<br />

683


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

WH1 (hr) RB1 (min) WHBTRB<br />

1 (hr)<br />

Table 1.Data set for (firer job + mixer job)<br />

WH2 (hr) RB2 (min) WHBTR<br />

B2 (hr)<br />

OHH<br />

7 <strong>20</strong> 3 1 0 0 100 305<br />

6 30 2 2 0 0 89 290<br />

5 30 2 3 10 2 65 275<br />

4 <strong>20</strong> 2 4 15 2 42 260<br />

3 10 3 5 15 2 26 245<br />

EARNIN<br />

GS<br />

WH1<br />

(hr)<br />

RB1<br />

(min)<br />

WHBTRB1 (hr)<br />

Table 2.Data set for (firer job + firer polisher job)<br />

WH2<br />

(hr)<br />

RB2<br />

(min)<br />

WHBTRB2 (hr) OHH EARNINGS<br />

7 30 3 2 0 0 95 350<br />

6 30 3 2 0 0 75 310<br />

5 <strong>20</strong> 2 3 0 0 63 305<br />

4 <strong>20</strong> 2 4 10 2 40 300<br />

3 15 2 5 15 2 23 295<br />

WH1<br />

(hr)<br />

RB1<br />

(min)<br />

WHBTRB1 (hr)<br />

Table 3.Data set for (firer job + annealer job)<br />

WH2<br />

(hr)<br />

RB2<br />

(min)<br />

WHBTRB2 (hr) OHH EARNINGS<br />

7 10 2 1 0 0 92 295<br />

6 10 2 2 0 0 70 270<br />

5 <strong>20</strong> 2 3 10 2 58 245<br />

4 10 2 4 10 2 36 2<strong>20</strong><br />

3 30 2 5 15 3 <strong>19</strong> <strong>19</strong>5<br />

WH1<br />

(hr)<br />

RB1<br />

(min)<br />

WHBTRB1<br />

(hr)<br />

Table 4. Data set for (firer job + sorter job)<br />

WH2<br />

(hr)<br />

RB2<br />

(min)<br />

WHBTRB2<br />

(hr)<br />

OHH<br />

7 10 2 1 0 0 88 305<br />

6 <strong>20</strong> 2 2 0 0 67 290<br />

5 30 3 3 15 2 46 275<br />

4 30 3 4 10 2 29 260<br />

EARNINGS<br />

684


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3 30 3 5 15 2 14 245<br />

Table 5. Data set for (firer job + packager job)<br />

WH1<br />

(hr)<br />

RB1<br />

(min)<br />

WHBTRB1<br />

(hr)<br />

WH2<br />

(hr)<br />

RB2<br />

(min)<br />

WHBTRB2<br />

(hr)<br />

OHH<br />

7 30 3 2 0 0 85 317.4<br />

6 30 3 2 0 0 61 277.4<br />

5 25 2 3 0 0 38 256.1<br />

4 25 3 4 15 2 22 244.8<br />

3 <strong>20</strong> 2 5 15 2 10 213.5<br />

EARNINGS<br />

Table 6. Data set for (firer job + decorator job)<br />

WH1<br />

(hr)<br />

RB1<br />

(min)<br />

WHBTRB1<br />

(hr)<br />

WH2<br />

(hr)<br />

RB2<br />

(min)<br />

WHBTRB2<br />

(hr)<br />

OHH<br />

7 30 3 2 0 0 81 325.0<br />

6 25 3 2 0 0 56 285.0<br />

5 25 2 3 5 1 33 307.5<br />

4 <strong>20</strong> 2 4 10 2 18 250.0<br />

3 15 3 5 15 2 8 242.5<br />

EARNINGS<br />

Table 7. Data set for (firer job + lifter job)<br />

WH1<br />

(hr)<br />

RB1<br />

(min)<br />

WHBTRB1<br />

(hr)<br />

WH2<br />

(hr)<br />

RB2<br />

(min)<br />

WHBTRB2<br />

(hr)<br />

OHH<br />

EARNINGS<br />

7 30 2 1 0 0 76 305<br />

6 <strong>20</strong> 2 2 5 0 50 290<br />

5 <strong>20</strong> 1 3 10 2 30 275<br />

4 <strong>20</strong> 1 4 10 2 13 260<br />

3 15 1 5 15 2 4 245<br />

685


6. Result Analysis<br />

According to the job combination the results are as follows—<br />

a. Result <strong>of</strong> Firer Job + Mixer Job-<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

b. Results <strong>of</strong> Firer Job+ Firer Polisher Job-<br />

Figure 5.1.1. Table: 1- Combination <strong>of</strong> Firer Job + Mixer Job<br />

Figure 5.1.2. Table:2- Combination <strong>of</strong> Firer Job + Firer Polisher Job<br />

c. Results <strong>of</strong> Firer Job + Annealer Job-<br />

Figure 5.1.3. Table:3- Combination <strong>of</strong> Firer Job + Annealer Job<br />

d. Results <strong>of</strong> Firer Job + Sorter Job-<br />

686


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

e. Results <strong>of</strong> Firer Job + Packager Job-<br />

Figure 5.1.4. Table:4- Combination <strong>of</strong> Firer Job + Sorter Job<br />

Figure 5.1.5, Table:5- Combination <strong>of</strong> Firer Job + Packager Job<br />

f. Results <strong>of</strong> Firer Job + Decorator Job-<br />

Fig.5.1.6, Table:6- Combination <strong>of</strong> Firer Job + Decorator Job<br />

g. Results <strong>of</strong> Firer Job + Lifter Job-<br />

687


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Fig.5.1.7, Table:7- Combination <strong>of</strong> Firer Job + Lifter Job<br />

With these figures it is clear that we are getting some points which shows that if worker follows these scheduling<br />

he will get maximum earning with minimum occupation health hazard .O.H.H <strong>of</strong> the worker can be reduced by<br />

providing rest breaks between their sessions, but if we increase rest break then total duration decreases and<br />

earnings <strong>of</strong> worker will reduce so every worker will not agree with these changes.<br />

7. CONCLUSION<br />

Workplace change is not possible without considering job training, technical skills and vocational education.<br />

.Switching over alternate jobs within the organization can also reduce the O.H.H <strong>of</strong> the workers and earning <strong>of</strong><br />

worker will reduce so every worker will not agree with these changes .Health and hygiene cannot be achieved<br />

without an investment in safe and healthy behaviour among the workers, factory owners and others. There must<br />

be drinking water arrangement near the working site to avoid dehydration problem. Worker should use glasses<br />

for the safety <strong>of</strong> his/her eyes from the excessive heat.<br />

REFERENCES<br />

1. Combined study <strong>of</strong> Human Engineering and Ergonomics Risk Analysis Process With its Implementation<br />

(<strong>20</strong>12) by Ajit, Ruchi, ManishaVerma, Jyoti Sharma, Dr. RK Srivastava.<br />

2. Application <strong>of</strong> Artificial Intelligence Techniques To Minimize The Occupational Health Hazards in Glass<br />

Making Industry (<strong>20</strong>12) by Ruchi, Ajit, ManishaVerma, Dr. RK Srivastava.<br />

3. Occupational health and safety risks: Towards the integration into project management (<strong>20</strong>11) by Adel<br />

Badri, Andre Gbodossou, Sylvie Nadeau.<br />

4. Using pliers in assembly work: Short & long task duration effects <strong>of</strong> gloves on hand performance<br />

capabilities & subjective assessments <strong>of</strong> discomfort & ease <strong>of</strong> tool manipulation (<strong>20</strong>11) by ImanDianat,<br />

Christine M. Haslegrave, Alex W. Stedmon.<br />

5. ‘What is Human Factors and Ergonomics’ by Eric F. Shaver and Curt C. Braun.<br />

6. A Genetic Algorithm approach to assessing work zone casualty risk (<strong>20</strong>11) by QiangMeng, JinxianWeng.<br />

7. Will Musculoskeletal and visual stress change when visual display unit (VDU) operators move from small<br />

<strong>of</strong>fices to an ergonomically optimized <strong>of</strong>fice landscape (<strong>20</strong>11) by MagneHelland, Gunnar Horgen, Tor<br />

Martin Kvikstad, Tore Garthus, ArneAaras.<br />

8. ‘Human Engineering and Ergonomics Risk Analysis Process, Improved capability for Reducing Human<br />

Injury Risks’ by Larry Avery and Tom Malone.<br />

9. Upper limb muscle forces during a simple reach-to-grasp movement: a comparative study (<strong>20</strong>09) by<br />

N.Louis, P.Gorce.<br />

10. Future directions in fatigue and safety research by Y.LanNoy, William J. Horrey, Stephen M.Popkin, Simon<br />

Folkard, Heidi D.Howarth, Theodore K.Courtney (<strong>20</strong>09)<br />

11. Applying Ergonomics to systems: Some documented “lessons learned” (<strong>20</strong>08) by Hal W.Hendrick.<br />

12. Reducing occupational health hazard at maximum earning: A Multiobjective Optimization Using NSGA-II<br />

(<strong>20</strong>08) by Sanjay Srivastava and Deepak Kr. Singh.<br />

13. A new conceptual framework to improve the application <strong>of</strong> occupational health & safety management<br />

systems (<strong>20</strong>08) by A.M.Makin, C.Winder.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

14. Occupatinal health and safety management in small and medium-sized enterprises: An overview <strong>of</strong> the<br />

situation in Thailand (<strong>20</strong>08) by PornpimolKongtip, WitayaYoosook,SuttinumChantanakul.<br />

15. Salvendy, G.(<strong>20</strong>06) Handbook <strong>of</strong> Human Factors and Ergonomics.<br />

16. Dahlberg, R., Karlqvist, L., Bildt, C., and Nykvist, K., <strong>20</strong>04, Do Work Technique and Musculoskeletal<br />

Symptoms Differ between Men and Women Performing the same type <strong>of</strong> Work Tasks Applied Ergnomics<br />

35, 521-529.<br />

17. Modelling <strong>of</strong> Ergonomics and Muscular Comfort (<strong>20</strong>01) by EberhardHaug, Alain Tramecon, J.C.Allain,<br />

Hyung-Yun Choi.<br />

18. Veldhuizen D.A.V & G.B Lamont, Multiobjective evolutionary algorithms: analyzing the state-<strong>of</strong>-the-art,<br />

Evolutionary Computation 8(2) (<strong>20</strong>00),PP. 125-147.<br />

689


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

STUDY OF MANUAL MATERIAL HANDLING TASKS USING<br />

TAGUCHI TECHNIQUE<br />

Jaswinder Singh 1 , P Kalra 2 , R S Walia 3<br />

1<br />

Research Scholar, Department <strong>of</strong> Production Engineering, PEC <strong>University</strong> <strong>of</strong> <strong>Technology</strong>, Chandigarh, UT<br />

2 Pr<strong>of</strong>essor, Department <strong>of</strong> Production Engineering, PEC <strong>University</strong> <strong>of</strong> <strong>Technology</strong>, Chandigarh, UT<br />

2<br />

Associate Pr<strong>of</strong>essor, Department <strong>of</strong> Production Engineering, PEC <strong>University</strong> <strong>of</strong> <strong>Technology</strong>, Chandigarh, UT<br />

e-mail:: waliaravinder@yahoo.com<br />

Abstract<br />

Measurement <strong>of</strong> energy expenditure <strong>of</strong> the worker during manual material handling (MMH) task depends upon<br />

various parameters that can be used to assign the task to particular worker. In this study three important<br />

variables related to MMH task i.e. Worker’s Age, Work Time Duration and Work Place Temperature at three<br />

different levels were analyzed using Taguchi L9 orthogonal array. One response i.e. worker’s Heart Rate (HR)<br />

during the each trail <strong>of</strong> manual material handling (MMH) task was measured. For the optimization <strong>of</strong> response<br />

the signal-to-noise (S/N) ratio was obtain for each trial. The analysis <strong>of</strong> S/N ratio and raw data was done by<br />

using analysis <strong>of</strong> variance (ANOVA) to identify the optimal condition in which response was optimized. Results<br />

shows that the Worker Age was found to be the most significant factor and the Work Time Duration was found to<br />

be least significant factor for heart rate response. The percentage contributions <strong>of</strong> Worker Age, Work Time<br />

Duration and Workplace Temperature were 73.51%, 3.32% and 18.46% respectively for HR.<br />

Keywords: Signal-to-Noise ratio (S/N), Heart Rate (HR), Manual Material Handling (MMH), Taguchi technique<br />

1. Introduction<br />

Manual Material Handling (MMH) is a general process in all type <strong>of</strong> manufacturing industries under which the<br />

workers are working in different types <strong>of</strong> manufacturing tasks like lifting or lowering, carrying and holding etc.<br />

During the Manual Material Handling task the risk factors leading to musculoskeletal disorders (MSDs) are<br />

always present. Physiological measures for assessing physical stresses are necessary for measuring the<br />

expenditure <strong>of</strong> worker’s energy during the task. Two physiological measures for approximating the physical<br />

stress on the worker are used in experimental research are volume <strong>of</strong> Oxygen Intake (VO2) and Heart Rate (HR).<br />

Measurement <strong>of</strong> oxygen intake allows a reliable assessment <strong>of</strong> physical workload for activities more than five<br />

minutes are marked by Astrand (<strong>19</strong>77). By calculation the oxygen content <strong>of</strong> inhaled air at different conditions<br />

<strong>of</strong> the task a reliable estimate <strong>of</strong> energy consumption in different trails can be compared. This assessment method<br />

provides a very reliable means for assessing physical stress and can be applied to a range <strong>of</strong> physical activities. A<br />

second physiological assessment method arises from the measure <strong>of</strong> heart rate during MMH. The relationship<br />

between the two responses is roughly linear (Corlett, <strong>19</strong>86). This linear relationship appears to break down<br />

during very high range <strong>of</strong> parameters. Several studies provide examples <strong>of</strong> using heart rate and oxygen intake to<br />

assess MMH work as Wu (<strong>19</strong>98) examined the differences between symmetrical and asymmetrical MMH lifting<br />

tasks using heart rate data, VO2 and rating <strong>of</strong> perceived exertion (RPE) and concluded that the maximum<br />

acceptable weight <strong>of</strong> lift (MAWL) were significantly lower for asymmetric lifting than for symmetric lifting in<br />

the sagittal plane. The MAWL decreased with an increase in the angle <strong>of</strong> asymmetry, however, the Heart<br />

Rate, Oxygen Intake and RPE remained unchanged, lifting frequency had no significant effect on the percentage<br />

decrease in MAWL from the sagittal plane values and Both the physiological costs (Heart Rate and Oxygen<br />

Intake) and rating <strong>of</strong> perceived exertion increased with an increase in lifting frequency though maximum<br />

acceptable weight <strong>of</strong> lift decreased. Wright (<strong>19</strong>99) concluded that maximum acceptable weight carrying for twohanded<br />

tasks was significantly influenced by age for males as the younger males carried 26% more weight than<br />

older males but the females performing two-handed carrying tasks exhibited no age effect. On the other hand<br />

one-handed carrying tasks were not affected either by age or frequency for both males and females. Marras<br />

(<strong>20</strong>05) concluded in his research by taking factors <strong>of</strong> asymmetric lift, different loads and different frequencies in<br />

eight hour shift that spine load increased after the first two hours <strong>of</strong> lifting exposure regardless <strong>of</strong> lifting<br />

frequency. Maiti (<strong>20</strong>06) found the effect <strong>of</strong> lifting parameters and their interactions on heart rate and also<br />

remarked that the interaction effects between different lifting parameters should be considered in addition to the<br />

effects <strong>of</strong> individual lifting parameters. Wu (<strong>20</strong>06) examined the effects <strong>of</strong> container width, carrying rate, and<br />

distance on the maximum acceptable weight carried (MAWC) by analyze the heart rate and rating <strong>of</strong> perceived<br />

exertion (RPE) to a 1-hour work period <strong>of</strong> carrying tasks. Ciriello (<strong>20</strong>07) studied the effect <strong>of</strong> high lifting<br />

frequency on maximum acceptable weights <strong>of</strong> lifting. Sean (<strong>20</strong>07) in a study on material handling capacity in<br />

different postures examined that heart rate was not significantly affected by posture, but was increased in<br />

asymmetric conditions, lifting/lowering and to/from the high shelf .Oxygen intake was increased by working<br />

posture, lifting/lowering asymmetrically, and when performing the task to the high shelf. Fredericks (<strong>20</strong>08)<br />

690


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

conducted a study <strong>of</strong> metal pouring operation done in the small foundries by measuring the oxygen intake, heart<br />

rate, and blood pressure. Li (<strong>20</strong>08) concluded that both task frequency and lifting and lowering heights influence<br />

oxygen intake, heart rate and the RPE. Julien (<strong>20</strong>10) concluded that the human Power output in the heat (35ºC)<br />

was reduced from <strong>20</strong> min onwards compared with exercise in the thermo neutral (<strong>20</strong>ºC) condition and also<br />

remarked that the rise in cardiovascular strain was associated with reductions in sustainable power output, peak<br />

oxygen intake and maximal power output in the heat. Singh (<strong>20</strong>10) in his research on effect <strong>of</strong> mechanical lifting<br />

aid on lifting task concluded that the mechanical lifting aid proved to be beneficial as it not only saves task time<br />

by increasing frequency <strong>of</strong> lifting but also it reduces the physical stress associated with the worker by bringing<br />

lifting index within limits as per revised NIOSH lifting equation. Snook (<strong>20</strong>10) in his research study concluded<br />

that the hot environment significantly reduced work load, and significantly improved heart rate and they also<br />

concluded that the worker can compensates for increases in heat stress by reducing his work load. Batish (<strong>20</strong>11)<br />

in his experimental study concluded that Lift frequency was the most significant factor in the MMH task and<br />

operator and horizontal distance were the least significant factors by using response factors as volume <strong>of</strong> Oxygen<br />

Intake and Heart Rate. In this study the aim was to evaluate the main effects <strong>of</strong> Age, Work time duration, Work<br />

place Temperature on the heart rate and oxygen intake <strong>of</strong> workers involved in lifting tasks. Oxygen intake and<br />

heart rate during MMH tasks already had been measured by researchers but with less extent for North Indian<br />

workers involved in such task. The physiological characteristics and body metabolism <strong>of</strong> north Indian male<br />

workers is different as compared with others. Moreover the environmental conditions are different in which such<br />

lifting tasks cause different amount <strong>of</strong> exertion and stress. The effect <strong>of</strong> worker’s Age, Work Time Duration and<br />

Workplace Temperature on the volume <strong>of</strong> oxygen intake and heart rate <strong>of</strong> workers involved in continuous lifting<br />

or lowering tasks had been studied and attempts had been made to generate optimal conditions by analyzed the<br />

response parameters using ANOVA.<br />

2. Material and Methods<br />

2.1 Workers details:<br />

Three male workers having at least 5 years <strong>of</strong> industrial experience <strong>of</strong> MMH tasks participated in the laboratory<br />

study. There were free from any sort <strong>of</strong> illness and back pain. The participants were instructed properly about the<br />

test procedures prior to performing them and also anthropometric measurements <strong>of</strong> all three workers were taken.<br />

An informed consent form was signed by each participant. The anthropometric details <strong>of</strong> the workers are given in<br />

Table 1.<br />

Table: 1 Anthropometric Details <strong>of</strong> the workers<br />

Subject Age (Years) Height (cm) Weight (kg)<br />

1 <strong>20</strong> 165.3 63.5<br />

2 30 172.7 70.9<br />

3 40 169.4 67.6<br />

Mean 30 169.1 67.3<br />

2.2 Equipment Details:<br />

COSMED pulmonary function equipment Fitmate Pro was used to measure the heart rate. This equipment<br />

consists <strong>of</strong> a POLAR heart rate belt for measuring the Heart rate (beats per minute). When belt was put around<br />

the chest <strong>of</strong> the subject and one end <strong>of</strong> a probe for transferring the signal from human heart to machine was<br />

attached to body <strong>of</strong> worker and other end was connected to the main unit and it produces a variation in heart rate<br />

with respect to time.<br />

2.3 Experimental method and analysis <strong>of</strong> data:<br />

In the present study L9 Taguchi orthogonal array was used (Fisher, <strong>19</strong>25). The response parameter i.e. the Heart<br />

Rate (HR) data was measured using COSMED pulmonary function equipment. The responses were in the form<br />

<strong>of</strong> curves for heart rate with respect to time. The analysis was done to determine the effect <strong>of</strong> the various<br />

parameters (Worker Age, Work Time Duration and Workplace Temperature). The quality characteristic for HR<br />

was taken as smaller-the-better type. The S/N ratio for the Smaller-the-better type <strong>of</strong> response can be computed<br />

as:<br />

S/NSB = Where, Yk, k= 1, 2, …, n are the response values under the trial<br />

conditions repeated R times.<br />

691


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Analysis <strong>of</strong> variance (ANOVA) was performed to identify the process parameters that were statistically<br />

significant. With the ANOVA analyses, the optimal combination <strong>of</strong> the process parameters was predicted.<br />

Worker Age, Work Time Duration and Workplace Temperature were selected for investigating the effect on HR<br />

during MMH task. Vertical Height, lifting Frequency, Box Size and Weight <strong>of</strong> Lifting Load were kept constant<br />

during the entire experimentation. The design parameters as well as their chosen levels considered for the<br />

Taguchi experiment are listed in Table 2.<br />

Table 2: Parameters with their levels<br />

Parameters<br />

Levels Age <strong>of</strong> Worker<br />

(Years)<br />

Work Time Duration<br />

(Minutes)<br />

Workplace Temperature<br />

(Degree Centigrade)<br />

Level 1 <strong>20</strong> 9 <strong>20</strong><br />

Level 2 30 13 27<br />

Level 3 40 17 34<br />

Fixed Parameters<br />

Vertical Height 90 cm, Lifting Frequency 4 lifts/minute, Box size 40*40*<strong>20</strong> cm and<br />

weight <strong>of</strong> lifting load 15 Kg<br />

The basic objective <strong>of</strong> the study was to evaluate the effect <strong>of</strong> parameters associated with a lifting task to<br />

minimize the risk <strong>of</strong> injuries caused during MMH task. The desired responses from such a study would be Heart<br />

Rate during the lifting/lowering task. Based on the literature review and the pilot experiment results Workers<br />

Age, Working Time duration, and Workplace Temperature were identified for this study. Three male workers <strong>of</strong><br />

age <strong>20</strong>, 30 and 40 years had participated in this study. All three selected male workers were not having any type<br />

<strong>of</strong> disease or health problems. The experiments were conducted at each trial conditions as given in Table 3. For<br />

each trial, experiments were replicated (three times). For each experiment free style lifting technique was used.<br />

Pebbles were used as the lifting material. The responses <strong>of</strong> heart rate during all nine trails each repeated three<br />

times are given in Table 3 along with its S/N ratio considering as smaller-the-better.<br />

Table 3: Experimental Design and Responses <strong>of</strong> each Trial<br />

Trials Parameters Responses <strong>of</strong> Heart Rate<br />

Age (Years)<br />

Work Time<br />

Duration (Minutes)<br />

Workplace<br />

temperature<br />

(Degree Centigrade)<br />

R1 R2 R3<br />

S/N Ratio<br />

1 <strong>20</strong> 9 <strong>20</strong> 88.03 90.15 87.4 -38.94<br />

2 <strong>20</strong> 13 27 95.6 91.22 93.23 -39.40<br />

3 <strong>20</strong> 17 34 110.22 108.38 112.27 -40.85<br />

4 30 9 27 115.31 113.16 116.31 -41.21<br />

5 30 13 34 135.48 128.78 131.5 -42.41<br />

6 30 17 <strong>20</strong> 118.12 114.14 110.36 -41.15<br />

7 40 9 34 132.01 135.26 127.8 -42.39<br />

8 40 13 <strong>20</strong> 122.78 125.11 1<strong>20</strong>.65 -41.79<br />

9 40 17 27 133.28 135.21 128.65 -42.44<br />

TOTAL 1050.83 1041.41 1028.17 -370.59<br />

Mean HR T = 115.57<br />

692


3. Results and Discussions<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3.1. HR Measure:<br />

The average values <strong>of</strong> heart rate (HR) and the S/N ratio for each parameter at level L1, L2 and L3 were<br />

calculated and are given in Table 4. These values have been plotted in Figure 1 (a, b, c). From the response<br />

curves for HR at different levels <strong>of</strong> the process parameters, it was observed that as the value <strong>of</strong> parameters<br />

increases the HR <strong>of</strong> the worker also increases for MMH task figure 1.<br />

Table 4: Average Values and Main effects <strong>of</strong> Heart Rate<br />

Level Worker Age Work Time Duration Work Place Temperature<br />

Raw Data S/N Ratio Raw Data S/N Ratio Raw Data S/N Ratio<br />

L1 97.39 -39.73 111.71 -40.85 108.53 -40.63<br />

L2 1<strong>20</strong>.35 -41.59 116.03 -41.<strong>20</strong> 113.55 -41.01<br />

L3 128.97 -42.21 118.96 -41.48 124.63 -41.88<br />

L2-L1 22.96 -1.86 4.32 -0.35 5.02 -0.39<br />

L3-L2 8.62 -0.62 2.62 -0.28 11.08 -0.87<br />

DIFFERENCE -14.34 1.24 -1.40 0.07 60.6 -0.48<br />

Figure 1: Effect <strong>of</strong> process parameters on Heart Rate and S/N ratio (main effects)<br />

Figure: 1(a) Effect <strong>of</strong> Worker Age on raw data and S/N ratio<br />

Figure: 1(b) Effect <strong>of</strong> Work Time duration on raw data and S/N ratio<br />

693


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure: 1(c) Effect <strong>of</strong> Workplace Temperature on raw data and S/N ratio<br />

Figure 1(a, b, c) depicts the change in Heart Rate by the worker during MMH task with respect to the Worker<br />

Age, work time duration and workplace temperature. From figure 1(a) it was concluded that as the age <strong>of</strong> worker<br />

increases; the Heart Rate <strong>of</strong> the worker also increases during MMH task. The slope <strong>of</strong> curve for the age range <strong>of</strong><br />

<strong>20</strong> to 30 was more than between 30 to 40 years range, which means that the HR increases continuously with age<br />

but with a large extent up to age <strong>of</strong> 30 and after that somewhat less extent as compare to previous one. Wright<br />

(<strong>19</strong>99) also concluded that younger workers can carry more load than that <strong>of</strong> older workers. It can be observed<br />

from Figure 1(b) that with the increase in the work Time Duration the HR <strong>of</strong> the worker also increases. The slope<br />

<strong>of</strong> curve between Work Time Duration range <strong>of</strong> 9 to 13 minutes was more than the slope between 13 to 17<br />

minutes work time duration range. Marras (<strong>20</strong>05) also concluded that the increase in time duration will affects<br />

the human comfort. From figure 1(c) it can be seen that as the temperature <strong>of</strong> the work place increases the HR<br />

also increases. For the Temperature range between <strong>20</strong>°C to 27°C the change in slope <strong>of</strong> HR was less as compare<br />

to range between 27°C to 34°C, which implies that the high temperature will have a high effect on the human<br />

working capability and HR <strong>of</strong> worker. For the temperature range between <strong>20</strong>°C to 27°C the HR increases with<br />

less extent as compare to range <strong>of</strong> 27°C to 34°C. It was observed that the low temperature zone (<strong>20</strong>°C to 27°C)<br />

was comfortable zone for MMH than the high temperature zone (27°C to 34°C). Snook (<strong>20</strong>10) also concluded<br />

that increase in temperature will effect on increase in HR <strong>of</strong> Worker during MMH.<br />

Table 5: ANOVA S/N (HR)<br />

Source SS DOF V F-Ratio SS' P (%)<br />

Worker Age 9.96 2 4.98<br />

*<br />

59.75 9.79 74.12<br />

Work Time Duration 0.61 2 0.3 3.64 0.44 --<br />

Work Place Temperature 2.48 2 1.24 14.87 -- --<br />

Error 0.17 2 0.08 -- 3.42 25.88<br />

Total 13.21 8 -- -- 13.2 100<br />

*Significant at 95% confidence level, P (%): Percentage <strong>of</strong> contribution; F Table value: <strong>19</strong>,<br />

SS: Sum <strong>of</strong> squares; DOF: Degree <strong>of</strong> Freedom; V: Variance; SS’: Pure Sum <strong>of</strong> Squares<br />

Table 6: ANOVA RAW (HR)<br />

Source SS DOF V F-Ratio SS' P (%)<br />

Worker Age 4797.28 2 2398.64<br />

*<br />

<strong>20</strong>4.18 4773.79 73.51<br />

Work Time Duration 239.13 2 1<strong>19</strong>.56<br />

*<br />

10.18 215.63 3.32<br />

Work Place Temperature 1222.42 2 611.21<br />

*<br />

52.03 1<strong>19</strong>8.92 18.46<br />

Error 234.96 <strong>20</strong> 11.75 -- 30.544 4.71<br />

Total 6493.79 26 -- -- 6493.78 100<br />

*Significant at 95% confidence level, P (%): Percentage <strong>of</strong> contribution; F Table value: 3.49,<br />

SS: Sum <strong>of</strong> squares; DOF: Degree <strong>of</strong> Freedom; V: Variance; SS’: Pure Sum <strong>of</strong> Squares<br />

694


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

As the HR is the ‘smaller-the-better’ type quality characteristic, smaller the values <strong>of</strong> HR were sought. From<br />

Figure 1(a) to (c) it was seen that the first level <strong>of</strong> each <strong>of</strong> the parameters, i.e., (A1), (B1) and (C1) may provide<br />

minimum value <strong>of</strong> HR. As in the case <strong>of</strong> parameters A, B and C the smallest value <strong>of</strong> mean response<br />

corresponded to the largest value <strong>of</strong> S/N ratio. In order to study the significance <strong>of</strong> the process parameters<br />

towards the HR, ANOVA was performed. The pooled versions <strong>of</strong> ANOVA <strong>of</strong> the S/N data and the raw data for<br />

HR are given in Tables 5 and 6. From these tables, it was clear that parameters A, B and C significantly affect<br />

both the mean and the variation in the HR values The percentage contributions <strong>of</strong> Worker Age, Work Time<br />

Duration and Workplace Temperature were 73.51%, 3.32% and 18.46% respectively for HR (Table 6).<br />

3.1.1. Estimation <strong>of</strong> optimum performance characteristics<br />

The optimum value <strong>of</strong> Heart Rate was predicted at the selected levels <strong>of</strong> significant parameters A1, B1 and C1<br />

(Table 4). The estimated mean <strong>of</strong> the response characteristic was determined as<br />

Heart Rate =A1+ B1 + C1 - 2* T<br />

Where,<br />

T : Overall mean <strong>of</strong> HR= 115.57 (Table 3)<br />

A1: Average HR at the First level <strong>of</strong> Worker Age = 97.39 (Table 4)<br />

B1: Average HR at the First level <strong>of</strong> Work Time Duration = 111.71 (Table 4)<br />

C1: Average HR at the First level <strong>of</strong> Workplace Temperature = 108.53 (Table 4)<br />

Substituting the values <strong>of</strong> various terms in the above equation,<br />

HR = 97.39 + 111.71 + 108.53 – (2* 115.57) = 86.49<br />

The 95% confidence interval <strong>of</strong> confirmation experiments CICE and <strong>of</strong> population CIPOP was calculated by<br />

using the following equations (Walia, <strong>20</strong>06)<br />

And<br />

Where,<br />

CI<br />

CE<br />

=<br />

F<br />

α<br />

CI =<br />

POP<br />

(1,f<br />

e<br />

F<br />

α<br />

) V<br />

e<br />

(1,f<br />

n<br />

⎡ 1<br />

⎢<br />

⎣n<br />

eff<br />

e<br />

eff<br />

) V<br />

e<br />

+<br />

1 ⎤<br />

⎥<br />

R ⎦<br />

Fα (1, fe): The F ratio at the confidence level <strong>of</strong> (1 – α) against DOF <strong>of</strong> mean= 1 and fe = error DOF =<br />

<strong>20</strong><br />

So, F0.05 (1, <strong>20</strong>) = 4.35 (Tabulated F value)<br />

N: Total number <strong>of</strong> results = 27 (trails = 9, repetition = 3)<br />

R: Sample size for confirmation experiments = 3<br />

Ve: Error variance = 11.75 (Table 6),<br />

= 3.86<br />

So,<br />

CICE = ±5.50<br />

CIPOP = ±3.64<br />

The predicted optimal range for a confirmation runs <strong>of</strong> three experiments is:<br />

Mean HR- CICE


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4. Conclusions<br />

1) As the Age <strong>of</strong> Worker increases the VO2 Intake and Heart Rate <strong>of</strong> worker were increases for the same type<br />

<strong>of</strong> lifting task. So based on the results it’s recommended that the lower age worker should be preferred for<br />

the MMH task.<br />

2) With the increase in the time duration for MMH task, VO2 intake and HR increases, so proper rest break<br />

should be given between the MMH task and continuity for lifting task for longer time should be avoided.<br />

3) Based on the results the lifting task at higher temperature results in higher physiological strains, so MMH<br />

task at higher temperature should be avoided.<br />

References<br />

1) Astrand Per-Ol<strong>of</strong> and Rodahl Kaare (<strong>19</strong>77),“Textbook <strong>of</strong> work physiology (2 nd ed.)”, McGraw-Hill Book<br />

Company<br />

2) Batish Ajay, Bhattacharya Anirban and Singh Baljeet (<strong>20</strong>11), “Multi-Response Optimization and Empirical<br />

Modeling <strong>of</strong> Cardiopulmonary Responses during Manual Lifting Tasks”, Human Factors and Ergonomics in<br />

Manufacturing & Service Industries, vol.21 (1), pp. 29–43<br />

3) Ciriello Vincent M (<strong>20</strong>05), “The effects <strong>of</strong> box size, vertical distance, and height on lowering tasks for<br />

female industrial workers”, International Journal <strong>of</strong> Industrial Ergonomics, vol. 35, pp. 857–863<br />

4) Ciriello Vincent M (<strong>20</strong>07), “The effects <strong>of</strong> container size, frequency and extended horizontal reach on<br />

maximum acceptable weights <strong>of</strong> lifting for female industrial workers”, Applied Ergonomics, vol. 38, pp.<br />

340–351<br />

5) Corlett N., Wilson J. and Manenica I. (Eds.) (<strong>19</strong>86), “The ergonomics <strong>of</strong> working postures: models, methods<br />

and cases”, Philadelphia, PA: Taylor and Francis.<br />

6) Fredericks K. Tycho, Kumar R. Anil & Karim Sadat (<strong>20</strong>08), “An ergonomic evaluation <strong>of</strong> a manual metal<br />

pouring operation”, International Journal <strong>of</strong> Industrial Ergonomics, vol. 38, pp.182–<strong>19</strong>2.<br />

7) Julien D. Periard, Matthew N. Cramer, Phillip G. Chapman, Corinne Caillaud and Martin W. Thompson<br />

(<strong>20</strong>10), “Cardiovascular strain impairs prolonged self-paced exercise in the heat”, Experimental Physiology,<br />

vol. 96(2), pp. 134–144, www.ep.physoc.org<br />

8) Li Kai Way, Yu Ruifeng, Gao Yang, Maikala Rammohan V and Tsai Hwa-Hwa (<strong>20</strong>08), “Physiological and<br />

perceptual responses in male Chinese workers performing combined manual materials handling tasks”,<br />

International Journal <strong>of</strong> Industrial Ergonomics, pp. 1-6<br />

9) Maiti Rina and Bagchi Tapan P (<strong>20</strong>06), “Effect <strong>of</strong> different multipliers and their interactions during manual<br />

lifting operations”, International Journal <strong>of</strong> Industrial Ergonomics, vol. 36, pp. 991–1004<br />

10) Marras W.S, Parakkat J, Chany A.M, Yang G, Burr D and Lavender S.A (<strong>20</strong>06), “Spine loading as a<br />

function <strong>of</strong> lift frequency, exposure duration and work experience”, www.sciencedirect.com,Clinical<br />

Biomechanics, vol. 21, pp. 345–352<br />

11) Sean Gallagher(<strong>20</strong>07), “Acceptable weights and physiological costs <strong>of</strong> performing combined manual<br />

handling tasks in restricted postures” (Abstract), Ergonomics, vol. 34(7), pp. 939-952<br />

12) Singh Sarbjeet and Kumar Sunand (<strong>20</strong>10), “The Effect <strong>of</strong> Mechanical Lifting Aid in Single Task Lifting<br />

using Revised NIOSH Lifting Equation”, International Journal <strong>of</strong> Advanced Engineering <strong>Technology</strong>, vol.<br />

1(2), pp.165-172<br />

13) Snook Stover H and Ciriello Vincent M (<strong>19</strong>74), “The Effects <strong>of</strong> Heat Stress on ManualHandlingTasks”,<br />

American Industrial Hygiene Association Journal, vol. 35(11), pp. 681-685<br />

14) Walia Ravinder Singh (<strong>20</strong>06), “Ph. D Thesis : Development and Investigation in Centrifugal Force assisted<br />

Abrasive Flow Machining Process”, IIT Roorkee<br />

15) Wright Ursula R and Mittal Anil (<strong>19</strong>99), “Maximum Weights <strong>of</strong> Handling Acceptable to People Aged 55–<br />

74 Years”, Journal <strong>of</strong> Occupational Rehabilitation, vol. 9(1), pp. 15-21<br />

16) Victor M. Reis, Roland Vanden Tillaarand Mario C Marques(<strong>20</strong>11), “Higher precision <strong>of</strong> heart rate<br />

compared with VO2 to predict exercise intensity in endurance-trained runners”, Journal <strong>of</strong> Sports <strong>Science</strong><br />

and Medicine, vol.10, pp.164-168<br />

17) Wu wei-pi (<strong>19</strong>98), “Psychophysically determined symmetric and asymmetric lifting capacity <strong>of</strong> Chinese<br />

males for one hour's work shifts ”,http://dx.doi.org/10.1016/S0169-8141(99)00055-4<br />

18) Wu S. P. (<strong>20</strong>06), “Psychophysically determined 1-h load carrying capacity <strong>of</strong> Chinese females”,<br />

International Journal <strong>of</strong> Industrial Ergonomics, vol. 36, pp. 891–899.<br />

<strong>19</strong>) Yoopat Pongjan, Toicharoen Ponkamon, Boontong Sirada, Glinsukon Thirayudh, Vanwonerghem<br />

Kamieland, Louhevaara Veikko (<strong>20</strong>02), “Cardiorespiratory capacity <strong>of</strong> Thai workers in different age and job<br />

categories”, Journal for Physiological Anthropology and Applied Human <strong>Science</strong>s, vol.21(2), pp. 121-128.<br />

696


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

MANUAL MATERIAL HANDLING TASKS PROCESS OPTIMIZATION<br />

USING PHYSIOLOGICAL TECHNIQUE<br />

Jaswinder Singh 1 , P Kalra 2 , R S Walia 3<br />

1<br />

Research Scholar, Department <strong>of</strong> Production Engineering, PEC <strong>University</strong> <strong>of</strong> <strong>Technology</strong>, Chandigarh, UT<br />

2 Pr<strong>of</strong>essor, Department <strong>of</strong> Production Engineering, PEC <strong>University</strong> <strong>of</strong> <strong>Technology</strong>, Chandigarh, UT<br />

3<br />

Associate Pr<strong>of</strong>essor, Department <strong>of</strong> Production Engineering, PEC <strong>University</strong> <strong>of</strong> <strong>Technology</strong>, Chandigarh, UT<br />

e-mail:: waliaravinder@yahoo.com<br />

Abstract<br />

The present study follow a physiological approach to evaluate an aerobic capacity or metabolic expenditure<br />

capabilities during manual material handling (MMH) tasks on Indian male workers. This study involves six<br />

independent lifting variables Handle, Box size, Worker, Vertical distance, Weight, Horizontal position. The<br />

selected response/dependent variable is heart rate. Using the Taguchi L18 Orthogonal array (OA) was applied to<br />

evaluate the effect <strong>of</strong> these lifting parameters and plots <strong>of</strong> raw and signal- to- noise data used for compute the<br />

significance and their effect on the response parameter. The analysis <strong>of</strong> variance (ANOVA) has been used to<br />

evaluate an optimal result <strong>of</strong> the parameter. The conformation experiments have validated an optimal level <strong>of</strong><br />

variable.<br />

Keywords: Physiological approach; Manual material handling (MMH) task; Heart rate<br />

1. Introduction<br />

Manual Material Handling (MMH) includes a wide variety <strong>of</strong> activities such as loading and unloading boxes or<br />

carbons, removing materials from a conveyor belt, stacking items in a warehouse, etc. As a result, workers may<br />

suffer from musculoskeletal disorders (MSDs). Various short and long term health effects can be attributed to<br />

MMH. Manual materials handling (MMH) tasks are very common in workplaces. The major causes <strong>of</strong> severe<br />

industrial injury due the manual material handling (MMH) (Ciriello, <strong>20</strong>05). More than a quarter <strong>of</strong> all injuries<br />

related to industrial work are directly associated with MMH activities was estimated. Many <strong>of</strong> these injuries arise<br />

from improper handling <strong>of</strong> materials. One <strong>of</strong> the most widely accepted approaches in designing MMH tasks is to<br />

design the job so as not to exceed the capabilities <strong>of</strong> the materials handlers. In order to control the frequency,<br />

severity and tremendous economic losses <strong>of</strong> these injuries, a variety <strong>of</strong> research and design guidelines have been<br />

proposed (Waters et al., <strong>19</strong>93). The MMH tasks are very common in manufacturing and construction sites, and<br />

are one <strong>of</strong> the major contributors for musculoskeletal symptoms for workers engaged in Manual material<br />

handling (MMH . National Institute for Occupational Safety and Health (NIOSH) developed an equation in <strong>19</strong>81<br />

after recognizing the growing problem <strong>of</strong> work related back injuries and revised (in <strong>19</strong>91) to uses lifting<br />

multipliers (factors) to calculate corresponding recommended weight limits for particular task(Waters et al.,<br />

<strong>19</strong>93). Maiti, et.al, <strong>20</strong>06 studied the effect <strong>of</strong> lifting parameters and their interactions on heart rate and concluded<br />

that the interaction effects between lifting parameters must be considered in addition to the effects <strong>of</strong> individual<br />

lifting parameters. The maximum acceptable weights (MAW) lift having a significant effect due to the high<br />

lifting frequency (<strong>20</strong> lifts/min) (Ciriello, <strong>20</strong>06).For several decades the elimination or at least a reduction in the<br />

risk <strong>of</strong> injury due to lifting tasks has been a topic <strong>of</strong> interest in many fields <strong>of</strong> research. Measurements <strong>of</strong> heart<br />

rate and whole body oxygen consumption can be used to predict the maximum aerobic work capacity for a given<br />

type <strong>of</strong> work. A person’s aerobic capacity depends upon an efficient cardiovascular system. Aerobic capacity is<br />

considered to be the best single measure index <strong>of</strong> overall physical fitness (Sharkey, <strong>19</strong>91). Heart rate is affected<br />

by heat, humidity, and emotional and psychological stress. If these are present in significant amounts, the linear<br />

relationship between heart rate and oxygen consumption will be affected (Astrand and Rodahl, <strong>19</strong>77). A person’s<br />

maximum aerobic work capacity is the maximum amount <strong>of</strong> work that can be done when there is enough oxygen<br />

to supply the muscles. Aerobic work capacity is an important parameter to evaluate the suitability <strong>of</strong> a given<br />

work load. The purpose <strong>of</strong> this study to evaluate physical work capacity (PWC, a measurement <strong>of</strong> metabolic<br />

expenditure capabilities in terms <strong>of</strong> heart rate) during manual lifting tasks on Indian male workers using a<br />

physiological approach.<br />

2. MATERIAL AND METHODS<br />

2.1 Workers details:<br />

The study was conducted on three industrial workers <strong>of</strong> age 22-26. The full procedure <strong>of</strong> the experiment was<br />

explained to the workers. And it was confirmed that the workers are healthy and free from musculoskeletal<br />

disorders or cardiovascular problem.<br />

697


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 1. Anthropometric Data <strong>of</strong> workers<br />

Classifications Age Weight Height<br />

Range 22-26 56-65 160-165<br />

Mean 24 60.5 162.5<br />

2.2 Experimental apparatus:<br />

COSMED pulmonary function equipment Fitmate Pro was used to measure the heart rate. This equipment<br />

consists <strong>of</strong> a POLAR heart rate belt for measuring the Heart rate (beats per minute). When belt was put around<br />

the chest <strong>of</strong> the subject and one end <strong>of</strong> a probe for transferring the signal from human heart to machine was<br />

attached to body <strong>of</strong> worker and other end was connected to the main unit and it produces a variation in heart rate<br />

with respect to time. The test was conducted <strong>of</strong> three different heights 1= floor to knee height. 2= floor to waist<br />

height, 3=floor to shoulder height. Three different size boxes were made (description <strong>of</strong> the boxes are shown in<br />

the table below) with two handle positions on them. First position is on the top (5cm away from) the top edge<br />

and second at the mid <strong>of</strong> the box. The boxes were made <strong>of</strong> 1cm thick wood board. While making the boxes<br />

Drury’s guidelines were kept in mind. The sharp edges and corners were removed for the safety from the boxes<br />

as shown in figure 1.<br />

Table 2. Box’s specifications<br />

Box sixes<br />

Handle positions<br />

25*25*25 Upper<br />

35*35*35 Lower<br />

45*45*45 ----<br />

Figure1. Isometric view <strong>of</strong> boxes used in experiments<br />

3. Experimental procedure:<br />

As in previous studies it has been found that most difficult position in manual lifting is lifting from the floor<br />

height. And lifting from floor could be up to knee, waist or shoulder height mainly. So keeping these information<br />

in mind these three handling position were decided to check the optimal position <strong>of</strong> the handle. Two handle<br />

positions were used for the experiment one at top and other at mid <strong>of</strong> the box. Optimality <strong>of</strong> the handle was<br />

checked at three different horizontal heights and three different weights <strong>of</strong> three different size boxes. The detail<br />

<strong>of</strong> the box size, handle position, vertical distance, weights and horizontal distance are given in the table below.<br />

Taguchi’s L18 technique was used to perform the experiments. 18 experiments were conducted with different<br />

combinations <strong>of</strong> above given parameters and variables. And the frequency <strong>of</strong> lifting was fixed in all experiments<br />

as 6/min and each experiment was conducted for the time <strong>of</strong> 10mins. As Grandjean (<strong>19</strong>85) and Green et al.<br />

(<strong>19</strong>86) stated that HR reflects an increase in both mental and physical workloads. And Dutta & Taboun (<strong>19</strong>89)<br />

shown that HR consumption varies when weight handled varies. So HR <strong>of</strong> workers was measured to check the<br />

effect <strong>of</strong> above parameters and variables on the workers. Then the workers were asked to lift the box and place it<br />

up given height defined by Taguchi L18 techniques. The experiments were conducted at room temperature. Each<br />

experiment was repeated for three times to check the accurate value. The rest <strong>of</strong> 45 min was given to worker<br />

after performing the experiment. The worker was asked to lift the boxes free style and without any rush. No<br />

moral support was given to the worker during the experiments.<br />

698


S.<br />

No.<br />

A=<br />

Handle<br />

B= Box<br />

size<br />

C=<br />

Worker<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 3. Parameters with Taguchi’s L18<br />

D=Vertical<br />

distance<br />

E=Weight<br />

F=Horizontal<br />

position<br />

S/N<br />

Ratio<br />

Heart Rate<br />

R1 R2 R3<br />

1 1 Small 1 Knee 10 25 89.82 90.14 93.2 -39.<strong>19</strong><br />

2 1 Small 2 waist <strong>20</strong> 30 108.15 100.01 103.67 -40.34<br />

3 1 Small 3 Shoulder 30 35 101.56 98.32 116.64 -40.49<br />

4 1 Medium 1 Knee <strong>20</strong> 30 97.53 98.64 99.21 -39.87<br />

5 1 Medium 2 waist 30 35 117.06 1<strong>20</strong>.46 121.24 -41.55<br />

6 1 Medium 3 Shoulder 10 25 110.62 109.39 108.37 -40.79<br />

7 1 Large 1 waist 10 35 102.15 106.45 104.53 -40.37<br />

8 1 Large 2 Shoulder <strong>20</strong> 25 127.72 126.41 1<strong>20</strong>.11 -41.92<br />

9 1 Large 3 Knee 30 30 110.43 108.<strong>19</strong> 100.02 -40.53<br />

10 2 Small 1 Shoulder 30 30 112.52 111.84 118.74 -41.17<br />

11 2 Small 2 Knee 10 35 102.34 107.48 104.46 -40.41<br />

12 2 Small 3 waist <strong>20</strong> 25 102.16 103.29 100.13 -40.16<br />

13 2 Medium 1 waist 30 25 109.91 107.78 112.29 -40.83<br />

14 2 Medium 2 Shoulder 10 30 118.69 116.07 117.03 -41.38<br />

15 2 Medium 3 Knee <strong>20</strong> 35 105.38 109.43 107.57 -40.63<br />

16 2 Large 1 Shoulder <strong>20</strong> 35 108.59 112.48 111.96 -40.91<br />

17 2 Large 2 Knee 30 25 114.89 108.11 109.01 -40.88<br />

18 2 Large 3 waist 10 30 110.31 114.28 111.14 -40.98<br />

4. Results and Discussion:<br />

Taguchi recommends the use <strong>of</strong> S/N ratio to measure the quality characteristics deviating from the desired<br />

values. The quality characteristic for HR and for VO 2 it is taken as “lower-the better”. The S/N ratio for the<br />

“lower-the-better” <strong>of</strong> response can be computed (Ross, <strong>19</strong>88; Roy, <strong>19</strong>90) as:<br />

Where, Y j (j= 1, 2, 3…….n) is the response value under the trail condition repeated R times.<br />

Analysis <strong>of</strong> Variance (ANOVA) is performed to identify the process parameters that are statistically significant.<br />

With the S/N and ANOVA analyses, the optimal combination <strong>of</strong> the process parameters is predicted. The design<br />

parameters as well as their chosen levels considered for Taguchi experiments are listed in Table 4.<br />

Table 4. Process parameters and their values at different levels<br />

Symbols Parameters Level 1 Level 2 Level 3<br />

A Handle Upper Lower --<br />

B Box size 25*25*25(Small) 35*35*35(Medium) 45*45*45(Large)<br />

C Worker 1 2 3<br />

D Vertical distance Knee Waist Shoulder<br />

E Weight 10 15 <strong>20</strong><br />

F Horizontal position <strong>20</strong> 25 30<br />

Frequency = 6 repetition /min, Temperature = 32±2°C.<br />

4.1 Effects on Heart Rate:<br />

The optimal combination levels <strong>of</strong> the lifting parameters correlated with the handle position on the box that<br />

yielded lower HR are determined by analyzing the S/N ratios and raw data values. Table 5 shows the<br />

experimental conditions using Taguchi L18 orthogonal array and measured values <strong>of</strong> HR for three different trial<br />

runs along with corresponding S/N ratio. The effect <strong>of</strong> process parameters on HR for both the raw data and S/N<br />

ratio are analysed using ANOVA. The optimum combination levels <strong>of</strong> process parameters are determined from<br />

the raw data and S/N ratio response graphs plotted in Figures 2-7. The average value <strong>of</strong> the raw data and S/N<br />

ratio for parameter at level L1, L2 and L3 are calculated and are given in Table 5 and 6 respectively. The pooled<br />

versions <strong>of</strong> ANOVA <strong>of</strong> the raw data and S/N ratio for VO2 are given in Table 7 and 8.<br />

699


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 2 shows that type <strong>of</strong> handle is a significant parameter affecting the HR. High HR is observed in case <strong>of</strong><br />

lower handle position, the reason for this may be that while lifting from floor the worker has to bend more than<br />

that <strong>of</strong> upper handle position so worker has to exert much force as compared to upper handle position. As J.M.<br />

Deeb et al. (<strong>19</strong>85) have shown that Handle-position effects on forces exerted, heart rate and psychophysical<br />

indices were large compared with the effect produced by a 25% change in container weight. C.G. Drury (<strong>19</strong>80)<br />

stated that. The effect <strong>of</strong> handles was equivalent to a weight change <strong>of</strong> 1-2 kg for Heart Rate and Rated<br />

Perceived Exertion, but much higher (2-14 kg) for Body Part Discomfort measures.<br />

Table 5. Main effects <strong>of</strong> HR (Raw data)<br />

LEVEL HANDLE BOX SIZE WORKER VERTICAL DISTANCE WEIGHT<br />

HORIZONTAL<br />

POSITION<br />

L1 107.04 103.58 104.88 103.10 106.47 107.96<br />

L2 109.92 110.37 113.50 108.61 107.91 108.69<br />

L3 * 111.49 107.07 113.73 111.06 108.78<br />

L2-L1 2.88 6.79 8.62 5.51 1.44 0.73<br />

L3-L2 * 1.12 -6.43 5.11 3.14 0.09<br />

DIFFERENCE 2.88 -5.67 -15.05 -0.40 1.70 -0.64<br />

L1, L2 and L3 represent levels 1, 2 and 3 respectively <strong>of</strong> parameters., L2-L1 is the average main effect when the corresponding<br />

parameter changes from level 1 to level 2. L3-L2 is the average main effect when the corresponding parameter changes from level 2 to<br />

level 3.<br />

Table 6. Main effects <strong>of</strong> HR (S/N Ratio)<br />

LEVEL HANDLE BOX SIZE WORKER<br />

VERTICAL<br />

HORIZONTAL<br />

WEIGHT<br />

DISTANCE<br />

POSITION<br />

L1 -40.56 -40.29 -40.39 -40.25 -40.52 -40.63<br />

L2 -40.82 -40.84 -41.08 -40.71 -40.64 -40.71<br />

L3 * -40.93 -40.60 -41.11 -40.91 -40.73<br />

L2-L1 -0.25 -0.55 -0.69 -0.46 -0.12 -0.08<br />

L3-L2 * -0.09 0.49 -0.40 -0.27 -0.01<br />

DIFFERENCE -0.25 0.46 1.18 0.05 -0.15 0.07<br />

L1, L2 and L3 represent levels 1, 2 and 3 respectively <strong>of</strong> parameters. L2-L1 is the average main effect when the corresponding<br />

parameter changes from level 1 to level 2. L3-L2 is the average main effect when the corresponding parameter changes from level 2<br />

to level 3.<br />

Table 7. Pooled ANNOVA (Raw data)<br />

SOURCE SS DOF V F-RATIO SS’ P%<br />

HANDLE 112.<strong>20</strong> 1.00 112.<strong>20</strong> 7.35* 96.95 2.71<br />

BOX SIZE 659.06 2.00 329.53 21.60* 628.54 17.55<br />

WORKER 722.29 2.00 361.14 23.67* 691.77 <strong>19</strong>.31<br />

VERTICAL DISTANCE 1016.06 2.00 508.03 33.29* 985.54 27.51<br />

WEIGHT 424.53 2.00 212.26 13.91* 394.01 11.00<br />

HORIZONTAL POSITION 7.27 2.00 3.63 0.24 -- --<br />

ERROR 640.89 42.00 15.26 -- 785.49 21.93<br />

TOTAL 3582.30 53.00 -- -- 3582.30 100.00<br />

*Significant at 95% confidence level, F Table (Handle position);4.07, F Table (Others);3.22; SS: Sum <strong>of</strong> squares; DOF: Degree <strong>of</strong> Freedom; ;<br />

V: Variance; SS’: Pure Sum <strong>of</strong> Squares<br />

Table 8. Pooled ANNOVA (S/N Ratio)<br />

SOURCE SS DOF V F-RATIO SS’ P%<br />

HANDLE 0.29 1.00 0.29 2.25 -- --<br />

BOX SIZE 1.44 2.00 0.72 5.55* 1.18 17.43<br />

WORKER 1.52 2.00 0.76 5.86* 1.26 18.63<br />

VERTICAL DISTANCE 2.22 2.00 1.11 8.57* 1.96 29<br />

WEIGHT 0.48 2.00 0.24 1.86 -- --<br />

HORIZONTAL POSITION 0.03 2.00 0.02 0.13 -- --<br />

ERROR 0.78 6.00 0.13 -- 2.36 34.91<br />

TOTAL 6.77 17.00 -- -- 6.77 100<br />

*Significant at 95% confidence level, F Table (Handle position);5.99, F Table (Others);5.14, SS: Sum <strong>of</strong> squares; DOF: Degree <strong>of</strong> Freedom; V:<br />

Variance; SS’: Pure Sum <strong>of</strong> Squares<br />

700


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 2. Effect <strong>of</strong> type <strong>of</strong> Handle on S/N ratio and HR<br />

Figure 3. Effect <strong>of</strong> box size on S/N ratio and HR<br />

Figure 4. Effect <strong>of</strong> worker on S/N ratio and HR<br />

Figure 5. Effect <strong>of</strong> vertical distance on S/N ratio and HR<br />

701


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 6. Effect <strong>of</strong> Weight on S/N ratio and HR<br />

Figure 7. Effect <strong>of</strong> Horizontal position on S/N ratio and HR<br />

A Figure 3 show that HR increases with increase in box size, for small box size the HR was minimum and for<br />

large box HR was higher. This occurred because big boxes are difficult to lift as compared to small boxes as<br />

Vincent M. Ciriello (<strong>20</strong>03) stated that the MAWs <strong>of</strong> lifting with the large box were significantly effected by<br />

frequency. And W.P. Neumann & L. Figure 5 shows the effect <strong>of</strong> vertical position on the lifting. The graph in<br />

figure 5 shows that by increasing the vertical height <strong>of</strong> handling position the HR also increases. Value <strong>of</strong> HR is<br />

small for vertical handling position at knee and higher for handling position at shoulder. As Tzu-Hsien Lee<br />

(<strong>20</strong>04) shown that the highest lifting strength occurred in the interval <strong>of</strong> exertion height between 10 and 45 cm<br />

while the lowest lifting strength at the exertion height <strong>of</strong> 105 cm. And Pernille K<strong>of</strong>oed Nielsen et al. (<strong>19</strong>97) have<br />

shown that The maximum load on the low back occurred at the low lifting height (36.3 and 54.4 cm) whereas the<br />

maximum load on the shoulders occurred at the high lifting height (144.9 and 163.0 cm). So for handling<br />

position at shoulder the worker feel much uncomfortable that handling position at knee as more force is required<br />

to pick and place a box on large height as compare to small height. So the HR for handling position at shoulder<br />

came higher than handling position at knee. Heavy weight is difficult to lift as compare to light weight; same can<br />

be seen in the figure 6. Figure 7 shows the effect <strong>of</strong> horizontal position on the HR. According to the graph, the<br />

value <strong>of</strong> HR is increased with increasing the horizontal distance. The value <strong>of</strong> HR was less for horizontal<br />

distance <strong>of</strong> <strong>20</strong> cm as compared to horizontal distance <strong>of</strong> 30cm. This happened because while travelling<br />

horizontally one has to exert much force than static lifting. If the horizontal distance, weight <strong>of</strong> lift and handling<br />

position all occur at the same time then it’s very important to take care <strong>of</strong> the horizontal distance. As Ciriello<br />

(<strong>20</strong>06) stated that the effects <strong>of</strong> lifting with an extended horizontal reach decreased the maximum acceptable<br />

weight (MAW) from 22% and 18% for the mid and centre lift positions.<br />

Figures 2-7 reveals that the optimum levels <strong>of</strong> parameters for HR are: upper handle (level 1), small box size<br />

(level 1), first worker (level 1), up to knee handling position (level 1), 10kg weight (level 1), <strong>20</strong>cm horizontal<br />

distance (level 1). It is clear that parameter A, B, C, D, E and F significantly affect both the mean and the<br />

variation in the HR values. The percentage contribution <strong>of</strong> each significant factor was; type <strong>of</strong> worker (27.55%),<br />

vertical handling position (<strong>19</strong>.31%), box size (17.55%), weight (11.00%), type <strong>of</strong> handle position (2.71%), and<br />

respectively.<br />

4.1.1. Estimation <strong>of</strong> Optimum Performance Characteristics for HR:<br />

The optimum value <strong>of</strong> HR (beats/min.) is predicted at the selected levels <strong>of</strong> significant parameters A1, B1, C1,<br />

D1, E1 and F1. The estimated mean <strong>of</strong> the response characteristic HR is determined (Ross <strong>19</strong>88; Roy <strong>19</strong>90) as<br />

μ HR = A1+B1+C1+D1+E1+F1-5T<br />

Where T: Overall mean <strong>of</strong> HR = 108.48, A1: Average HR at the upper handle = 107.04, B1: Average HR at the<br />

box size = 103.58, C1: Average HR at the first worker =104.88, D1: Average HR at the first handling position =<br />

103.10, E1: Average HR at the first weight = 106.47, F1: Average HR at the first horizontal position = 107.96<br />

(Ref. to Table 5 and Figures 2-7)<br />

702


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Substituting the values <strong>of</strong> various terms in the above equation<br />

μ HR = 107.04 + 103.58 + 104.88 + 103.10 + 106.47 + 107.96- 5× 108.48 = 90.73<br />

The 95% confidence interval <strong>of</strong> confirmation experiments (CICE) and <strong>of</strong> population (CI POP ) is calculated by<br />

using the following equations:<br />

Where Fα (1,fe): The F ratio at the confidence level <strong>of</strong> (1-α) against DOF 53 and error DOF fe=42, N: Total<br />

number <strong>of</strong> results = 54 (Treatment=18, Repetition=3), R : Sample size for confirmation experiments =3Ve: Error<br />

variance = 1.06, fe error DOF = 42.<br />

N efficiency = N/1+ [DOF associate in the estimate <strong>of</strong> mean response] = 4.5<br />

F0.05 (1, 42) = 4.076 (tabulated F value), So CI CE = ±5.87, CI POP = ±3.71<br />

The predicted optimal range (for a confirmation runs <strong>of</strong> three experiments) is :<br />

μ HR – CI CE < μ HR < μ HR + CI CE ; 84.86< μ HR < 96.6<br />

The 95% conformation interval <strong>of</strong> the predicted mean is as follows:<br />

μ HR – CI POP < μ HR < μ HR + CI POP ; 87.02 < μ HR < 94.44<br />

The optimal value <strong>of</strong> process parameters for the predicted range <strong>of</strong> optimal HR are as follows: Type <strong>of</strong> Handle<br />

position (A, 1st level) = upper handle, Box size (B, 1st level) = 25*25*25, Worker (C, 1st level) = 1, vertical<br />

distance (D, 1st level) = Knee, weight (E, 1st level) = 10kg, Horizontal position (F, 1st level) = <strong>20</strong>cm.<br />

4.1.2. Confirmation Experiment for HR:<br />

The purpose <strong>of</strong> confirmation experiment is to validate the conclusions drawn during the analysis phase. The<br />

three confirmation experiments for HR are conducted at the optimum setting <strong>of</strong> the process parameters. The type<br />

<strong>of</strong> handle is set at 1st level, box size at 1st level, worker at 1st level, handling position at 1st level, weight at 1st<br />

level, horizontal distance at 1st level. The Confirmation experimental value <strong>of</strong> average HR is found to be<br />

92.7/min, which fall within the 95% confidence interval <strong>of</strong> the predicted optimum parameters.<br />

5. Conclusion:<br />

In this study we found that handle plays an important role in manual material handling tasks. If the better<br />

position <strong>of</strong> the handle could be found then we can minimise the work related injuries. It was concluded from<br />

figure 2 that the value <strong>of</strong> HR was less in case <strong>of</strong> upper handle position as compare to lower handle position, so<br />

upper handle position was found more suitable to worker for lifting in present study . This happened because in<br />

case <strong>of</strong> lower handle position worker has to bend more to pick the box as compared to lower handle box position<br />

which resulted in increased HR <strong>of</strong> worker. Other facts found in experiment are given below.<br />

• The optimum levels <strong>of</strong> parameters for HR are: handle position (level 1), 25 box size (level 1), first worker<br />

(level 1), knee position vertical distance (level 1), 10kg weight (level 1) and <strong>20</strong>cm horizontal distance (level 1).<br />

• For HR, the maximum percentage contributions <strong>of</strong> four factors are worker (27.55%), vertical distance<br />

(<strong>19</strong>.31%), box size (17.55%) and weight (11.00%) respectively.<br />

• The predicted optimal range for HR was CI POP : 84.86


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

6. Drury C G. & J.M. Deeb (<strong>19</strong>86). Handle Positions and Angles in a Dynamic Lifting Task. Ergonomics 29<br />

(6), 743-768.<br />

7. Grandjean, E. (<strong>19</strong>85). Fitting the Task to the Man—An Ergonomic Approach. Taylor & Francis, London<br />

Green, M.S., Luz, Y., Jucha, E., Cocos, M., Rosenberg, N., (<strong>19</strong>86). Factors affecting ambulatory heart rate<br />

in industrial workers. Ergonomics 29, 1017–1027<br />

8. Maiti.Rina, Bagchi.Tapan.P, “Effects <strong>of</strong> different multipliers and their interactions during manual lifting<br />

operations”, International Journal <strong>of</strong> Industrial Ergonomics 36 (<strong>20</strong>06).pp 991-1004.<br />

9. National Institute for Occupational Health (NIOSH), (<strong>19</strong>81), “Work practice guide for manual lifting”,<br />

(Publication No. 81–122), Cincinnati, OH, USA: U.S. Government Printing Office.<br />

10. Pernille K<strong>of</strong>oed Nielsen (<strong>19</strong>97). The muscular load on the lower back and shoulders due to lifting at<br />

different lifting heights and frequencies Applied Ergonomics Vol. 29, No. 6, pp. 445Ð450, <strong>19</strong>98<br />

11. Tzu-Hsien Lee (<strong>20</strong>04) Static lifting strengths at different exertion heights International Journal <strong>of</strong> Industrial<br />

Ergonomics 34 (<strong>20</strong>04) 263–269<br />

12. Waters, T. R., V. Putz-Anderson, (<strong>19</strong>93), "Revised NIOSH equation for the design and evaluation <strong>of</strong> manual<br />

lifting tasks." Ergonomics, vol. 36, pp. 749-76.<br />

704


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

OFFICE EFFICIENCY ENHANCEMENT THROUGH TPM: AN<br />

EMPIRICAL STUDY<br />

Rajender Kumar 1 , Vikas Kumar 2 , Sultan Singh 3 , S.K.Gupta 4<br />

1 Reseach Scholar, Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> Univ. <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad,<br />

India<br />

2 Associate Pr<strong>of</strong>., Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> Univ. <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad,<br />

India<br />

3 Joint Director, State Board <strong>of</strong> Technical Education Haryana, Panchkula, India<br />

4<br />

Associate Pr<strong>of</strong>., Department <strong>of</strong> Mechanical Engineering, FET, MRIU, Faridabad, India.<br />

e-Mail: rajender629@yahoo.com<br />

Abstract<br />

The global economy has become competitive which has made quality as one <strong>of</strong> the most important factors in an<br />

organization's survival and success. Therefore, the continuous quality improvement becomes compulsive in all<br />

aspects. Total Productive Maintenance (TPM) is a right answer or choice for continuous improvement. TPM has<br />

the permanent features <strong>of</strong> a business environment to give comprehensive advantage for existence in these<br />

competitive global markets. Moreover, the world over manufacturing has received a great deal <strong>of</strong> attention in<br />

the recent few years for the improvement in <strong>of</strong>fice efficiency efficient utilization <strong>of</strong> resources, because <strong>of</strong> the<br />

market becoming customer oriented and low <strong>of</strong>fice efficiency affects the today’s cost environment, . This paper<br />

reveals efficiency improvement in <strong>of</strong>fice through ‘Office TPM’ which is one <strong>of</strong> the most important pillars out <strong>of</strong> 8<br />

pillars. Office TPM has the main objective to make an efficient working in the <strong>of</strong>fices that eliminates losses and<br />

regulate out-put by applying 5’S principles that is CANDO (Cleaning, arranging, neatening, discipline and<br />

order in workplace organization. It should be started after activating four other pillars <strong>of</strong> AM, Kaizen, PM, and<br />

QM. This will improve the <strong>of</strong>fice efficiency in manner <strong>of</strong> resources utilization, improve productivity, efficiency in<br />

the administrative functions, identify and eliminate losses, curtailment <strong>of</strong> paper work and efficient use <strong>of</strong> paper<br />

working, improvement in working environment, and self monitoring by employees in achieving laid objectives<br />

etc.<br />

Keyword: Office efficiency, Environment, Paper work, Work efficiency.<br />

1. Introduction<br />

Quality, as a concept, does not easily fit into any given timeframe. It may be defined as meeting certain set<br />

standards and specification requirements, being suitable for use, or the degree <strong>of</strong> customer satisfaction. The<br />

journey <strong>of</strong> quality has passed through significant changes in the previous century. Figure 1 shows the successful<br />

changes in the quality management. The quality improvement enhances the performance efficiency in all the<br />

fields applicable to manufacturing environment [6].<br />

Figure 1. Successful changes in quality management<br />

In today’s competitive era, the manufacturing industry has experienced an unprecedented degree <strong>of</strong> change<br />

involving drastic changes in management approaches, new products and process technologies, and customer<br />

expectations including supplier attitudes [1]. The global marketplace has witnessed an increased pressure from<br />

customers and competitors in manufacturing as well as service sector due to these rapid changes [4]. The rapidly<br />

changing global marketplace affects in improvements <strong>of</strong> a company’s performance by focusing on cost cutting,<br />

705


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

increasing productivity levels, quality and guaranteeing deliveries in order to satisfy customers [13].<br />

Organizations that want to survive in today’s highly competitive business environment must address the need for<br />

diverse product range with state-<strong>of</strong>-the-art product features, coupled with high quality, lower costs, and more<br />

effective, swifter Research and Development (R&D) [5, 7]. TPM consists <strong>of</strong> six major activities explained<br />

below:<br />

1. Elimination <strong>of</strong> big losses like low productivity, availability <strong>of</strong> machine, quality <strong>of</strong> products etc. based on<br />

project teams organized by the production maintenance, and plant engineering departments.<br />

2. Planned Maintenance carried out by the maintenance departments.<br />

3. Autonomous maintenance carried out by the production departments.<br />

4. Preventive engineering carried out mainly by the plant engineering department.<br />

5. Easy to manufacture product design carried out by the product design departments.<br />

6. Education to support the above activities.<br />

TPM basically works on major 8 pillars (JH, KK, PM, QM, E&T, OT, 5s and SHE), each being set to achieve a<br />

“zero” target. These 8 pillars are shown in Figure 2. The 8 Pillars <strong>of</strong> TPM are explained with their key activities<br />

in Table 1 below.<br />

Figure 2. Pillars <strong>of</strong> TPM Methodology<br />

1.1 Office TPM<br />

Office TPM should be started after activating four other pillars <strong>of</strong> TPM (AM, Kaizen, PM, and QM). It must be<br />

followed to improve productivity, efficiency in the administrative functions and identify and eliminate losses.<br />

This includes analyzing processes and procedures towards increased <strong>of</strong>fice automation. Office TPM addresses<br />

twelve major losses, they are processing loss; cost loss including in areas such as procurement, accounts,<br />

marketing, sales leading to high inventories; communication loss; idle loss; set-up loss; accuracy loss; <strong>of</strong>fice<br />

equipment breakdown; communication channel breakdown, telephone and fax lines; time spent on retrieval <strong>of</strong><br />

information; non availability <strong>of</strong> correct on line stock status; customer complaints due to logistics; and expenses<br />

on emergency dispatches/purchases [16]. The main purposes <strong>of</strong> Office TPM are as follows:<br />

• Achieve zero function losses<br />

• Create efficient <strong>of</strong>fices<br />

• Implement service support functions for production departments<br />

In <strong>of</strong>fice TPM, all leaders and other members <strong>of</strong> administration (directly or indirectly attached with the<br />

organization) support the production functions with main focus on better plant performance.<br />

706


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 1. TPM pillars with key activities<br />

Sr. No. Pillars Key activity<br />

1. Autonomous Maintenance<br />

(Jishu Hozen)<br />

It means "Maintaining one's equipment by oneself". There are 7<br />

Steps in & Activities <strong>of</strong> Jishu Hozen.<br />

2. Focused Improvement<br />

It comprises <strong>of</strong> continuous improvement even in small steps<br />

(Kobetsu Kaizen)<br />

3. Planned Maintenance It focuses on increasing availability <strong>of</strong> equipments & reducing<br />

breakdown <strong>of</strong> machines.<br />

4. Quality Maintenance<br />

(Hinshitsu Hozen)<br />

Quality Maintenance is establishment <strong>of</strong> machine<br />

conditions that will not allow the occurrence <strong>of</strong> defects &<br />

control <strong>of</strong> such conditions is required to sustain Zero Defect.<br />

5. Education & Training Formation a team <strong>of</strong> workers to performs the<br />

autonomous maintenance activity<br />

6. Initial Control To establish a system <strong>of</strong> the production for new product &<br />

equipment in a minimum run up time.<br />

7. Safety, Hygiene &<br />

Environment<br />

The main role <strong>of</strong> SHE (Safety, Hygiene & Environment) is to<br />

create Safe & healthy work place where accidents do not occur,<br />

uncover & improve hazardous areas & do activities that preserve<br />

environment.<br />

8. Office TPM To make an efficient working <strong>of</strong> <strong>of</strong>fice that eliminates losses and<br />

regulate out-put by applying 5’S in <strong>of</strong>fice and working areas.<br />

This will also helps in improving synergy between various<br />

business functions and removing procedural hassles with main<br />

focus on cost-related issues.<br />

1.2 Benefits <strong>of</strong> Office TPM<br />

Office TPM benefits include participation <strong>of</strong> all people in support functions for focusing on better plant<br />

performance, better utilized work area, reduce repetitive work, reduced administrative costs, reduced inventory<br />

carrying cost, reduction in number <strong>of</strong> files, productivity <strong>of</strong> people in support functions, reduction in breakdown<br />

<strong>of</strong> <strong>of</strong>fice equipment, reduction <strong>of</strong> customer complaints due to logistics, reduction in expenses due to emergency<br />

dispatches/purchases, reduced manpower, and clean and pleasant work environment.<br />

1.3 Literature review<br />

TPM is a strategic approach to improve the performance <strong>of</strong> maintenance activities which leads effectively and<br />

efficiently working <strong>of</strong> machines and equipments. TPM seeks to engage all levels and functions in an<br />

organization to maximize the Plant efficiency as well as the effectiveness <strong>of</strong> production equipment. Some <strong>of</strong> the<br />

literature on TPM is as follows:<br />

The origin <strong>of</strong> TPM is traced back to <strong>19</strong>51 when Preventive Maintenance was introduced in Japan, described by<br />

Seiichi Nakajima (Known as the father <strong>of</strong> TPM) [10]. The Japanese has developed TPM to support their lean<br />

manufacturing system based on Preventive Maintenance, Corrective Maintenance and Maintenance Prevention<br />

concepts and methodologies that was originated and developed in the U.S.A. He investigated about the<br />

Equipment Effectiveness (is a measure <strong>of</strong> the value added to production through equipment). The process <strong>of</strong><br />

O.E.E. finding is to increase equipment effectiveness so each piece <strong>of</strong> equipment can be operated to its full<br />

potential and maintained at that level. Nakajima describes that TPM maximizes equipment effectiveness though<br />

two types <strong>of</strong> activity to insure that the equipment performs to design specifications, which is the true focus <strong>of</strong><br />

TPM. Five key elements for characterizing the TPM are as follows:.<br />

• TPM strives for maximum equipment effectiveness.<br />

• TPM establishes a total system <strong>of</strong> Preventive Maintenance for the entire life <strong>of</strong> the equipment.<br />

• TPM includes participation by all sectors <strong>of</strong> the organization that plan, use, and maintain equipment.<br />

• TPM participation is from top management to the frontline staff.<br />

• Execution <strong>of</strong> TPM is based on Small Group Activity.<br />

707


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

TPM is a methodology originating from Japan to support its lean manufacturing system, since dependable and<br />

effective equipment are essential pre-requisite for implementing Lean manufacturing initiatives in the<br />

organizations [14]. While Just-In-Time (JIT) and Total Quality Management (TQM) programs have been around<br />

for a while, the manufacturing organizations <strong>of</strong>f late, have been putting in enough confidence upon the latest<br />

strategic quality maintenance tool as TPM. Figure 3 shows the relationships between TPM and Lean<br />

Manufacturing building blocks. It is clearly revealed, that TPM is the corner stone activity for most <strong>of</strong> the lean<br />

manufacturing philosophies and can effectively contribute towards success <strong>of</strong> lean manufacturing [2].<br />

Figure 3 Relationship between TPM and lean manufacturing philosophies<br />

TPM is a production-driven improvement methodology that is designed to optimize equipment reliability and<br />

ensure efficient management <strong>of</strong> plant assets [12]. TPM is a change philosophy, which has contributed<br />

significantly towards realization <strong>of</strong> significant improvements in the manufacturing organizations in the West and<br />

Japan [9].<br />

The goal <strong>of</strong> a TPM program is to increase production and improve employees’ moral and job satisfaction. This<br />

case study did demonstrate these benefits, but there are training issues that need to be addressed for such success<br />

to be achieved, and similarly a full commitment <strong>of</strong> senior management to the program is also essential [11].<br />

2. Empirical study on <strong>of</strong>fice efficiency/Review <strong>of</strong> <strong>of</strong>fice efficiency<br />

An <strong>of</strong>fice comprises <strong>of</strong> people, equipment, space and the environment. The efficient working <strong>of</strong> any <strong>of</strong>fice is<br />

related with the output <strong>of</strong> the people working in that <strong>of</strong>fice. This efficiency is related with the ergonomics, and<br />

good working environment. In the present study,<br />

• The generation <strong>of</strong> papers and receipt <strong>of</strong> papers is a voluminous task in the sense that more papers means<br />

more storage. It is estimated that the average consumption <strong>of</strong> paper <strong>of</strong> A4 size is around 10000 Nos. per<br />

person per annum. This creates tons <strong>of</strong> files for purpose <strong>of</strong> storage as these are for future references.<br />

• The problem mentioned above also has another aspect <strong>of</strong> retrieving the information from these papers for<br />

future reference. Still there is lack <strong>of</strong> provision with regard to finding information from these papers.<br />

• By environment, it is meant that either the <strong>of</strong>fices are clematises or should have good ventilation system.<br />

The power shortage being a necessary evil, therefore good ventilation is an essential part. Some <strong>of</strong> the<br />

<strong>of</strong>fices are badly lighted which results in downgraded efficiency.<br />

• The shortage <strong>of</strong> space gives rise to packing <strong>of</strong> the peoples in that small area. This leads to creating a fish<br />

market since the noise level is quite high that it becomes difficult to concentrate on work. In the good<br />

<strong>of</strong>fices, there is always a provision for having a separate visitor room so-that noise level is kept low and<br />

performance efficiency high.<br />

• The communication system in an <strong>of</strong>fice is no more a problem since the introduction <strong>of</strong> mobile phones and<br />

almost every one having the same in their pocket. This comfort <strong>of</strong> communication system is bad as well<br />

since ringing <strong>of</strong> the bell in different tones creates an imbalance in the working environment.<br />

• Good lighting is another feature which enhances the performance efficiency. In India, it is a common<br />

practice to have tea and breakfast intervals as regularly as possible. This is a structured attack on the<br />

working efficiency. Therefore, the timing for this break needs to be notified.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2.1 Suggestions for improvement in <strong>of</strong>fice efficiency/ Ways to improve <strong>of</strong>fice efficiency<br />

The <strong>of</strong>fice environment is broadly divided in two categories a) Stereo Type/Routine Working, b) Creative<br />

working with mental application. This statement is a guiding factor in deciding the type <strong>of</strong> <strong>of</strong>fice I.e. ‘Open<br />

Office’ or ‘Closed Office’. The closed <strong>of</strong>fices are thinner in density but bad in space utilization. On contrary<br />

open <strong>of</strong>fices are denser in population, best space utilization but bad in efficiency because <strong>of</strong> communal noise<br />

level. Suggestions for improving the <strong>of</strong>fice efficiency are as follows/Following are the ways to improve<br />

<strong>of</strong>fice efficiency,:<br />

• The solution regarding space requirement, layout designing and allocation <strong>of</strong> activities is guided by the<br />

above parameters. There is normal tendency that <strong>of</strong>fice goers take their lunch in their seats. This affects the<br />

hygienic environment and house keeping <strong>of</strong> the <strong>of</strong>fice. Therefore, allocation <strong>of</strong> a separate lunch room is an<br />

essential part <strong>of</strong> any <strong>of</strong>fice along with a nicely dressed up pantry.<br />

• The clean and odorless washrooms contribute a lot for efficient working <strong>of</strong> the <strong>of</strong>fice. The aisles need to be<br />

thoroughly defined and has to be a part <strong>of</strong> good <strong>of</strong>fice layout.<br />

• It has been observed that voluminous consumption <strong>of</strong> papers is having a connected problem in name <strong>of</strong><br />

almirah’s for storage. This storage space cuts down the ethical use space and therefore, a review is very<br />

much is essential in this regard. This problem, pertaining to papers, can be tackled in two ways:<br />

a. Extensive use <strong>of</strong> computers by each and every individual. This practice <strong>of</strong> using shall cut down on large<br />

quantities <strong>of</strong> the papers resulting in huge saving in terms <strong>of</strong> cost, time and efficiency.<br />

b. The observation regarding usage <strong>of</strong> papers in <strong>of</strong>fice is that the papers are used on single side only.<br />

Therefore, the usage on both sides will also cut down in the requirements <strong>of</strong> papers including the storage<br />

space.<br />

• In most <strong>of</strong> the <strong>of</strong>fices the activities are carried out thoughtlessly which leads to unnecessary wastage <strong>of</strong> time<br />

including generation <strong>of</strong> no. <strong>of</strong> papers on the same subject. The improvement in this area shall improve the<br />

economy and efficiency.<br />

• The present communicated system is connected with frequent use <strong>of</strong> mobiles in <strong>of</strong>fices. The use <strong>of</strong> mobile<br />

affects the performance because <strong>of</strong> noise level and typically the generation <strong>of</strong> communal noises. This<br />

necessitates the use <strong>of</strong> mobile phones on vibratory mode only.<br />

• Another factor which can enhance the efficiency <strong>of</strong> an organization is to put the working staff under<br />

scanner.<br />

• The tea break for the staff members may be restricted to one no. in the forenoon and another one no. in the<br />

afternoon session. This break time need to be utilized for sharing the information amongst all the employees.<br />

Even common space for lunch is used for sharing the information and resolving the pending issues.<br />

• For a good <strong>of</strong>fice, it is essential to display all the information through a central information system or cell<br />

depicting the subject and file no. for an easy access and smooth flow <strong>of</strong> information. The display <strong>of</strong><br />

information regarding files centrally with subject and code no (allotted by company itself) shall help in<br />

achieving locating the information fast with unnecessary search and discussions with colleagues. This<br />

approach will also help to achieve 3 E’s: Economical, Environmental, and Efficient working.<br />

• The continuous working in an <strong>of</strong>fice generates a huge amount <strong>of</strong> papers as mentioned above. In case, these<br />

records are not viewed periodically then the space requirements will break boundary wall as well. This<br />

periodic review, may be at the end <strong>of</strong> the financial year shall help in segregating useful and non-useful<br />

papers. The non-useful papers, ones identified, need to be shrouded. Such an activity will help in limiting<br />

the useful records.<br />

• These above mentioned recommendations on clubbing shall result into huge savings, most efficient<br />

working, best utilization <strong>of</strong> resources, and a good working environment to all <strong>of</strong>fice peoples.<br />

• The performance parameters for measurement <strong>of</strong> working efficiency in an <strong>of</strong>fice are indirect and not as in<br />

case <strong>of</strong> manufacturing practices. The best system to evaluate the working efficiency in the <strong>of</strong>fices is to log<br />

the manner in which duty hours have been spent by an individual.<br />

References<br />

1. Ahuja, I.P.S., Khamba, J.S. and Choudhary, R. (<strong>20</strong>06). “Improved organizational behavior through<br />

strategic total productive maintenance implementation”, Paper No. IMECE<strong>20</strong>06-15783, ASME<br />

International Mechanical Engineering Congress and Exposition (IMECE), Chicago, IL, November 5-10,<br />

pp. 1-8.<br />

2. Ahuja, I.P.S. and Khamba, J.S. (<strong>20</strong>08). “Total Productive Maintenance: Literature review and directions”,<br />

International Journal <strong>of</strong> Quality & Reliability Management, Vol. 25, Iss. 7, pp. 709-756.<br />

3. Almeanazel, O.T.R. (<strong>20</strong>10). “Total Productive Maintenance Review and Overall Equipment Effectiveness<br />

Measurement”, Jordan Journal <strong>of</strong> Mechanical and Industrial Engineering, Vol. 4, Iss. 4, pp. 517 – 522.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4. George, M. (<strong>20</strong>02). “Lean Six Sigma: Combining Six Sigma Quality with Lean Speed”, McGraw-Hill,<br />

New York, NY.<br />

5. Gotoh, F. (<strong>19</strong>91). “Equipment Planning for TPM”, Productivity Press, Portland, OR.<br />

6. Hary, A. and Klujber, D. (<strong>20</strong>01). “Assessment approaches and strategies for the Quality system<br />

improvement”, Periodica Polytechnica Ser. Soc. Man. Sci., Vol. 9, Iss. 2, pp. 127-139.<br />

7. Hipkin, I.B. and Cock, C.D. (<strong>20</strong>00). “TQM and BPR: lessons for maintenance management”, Omega: The<br />

International Journal <strong>of</strong> Management <strong>Science</strong>, Vol. 28, Iss. 3, pp. 277-92.<br />

8. Jitender, Shergill, H. and Kumar, R. (<strong>20</strong>12). “TPM Methodology: a way <strong>of</strong> improving Overall Equipment<br />

Efficiency”, International Journal on Emerging Technologies, Vol.3, Iss.1, pp. 97-101.<br />

9. Maggard, B.N. and Rhyne, D.M. (<strong>19</strong>92). “Total productive maintenance: a timely integration <strong>of</strong><br />

production and maintenance”, Production and Inventory Management Journal, Vol. 33, Iss. 4, pp. 6-10.<br />

10. Nakajima S. (<strong>19</strong>88). “Introduction to TPM”, Productivity Press, Portland.<br />

11. Patra, N.K, Tripathy, J.K. and Choudhary, B.K. (<strong>20</strong>05). "Implementing the <strong>of</strong>fice total productive<br />

maintenance (“<strong>of</strong>fice TPM”) program: a library case study", Library Review, Vol. 54, Iss: 7, pp.415 – 424.<br />

12. Robinson, C.J. and Ginder, A.P. (<strong>19</strong>95). “Implementing TPM: The North American Experience”,<br />

Productivity Press, Portland, OR.<br />

13. Raouf, A. (<strong>19</strong>94). “Improving capital productivity through maintenance”, International Journal <strong>of</strong><br />

Operations & Production Management, Vol. 14, Iss. 7, pp. 44-52.<br />

14. Sekine, K. and Arai, K. (<strong>19</strong>98). “TPM for the lean Factory-Innovative Methods and Worksheets for<br />

Equipment Management”, Productivity Press, Portland, OR.<br />

15. Sharma, K., Gera, G., Kumar, R., Chaudhary, H.K. and Gupta, S.K. (<strong>20</strong>12). “An empirical study approach<br />

on TPM implementation in manufacturing industry”, International Journal on Emerging Technologies,<br />

Vol.3, Iss.1, pp. 18-23.<br />

16. Wakjira, M.W. and Singh, A.P. (<strong>20</strong>12). “Total Productive Maintenance: A Case Study in Manufacturing<br />

Industry”, Global Journal <strong>of</strong> Researches in Engineering (Industrial Engineering)”, Vol. 12, Iss. 1, pp. 25-<br />

32.<br />

17. Wireman, T. (<strong>19</strong>90b). “Total Productive Maintenance – An American Approach”, Industrial Press Inc.,<br />

New York (NY).<br />

710


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

ENHANCING PRODUCTIVITY BY STRATEGIC IMPROVEMENT IN<br />

THROUGHPUT-TIME ON ASSEMBLY LINE: A CASE STUDY<br />

S.K. Gupta 1 , Dr. V.K. Mahna 2 , Dr. R.V. Singh 3 , Rajender Kumar 4<br />

1 Research Scholar, Department <strong>of</strong> Mechanical Engineering, FET, MRIU, Faridabad<br />

2 Dean Academics and Executive Director, MRIU, Faridabad<br />

3 Pr<strong>of</strong>. & Head, Department <strong>of</strong> Mechanical Engineering, FET, MRIU, Faridabad;<br />

4<br />

Asst. Pr<strong>of</strong>., Department <strong>of</strong> Mechanical Engineering, FET, MRIU, Faridabad<br />

e-mail:<br />

1 gupta.sarojkumar@gmail.com, 2 rajender629@yahoo.com<br />

Abstract<br />

The targets <strong>of</strong> an increased productivity, operational availability and better overall efficiency, on the production<br />

lines are the most important goals for almost all manufacturing organizations. The specific objectives <strong>of</strong> this<br />

case study are firstly to reduce setup time and secondly, reduction in waiting time on the line with focuses on<br />

economic lot size and buffer stock. Design for production (DFP) is a tool to identify the losses in the line and<br />

iron out these losses in a systematic way to achieve improved throughput time, higher efficiency, higher<br />

productivity and improved manufacturing cost. The reduction in throughput time gives a base <strong>of</strong> 44% increase in<br />

production (Refer Sec. 4.0) i.e. present average production quantity <strong>of</strong> 37805 Nos. gets increased to 54440 Nos.<br />

with defining buffer stock and optimal lot size.<br />

Keywords: Setup Time, Buffer Stock, Waiting time, Throughput Time, Economic Lot Size.<br />

1. Introduction<br />

All production units aim at utilizing existing resources and enhancing the output to achieve cost oriented<br />

product. The design for production (DFP) is a powerful tool to curtail the inputs in terms <strong>of</strong> time & cost. The<br />

assembly line, by and large, are manual in nature therefore, need a close control on the performance <strong>of</strong> manual<br />

labour. In manufacturing industries, the throughput time is identified as the length <strong>of</strong> time between the release <strong>of</strong><br />

a production order to the factory floor and its receipt into finished goods inventory or its shipment to the<br />

customer.<br />

The throughput time comprises <strong>of</strong> setup time, waiting time, cycle time, inspection time, and move time. The<br />

activities <strong>of</strong> movement can be cut down to some extent by mechanizing the process <strong>of</strong> moving the material (if<br />

possible). The inspection time is very much part <strong>of</strong> the cycle time and can be brought down again to a lesser<br />

level by introducing digital/air gauging systems. The amount <strong>of</strong> time spent on setup and also waiting for material<br />

is a general phenomenon on any assembly line particularly in case the product is multi model mix. The amount<br />

<strong>of</strong> time setting up the line for a particular model may vary between 10-<strong>20</strong>% and waiting for material <strong>20</strong>-30%.<br />

The waiting for material is directly associated with prevalent lot size and availability <strong>of</strong> buffer stock being<br />

followed and bigger the lot size higher is the waiting time. Therefore, these two areas need a thorough study and<br />

investigation to reduce the through put time and enhancing the process performance in terms <strong>of</strong> productivity<br />

without utilizing any extra resources i.e. over time to compensate for the system inefficiencies.<br />

In an Assembly Line, the cycle time is also an essential part <strong>of</strong> the throughput time that means it needs to<br />

investigate the allocation <strong>of</strong> tasks to workstations. This study itself is a complete subject within itself to establish<br />

the no. <strong>of</strong> workstations as per existing production requirements under the heading <strong>of</strong> assembly line balancing.<br />

2. Literature Review<br />

At present manufacturers must be able to manufacture a wide variety <strong>of</strong> highly differentiated and high quality<br />

products in a cost-effective manner, and respond quickly to changes in the product designs and volumes in order<br />

to compete effectively [1].<br />

Recently most <strong>of</strong> the manufacturing units have focused on market demand and customers responsiveness. This<br />

has led to the implementation and adoption <strong>of</strong> lean manufacturing techniques in the automotive industry. Due to<br />

the complexity and demand behavior from customers, the role <strong>of</strong> better change over or setup time reduction and<br />

minimizing the waiting time (through better scheduling and also optimizing the lot size). It can help better<br />

response in small batch manufacturing [3]. In the past two decades, setup time reduction and quality<br />

improvement programs have become prevalent in manufacturing industry. Applying lean principles represents a<br />

systematic method for identifying all the activities which contribute in the value stream <strong>of</strong> the decision making<br />

711


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

process and eliminating activities that generates losses [7]. There is no shortage <strong>of</strong> reasons for long procurement<br />

process cycle times [4, 6]. In conducting detailed examinations <strong>of</strong> processes typically one or more <strong>of</strong> the<br />

following is found. Specific causes include, but are not limited to:<br />

• Waiting<br />

• Non-Value-Added Process Steps<br />

• Serial Versus Parallel Operations<br />

• Repeating Process Steps<br />

• Batching<br />

• Excessive Controls and Bureaucracy<br />

• Unnecessary Transfer <strong>of</strong> Materials or Information<br />

• Long Material/People Travel Distances<br />

• Ambiguous Goals and Objectives<br />

• Poorly Designed Procedures and Forms<br />

• Outdated Processes and Technologies<br />

• Process Variability<br />

• Lack <strong>of</strong> Information<br />

• Poor Communication<br />

• Limited Coordination<br />

• Ineffective Training<br />

The various factors constituting the throughput time have been investigated by the no. <strong>of</strong> authors time to time in<br />

following Table 1. This is a guideline for investigation and estimation <strong>of</strong> improving the throughput time.<br />

Table 1. Previous Research on Throughput Time Reduction Factors [2]<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3. Problem statement<br />

Reduction in manufacturing throughput time can generate numerous benefits, including lower work-in-process<br />

and finished goods inventory levels, improved quality, lower costs, and less forecasting error (because forecasts<br />

are for shorter time horizons). More importantly, reductions in manufacturing throughput time increases<br />

flexibility and reduce the time required to respond to customer orders. This can be vital to the survival and<br />

pr<strong>of</strong>itability <strong>of</strong> numerous firms, especially those experiencing increased market pressures for shorter delivery<br />

lead times <strong>of</strong> customized product [2]. The throughput time needs to be investigated and major parameters<br />

constituting this time need to be separated and studied in detail. In an assembly line these major constituents are<br />

setup time and waiting time which by and large vary between 25-50%. Therefore, the area is <strong>of</strong> prime<br />

importance for assessment and improvement.<br />

4. Case study<br />

In the present competitive market, cost <strong>of</strong> manufacturing is a concerned to all entrepreneurs so-that they may be<br />

part <strong>of</strong> the market for all types. This means cost <strong>of</strong> manufacturing need to be contained as far as possible. The<br />

flow time <strong>of</strong> the product or throughput time need to be constantly improved so-that cost efficient product is<br />

delivered to the customer. This case study deals with Assembly Line <strong>of</strong> Automotive Car Shock Absorbers <strong>of</strong><br />

XYZ manufacturing unit. The present assembly process is given in Figure 1.<br />

Figure 1. Assembly Process diagram<br />

The first step in the study relates to assessment <strong>of</strong> lost time as there is no data existing in this regard. Therefore, a<br />

statistical survey was conducted to ascertain the classification <strong>of</strong> productive time and lost time. This survey was<br />

based on confidence level <strong>of</strong> ±5% and accuracy <strong>of</strong> ± 2%.<br />

Table 2. Observation inferences<br />

Sr. No. Description % <strong>of</strong> Time Description<br />

1 Productive Time 52.72<br />

2 Lost Time 47.28<br />

3 Breakup <strong>of</strong> Lost Time<br />

a) Setup Time<br />

b) Waiting for Material<br />

Total<br />

18.78<br />

28.50<br />

47.28<br />

It was observed that the setup change varies 5-7 nos. on a given day. The average monthly production had been<br />

37805 nos. and model wise details are as per Table 3 & 4. It was further observed that the piston and tube data<br />

confirmed to, 2 distinct categories. This categorization is as per the Table 3 & 4 given below. Also, is the<br />

contribution <strong>of</strong> both categories in terms <strong>of</strong> contribution as depicted in the below given Pie-Chart in Figure 4.<br />

713


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 3. Category A as per cylinder and piston size<br />

Sr.<br />

No. Cylinder Dia. Piston Dia. Item Code Shocker Description<br />

Average<br />

Qty./months<br />

1 41.15 25.4 3316 M. Car 1" 2156<br />

Maruti Zen Rear<br />

41.15 25.4 3344<br />

2<br />

(Gas)<br />

2114<br />

3 41.15 25.4 4133 Alto Strut Ele 2103<br />

4 41.15 25.4 3383 M. Benz <strong>20</strong>87<br />

5 41.15 25.4 4136 WagonR Strut Assy 1687<br />

6 41.15 25.4 3528 M. Benz 1530<br />

7 41.15 25.4 3526 M. Benz 1508<br />

Maruti EX/DX<br />

41.15 25.4 3358<br />

8<br />

Rr.(Gas)<br />

1492<br />

9 41.15 25.4 4135 WagonR Strut Ele 1240<br />

10 41.15 25.4 4134 Alto Strut Assy 1184<br />

11 41.15 25.4 3380 MUL Alto Gas 1180<br />

12 41.15 25.4 3345 Jeep XL 804<br />

13 41.15 25.4 3379 Wagon R (Gas) 744<br />

Mercedez Benz<br />

41.15 25.4 3382<br />

14<br />

Monex<br />

659<br />

15 41.15 25.4 3357 Santro Rear 580<br />

16 41.15 25.4 4113 M. Car Strut Ele. 466<br />

17 41.15 25.4 3317 M. Van 1" 444<br />

18 41.15 25.4 3354 Qualis Front 370<br />

<strong>19</strong> 41.15 25.4 3452 Amb. Fr. Isuzu 340<br />

M. Van Strut Assy<br />

41.15 25.4 41<strong>20</strong><br />

<strong>20</strong><br />

RH<br />

332<br />

21 41.15 25.4 4118 M. Zen Strut Ele. <strong>20</strong>0<br />

22 41.15 25.4 3353 Qualis Rear 170<br />

23 41.15 25.4 4115 Zen Strut Assy 52<br />

24 41.15 25.4 4117 M. Car Strut Assy 22<br />

25 41.15 25.4 3337 Amb. Issuzu 0<br />

26 41.15 25.4 3456 Amb. Nova Fr. 0<br />

Total 23464<br />

Model wise Production Data-'Category A'<br />

2500<br />

Production Quantity<br />

in Units<br />

<strong>20</strong>00<br />

1500<br />

1000<br />

500<br />

0<br />

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 <strong>19</strong> <strong>20</strong> 21 22 23 24 25 26<br />

Serial No. <strong>of</strong> Model<br />

Figure 2. Model wise average monthly production detail for Category ‘A’<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 4. Category B as per cylinder and piston size<br />

Sr.<br />

No. Cylinder Dia. Piston Dia. Item Code Shocker Description<br />

Average<br />

Qty./months<br />

1 51 30.15 3371 Bolero Front 2<strong>20</strong>3<br />

2 51 30.15 3343 Bollero Rr. 1814<br />

3 51 30.15 4127 Tata Indica Fr. Assy RH 1568<br />

4 51 30.15 3423 Scorpio Fr. 1348<br />

5 51 30.15 4126 Tata Indica Fr. Assy LH 1268<br />

6 51 30.15 3424 Scorpio Rr. 1<strong>20</strong>6<br />

7 51 30.15 3435 Sumo Fr. 1038<br />

8 51 30.15 3329 Tata Indica 770<br />

9 51 30.15 3570 Tata Safari Rr 768<br />

10 51 30.15 4122 M. Van Strut ele LH 632<br />

11 51 30.15 4123 M. Van Strut ele RH 492<br />

12 51 30.15 3438 Tata Sumo Rr. 468<br />

13 51 30.15 3569 Tata Safari Fr 264<br />

14 51 30.15 3476 Tavera Fr. 230<br />

15 51 30.15 4128 Tata Indica 156<br />

16 51 30.15 3475 Tavera Rr 100<br />

17 51 30.15 4129 Tata Indica 16<br />

18 51 30.15 3407 INDICA STRUT 0<br />

Total 14341<br />

Model wise Production Data- 'Category B'<br />

2500<br />

Production Quantity<br />

in Units<br />

<strong>20</strong>00<br />

1500<br />

1000<br />

500<br />

0<br />

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18<br />

Serial No. <strong>of</strong> Model<br />

Figure 2. Model wise average monthly production detail for Category ‘A’<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

CATEGORY WISE CONTRIBUTION CHART<br />

Category B,<br />

37.94<br />

Category A,<br />

62.06<br />

Figure 4. Category wise contributions<br />

4. Analysis<br />

A scientific assessment <strong>of</strong> economic lot size is a basic requirement for smooth flow <strong>of</strong> production. Therefore, the<br />

calculations <strong>of</strong> this economic lot size are as follows:<br />

Economic Lot Size (E) = 5 √ [(N*S)/(F*C)] --- ( I )<br />

Where, N represents the No. <strong>of</strong> Pieces Produced/month<br />

S represents the Setup Cost in Rupees<br />

F represents the Cost Carrying Factor in Percentage (Generally taken b/w 5-30%)<br />

C represents the Cost <strong>of</strong> the Component in Rupees/unit<br />

In present case, N = 70400 Units,<br />

S = Rupees 250,<br />

F = <strong>20</strong>%,<br />

C = Rupees 310/unit<br />

By substituting this data in equation ( I )<br />

E = 5 √ [(70400*250)/(<strong>20</strong>*3<strong>20</strong>)<br />

= 270.79 Nos. (Say 270 Nos.)<br />

The waiting time on the line is because <strong>of</strong> non availability <strong>of</strong> material since there is no Buffer Stock or Buffer<br />

Zone on the line. Now the question arises is, what should be the quantity to be kept in the buffer zone The<br />

calculation for this quantity is as follows:<br />

1. Observed Waiting Time as per Table 2 is 28.5% i.e. 274 minutes on 2 shift basis.<br />

2. The Cycle time for production <strong>of</strong> one unit is 58 sec. say one minute.<br />

3. Therefore, the Buffer Stock needs to be 270 Nos. for each model.<br />

The data as per Tables 3 & 4 clearly define basic division <strong>of</strong> car shockers in two distinct categories. Presently,<br />

the line is running with intermix <strong>of</strong> models on arbitrary basis with primary understanding that whatsoever<br />

material is available is put on the line. Apart from this the laid down practice <strong>of</strong> making a lot <strong>of</strong> 500 Nos. is<br />

flouted on regular basis.<br />

1. This is evident that present no. <strong>of</strong> changes can be scheduled in a systematic way in a sequence i.e. the<br />

first programme <strong>of</strong> three models from Category ‘A’ may be run constantly in the forenoon session and<br />

two models from Category ‘B’ in the afternoon. This process is reversed in the second shift i.e.<br />

Category ‘B’ first and the Category ‘A’ in last. This allocation <strong>of</strong> Three Nos. from Category ‘A’ & Two<br />

Nos. from Category ‘B’ is based on past production data and the contribution <strong>of</strong> each category in the<br />

approximate ratio <strong>of</strong> 60: 40 (Refer Table 3&4) This shall help in cutting down the present no. <strong>of</strong> setup<br />

changes from 6 Nos. per shift to 1 Nos. per shift, thereby giving a saving <strong>of</strong> 5 Nos. <strong>of</strong> setups. The setup<br />

time for one change under present circumstances is 15 minutes therefore; the lost time gets improved by<br />

83.33% i.e. saving <strong>of</strong> 1.25 hrs/shift, improving the through put 16% approximately.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. The statistical study shows waiting time (No Material) is 28.50% i.e. 2.28 hrs/shift which is quite large<br />

and need to be cut down. The objective can be achieved by reducing the lot size from existing 500 Nos.<br />

to proposed 270 Nos. Therefore, the suggested lot size should start from minimum 50 to maximum 270<br />

nos. with a Buffer <strong>of</strong> 270 nos. as calculated above. This scheduling shall help in eliminating the waiting<br />

time and improving the throughput time by 3.53 hrs/shift [(2.28 + 1.25) hrs] i.e. 44% increase in<br />

production.<br />

6. Validation and Conclusion<br />

1. The average production per month <strong>of</strong> Category ‘A’ is 23464 Nos. (Table 3) and for Category ‘B’ is 14341<br />

Nos. (Table 4), which amounts to average production <strong>of</strong> car shock absorbers per month as 37805 Nos.<br />

(Category ‘A’ + Category ‘B’).<br />

2. The settled target for production <strong>of</strong> car shock absorbers is 1600 Nos./shift i.e. 3<strong>20</strong>0 Nos./day. Considering<br />

actual working <strong>of</strong> 22 days per month the Total desired production per month is 70400 Nos.<br />

3. The comparison <strong>of</strong> the present production with the targeted production shows result as 53.7% which means<br />

46.3% is lost because <strong>of</strong> setup time and waiting time.<br />

4. This confirms that the statistical estimation <strong>of</strong> lost time is very much inline with the actual data i.e. 47.28%<br />

as statistical result and 46.3% as actual result.<br />

5. The reduction in throughput time gives a base <strong>of</strong> 44% increase in production (Refer Sec. 4.0) i.e. present<br />

average production quantity <strong>of</strong> 37805 Nos. gets increased to 54440 Nos.<br />

6. The creation <strong>of</strong> buffer stock will increase the inventory levels but throughput will be smooth and delivery to<br />

the customer is fast.<br />

References<br />

1. Cruz, J.M., Diaby, M., Nsakanda, A.L. (<strong>20</strong>08). “A Geometric Programming Model <strong>of</strong> the Lot-Scheduling<br />

Problem with Investments in Setup Reductions and Process Improvements”, American Conference on<br />

Applied Mathematics (MATH '08), Harvard, Massachusetts, USA, March 24-26, <strong>20</strong>08.<br />

2. Deros B.M., Mohamad D., Idris M.H.M., Rahman M.N.A., Ghani J.A. and Ismail, A.R. (<strong>20</strong>11). “Setup Time<br />

Reduction in an Automotive Battery Assembly Line”, International Journal <strong>of</strong> Systems Applications,<br />

Engineering & Development, Vol. 5, Iss.5, pp. 618-625.<br />

3. Gest, G., Culley, R.I., Mileham, A.R. and Owen, G.W. (<strong>19</strong>95). “Review <strong>of</strong> Fast Tools Change Systems”,<br />

Computer Integrated Manufacturing System, Vol. 8, Iss. 3, pp. <strong>20</strong>5-210.<br />

4. Kivenko, K. (<strong>19</strong>94). "Cycle Time Reduction”, APICS-The Performance Advantage, pp. 21-24.<br />

5. Kumar, R., Gupta S.K., Singh, R.V. and Gera, G. (<strong>20</strong>12). “Improving industrial performance through Cycle<br />

Time Reduction Technique (A Case Study)”, in the proceeding <strong>of</strong> National Conference on Emerging Trends<br />

in Mechanical Engineering (ETME-<strong>20</strong>12), held at ITM <strong>University</strong>, Gurgaon (Hr.), June 1, <strong>20</strong>12, pp.<br />

6. Nichols, E. L., Frolick, M.N. and Wetherbe, J.C. (<strong>19</strong>95). "Cycle Time Reduction: An Inter-organizational<br />

Supply Chain Perspective”, Cycle Time Research, Vol. 1, No. 1, pp. 63-84.<br />

7. Rohan, R, and Sindila, G. <strong>20</strong>08. “Applying Lean Principles to Improve Organization’s Decisional Process”,<br />

DNCOCO.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

APPLICATION OF TAGUCHI METHOD IN PROCESS<br />

OPTIMIZATION<br />

Shyam Kumar Karna 1 , Ran Vijay Singh 2 , Rajeshwar Sahai 3<br />

1 Ph.D. Scholar, M. R. I. U., Faridabad<br />

2 Pr<strong>of</strong>essor & Head, Mechanical Engineering Department, MRIU, Faridabad<br />

3<br />

Pr<strong>of</strong>essor, Mechanical Engineering Department, BSAITM, Faridabad<br />

e-mail: Skkarna<strong>20</strong>05@gmail.com<br />

Abstract<br />

The objective <strong>of</strong> the study is to optimize the process by applying the Taguchi method with orthogonal array<br />

robust design. Taguchi Parameter Design is a powerful and efficient method for optimizing the process, quality<br />

and performance output <strong>of</strong> manufacturing processes, thus a powerful tool for meeting this challenge. Off-line<br />

quality control is considered to be an effective approach to improve product quality at a relatively low cost. The<br />

Taguchi method is one <strong>of</strong> the conventional approaches for this purpose. This procedure eliminates the need for<br />

repeated experiments, time and conserves the material by the conventional procedure. Optimization <strong>of</strong> process<br />

parameters is done to have great control over quality, productivity and cost aspects <strong>of</strong> the process. Off-line<br />

quality control is considered to be an effective approach to improve product quality at a relatively low cost. The<br />

Taguchi method is a powerful tool for designing high quality systems. The approach is based on Taguchi<br />

method, the signal-to-noise (S/N) ratio and the analysis <strong>of</strong> variance (ANOVA) are employed to study the<br />

performance characteristics.<br />

1. Introduction<br />

After World War II, the Japanese manufacturers were struggling to survive with very limited resources. If it were<br />

not for the advancements <strong>of</strong> Taguchi the country might not have stayed afloat let alone flourish as it has. Taguchi<br />

revolutionized the manufacturing process in Japan through cost savings. He understood, like many other<br />

engineers, that all manufacturing processes are affected by outside influences, noise. However, Taguchi realized<br />

methods <strong>of</strong> identifying those noise sources, which have the greatest effects on product variability. His ideas have<br />

been adopted by successful manufacturers around the globe because <strong>of</strong> their results in creating superior<br />

production processes at much lower costs.<br />

Taguchi methods are statistical methods developed by Genichi Taguchi to improve the quality <strong>of</strong> manufactured<br />

goods and more recently also applied to engineering (Rosa et al. <strong>20</strong>09), biotechnology (Rao et al. <strong>20</strong>08, Rao et<br />

al. <strong>20</strong>04), marketing and advertising (Selden <strong>19</strong>97). Pr<strong>of</strong>essional statisticians have welcomed the goals and<br />

improvements brought about by Taguchi methods, particularly by Taguchi's development <strong>of</strong> designs for studying<br />

variation.<br />

2. State-<strong>of</strong>-art<br />

There is a broad consensus in academia and industry that reducing variation is an important area in quality<br />

improvement (Shoemaker et al. <strong>19</strong>91, Thornton et al. <strong>19</strong>99, Gremyr et al. <strong>20</strong>03 and Taguchi et al. <strong>20</strong>05). "The<br />

enemy <strong>of</strong> mass production is variability. Success in reducing it will invariably simplify processes, reduce scrap,<br />

and lower costs” (Box and Bisgaard <strong>19</strong>88). Definition <strong>of</strong> quality loss as “the amount <strong>of</strong> functional variation <strong>of</strong><br />

products plus all possible negative effects, such as environmental damages and operational costs” supports this<br />

view (Taguchi’s <strong>19</strong>93). In the <strong>19</strong>80s Genichi Taguchi (<strong>19</strong>85; <strong>19</strong>86; <strong>19</strong>93) received international attention for his<br />

ideas on variation reduction, starting with the translation <strong>of</strong> his work published in Taguchi and Wu (<strong>19</strong>79).<br />

The main objective in the Taguchi method is to design robust systems that are reliable under uncontrollable<br />

conditions (Taguchi<strong>19</strong>78, Byrne<strong>19</strong>87 and Phadke<strong>19</strong>89). The method aims to adjust the design parameters<br />

(known as the control factors) to their optimal levels, such that the system response is robust – that is, insensitive<br />

to noise factors, which are hard or impossible to control (Phadke<strong>19</strong>89).<br />

Some very informative studies were found that were conducted using the Taguchi Parameter Design method for<br />

the purpose <strong>of</strong> optimizing turning parameters (Vernon et al.<strong>20</strong>03, Davim<strong>20</strong>01, <strong>20</strong>03, Lin <strong>20</strong>04, Manna et al.<br />

<strong>20</strong>04, Yih-Fong<strong>20</strong>06). These studies made use <strong>of</strong> various work piece materials and controlled parameters to<br />

optimize surface roughness, dimensional accuracy, or tool wear. Each utilized different combinations and levels<br />

<strong>of</strong> cutting speed, feed rate, depth <strong>of</strong> cut, cutting time, work piece length, cutting tool material, cutting tool<br />

geometry, coolant, and other machining parameters. These studies all discovered clear and useful correlations<br />

718


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

between their control and response parameters. This would indicate that there are a number <strong>of</strong> different<br />

parameters that can be included in this type <strong>of</strong> study, and unique combination <strong>of</strong> parameters can be tailored to<br />

suit a given situation.<br />

3. Process Optimization<br />

It refers to the procedure or procedures used to make a system or design as effective or functional as possible,<br />

especially the mathematical techniques involved.<br />

Also optimization is putting together a portfolio in such a way that return is maximized for a given risk level, or<br />

risk is minimized for a given expected return level. Process optimization is the discipline <strong>of</strong> adjusting a process<br />

to optimize some specified set <strong>of</strong> parameters without violating some constraint. The most common goals are<br />

minimizing cost, maximizing throughout, and/or efficiency. This is one <strong>of</strong> the major quantitative tools in<br />

industrial decision-making.<br />

3.1 Process Optimization Tools<br />

Many relate process optimization directly to use <strong>of</strong> statistical techniques to identify the optimum solution. This<br />

is not true. Statistical techniques are definitely needed. However, a thorough understanding <strong>of</strong> the process is<br />

required prior to committing time to optimize it. Over the years, many methodologies have been developed for<br />

process optimization including Taguchi method, six sigma, lean manufacturing and others.<br />

4. Taguchi’s Method<br />

Taguchi's techniques have been used widely in engineering design (Ross<strong>19</strong>96 & Phadke<strong>19</strong>89). The Taguchi<br />

method contains system design, parameter design, and tolerance design procedures to achieve a robust process<br />

and result for the best product quality (Taguchi<strong>19</strong>87& <strong>19</strong>93). The main trust <strong>of</strong> Taguchi's techniques is the use <strong>of</strong><br />

parameter design (Ealey Lance A.<strong>19</strong>94), which is an engineering method for product or process design that<br />

focuses on determining the parameter (factor) settings producing the best levels <strong>of</strong> a quality characteristic<br />

(performance measure) with minimum variation. Taguchi designs provide a powerful and efficient method for<br />

designing processes that operate consistently and optimally over a variety <strong>of</strong> conditions. To determine the best<br />

design, it requires the use <strong>of</strong> a strategically designed experiment, which exposes the process to various levels <strong>of</strong><br />

design parameters.<br />

Experimental design methods were developed in the early years <strong>of</strong> <strong>20</strong>th century and have been extensively<br />

studied by statisticians since then, but they were not easy to use by practitioners (Phadke <strong>19</strong>89). Taguchi's<br />

approach to design <strong>of</strong> experiments is easy to be adopted and applied for users with limited knowledge <strong>of</strong><br />

statistics; hence it has gained a wide popularity in the engineering and scientific community.<br />

Taguchi specified three situations:<br />

1. Larger the better (for example, agricultural yield);<br />

2. Smaller the better (for example, carbon dioxide emissions); and<br />

3. On-target, minimum-variation (for example, a mating part in an assembly).<br />

P-Diagram<br />

7<strong>19</strong>


4.1 Contributions <strong>of</strong> Taguchi methods<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Taguchi has made a very influential contribution to industrial statistics. Key elements <strong>of</strong> his quality philosophy<br />

include the following:<br />

Taguchi loss function (Ross <strong>19</strong>96), used to measure financial loss to society resulting from poor quality;<br />

The philosophy <strong>of</strong> <strong>of</strong>f-line quality control ( Logothetis and Wynn<strong>19</strong>89), designing products and processes so that<br />

they are insensitive ("robust") to parameters outside the design engineer's control; and<br />

Innovations in the statistical design <strong>of</strong> experiments Atkinson, Donev, and Tobias, (<strong>20</strong>07), notably the use <strong>of</strong> an<br />

outer array for factors that are uncontrollable in real life, but are systematically varied in the experiment. Taguchi<br />

proposed a standard 8-step procedure for applying his method for optimizing any process.<br />

4.2 Taguchi's rule for manufacturing<br />

Taguchi realized that the best opportunity to eliminate variation is during the design <strong>of</strong> a product and its<br />

manufacturing process. Consequently, he developed a strategy for quality engineering that can be used in both<br />

contexts. The process has three stages:<br />

• System design<br />

• Parameter design<br />

• Tolerance design<br />

System design<br />

This is design at the conceptual level, involving creativity and innovation.<br />

Parameter design<br />

Once the concept is established, the nominal values <strong>of</strong> the various dimensions and design parameters need to be<br />

set, the detail design phase <strong>of</strong> conventional engineering. This is sometimes called robustification.<br />

Tolerance design<br />

With a successfully completed parameter design, and an understanding <strong>of</strong> the effect that the various parameters<br />

have on performance, resources can be focused on reducing and controlling variation in the critical few<br />

dimensions.<br />

5. Mathematical modeling:<br />

“ORTHOGONAL ARRAYS “(OAs) experiments Using OAs significantly reduces the number <strong>of</strong> experimental<br />

configurations to be studied (Montgomery<strong>19</strong>91). The effect <strong>of</strong> many different parameters on the performance<br />

characteristic in a process can be examined by using the orthogonal array experimental design proposed by<br />

Taguchi. Once the parameters affecting a process that can be controlled have been determined, the levels at<br />

which these parameters should be varied must be determined. Determining what levels <strong>of</strong> a variable to test<br />

requires an in-depth understanding <strong>of</strong> the process, including the minimum, maximum, and current value <strong>of</strong> the<br />

parameter. If the difference between the minimum and maximum value <strong>of</strong> a parameter is large, the values being<br />

tested can be further apart or more values can be tested. If the range <strong>of</strong> a parameter is small, then less value can<br />

be tested or the values tested can be closer together.<br />

Array Selector<br />

6. Taguchi’s design <strong>of</strong> experiments<br />

DOE's Planning<br />

1. Design and Communicate the Objective<br />

2. Define the Process<br />

3. Select a Response and Measurement System<br />

4. Ensure that the Measurement System is Adequate<br />

7<strong>20</strong>


5. Select Factors to be Studied<br />

6. Select the Experimental Design<br />

7. Set Factor Levels<br />

8. Final Design Considerations<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

7. Eight-Steps in Taguchi methodology:<br />

Step-1: Identify the main function, side effects, and failure mode<br />

Step-2: Identify the noise factors, testing conditions, and quality characteristics<br />

Step-3: Identify the objective function to be optimized<br />

Step-4: Identify the control factors and their levels<br />

Step-5: Select the orthogonal array matrix experiment<br />

Step-6: Conduct the matrix experiment<br />

Step-7: Analyze thedata, predict the optimum levels and performance<br />

Step-8: Perform the verification experiment and plan the future action<br />

8. Analyzing and examining result<br />

(i) Determine the parameters signification (ANOVA)-Analysis <strong>of</strong> variance (Hafeez et al. <strong>20</strong>02)<br />

(ii) Conduct a main effect plot analysis to determine the optimal level <strong>of</strong> the control factors.<br />

(iii) Execute a factor contribution rate analysis.<br />

(iv) Confirm experiment and plan future application<br />

9. Significance:<br />

Taguchi started to develop new methods to optimize the process <strong>of</strong> engineering experimentation. He believed<br />

that the best way to improve quality was to design and build it into the product. He developed the techniques<br />

which are now known as Taguchi Methods. His main contribution lies not in the mathematical formulation <strong>of</strong> the<br />

design <strong>of</strong> experiments, but rather in the accompanying philosophy. His concepts produced a unique and powerful<br />

quality improvement technique that differs from traditional practices. He developed manufacturing systems that<br />

were “robust” or insensitive to daily and seasonal variations <strong>of</strong> environment, machine wear and other external<br />

factors.<br />

The Taguchi approach to quality engineering places a great deal <strong>of</strong> emphasis on minimizing variation as the<br />

main means <strong>of</strong> improving quality. The idea is to design products and processes whose performance is not<br />

affected by outside conditions and to build this in during the development and design stage through the use <strong>of</strong><br />

experimental design. The method includes a set <strong>of</strong> tables that enable main variables and interactions to be<br />

investigated in a minimum number <strong>of</strong> trials.<br />

Taguchi Method uses the idea <strong>of</strong> Fundamental Functionality, which will facilitate people to identify the common<br />

goal because it will not change from case to case and can provide a robust standard for widely and frequently<br />

changing situations. It is also pointed out that the Taguchi Method is also very compatible with the human<br />

focused quality evaluation approaches that are coming up.<br />

References:<br />

• Atkinson, A. C. and Donev, A. N. and Tobias, R. D. (<strong>20</strong>07) “Optimum Experimental Designs, with<br />

SAS”, Oxford <strong>University</strong> Press.<br />

• Box, G. and S. Bisgaard (<strong>19</strong>88) "Statistical Tools for Improving Designs", Mechanical Engineering,<br />

Vol 110 No (1), pp. 32-40<br />

• Byrne D. M. , S. Taguchi (<strong>19</strong>87) “The Taguchi approach to parameter design,”Quality Progress, vol.<br />

<strong>20</strong> (12), pp. <strong>19</strong>-26<br />

• Davim, J. P. (<strong>20</strong>01) “A note on the determination <strong>of</strong> optimal cutting conditions for surface roughness<br />

obtained in turning using design <strong>of</strong> experiment”, Journal <strong>of</strong> Material Processing <strong>Technology</strong>, 116(2/3),<br />

305-308<br />

• Davim, J.P. (<strong>20</strong>03) “Design <strong>of</strong> optimization <strong>of</strong> cutting parameters for turning metal matrix composites<br />

based on the orthogonal arrays”, Journal <strong>of</strong> Materials Processing <strong>Technology</strong>, 132, 340–344<br />

• Ealey Lance A. (<strong>19</strong>94) “Quality by design Taguchi methods and US industry.” 2 nd ed. Sidney: Irwin<br />

pr<strong>of</strong>essional publishing and ASI Press; p. 189–<strong>20</strong>7<br />

• Gremyr, I., M. Arvidsson, et al. (<strong>20</strong>03) "Robust Design Methodology: Status in the Swedish<br />

Manufacturing Industry", Quality and Reliability Engineering International, Vol <strong>19</strong> No (4), pp. 285-293<br />

721


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

• Hafeez K., H. Rowland, Kanji, S.Iqbal (<strong>20</strong>02) “Design optimization using ANOVA”, Journal <strong>of</strong><br />

Applied Statistics, , vol. 29, issue 6, pages 895-906<br />

• Lin, C. L. (<strong>20</strong>04) “Use <strong>of</strong> the Taguchi method and grey relational analysis to optimize turning<br />

operations with multiple performance characteristics”, Materials and Manufacturing Processes, <strong>19</strong>(2),<br />

<strong>20</strong>9-2<strong>20</strong><br />

• Logothetis, N. and Wynn, H. P. (<strong>19</strong>89) “Quality Through Design: Experimental Design, Off-line<br />

Quality Control, and Taguchi's Contributions”. Oxford <strong>University</strong> Press, Oxford <strong>Science</strong> Publications.<br />

• Manna, A., & Bhattacharyya, B. (<strong>20</strong>04) “Investigation for optimal parametric combination for<br />

achieving better surface finish during turning <strong>of</strong> Al /SiC-MMC”. International Journal <strong>of</strong> Advanced<br />

Manufacturing <strong>Technology</strong>, 23, 658-665<br />

• Montgomery, D. C. (<strong>19</strong>91) “Design and Analysis <strong>of</strong> Experiments” ed. John Wily, New York.<br />

• Phadke M.S. (<strong>19</strong>89) “Quality Engineering Using Robust Design”, Prentice Hall, Englewood Cliffs,<br />

New Jersey.<br />

• Rosa, Jorge Luiz; Robin, Alain; Silva, M. B.; Baldan, Carlos Alberto; Peres, Mauro Pedro. (<strong>20</strong>09)<br />

“Electrodeposition <strong>of</strong> copper on titanium wires: Taguchi experimental design approach.” Journal <strong>of</strong><br />

Materials Processing <strong>Technology</strong>, v. <strong>20</strong>9, p. 1181-1188<br />

• Rao, Ravella Sreenivas; C. Ganesh Kumar, R. Shetty Prakasham, Phil J. Hobbs (<strong>20</strong>08) "The Taguchi<br />

methodology as a statistical tool for biotechnological applications: A critical appraisal". Biotechnology<br />

Journal 3 (4): 510–523<br />

• Rao, R. Sreenivas; R.S. Prakasham, K. Krishna Prasad, S. Rajesham, P.N. Sarma, L. Venkateswar Rao<br />

(<strong>20</strong>04) "Xylitol production by Candida sp.: parameter optimization using Taguchi approach". Process<br />

Biochemistry 39 (8): 951–956<br />

• Ross, P.J., (<strong>19</strong>96) "Taguchi Techniques for Quality Engineering: Loss Function, Orthogonal<br />

Experiments, Parameter and Tolerance Design - 2nd ed.", New York, NY: McGraw-Hill.<br />

• Selden, Paul H. (<strong>19</strong>97) “Sales Process Engineering: A Personal Workshop” Milwaukee, Wisconsin:<br />

ASQ Quality Press. p. 237.<br />

• Shoemaker, A. C., K. L. Tsui (<strong>19</strong>91) "Economical Experimentation Methods for Robust Design",<br />

Technometrics, Vol 33 No (4), pp. 415-427.<br />

• Thornton, A. C., S. Donnely, (<strong>19</strong>99) “More Than Just Robust Design: Why Product Development<br />

Organizations Still Contend With Variation and Its Impact on Quality”, Annual Taguchi Symposium,<br />

ASME.<br />

• Taguchi, G (<strong>19</strong>78) "Off-line and On-line Quality Control Systems," Proceeding <strong>of</strong> International<br />

Conference on Quality, Tokyo, Japan.<br />

• Taguchi, G. and Y. Wu (<strong>19</strong>79) “Introduction to Off-Line Quality Control”, Central Japan Quality<br />

Control Association, Nagoya, Japan.<br />

• Taguchi, G. (<strong>19</strong>85) "Quality Engineering in Japan", Bulletin <strong>of</strong> the Japan Society <strong>of</strong> Precision<br />

Engineering, Vol <strong>19</strong> No (4), pp. 237-242.<br />

• Taguchi, G. (<strong>19</strong>86) “Introduction to Quality Engineering - Designing Quality into Products and<br />

Processes”, Asian Productivity Organization, Tokyo.<br />

• Taguchi, G. (<strong>19</strong>87) “System <strong>of</strong> Experimental Design” Unipub/Kraus, International Publication<br />

• Taguchi, G. (<strong>19</strong>93) “Taguchi on Robust <strong>Technology</strong> Development - Bringing Quality Engineering<br />

Upstream”, ASME Press, New York.<br />

• Taguchi, G., S. Chowdhury (<strong>20</strong>05) “Taguchi's Quality Engineering Handbook”, ASI Consulting Group,<br />

LLC, Livonia, Michigan.<br />

• Vernon, A., & Özel, T. (<strong>20</strong>03) “Factors affecting surface roughness in finish hard Turning”, Paper<br />

presented at the 17th International Conference on Production Research, Blacksburg, Virginia.<br />

• Yih-Fong, T. (<strong>20</strong>06) “Parameter design optimisation <strong>of</strong> computerised numerical control turning tool<br />

steels for high dimensional precision and accuracy”, Materials and Design, 27(8), 665-675<br />

722


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

A REVIEW OF LITERATURE ON WORKER ALLOCATION PROBLEM<br />

IN FMS<br />

Lalit Kumar, Mohit Bansal, Sanjeev Goyal<br />

Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, INDIA<br />

Email: rathee.lalit.<strong>20</strong>07@gmail.com<br />

Abstract<br />

A flexible manufacturing system (FMS) is a manufacturing system in which there is some amount <strong>of</strong> flexibility that<br />

allows the system to react in the case <strong>of</strong> changes, whether predicted or unpredicted. There are various components<br />

which are associated with FMS; worker allocation (WA) is one amongst them. In this paper authors have reviewed<br />

various literatures available on this topic and have tried to prepare a very concise and progressive review. Authors<br />

have classified the papers in basically four categories, each category covers a number <strong>of</strong> publications in which all<br />

the major related aspects <strong>of</strong> the problem are discussed. Manufacturing managers can refer this paper for the<br />

application <strong>of</strong> various important factors relating WA problem.<br />

Keywords: FMS, Literature, Task, Worker Allocation<br />

1. Introduction<br />

The purpose <strong>of</strong> this paper is to address the worker allocation problem in a stochastic environment. This provides a<br />

thorough review <strong>of</strong> earlier papers in the field <strong>of</strong> worker allocation for a comprehensive understanding <strong>of</strong> worker<br />

allocation problem.<br />

Worker allocation could be defined as allocating the best worker to a process, thereby optimizing the performance <strong>of</strong><br />

the system. In order to optimize the performance <strong>of</strong> the system, worker allocation has to be done based on<br />

productivity <strong>of</strong> the workers. Processing time and quality level <strong>of</strong> workers are the dominant productivity measures in<br />

context with worker allocation.<br />

It is worthwhile here to discuss the work <strong>of</strong> Kodituwakku and Dhayarathne (<strong>20</strong>11), which presents master worker<br />

optimization layer. The feature <strong>of</strong> this layer is that it uses the prior knowledge and numerical data relating to the<br />

groups <strong>of</strong> computers for discussion making process and solves the problems with the aid <strong>of</strong> computer. The work<br />

done by Jarugumilli and Grasman (<strong>20</strong>10) is formulated in the form <strong>of</strong> the workforce planning problem using a twophase<br />

goal programming approach for a high volume manufacturing facility with several machine groups at each<br />

operation. Decision makers are constantly on the lookout for techniques to enable quality improvement. Worker<br />

allocation is one such technique that has become popular in the recent times. Though worker allocation is not new, it<br />

has now found more subscribers, and occupies a prominent place. The work on the worker allocation problem<br />

solved by using genetic algorithm is also discussed by Zhang, Gen and Lin (<strong>20</strong>08), which is again a very useful tool<br />

to solve the problems <strong>of</strong> WA.<br />

But in reality this proves to be a concept that helps in innovation and the optimization <strong>of</strong> resources. Considering the<br />

growth <strong>of</strong> publications, till today there are not any such reviews attempts have been made on the topic <strong>of</strong> worker<br />

allocation. It is essential that the present attempt by the authors will definitely help the researchers. This paper,<br />

besides providing a review <strong>of</strong> literature on worker allocation, covers the following objectives:<br />

(1) Allotting the publications in a refined manner which will ease the search part<br />

(2) Scrutiny <strong>of</strong> publications on the basis <strong>of</strong> different categories; and<br />

(3) Finding results and aspects <strong>of</strong> future work.<br />

An interactive methodology for classifying the literature is used. The growth and categorization <strong>of</strong> publications are<br />

presented in a graphical form for an easy understanding. The papers have been closely examined.<br />

2. Methodology and Scheme <strong>of</strong> Review<br />

The classification scheme proposed in this paper includes a simultaneous parallel categorization that highlights the<br />

growth <strong>of</strong> literature from time to time and also the coverage <strong>of</strong> worker allocation specific to different groups like:<br />

723


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2.1 Worker Allocation: General Aspects or Fundamentals<br />

Here the authors will try to find out what, why and when about allocating the worker because until and unless the<br />

concept <strong>of</strong> allocation is not taken into the consideration, the result can never be found out that’s why all publications<br />

under this category deal with very general and fundamental concepts <strong>of</strong> worker allocation. Fundamentals are usually<br />

covered to a large extent particularly when the discipline is in the introduction and growth stage. This can be<br />

confirmed by the number <strong>of</strong> publications, which appeared in the early time period <strong>of</strong> the time scale considered.<br />

2.2 Worker Allocation: Applicable to FMS Sector<br />

People are more interested to know about the application <strong>of</strong> worker allocation specifically to the manufacturing<br />

sectors that can be flexible and non flexible one. Under this categorization the authors will review the literature for<br />

worker allocation on FMS sector. Therefore this should be a useful group.<br />

2.3 Worker Allocation: As Resource Allocation<br />

Resource allocation is regarded as one <strong>of</strong> the very important factor because allocation <strong>of</strong> workers, reduction <strong>of</strong> cycle<br />

time, scheduling <strong>of</strong> machines, task allocation all acts as resources which are to be optimized and when the<br />

techniques are used then they will provide a very useful contribution towards its conclusion. This category is<br />

considered to recognize and appreciate the novel approaches or paradigm shifts in worker allocation techniques.<br />

2.4 Worker Allocation: Applicable to Various Sectors<br />

Under this category, authors examined the application <strong>of</strong> worker allocation among various sectors as Apparel<br />

production, cellular manufacturing, assembly cells, toxic environment, room dormitory, and many others. All these<br />

factors will help to reach at a conclusion.<br />

It is understandable that a very strict demarcation in the categorization is not possible since there may be certain<br />

overlaps in the publications analyzed.<br />

A Pareto diagram <strong>of</strong> the number <strong>of</strong> publications in different categories is given in “Fig. 1”. All the publications in<br />

the categories described earlier have further been coded based on the chronological appearance <strong>of</strong> the article, for the<br />

convenience <strong>of</strong> the readers. The first code in the form a number from 1 to 4 refers to the categories 1 to 4 illustrated<br />

above. Coding has been done from <strong>19</strong>90 onwards. Also, the time interval for the first and second category is taken<br />

as five years. This is adopted, since the numbers <strong>of</strong> publications during the first ten years are not many. Publications<br />

after <strong>20</strong>00 have been categorized on a time interval <strong>of</strong> two years. Thus, the time periods are represented as “a”, &<br />

“b”, (five years: January <strong>19</strong>90-December <strong>19</strong>94, & January <strong>19</strong>95-December <strong>19</strong>99), “c”, to ‘g”, (two years each:<br />

January <strong>20</strong>00-January <strong>20</strong>11). This time based coding is displayed in Table I.<br />

Figure1. Pareto diagram showing the number <strong>of</strong> publications and categories<br />

724


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 1. The coding pattern for classification based on time<br />

Time Frame<br />

Jan.<strong>19</strong>90 Jan.<strong>19</strong>95 Jan. <strong>20</strong>00 Jan. 03 Jan. 05 Jan. 07 Jan.09<br />

Dec.<strong>19</strong>94 Dec. <strong>19</strong>99 Dec.<strong>20</strong>02 Dec.04 Dec. 06 Dec. 09 Onwards<br />

Category a b c d e f g<br />

1 1-a 1-b 1-c 1-d 1-e 1-f 1-g<br />

2 2-a 2-b 2-c 2-d 2-e 2-f 2-g<br />

3 3-a 3-b 3-c 3-d 3-e 3-f 3-g<br />

4 4-a 4-b 4-c 4-d 4-e 4-f 4-g<br />

3. Observation and Comment<br />

In this review, 100 publications in total are analyzed for the purpose <strong>of</strong> providing insights to the growth and<br />

development <strong>of</strong> worker allocation concept. These publications include specific papers in national/international<br />

journals, and conferences. Other articles such as exclusive reports in news magazines, newsletters, special columns<br />

and editorials are left out as the authors feel that they deal with general information in a limited manner. Similarly<br />

books written on worker allocation are also omitted from the review. Further, 26 publications belong to general<br />

aspects or fundamentals <strong>of</strong> worker allocation, 26 papers pertain to specific applications <strong>of</strong> worker allocation:<br />

applicable to FMS sector, 30 publications come under worker allocation: as resource allocation and finally, 18<br />

publications fall under the category worker allocation: applicable to various sectors.<br />

The U-shaped assembly lines is discussed by many authors and all these laments the facts <strong>of</strong> WA problem solution,<br />

this work was compiled by R. Sirovetnukul and P. Chutima (<strong>20</strong>09), in their paper named “worker allocation in U-<br />

shaped assembly lines with multiple objectives”. In the work <strong>of</strong> Wang, Liu and Wang (<strong>20</strong>10), ant colony algorithm<br />

is used to research task allocation and knowledge workers scheduling Ant colony optimization algorithm can reduce<br />

the number <strong>of</strong> optimization iteration and computing time. Under the category 4 the work <strong>of</strong> Brennan and Orwig<br />

(<strong>19</strong>94) is discussed as it discusses an algorithm approach to work allocation in combination with two different<br />

priorities and explains how this would affect firm performance and exploit its inherent flexibility. A faster and<br />

cheaper way compared with other methods is PSO (Particle Swarm Optimization) and the solution <strong>of</strong> problems was<br />

discussed by the work <strong>of</strong> Qing and Chao (<strong>20</strong>11).<br />

“Fig.2.” provides statistics <strong>of</strong> the mix <strong>of</strong> publications. In the pie chart we have just categorized our four factors and<br />

analyzed that all the four categories have equal distribution <strong>of</strong> papers but just one category which shows the<br />

applicability <strong>of</strong> worker allocation to various factors like Apparel production, cellular manufacturing, assembly cells,<br />

toxic environment, room dormitory etc. have the lesser number <strong>of</strong> publication than the others as just 18% <strong>of</strong> total are<br />

present.<br />

Figure 2. Mix <strong>of</strong> publications<br />

“Fig.3.” as shown below is showing the chronological categorization <strong>of</strong> all the four types. The first two<br />

categorization is consisting <strong>of</strong> five year gap and after that all preceding years are consists <strong>of</strong> a gap period <strong>of</strong> two<br />

years.<br />

The graph shows various vital trends. As in the year range <strong>of</strong> <strong>20</strong>05-06 slope is continuously upwards i.e. in this<br />

category the interest shown is quite higher than the other ones. One more thing that is interesting here is that these<br />

all categories show a similar rising trend in the last few year’s i.e. in the current years, topic <strong>of</strong> worker allocation is<br />

major concern for the researchers in the coming years and this is one <strong>of</strong> the hottest topic which is discussed today.<br />

725


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

As observed from the graph that in the category 2 (worker Allocation: Applicable to FMS Sector) during the time<br />

period <strong>19</strong>95-<strong>20</strong>00 it was very hot topic as a lot <strong>of</strong> work had been done over it which shows the interest <strong>of</strong><br />

researchers but after year <strong>20</strong>00 the slope is showing the declining trends.<br />

Figure 3. Graph showing chronological appearance <strong>of</strong> all publications<br />

4. References in the Bibliographical Index<br />

The bibliographic codes <strong>of</strong> different papers in all these four categories are shown below which can be traced with<br />

the time frame table and references. These codes are categories with the help <strong>of</strong> time frame table for yearly division<br />

and then categories into four categories which are chosen and discussed in methodology <strong>of</strong> review. This will provide<br />

a very good knowledge base to the researchers.<br />

Category 1: Worker Allocation: General/ Fundamentals/ Models<br />

1 A Sandra Parker, Eric M.Malstrom, Lisa M.Irwin, Grant<br />

DuCote (<strong>19</strong>94).<br />

1B Amanda Haynes (<strong>19</strong>99),<br />

A. Mital, A. Pennathur, R.L Huston, D. Thompson, M. Pittman, G.Markle, D.B Kaber, L.Crumpton, R.R<br />

Bishu, K.P Rajurkar, V Rajan, J.E Fernandez, M McMulkin,<br />

S. Deivanayagam, P.S Ray, D Sule (<strong>19</strong>99),<br />

Ulrich A.W.Tetzlaff and Erwin Pesch (<strong>19</strong>99).<br />

1C K. Nomoto, K Shima, M.Wakamatsu, Y.Shimizu, (<strong>20</strong>02).<br />

1D Bopaya Bidanda, Poonsiri Ariyawongrat, Kim Lascola<br />

Needy, Bryan A. Norman,Wipawee Tharmmaphornphilas (<strong>20</strong>03),<br />

Thomas K.L. Tong, C.M. Tam (<strong>20</strong>03).<br />

1E: Linn I.Sennott, Mark P.Van Oyen, Seyed M.R. Iravani<br />

(<strong>20</strong>06),<br />

Tijen Ertay, Da Ruan(<strong>20</strong>05).<br />

1F: Joni Hytonen, Esko Niemi, Ville Toivonen (<strong>20</strong>08),<br />

Tian- Syung Lan, Chih- Yao Lo , Cheng- I Hou (<strong>20</strong>08),<br />

Wenqiang Zhang, Mitsuo Gen and Lin Lin (<strong>20</strong>08).<br />

1G: Cecilia Navarra (<strong>20</strong>11),<br />

Eric J. Bartelsman, Pieter A. Gautier,Joris de Wind (<strong>20</strong>10),<br />

Esko Niemi (<strong>20</strong>09),<br />

Per Krusell, Toshihiko Mukoyama, Richard Rogerson, Aysegul Sahin (<strong>20</strong>10),<br />

Qing Wang, Min Liu, Qing Wang (<strong>20</strong>10),<br />

R.V. Murali, G. Prabhakaran, A.B. Puri, D. Ragavesh (<strong>20</strong>09),<br />

R. Sirovetnukul, P. Chutima (<strong>20</strong>09),<br />

R. Sirovetnukul1, P. Chutima (<strong>20</strong>10),<br />

Shrikant Jarugumilli, Scott. E. Grasman (<strong>20</strong>10),<br />

Sicong Tan, Wei Weng, and Shigeru Fujimura (<strong>20</strong>09),<br />

Soh, Lai Seng (<strong>20</strong>09),<br />

Wang Qing, Zheng Han-chao,(<strong>20</strong>11),<br />

Xianhui Zeng, Wai-Keung Wong, Sunney Yung-Sun Leung (<strong>20</strong>12).<br />

Category 2: Worker Allocation: FMS Applications<br />

726


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2 A Avneesh Prakash and Mingyuan Chen (<strong>19</strong>93),<br />

Chang-Qing Jiang, Madan G. Singh, Fellow, and Khalil S. Hindi (<strong>19</strong>91),<br />

Michael R. Spano Sr., Peter J. O'Grady, Robert E. Young (<strong>19</strong>93),<br />

Paul A. Savory, Gerald T. Mackulak, Jeffery K. Cochran (<strong>19</strong>91),<br />

Paul h. Algoet (<strong>19</strong>89),<br />

J. Rocha, C. Ramos (<strong>19</strong>94).<br />

2B Andrey V. Savkin (<strong>19</strong>98),<br />

Ding-Yu Lin, Sheue-Ling Hwang (<strong>19</strong>99),<br />

Jian-xin Xu (<strong>19</strong>96),<br />

MA.de Ridder, M.P. Spathopoulos (<strong>19</strong>94),<br />

Piero Persi, Walter Ukovich, Raffaele Pesenti, Marino<br />

Nicolich (<strong>19</strong>99),<br />

S. S. Erdogan and Keng Hon Teo (<strong>19</strong>96),<br />

M.P. Fanti, B. Maione, S. Mascolo, B. Turchiano (<strong>19</strong>95),<br />

Yung- Feng Chiu La-Chen Fu (<strong>19</strong>97).<br />

2C E. Atmaca, S. Erol (<strong>20</strong>00).<br />

2D Rakesh Narain, R.C. Yadav, Jiju Antony (<strong>20</strong>04),<br />

2E S. Chand (<strong>20</strong>06),<br />

Felix T.S. Chan, Rahul Swarnkar (<strong>20</strong>06),<br />

Manoj Kumar Tiwari, Sanjeev Kumar, Shashi Kumar,<br />

Prakash, and Ravi Shankar (<strong>20</strong>06),<br />

2F Anne Benoit, Loris Marchal, Jean-Franc¸ois Pineau, Yves<br />

Robert, Frederic Vivien (<strong>20</strong>08),<br />

B.Solvang, G.Sziebig, P.Korondi (<strong>20</strong>08),<br />

Tyagi Viraj & Jain Ajai (<strong>20</strong>08).<br />

2G Dongsheng Xu, Yinhua Ye, Yingna Lu and Shujin Deng<br />

(<strong>20</strong>10),<br />

S. R. Kodituwakku1 and H. R. O. E. Dhayarathne (<strong>20</strong>11),<br />

Martin Farnham, Emma Hutchinson (<strong>20</strong>11),<br />

K.Rezaie, S.N. Shirkouhi, S.M. Alem (<strong>20</strong>09).<br />

Category 3: Worker Allocation: As Resource Scheduling<br />

3 A Biman Kumar Ghosh, Martin G. Helander (<strong>19</strong>86),<br />

JH Gordon (<strong>19</strong>83),<br />

S.Jablonski, BReinwald, T.Rut, H.Wedekind (<strong>19</strong>90).<br />

3B<br />

Michela Taufer, Patricia J. Teller , David P. Anderson , and<br />

Charles L. Brooks (<strong>20</strong>05).<br />

3C Esbjörn Segelod (<strong>20</strong>02),<br />

Iima, H.; Sannomiya, N. (<strong>20</strong>01),<br />

Kurt M. Bretthauer, Bala Shetty (<strong>20</strong>02),<br />

Timothy Van Zandt (<strong>20</strong>00),<br />

Yanfeng Wang Perkins, J.R. Khurana, A. (<strong>20</strong>02).<br />

3D Abid A Burki, Mahmood-ul-Hasan Khan (<strong>20</strong>04),<br />

Ali Yalcin (<strong>20</strong>04),<br />

A.T Ernst, H Jiang, M. Krishnamoorthy, D Sier (<strong>20</strong>04),<br />

Charalambos Spathis, John Ananiadis (<strong>20</strong>04),<br />

H.C.W. Lau, A. Ning, W.H. Ip, K.L. Choy (<strong>20</strong>04).<br />

3E Chunlin Li, Layuan Li, Zhengding Lu (<strong>20</strong>05),<br />

Chunlin Li, Layuan Li (<strong>20</strong>05),<br />

Li Chunlin, Li Layuan (<strong>20</strong>06),<br />

M.S. Osman, M.A. Abo-Sinna, A.A. Mousa (<strong>20</strong>05),<br />

Oguzhan Ozbas (<strong>20</strong>05),<br />

Pornthep Anussornnitisarn, Shimon Y. N<strong>of</strong>, Opher Etzion<br />

(<strong>20</strong>05),<br />

Ricardo M. Bastos, Flavio M. de Oliveira, Jose Palazzo<br />

M.de Oliveira (<strong>20</strong>05),<br />

727


Sethavidh Gertphol, Viktor K. Prasanna (<strong>20</strong>05),<br />

Shengyong Wang, Song Foh Chew, and Mark A. Lawley<br />

(<strong>20</strong>05),<br />

Tai-Song Yin, Qing-Pu Zhang (<strong>20</strong>05),<br />

Zne-Jung Lee, Chou-Yuan Lee (<strong>20</strong>05).<br />

3F Azzedine Boukerche, Yunfeng GU (<strong>20</strong>07),<br />

Chia-Hsuan Wu, Ching-Cheng Chang, Ken N. Kuo (<strong>20</strong>08).<br />

3G Cao Xianzhou1, Yang Zhenhe (<strong>20</strong>11),<br />

Jingyao Li1, Shudong Sun1, Yuan Huang2, Ning Wang<br />

(<strong>20</strong>10),<br />

Ivica Sindiˇcic´, Stjepan Bogdan, and Tamara Petrovic<br />

(<strong>20</strong>11).<br />

Category 4: Worker Allocation: Extensions/ New Approaches/ Future Aspects<br />

4A Keith E. Herold and Reinhard Radermacher (<strong>19</strong>92),<br />

Linda L. Brennan, Robert A. Orwig (<strong>19</strong>94),<br />

Ramiro Villeda and Burton V. Dean (<strong>19</strong>90).<br />

4B Robert N. Tomastik, Peter B. Luh (<strong>19</strong>96).<br />

4C Agassounon, W.Martinoli, A.Goodman, R (<strong>20</strong>01),<br />

Jake Beal and Amanda Wozniak, Allen Rabinovich and<br />

Sebastian Ortiz (<strong>20</strong>02),<br />

G. Heike, M. Ramulu, E. Sorenson, P. Shanahan, K.<br />

Moinzadeh (<strong>20</strong>01).<br />

4D Chun-Hung Chen, Karen Donohue, Enver Yücesan, Jianwu<br />

Lin (<strong>20</strong>03),<br />

Gengui Zhou, Hokey Min, Mitsuo Gen (<strong>20</strong>03).<br />

4E Tayfun Sönmez, M. Utku Ünver (<strong>20</strong>05).<br />

4F Pyung-Hoi Koo, Woon-Seek Lee and Young Jin Kim<br />

(<strong>20</strong>07).<br />

Jaydeep Balakrishnan, Chun Hung Cheng (<strong>20</strong>07).<br />

4G Ali Azadeh, Behnaz Pourvalikhan Nokhandan, Sayed<br />

Mohammad Asadzadeh, Ehsan Fathi (<strong>20</strong>11),<br />

Amir Akrami, Mohammad Hasan Sebt, Mohammad Tagi<br />

Banki,Vahid Shahhosseini (<strong>20</strong>09),<br />

F. Andre, G. Gauvrit, C.Perez (<strong>20</strong>09),<br />

Jeff Crawford, Lori N.K. Leonard, Kiku Jones (<strong>20</strong>11),<br />

Ji-wen Sun, Li-feng Xi, Er-shun Pan, Shi-chang Du, Tangbin<br />

Xia (<strong>20</strong>09),<br />

Jose A. Diaz, Ileana G. Ptrez (<strong>20</strong>00),<br />

R.V. Murali, G. Prabhakaran, A.B. Puri, D. Ragavesh<br />

(<strong>20</strong>09),<br />

Q. Wang, S. Lassalle, A.R. Mileham, G.W. Owen (<strong>20</strong>09),<br />

Richard Edwards (<strong>20</strong>11)<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 2. Classification and brief description <strong>of</strong> models<br />

Sr.<br />

Authors Name Area <strong>of</strong> Implementation Technique Applied<br />

No.<br />

1. Abid A Burki, Mahmood-Ul-Hasan<br />

Khan.<br />

Pakistan's Manufacturing Resource Allocation & Energy<br />

Substitution<br />

2. W.Agassounon, A. Martinoli,<br />

Embedded System Scalable Distributed Algorithm<br />

R.Goodman.<br />

3. Ali Azadeh, Behnaz Pourvalikhan<br />

Nokhandan, Sayed Mohammad<br />

Asadzadeh, Ehsan Fathi.<br />

Cellular Manufacturing<br />

System<br />

Integrated Computer Simulation<br />

Genetic Algorithm Approach<br />

728


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4. Ali Yalcin. Automated Manufacturing<br />

Cells<br />

Supervisory Control With Resource<br />

Failures<br />

5. F. Andre, G.Gauvrit, C.Perez. Dynamic Adaptation Master-Worker Paradigm<br />

System<br />

6. Amanda Haynes. Manufacturing System Shop Floor Workers Control<br />

7. A Mital, A Pennathur, R.L.Huston, D<br />

Thompson, M.Pittman, G.Markle,<br />

Advanced Manufacturing<br />

System (AMT)<br />

Worker Training in Advanced<br />

Manufacturing System (AMT)<br />

D.B Kaber, L.Crumpton, R.R.Bishu,<br />

K.P Rajurkar, V.Rajan, J.E Fernandez,<br />

M. Mcmulkin, S.Deivanayagam, P.S<br />

Ray, D.Sule.<br />

8. Amir Akrami, Mohammad Hasan Sebt, Allocation to Project Expert Human Resources Process<br />

Mohammad Tagi Banki, Vahid<br />

Shahhosseini.<br />

9. Andrey V. Savkin. Flexible Manufacturing<br />

System<br />

Real-Time Scheduling as a Switched<br />

Server System<br />

10. Anne Benoit, Loris Marchal, Jean-<br />

Franc¸Ois Pineau, Yves Robert,<br />

FrEdEric Vivien.<br />

Concurrent Bags-<strong>of</strong>-Tasks<br />

on Heterogeneous<br />

Platforms<br />

Master-Worker Scheduling<br />

11. Avneesh Prakash, Mingyuan Chen. Flexible Manufacturing Factorial Design Techniques<br />

System<br />

12. E. Atmaca, S. Erol. Flexible Manufacturing Goal Programming Model<br />

System<br />

13. Azzedine Boukerche, Yunfeng Gu. Distributed Simulation Resource Allocation Scheme<br />

System<br />

14. A.T Ernst, H Jiang, M Krishnamoorthy, Rostering System Staff Scheduling<br />

D Sier.<br />

15. Biman Kumar Ghosh, Martin G. Manufacturing System Task Allocation<br />

Helander.<br />

16. Bopaya Bidanda,<br />

Manufacturing System Cell Design<br />

Poonsiri Ariyawongrat, Kim<br />

Lascola Needy, Bryan A. Norman,<br />

Wipawee Tharmmaphornphilas.<br />

17. Cao Xianzhou1, Yang Zhenhe. Flexible Job Shop Genetic Algorithm<br />

18. Cecilia Navarra. Italian Worker<br />

Cooperatives<br />

Empirical Analysis on Workers'<br />

Perception and Motivation<br />

<strong>19</strong>. S Chand. Flexible Manufacturing Autonomous Systems<br />

System<br />

<strong>20</strong>. Chang-Qing Jiang, Madan G. Singh, Flexible Manufacturing Optimized Routing<br />

Fellow, Khalil S. Hindi.<br />

System<br />

21. Charalambos Spathis, John Ananiadis. Public <strong>University</strong> Resource Allocation Reform<br />

22. Chia-Hsuan Wu, Ching-Cheng Chang, Healthcare System In Resource Allocation<br />

Ken N. Kuo.<br />

Taiwan<br />

23. Chunlin Li, Layuan Li, Zhengding Lu. Competitive Market Computational Grid<br />

24. Chunlin Li, Layuan Li. Distributed Utility Functions<br />

Decomposition System<br />

25. Chun-Hung Chen, Karen Donohue,<br />

Enver Yücesan, Jianwu Lin.<br />

For Monte Carlo<br />

Simulation<br />

Optimal Computing Budget<br />

Allocation<br />

26. Ding-Yu Lin, Sheue-Ling Hwang. Flexible Manufacturing Neural Network<br />

System<br />

27. Dongsheng Xu, Yinhua Ye, Yingna Lu<br />

and Shujin Deng.<br />

Project Management Two-Stage Stochastic Programming<br />

Model<br />

729


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

28. Eric J. Bertelsmann, Pieter A. Gautier,<br />

Joris De Wind.<br />

Industries Employment Protection, <strong>Technology</strong><br />

Choice, and Worker Allocation<br />

29. Esbjorn Segelod. Production System Resource Allocation<br />

30. Esko Niemi. Robotics and Computer- Make-To-Order Assembly Cells<br />

Integrated Manufacturing<br />

31. Felix T.S. Chan, Rahul Swarnkar.<br />

Gengui Zhou, Hokey Min, Mitsuo Gen.<br />

Flexible Manufacturing<br />

System<br />

Genetic Algorithm<br />

Approach<br />

Ant Colony & Fuzzy Programming<br />

Model<br />

Genetic Algorithm Approach<br />

32. G. Heike, M. Ramulu, E. Sorenson, P. Aerospace Industry Mixed Model Assembly<br />

Shanahan, K. Moinzadeh.<br />

33. H.C.W. Lau, A. Ning, W.H. Ip, K.L.<br />

Choy.<br />

Decision Support System O lap-Based Neural Network<br />

Approach<br />

34. H. Iima, N.Sannomiya. Modified Scheduling Genetic Algorithm<br />

Problems<br />

35. Ivica Sindi Cic, Stjepan Bogdan, and Manufacturing System Machine-Job Incidence Matrix<br />

Tamara Petrovic.<br />

36. Jake Beal And Amanda Wozniak, Random Hall Dormitory Desk Worker Allocation<br />

Allen Rabinovich And Sebastian Ortiz.<br />

37. Jaydeep Balakrishnan, Chun Hung Cellular Manufacturing Multi Period Planning<br />

Cheng<br />

38. Jeff Crawford, Lori N.K. Leonard,<br />

Human Resource Resource's Influence<br />

Kiku Jones.<br />

39. Jh Gordon. Project Management Heuristic Methods<br />

40. Jingyao Li, Shudong Sun1, Yuan<br />

Job Shop Hybrid Algorithm<br />

Huang, Ning Wang.<br />

41. Jian-Xin Xu. Flexible Manufacturing<br />

System<br />

Fuzzy Petri Net-Based Optimum<br />

Scheduling<br />

42. Ji-wen Sun, Li-feng Xi, Er-shun Pan. Multi station Sensor Allocation Optimization<br />

Manufacturing System<br />

43. Joni Hytonen, Esko Niemi, Ville<br />

Assembly Lines Workforce Allocation<br />

Toivonen.<br />

44. Jose A. Diaz, Ileana G. Ptrez. Sugar Cane Transportation Simulation And Optimization<br />

45. Keith E. Herold and Reinhard<br />

Radermacher.<br />

Absorption Heat Pump Optimum Allocation <strong>of</strong> Heat<br />

Transfer Surface<br />

46. Kurt M. Bretthauer, Bala Shetty. Nonlinear Resource Pegging Algorithm<br />

Allocation Problem<br />

47. Li Chunlin, Li Layuan. Joint Grid User Computational Grid<br />

48. Linda,L. Brennan, Robert A. Orwig. Knowledge-Intensive Worker allocation<br />

Firms<br />

49. Linn i. Sennott, Mark P. Van Oyen,<br />

Production Line Dynamic Assignment<br />

Seyed M.R. Iravani.<br />

50. Ma.De Ridder, M.P. Spathopoulos. Flexible Worker <strong>of</strong> A<br />

Flexible Manufacturing<br />

System<br />

Hierarchical Modeling and<br />

Distributive Control Systems<br />

51. Manoj Kumar Tiwari, Sanjeev Kumar,<br />

Shashi Kumar, Prakash, and Ravi<br />

Shankar.<br />

Flexible Manufacturing<br />

System<br />

Constraints-Based Fast Simulated<br />

Annealing Algorithm<br />

52. Martin Farnham, Emma Hutchinson. Labor Productivity Multi Skilling<br />

53. Michael R. Spano Sr., Peter J. O'grady, Flexible Manufacturing Computers Design<br />

730


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Robert E. Young.<br />

Systems<br />

54. Michela Taufer , Patricia J. Teller , Global Computing Effective Resource Management<br />

David P. Anderson , and Charles L.<br />

Brooks.<br />

Environment<br />

55. M.P. Fanti, B. Maione, S. Mascolo, Flexible Manufacturing Resource Allocation<br />

B.Turchiano.<br />

Systems<br />

56. M.S. Osman, M.A. Abo-sinna, A.A. Multi Objective Resource Genetic Algorithm<br />

Mousa.<br />

Allocation<br />

57. K. Nomoto, K. Shima, M.Wakamatsu, Manufacturing System Attention Allocation Model<br />

Y. Shimizu.<br />

58. Oguzhan Ozbas. Financial Organization Resources Allocation<br />

59. Paul A. Savory, Gerald T. Mackulak, Flexible Manufacturing Material Handling<br />

Jeffery K. Cochran.<br />

System<br />

60. Paul H. Algoet. Flexible Manufacturing<br />

System<br />

Steady-State Distribution & Flow<br />

Balance Equations<br />

61. Per Krusell , Toshihiko Mukoyama, General Equilibrium Three State Model<br />

Richard Rogerson, Ayşegül Şahin.<br />

62. Piero Persi, Walter Ukovich, Raffaele Flexible Manufacturing Hierarchic Approach<br />

Pesenti, Marino Nicolich.<br />

System<br />

63. Pornthep Anussornnitisarn, Shimon Y. Production System Decentralized Control<br />

N<strong>of</strong>, Opher Etzion.<br />

64. Pyung-Hoi Koo, Woon-Seek Lee And Assembly Cells Work Assignment<br />

Young Jin Kim.<br />

65. Qing Wang, Min Liu, Qing Wang. Task Allocation & Ant Colony Algorithm<br />

Knowledge Workers<br />

Scheduling System<br />

66. Q. Wang, S. Lassalle, A.R. Mileham,<br />

G.W. Owen.<br />

Walking Worker Line Computer Simulation &<br />

Mathematical Modeling Approach<br />

67. Rakesh Narain, R.C. Yadav, Jiju Flexible Manufacturing Productivity Gains<br />

Antony.<br />

System<br />

68. Ramiro Villeda and Burton V. Dean. Toxic Substance<br />

Environment<br />

Safe Allocation and Scheduling<br />

5. Critical View and Conclusions<br />

There is not so much proliferation <strong>of</strong> literature on the topic <strong>of</strong> worker allocation, it can be said that the WA<br />

technique requires a lot <strong>of</strong> work because now a day’s many <strong>of</strong> the applications <strong>of</strong> FMS requires optimum allocation<br />

<strong>of</strong> resources and WA is one among them which is very effective to discuss for complete results. A categorization <strong>of</strong><br />

the publications shows that several aspects <strong>of</strong> worker allocation along with many interesting and diversified<br />

applications are having equal importance to the area <strong>of</strong> flexible manufacturing systems.<br />

This study <strong>of</strong> publications can serve a great deal towards quality improvement & review <strong>of</strong> 100 papers will help to<br />

understand the WA problem in a better way and definitely provide solutions for the same as WA is a key resource<br />

element in flexible manufacturing system. A small example <strong>of</strong> its effectiveness is that when the authors visited many<br />

small scale industries in the nearby area <strong>of</strong> Faridabad, then there the authors have seen that these industries were not<br />

giving any kind <strong>of</strong> preference to these matters. But when the same thing is observed on the large scale industries,<br />

they had told the authors that they were adopting these practices since many years and one <strong>of</strong> the example they have<br />

shared that in earlier times they were hiring the male candidates for the pick and place attachments & after a<br />

thorough study it was observed that when the female candidates was adopted for the same purpose then they were at<br />

very much ease as compare to their counterparts because <strong>of</strong> their fine edges <strong>of</strong> the forefingers.<br />

Recently a leading automobile manufacturer in India faced similar problems due to lack <strong>of</strong> managing capabilities in<br />

worker allocation. Still for some <strong>of</strong> the companies it may be a very high investment issue to implement the worker<br />

731


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

allocation practices as it is also affecting the budget <strong>of</strong> the smaller firms but at the time they are not much aware <strong>of</strong><br />

its utility because it comes at level in the benefits where you have to first invest in the starting and the results will<br />

come in a due period <strong>of</strong> time. So in all and all this is a part <strong>of</strong> continuous improvement which will definitely<br />

improve the net worth <strong>of</strong> the firms. By understanding the criticality the authors had chosen this to review the<br />

literature on WA problem. A concise representation <strong>of</strong> the earlier work on WA problem is presented for its better<br />

understanding. So the authors study will help the researchers as whole information <strong>of</strong> worker allocation is available<br />

in a concise form and they will find a very vast knowledge base through the authors work.<br />

The paper cites 100 articles from a variety <strong>of</strong> published sources mainly from <strong>19</strong>90 to <strong>20</strong>12 and a few published work<br />

prior to <strong>19</strong>90.<br />

The work done by the authors will definitely help to understand the problems <strong>of</strong> WA and will help to identify the<br />

critical areas and impacts <strong>of</strong> it on the FMS. It is hoped that this paper will improve the view towards the WA in the<br />

context <strong>of</strong> FMS.<br />

References<br />

1. Burki, A.A., Khan, M. U. H., (<strong>20</strong>04) Effects <strong>of</strong> Allocative Inefficiency on Resource Allocation and Energy<br />

Substitution in Pakistan's Manufacturing, Energy Economics, Vol. 26, n. 3, pp. 371-388.<br />

2. Agassounon, Martinoli, W., Goodman, A., (<strong>20</strong>01) A Scalable, Distributed Algorithm for Allocating<br />

Workers in Embedded Systems , Systems, Man, and Cybernetics, IEEE International Conference, Vol. 5,<br />

pp. 3367 – 3373.<br />

3. Azadeh, A., Nokhandan, B.P., Asadzadeh, S.M., Fathi, E., (<strong>20</strong>11) Optimal Allocation <strong>of</strong> Operators in a<br />

Cellular Manufacturing System by an Integrated Computer Simulation Genetic Algorithm Approach,<br />

International Journal <strong>of</strong> Operational Research , Vol. 10, n.3, pp. 333 – 360.<br />

4. Yalcin, A., (<strong>20</strong>04) Supervisory Control <strong>of</strong> Automated Manufacturing Cells with Resource Failures ,<br />

Robotics and Computer-Integrated Manufacturing, Vol. <strong>20</strong>, n. 2, pp. 111-1<strong>19</strong>.<br />

5. Andre F., Gauvrit, G., Perez, C., (<strong>20</strong>09) Dynamic Adaptation <strong>of</strong> the Master-Worker Paradigm, Ninth IEEE<br />

International Conference on Computer andInformation<strong>Technology</strong>, pp. 185 – <strong>19</strong>0.<br />

6. Haynes, A., (<strong>19</strong>99)Effects <strong>of</strong> World Class Manufacturing on Shop Floor Workers, Journal <strong>of</strong> European<br />

Industrial Training, Vol. 23, n. 6.<br />

7. Mital, A., Pennathur, A., Huston, R.L., Thompson, D., Pittman, M., Markle, G., Kaber, D.B., Crumpton, L.,<br />

Bishu, R.R., Rajurkar, K.P., Rajan, V., Fernandez, J.E., Mcmulkin, M., Deivanayagam, S., Ray, P.S., Sule,<br />

D., (<strong>19</strong>99) The Need for Worker Training in Advanced Manufacturing <strong>Technology</strong> AMT Environments ,<br />

International Journal Of Industrial Ergonomics, Vol. 24, n. 2, pp. 173-184.<br />

8. Akrami, A., Sebt, M.H., Banki, M.T., Shahhosseini, V., (<strong>20</strong>09) Optimized Allocation <strong>of</strong> Expert Human<br />

Resources to Project , Third Asia International Conference on Modelling & Simulation.<br />

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Florida USA.<br />

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Worker Scheduling <strong>of</strong> Concurrent Bags-<strong>of</strong>-Tasks on Heterogeneous Platforms, Proceedings <strong>of</strong> The IEEE.<br />

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732


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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

16. Bidanda, B., Ariyawongrat, P., Needy, K.L., Norman, B.A., Tharmmaphornphils, X., (<strong>20</strong>03) Human<br />

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733


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

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Knowledge-Intensive Firms, Proceedings <strong>of</strong> the IEEE.<br />

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on an Open Production Line with Specialists , European Journal <strong>of</strong> Operational Research,<br />

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51. Ridder, M.D., Spathopoulos, M.P., (<strong>19</strong>94) Hierarchical Modelling and Distributive Control Systems Design<br />

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Annealing Algorithm , IEEE Transactions on Systems, Man, And Cybernetics—Part A: Systems And<br />

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734


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

60. Savory, P.A., Mackulak, G.T., Cochran, J.K., (<strong>19</strong>91) Material Handling in a Flexible Manufacturing<br />

System Processing Part Families, Proceedings <strong>of</strong> the <strong>19</strong>91 Winter Simulation Conference Barry Nelson, W.<br />

David kelton, Gordon m. Clark EDS.<br />

61. Algoet, P.H., (<strong>19</strong>89) Flow Balance Equations for the Steady-State Distribution <strong>of</strong> a Flexible Manufacturing<br />

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62. Krusell, P., Mukoyama, T., Rogerson, R., Şahin, A., (<strong>20</strong>11) A Three State Model Of Worker Flows In<br />

General Equilibrium, Journal <strong>of</strong> Economic Theory,Vol.146,n.3,pp.1107-1133.<br />

63. Persi, P., Ukovich, W., Pesenti,R., Nicolich, M.,(<strong>19</strong>99) A Hierarchic Approach to Production Planning and<br />

Scheduling <strong>of</strong> a Flexible Manufacturing System, Robotics and Computer-Integrated Manufacturing,Vol.<br />

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Economics, Vol. 98, n. 2, pp. 114-128.<br />

65. Koo, P.H., Lee, W.S., Kim, Y.J., (<strong>20</strong>07) Performance Analysis <strong>of</strong> a New Work Assignment in Assembly<br />

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66. Wang, Q., Liu, M., Wang, Q., (<strong>20</strong>10) Optimization Of Task Allocation and Knowledge Workers<br />

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Processing and Trusted Computing.<br />

67. Wang, Q., Lassalle, S., Mileham, A. R., G.W. Owen, (<strong>20</strong>09) Analysis <strong>of</strong> a Linear Walking Worker Line<br />

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Manufacturing Systems, Vol. 28, n. 2-3, pp. 64-70.<br />

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69. Villeda, R.,Dean, B.V.,(<strong>19</strong>90) On the Optimal Safe Allocation and Scheduling <strong>of</strong> a Work Force in a Toxic<br />

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74. Murali, R.V., Prabhakaran, G., Puri, A.B., Ragavesh, D.,(<strong>20</strong>09) Worker Efficiency And Job Criticality<br />

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Objectives, Proceedings Of The <strong>20</strong>09 IEEE IEEM.<br />

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Scheduling In A Manufacturing Environment, Computers & Industrial Engineering, Vol. 27, n. 1-4, pp.<br />

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78. Gertpho, S.,Prasanna, P.K.,(<strong>20</strong>05) MIP Formulation for Robust Resource Allocation in Dynamic Real-<br />

Time systems , Journal <strong>of</strong> Systems and S<strong>of</strong>tware,Vol. 77, n. 1, pp. 55-65.<br />

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Failure Prone Manufacturing Systems, Proceedings <strong>of</strong> the IEEE International Conference on Automation<br />

<strong>Science</strong> and Engineering Edmonton, Canada.<br />

80. Jarugumilli, S., Grasman, S.E.,(<strong>20</strong>10)Single-Shift Worker Allocation using Two-Phase Goal Programming,<br />

Proceedings <strong>of</strong> the 4th Annual ISC Research Symposium ISCRS.<br />

81. Tan, S., Weng, W., Fujimura, S., (<strong>20</strong>09) Scheduling Of Worker Allocation In The Manual Labor<br />

Environment With Genetic Algorithm , Proceedings <strong>of</strong> The International Multiconference <strong>of</strong> Engineers and<br />

Computer Scientists Vol. 1.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

82. Solvang, B., Sziebig, G., Korondi, P., (<strong>20</strong>08)Multilevel Control <strong>of</strong> Flexible Manufacturing Systems,<br />

Human System Interactions, pp. 785 – 790.<br />

83. Soh, Seng, L.,(<strong>20</strong>09) Scheduling and Manpower Allocation for Hotel Banquet Functions, 16th<br />

International Conference on industrial Engineering and Engineering Management, pp. 1398 – 1402.<br />

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86. Kodituwakku1, S.R., Dhayarathne, H.R.O.E., (<strong>20</strong>11) Statistical Approach to Optimize Master-Worker<br />

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87. Yin, T.S., Zhan, Q.P.,(<strong>20</strong>05) Dynamic Game Analysis in Worker's Tacit Knowledge Sharing Process in<br />

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88. Sönmez, T., Unver, M.U.,(<strong>20</strong>05) House Allocation with Existing Tenants: An Equivalence, Games and<br />

Economic Behavio, Vol. 52, n, 1, pp. 153-185.<br />

89. Tong, T.K.L., Tam, C.M.,(<strong>20</strong>03) Fuzzy Optimization <strong>of</strong> Labor Allocation by Genetic Algorithms,<br />

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90. Lan, T.S., Lo, C.Y., Hou, C.I., (<strong>20</strong>08)Optimum Production Control And Workforce Scheduling Of<br />

Machining Project, Journal Of Applied <strong>Science</strong>s, Vol.8, pp. 836-841.<br />

91. Zandt, T.V.,( <strong>19</strong>95) Hierarchical Computation <strong>of</strong> the Resource Allocation Problem, European Economic<br />

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97. Zeng, X., Wong, W.K., Leung, S.Y.S.,(<strong>20</strong>12) An Operator Allocation Optimization Model for Balancing<br />

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736


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

TO STUDY THE IMPLEMENTATION OF PARETO ANALYSIS IN SME<br />

INDIAN INDUSTRIES BY USING CAUSE AND EFFECT DIAGRAM: A<br />

CASE STUDY<br />

Kailash Attri¹, Rajeev Kr. Saha²<br />

1 Research Scholar, Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & Tech., Faridabad,<br />

India<br />

2 Asst. Pr<strong>of</strong>., Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & Tech., Faridabad, India<br />

1* kailashattri.257@gmail.com<br />

Abstract<br />

The new generation has brought new challenges for firms, industries and countries. Success in such times is<br />

demanding new perspectives on competitiveness. Analysis <strong>of</strong> problems <strong>of</strong> SME in India identified cause in<br />

understanding about the concept and its implementation. Review <strong>of</strong> SME related literature, clearly indicated the<br />

factors responsiblefor problems <strong>of</strong> SME. The focus <strong>of</strong> this work is on review <strong>of</strong> literature at the small medium<br />

enterprise Indian industries and study <strong>of</strong> Pareto analysis -related frameworks and models. The studies are<br />

further classified on the cause and effect frameworkkey criteria. Select frameworks and models <strong>of</strong> Pareto<br />

Analysis were reviewed and categorized. A cause and effect diagram analysis is used for find out the real cause<br />

<strong>of</strong> problems <strong>of</strong> SME.<br />

Key words: Pareto Analysis, Cause and Effect Diagram, Small & Medium Enterprises (SME)<br />

1. Introduction<br />

SME are considered backbone <strong>of</strong> economic growth in all countries. Since economic reforms in <strong>19</strong>91, Indian<br />

small and medium enterprises (SME) are facing a very different scenario compared with the protective<br />

environment for the past. Due to global competition, technological advances and changing needs <strong>of</strong> consumers,<br />

competitive paradigms are continuously changing. These changes are driving firms to competitors,<br />

simultaneously along several different dimensions such as design and development <strong>of</strong> product, manufacturing,<br />

distribution, communication and Marketing[1].Seven Quality tool is becoming more efficient and more<br />

responsive to find out the cause <strong>of</strong> problems <strong>of</strong> SME Indian industries.Today is the time <strong>of</strong> competition.<br />

Everyone wants the better quality <strong>of</strong> product at minimum cost. There are various techniques to analyze and solve<br />

work related problems like brain storming, Pareto analysis, cause and effect analysis, along with several methods<br />

<strong>of</strong> data collection and analysis [4]. Pareto analysis and cause and effect analysis are widely being used in small<br />

medium scale industry to identify the cause <strong>of</strong> problems related to the quality and productivity [2]. The purpose<br />

<strong>of</strong> this paper is to identify the problem related to the Indian SME using cause and effect analysis. It plays a major<br />

role in integrating manufacturing and managing them more effectively. Almost every industrial company is now<br />

considering the implementation <strong>of</strong> an advanced system more efficiently.<br />

2. Research Objectives<br />

The Pareto Analysis framework is to be developed for analysis <strong>of</strong> strategy formulation in finding out the cause <strong>of</strong><br />

problems. Any SME can be analyzed and evaluated on the basis <strong>of</strong> various key items <strong>of</strong> framework. For our<br />

study, we have undertaken a Fabrication Company. Therefore this study is aimed to<br />

-Develop a case study with Pareto Analysis framework for analyzing the cause <strong>of</strong> problems<br />

- Identify performance indicators in SME.<br />

3. Company Pr<strong>of</strong>ile<br />

TFI Ltd is family run company, which started its operation in <strong>19</strong>94 with vision <strong>of</strong> becoming a supplier <strong>of</strong> heavy<br />

fabricated itemsfortheoriginal equipment manufacturers. With the coming <strong>of</strong> construction Equipments<br />

Company like JCB ltd, Action Construction Equipments, Riva, Hercules, Ind<strong>of</strong>arm,(ECEL, a unit <strong>of</strong> Escort’s<br />

ltd.), MetsoMinerals group etc, there was a strong need <strong>of</strong> good quality parts suppliers. The company becomes<br />

an automatic choice for thiscompany due to its commitment towards quality and on time delivery.TFI Ltd. is an<br />

ISO-9001 – <strong>20</strong>00 company and manufacturers <strong>of</strong> heavy fabrication items like main Frames, Boomscabin and<br />

other child parts for different models cranes. These materials help in producing consistent quality products. The<br />

total manpower employed is 150 which include qualified engineers having expertise in quality control, process<br />

control, product development etc. The unit has an annual turnover <strong>of</strong> 35 Cr and current year growth in all respect<br />

is targeted to be 12% higher then the previous year. The manufacturing operations are located in Faridabad<br />

having a total area <strong>of</strong> 1500 square yard.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3.1 Key Items <strong>of</strong> the Framework<br />

- Less accuracy <strong>of</strong> different types <strong>of</strong> machines.<br />

- Insufficient inventory <strong>of</strong> materials.<br />

- Discontinues flow <strong>of</strong> material inside the company.<br />

- Insufficient skills <strong>of</strong> labor.<br />

- Oldest methods <strong>of</strong> manufacturing are used in it.<br />

- Lack <strong>of</strong> coordination.<br />

- Insufficient tooling.<br />

- No testing and calibration <strong>of</strong> Instruments.<br />

- More pressure on Production.<br />

- Not concentrated about the quality <strong>of</strong> highly demanded product etc.<br />

3.2 Organization Hierarchies in TFI Ltd<br />

TFI ltd consists <strong>of</strong> various performance parameters which are related to different departments <strong>of</strong> company. Like<br />

Administration, Production, Quality Control, Customer interface and Suppliers Interface etc. Performance <strong>of</strong> a<br />

company is <strong>of</strong>ten measured as a ratio <strong>of</strong> output to input [8]. Performance Analysis confidence and trust are the<br />

two enduring values associated with TFI Ltd.TFI Ltd has maintained its leadership in the construction<br />

equipments manufacturing market by continuously improving its coming problems. Problem Analysis <strong>of</strong> a firm<br />

can be assessedon multiple parameters <strong>of</strong> Seven Q.C. tools and by comparingproductresults, process results, and<br />

customerresults with other competitors etc. Organization Hierarchies in TFI Ltd. [7]is shown in fig.1<br />

GENERAL MANAGER<br />

Administra<br />

tion<br />

Supplier<br />

Interface<br />

Team<br />

Production<br />

Quality<br />

Control<br />

Customer<br />

Interface<br />

team<br />

Finance &<br />

accounting<br />

Purchase<br />

Taxation<br />

Store<br />

Project<br />

& plant<br />

Maintenance<br />

Commercial<br />

Information System<br />

Figure1. Organization Hierarchies inTFI Ltd<br />

3.3 Pareto Analysis <strong>of</strong> TFI Ltd.<br />

TFI Ltd. is able to complete the order <strong>of</strong> OEM per month. The analysis <strong>of</strong> rejections pointed that 30% to 40%<br />

fabricating items are rejected due to quality problems <strong>of</strong> welding and machining, 40% <strong>of</strong> items are rejected due<br />

to welding defects, 30% are rejected due to machining problems and 5% problems are created due to production<br />

rate delay [3]. According to Pareto Analysis the major part <strong>of</strong> problems may be caused by small number <strong>of</strong><br />

possible causes. (Shown in Pareto diagram fig 2a).<br />

Major parts <strong>of</strong> rejection <strong>of</strong> items are created by minor causes. Thus,first <strong>of</strong> all company should concentrate on<br />

those minor causes which are responsible for major parts <strong>of</strong> rejection.In this particular case, welding defects are<br />

the minor cause due to which large numbers <strong>of</strong> parts arebeing rejected. It requires efforts at individual level,<br />

organizational level, and at inter-Organizational level. Pareto Analysis is very effective tool to analyze the<br />

case study to explore the present situation in TFI Ltd. The impact <strong>of</strong> these proposed actions on the performance<br />

is visualized in the context <strong>of</strong> TFI Ltd.[5] shown in fig.2b, Frame work <strong>of</strong> Pareto Analysis [9].<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

45%<br />

40%<br />

35%<br />

30%<br />

25%<br />

<strong>20</strong>%<br />

15%<br />

10%<br />

5%<br />

0%<br />

1 2 3<br />

Figure 2a.ParetoAnalysis diagram<br />

Taking total rejection along y axis, Cause <strong>of</strong> failure (defects) along x axis respectively<br />

(1) Welding defects Problem<br />

40% <strong>of</strong> items are rejected<br />

PARETO ANALYSIS<br />

AT TFI Ltd<br />

(2) Machining problems<br />

30% <strong>of</strong> items are rejected<br />

(3) Production rate delay<br />

5% problems are created<br />

Figure 2b.Frame work <strong>of</strong> Pareto Analysis<br />

3.4 Data analysis<br />

On the basis <strong>of</strong> this study and implementation in TFI ltd.The problems <strong>of</strong> company TFI ltd can also be find out<br />

with the help <strong>of</strong> cause and effect diagrams. .Welding defects, Machining defects and Production rate delays are<br />

the problems which are caused due to various key items. Cause and effects diagrams are very helpful to find out<br />

the real cause <strong>of</strong> problems as shown in fig 3a, 3b and 3c.<br />

-<br />

Inadequate skill <strong>of</strong> worker<br />

Careless worker<br />

Old welding m/c without indicators<br />

Welding defects<br />

High flow <strong>of</strong> inert gas<br />

Insufficient value <strong>of</strong> V, I<br />

Poor edge preparation<br />

Figure 3a. Cause and effects diagrams for welding defects<br />

739


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Labour turnover<br />

Less skill <strong>of</strong> worker<br />

Absenteeism<br />

Loose supervision with poor<br />

Production Process<br />

Insufficient production<br />

programming<br />

Poor maintenance, Break down maintenance<br />

Insufficient Inventory<br />

Material follow-up and Procurement<br />

Delay <strong>of</strong><br />

Production Rate<br />

Figure 3b. Cause and effects diagrams for delay <strong>of</strong> Production Rate<br />

Shortage <strong>of</strong> tech. staff in sales<br />

Unskilled operators<br />

Poor maintenance, Insufficient tooling<br />

Lack <strong>of</strong> training<br />

Machining<br />

Problems<br />

Improper tool work vel.<br />

ratio<br />

Improper tooling and material<br />

Error in gauges and fixtures<br />

Figure 3c. Cause and effects diagrams for Machining Problems<br />

3.5 Results<br />

Inthisstudyitfoundthat this study has demonstrated –that even a medium size organization, facing many pressure<br />

and constraints due to globalization <strong>of</strong> markets can sustain its competitiveness. For this it is essential that<br />

organizations should not target only end result but should develop its enablers also such as competitive strategies<br />

and processes to overcome on various pressure and constraints. On the basis <strong>of</strong> this analysis, it is observed that<br />

most <strong>of</strong> sub minor causes create major problems <strong>of</strong> defects.<br />

On the basis <strong>of</strong> Pareto analysis, and cause and effects diagrams, organizations can concentrate on the minor<br />

causes <strong>of</strong> problems. Because minor causes are responsible for large number <strong>of</strong> rejected items.<br />

These strategies are helpful to initiate healthy competition among different members <strong>of</strong> competitors<br />

thereby improving the competiveness in global market.<br />

3.6 Conclusions<br />

- This study will motivate SME Indian industries to upgrade themselves proactively to meet the changing<br />

requirement <strong>of</strong> market. Most <strong>of</strong> the SMEs are still far away from the idea <strong>of</strong> upgrading Research&Development<br />

activities, <strong>Technology</strong>up gradation, Application <strong>of</strong> IT tools and Advanced Management Systems as well as<br />

reluctance for change [6].<br />

- Effective communication and coordinated activity results in more refined and informed decision-making.<br />

References<br />

[1] Rajesh K. Singh, Suresh K. Garg. (<strong>20</strong>06) “Competitiveness Analysis <strong>of</strong> a medium scale Organization in<br />

India” International Journal <strong>of</strong> Global Business and Competitiveness, vol. No. PP. 27-40.<br />

[2] Narula, R. (<strong>20</strong>04),’’R & D collaboration by SMEs: New Opportunities and Limitations in the face <strong>of</strong><br />

Globalization”, Technovation, Vol.24, pp.153-161<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[3] Gunasekaran,A., Marri,H.B.,Mcgauahey,R.andGrieve,R.J.(<strong>20</strong>01),“Implications<strong>of</strong> organization and human<br />

behavior on the implementation <strong>of</strong> CIM in SMEs: an empirical analysis”, International Journal <strong>of</strong> CIM, vol.<br />

14, no. 2, PP. 175-85.<br />

[4] GunasekaranA.,C.Patel,E.Tirtiroglu, (<strong>20</strong>01), “PerformanceMeasuresandMetricsinaSupply Chain<br />

environment,”InternationalJournal<strong>of</strong>Operations&ProductionManagement,vol-21,no.1-2,PP.71-87.<br />

[5] Mahesh Chand& R K Singh, September 23 – 25, (<strong>20</strong>10), “Study <strong>of</strong> Select Issues <strong>of</strong> Supply Chain<br />

Management: A Case Study” at 4 th International Conference Advance in Mechanical Engineering, SVNIT<br />

Surat.<br />

[6] Panos Kouvelis, Joseph M. Milner (<strong>20</strong>02), “Supply chain capacity and outsourcing decisions: the dynamic<br />

interplay <strong>of</strong> demand and supply uncertainty”. (Journal <strong>of</strong> IIE Transactions <strong>20</strong>02 vol-34 page 717-728).<br />

[7] Kailash Attri & Mahesh Chand, November 17 –<strong>19</strong>, (<strong>20</strong>11), “Competitiveness Analysis <strong>of</strong> a Manufacturing<br />

Organization From Supply Chain Perspectives: A Case Study” at 14 th International Conference on Industrial<br />

Engineering, SVNIT Surat.<br />

[8] Singh R.K, Garg, S.K and Deshmukh,, S.G.(<strong>20</strong>04), “Competitiveness <strong>of</strong> small and medium enterprises:<br />

Case <strong>of</strong> an Indian auto component manufacturing organization”, IIMB Management Review, vol.16,No.4,<br />

PP ,94-102.<br />

[9] Singh R.K, Garg, S.K and Deshmukh,, S.G.(<strong>20</strong>05), “Measuring Competitiveness index: A framework”,<br />

Productivity Promotion, Vol. ., No.31, PP.39-50.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

LEAN MANUFACTURING SYSTEM: AN OVERVIEW<br />

Rakesh Kumar 1* , Vikas Kumar 2<br />

1 Research Scholar, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad-121006 (Haryana)<br />

2 Associate Pr<strong>of</strong>essor, Mechanical Engineering Department, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>,<br />

Faridabad-121006 (Haryana)<br />

1* e-mail: rakesh_siwach@yahoo.com<br />

Abstract<br />

Manufacturing organizations has always been facing pressure to align themselves with fast changing customer<br />

requirements quickly and at low cost. To meet these challenges Lean Manufacturing is widely accepted<br />

philosophy which helps industry by making them able to solve manufacturing issues, identification and<br />

elimination <strong>of</strong> waste, improving their productivity, quality, reducing cost and developing people for next level <strong>of</strong><br />

challenges. Purpose <strong>of</strong> this paper is to present concept and overview <strong>of</strong> Lean Manufacturing.<br />

Keywords: Lean Manufacturing, Concept, objectives, principles, implications, Lean structure<br />

1. Introduction<br />

Many <strong>of</strong> the best practices in manufacturing have been practiced and developed by Toyota. Toyota got famous<br />

for efficient operations in 80’s all over the world by effectively implementation <strong>of</strong> JIT system. Toyota<br />

Production System has been studied by many <strong>of</strong> researchers namely Adler, <strong>19</strong>93; Womack and Jones, <strong>19</strong>94;<br />

Liker, <strong>19</strong>98; Sobek et al. <strong>19</strong>98; Spear and Bowen, <strong>19</strong>99; Mike Rother, <strong>20</strong>09. Brox and Fader, <strong>20</strong>02 defined justin-time<br />

(JIT) production as a manufacturing way <strong>of</strong> life that identifies and eliminates all forms <strong>of</strong> waste from the<br />

system and calls for continual improvement. In this philosophy non value adding activities are identified and<br />

either reduced or eliminated resulting in reduction <strong>of</strong> cost, productivity improvement, improved quality and<br />

delivery. In <strong>19</strong>90 a book written by Womack, Jones and Ross “The machine that changed the word” studied<br />

Toyota production system and termed it as Lean Production or Lean Manufacturing. Now a days Lean<br />

manufacturing has been admired in manufacturing sector around the world and it has been looked upon as<br />

remedy to continue to be competitive in global market (25). Adoption and properly implementation <strong>of</strong> lean<br />

manufacturing has improved overall performance <strong>of</strong> manufacturing organizations so it has become the most<br />

powerful manufacturing system in the world (5, 24).<br />

Manufacturing industries over the global are rapidly shifting their production method from Ford model <strong>of</strong> batch<br />

manufacturing to a new approach <strong>of</strong> Toyota Production system named lean manufacturing. The simple reason is<br />

that the organizations which have adopted lean manufacturing or Toyota production system has gained more<br />

advantage then the previous one (11). Many researchers has studied on lean manufacturing implementation in<br />

India and has focused on industry which are still working on Henry Ford mass production principles and are<br />

motivated by an out-<strong>of</strong>-date batch and queue state <strong>of</strong> mind. At the same time scope <strong>of</strong> lean manufacturing<br />

implementation is studied in Indian context. It has been observed that many companies in India are now feeling<br />

the heat <strong>of</strong> global competition and this has motivated to take serious step forward towards adoption <strong>of</strong> lean<br />

manufacturing (14).<br />

2. Concept <strong>of</strong> Lean Manufacturing:<br />

The term lean describes Japanese systems, which comparative to mass production uses fewer resources to<br />

achieve the output, which is better in terms <strong>of</strong> quality and satisfy the needs <strong>of</strong> customers (26).Lean<br />

Manufacturing is set <strong>of</strong> tools and techniques which aim to create a customer centric organization by developing<br />

and adopting best manufacturing practices with the involvement <strong>of</strong> all level <strong>of</strong> employees. Continuous<br />

improvement culture with the use <strong>of</strong> different tools is the spirit <strong>of</strong> the idea. Researchers and practitioner has<br />

developed many tools and techniques to improve manufacturing from different ways and means.<br />

Purposes <strong>of</strong> lean manufacturing is to reduce manufacturing cost and lead time, work in progress inventory and<br />

improve product quality by identifying and eliminating all the forms <strong>of</strong> waste present in the system.<br />

I. Processes standardization – Standard Work or Processes standardization calls for very detailed<br />

production guidelines to be implemented, which clearly states all the contents <strong>of</strong> work, motion,<br />

sequences, timing and output <strong>of</strong> the action performed by operator. This ensures lesser variation in the<br />

repeated actions <strong>of</strong> the workers while performing their job.<br />

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II.<br />

III.<br />

IV.<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Pull-production – This is also called Just-in-Time (JIT) production, it aims to produce only what is<br />

needed, when it is needed. Production is pulled by the downstream workstation so that each workstation<br />

should only produce what is requested by the next workstation.<br />

Quality at the Source – Lean Manufacturing calls for defect free production lines. It aims for first time<br />

right approach. It aims for defects to be eliminated at the source and for quality inspection to be<br />

performed by the workers as part <strong>of</strong> the in-line production process.<br />

Continual improvement – Lean Manufacturing requires striving for perfection by continually removing<br />

layers <strong>of</strong> waste as they are uncovered. This in turn requires a high level <strong>of</strong> worker involvement in the<br />

continual improvement process.<br />

2.2 Objectives <strong>of</strong> Lean Manufacturing:<br />

The objectiveness <strong>of</strong> Lean Manufacturing is to enhance overall productivity lower cost <strong>of</strong> production, and<br />

reduced lead times <strong>of</strong> production. Some <strong>of</strong> the objectives include:<br />

I. Reduced work in progress (WIP) Inventory - Minimize inventory levels at all stages <strong>of</strong> production,<br />

particularly works-in-progress between production stages. Lower inventories also mean lower working<br />

capital requirements.<br />

II. Lower Cycle Times - Reduce manufacturing lead times and production cycle times by reducing waiting<br />

times between processing stages, as well as process preparation times and product/model conversion<br />

times.<br />

III. Improved Labor productivity - Improve labor productivity, both by reducing the idle time <strong>of</strong> workers<br />

and ensuring that when workers are working, they are using their effort as productively as possible<br />

(including not doing unnecessary tasks or unnecessary motions).<br />

IV. Reduced Defects - Reduce defects and unnecessary physical wastage, including excess use <strong>of</strong> raw<br />

material inputs, preventable defects, costs associated with reprocessing defective items, and<br />

unnecessary product characteristics which are not required by customers.<br />

V. Enhanced Output – Ins<strong>of</strong>ar as reduced cycle times, increased labor productivity and elimination <strong>of</strong><br />

bottlenecks and machine downtime can be achieved, companies can generally significantly increase<br />

output from their existing facilities.<br />

VI. Improved Flexibility - Have the ability to produce a more flexible range <strong>of</strong> products with minimum<br />

changeover costs and changeover time.<br />

VII. Better Utilization <strong>of</strong> equipment and space - Use equipment and manufacturing space more efficiently by<br />

eliminating bottlenecks and maximizing the rate <strong>of</strong> production though existing equipment, while<br />

minimizing machine downtime;<br />

2.3 Implications <strong>of</strong> Lean Manufacturing<br />

With the implementation <strong>of</strong> lean manufacturing in any industry several changes in manufacturing approach are<br />

expected. The major change come with change from batch production with planning for every station or shop is<br />

converted into smaller batch size production method tending to batch size <strong>of</strong> one piece or single piece flow line<br />

with scheduling and planning at down most steam process where material is pulled from value stream based on<br />

customer demand only. In new model <strong>of</strong> manufacturing work in process inventory is reduced as there is no or<br />

very less material between work stations waiting for processing. Quality is not dependent on certification <strong>of</strong> line<br />

inspector but it becomes sole responsibility <strong>of</strong> workman who manufactures the product and inspection is now an<br />

integral part <strong>of</strong> manufacturing activities <strong>of</strong> operator. Some major implications <strong>of</strong> conventional manufacturing<br />

model and lean model <strong>of</strong> manufacturing are discussed as follows:<br />

Table 1. Implications <strong>of</strong> Lean Manufacturing<br />

Scheduling<br />

Lot size<br />

Conventional manufacturing<br />

Scheduling is done on whole value stream<br />

based on production plan.<br />

(Push production)<br />

Bigger lot sizes<br />

Lean Manufacturing<br />

Scheduling is done at one place based on<br />

customer demand. Processes are scheduled by<br />

downstream processes.(Pull production)<br />

Smaller lot size<br />

(tends to single piece production)<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Work in<br />

progress (WIP)<br />

Inventory<br />

WIP inventory is kept between production<br />

stages<br />

Lesser inventory or single piece is kept between<br />

production stages<br />

Reference Reference is production and Supply Reference is Customer demand<br />

Quality<br />

inspection<br />

Quality control inspectors are responsible<br />

for quality.<br />

Worker is responsible for product quality<br />

3. Lean structure:<br />

There are many tools available for lean manufacturing implementation so it becomes important to understand<br />

that efforts to implement any one lean principle alone would achieve small improvement, but every tool has its<br />

own role and at the same time it supports other tools. Many organizations have attempted to implement few <strong>of</strong><br />

these lean tools separately but could not produce kind <strong>of</strong> success they have been striving for. On the other side<br />

the organizations have been in implementing techniques like JIT, Kanban, production leveling, team building,<br />

quality circle, simultaneously has gained much improvement (17). Lean structure represents how different tools<br />

are linked with each other and organization can work for lean manufacturing implementation with practical<br />

application <strong>of</strong> different tools from beginning to end in a systematic manner. Some organization has been very<br />

successful in continuously improving its performance because <strong>of</strong> implementing lean tool with coherence. Laid<br />

down lean tools can be grouped like basic tools, supporting tools and philosophies.<br />

Basic tools Supporting Concepts/ lean tools Philosophies Goals<br />

Visual<br />

management<br />

5S<br />

problem<br />

solving<br />

TPM<br />

Process<br />

stability<br />

Pull system<br />

SMED<br />

Kanban<br />

Contineous flow<br />

Heijunka<br />

Takt time<br />

Built in quality<br />

Poka yoke<br />

Seperate man and<br />

machine work<br />

Just-intime<br />

Jidoka<br />

Customer first<br />

Respect for people<br />

Kaizen<br />

Genba focus<br />

Highest safety<br />

Low cost<br />

Short lead time<br />

High morale<br />

High quality<br />

Physical and mental safety Training and feed back Team work<br />

Figure1. Lean structure<br />

3.1 Basic tools : First and foremost requirement <strong>of</strong> lean thinking and its practical implementation is to<br />

develop process stability by working with some basic tools like 5 S, TPM, Visual management, problem solving.<br />

It will help in reduction <strong>of</strong> process variation and hence process output.<br />

5S is the name <strong>of</strong> a workplace organization method that uses a list <strong>of</strong> five Japanese words: seiri, seiton, seiso,<br />

seiketsu, and shitsuke. The list describes how to systematize a work place for efficiency and effectiveness by<br />

identifying and storing the items used, maintaining the area and items, and sustaining the new order. The<br />

decision-making process usually comes from a dialogue about standardization, which builds understanding<br />

among employees <strong>of</strong> how they should do the work. Total productive maintenance (TPM) originated in Japan in<br />

<strong>19</strong>71 as a method for improved machine availability through better utilization <strong>of</strong> maintenance and production<br />

resources. Whereas in most production settings the operator is not viewed as a member <strong>of</strong> the maintenance team,<br />

in TPM the machine operator is trained to perform many <strong>of</strong> the day-to-day tasks <strong>of</strong> simple maintenance and<br />

fault-finding. Teams are created that include a technical as well as operators. In this setting the operators are<br />

enabled to understand the machinery and identify potential problems, correcting them before they can impact<br />

production and by so doing, decrease downtime and reduce costs <strong>of</strong> production.TPM is a critical add-on to lean<br />

manufacturing. If machine uptime is not predictable and if process capability is not sustained, the process must<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

keep extra stocks to buffer against this uncertainty and flow through the process will be interrupted.<br />

Unpredictable uptime is caused by breakdowns or badly performed maintenance. Correct maintenance will allow<br />

uptime to improve and speed production through a given area allowing a machine to run at its designed capacity<br />

<strong>of</strong> production. One way to think <strong>of</strong> TPM is "deterioration prevention": deterioration is what happens naturally to<br />

anything that is not "taken care <strong>of</strong>". For this reason many people refer to TPM as "total productive<br />

manufacturing". TPM is a proactive approach that essentially aims to identify issues as soon as possible and plan<br />

to prevent any issues before occurrence.<br />

3.2 Advance tools: Once process stability is established application <strong>of</strong> advance lean tools will result in<br />

improving continuous material flow with built in quality systems. Pull system is a scheduling pattern for<br />

manufacturing lines where downstream process is driven by customer demand and upstream processes gets<br />

signal from next level in the form <strong>of</strong> order for production. In pull system parts are processed against order only.<br />

SMED or single minute exchange <strong>of</strong> die is a concept to reduce changeover time. Waste activities during<br />

changeover process are identified and eliminated or reduced to minimum so as to minimize changeover time and<br />

improve flexibility to meet changing customer requirement. Kanban uses the rate <strong>of</strong> demand to control the rate<br />

<strong>of</strong> production, passing demand from the end customer up through the chain <strong>of</strong> customer-store processes. In <strong>19</strong>53,<br />

Toyota applied this logic in their main plant machine shop. Kanban is not an inventory control system; it is a<br />

scheduling system that helps determine what to produce, when to produce it, and how much to produce.<br />

Production leveling, also known as production smoothing or heijunka is a technique for reducing the waste. It is<br />

vital to the development <strong>of</strong> production efficiency in lean manufacturing system. The goal is to produce<br />

intermediate goods at a constant rate so that further processing may also be carried out at a constant and<br />

predictable rate. Takt time, derived from the German word Taktzeit which translates to cycle time, sets the pace<br />

for industrial manufacturing lines. For example, in automobile manufacturing, vehicles are assembled on a line,<br />

and are moved on to the next station after a certain time - the takt time. The time needed to complete work on<br />

each station has to be less than the takt time in order for the product to be completed within the allotted time.<br />

Takt time concept aims to match the pace <strong>of</strong> production with customer demand. Poka-yoke is a Japanese term<br />

that means ""mistake-pro<strong>of</strong>ing". A poka-yoke is any mechanism in a lean manufacturing process that helps an<br />

equipment operator avoids mistakes. Its purpose is to eliminate product defects by preventing, correcting, or<br />

drawing attention to human errors as they occur.<br />

3.3 Philosophies<br />

Philosophies are top management driven and principal approaches for lean manufacturing implementation. Lean<br />

manufacturing necessitates customer focused approach where material is pulled through manufacturing lines<br />

based on customer requirement. Implementation <strong>of</strong> Lean tools like quick change over (SMED), production<br />

leveling and Kanban enables an organization in correct orientation towards frequently changing customer<br />

requirements. Respect for people represents equal participation <strong>of</strong> each individual in organizational improvement<br />

and idea for excellence must be respected and considered for implementation in spite <strong>of</strong> level, age, designation<br />

etc..<br />

4. Conclusions<br />

Global competition in manufacturing sector supports Darwin’s theory <strong>of</strong> survival <strong>of</strong> the fittest. Organizations<br />

who can meet or exceed customer’s expectation can survive. For this condition organization needs sincere effort<br />

with some good techniques to keep them fit for survival. In order to excel in global market, any manufacturing<br />

organization needs to transform itself into a learning organization. Lean manufacturing system <strong>of</strong>fers set <strong>of</strong> tools<br />

and techniques which if applied appropriately can improve the strength <strong>of</strong> the organization in terms <strong>of</strong> making it<br />

capable to deliver product with low cost, better quality. Lean tools are not sufficient and cannot deliver the<br />

results until culture inside the organization is not improved. It is very important aspect and allows individuals<br />

and teams to think creatively and competitively to take careful risks to seek out, develop and adopt lean tools.<br />

Application <strong>of</strong> basic tools creates ground work for implementation <strong>of</strong> advanced tools. The result <strong>of</strong> lean tools is<br />

sustained by philosophies which are top management driven and cascades down to workmen level. Keeping in<br />

mind customer requirement, continuous improvement through kaizen, gemba focus and having respect for other<br />

employees is key to sustained result and will lead to improve lean culture. Safety, training and team work is the<br />

supporting and enabling tools which drives the whole process <strong>of</strong> lean manufacturing to deliver the ultimate goal<br />

<strong>of</strong> highest safety, lowest cost, better quality, short lead time and high morale.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

References<br />

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manufacturing performance", International Journal <strong>of</strong> Quality & Reliability Management, Vol. 25 Issue: 2<br />

pp. 147 – 172<br />

2. Farhana Ferdousi, Amir Ahmed (<strong>20</strong>09) “An Investigation <strong>of</strong> Manufacturing Performance Improvement<br />

through Lean Production: A Study on Bangladeshi Garment Firms”, International Journal <strong>of</strong> Business and<br />

Management volume l4, No 9 pp 106-116.<br />

3. Jiju Antony, Darshak A. Desai, (<strong>20</strong>09),"Assessing the status <strong>of</strong> six sigma implementation in the Indian<br />

industry: Results from an exploratory empirical study", Management Research News, Vol. 32 Issue: 5 pp.<br />

413 – 423<br />

4. I.P.S. Ahuja, J.S. Khamba, (<strong>20</strong>08),"Assessment <strong>of</strong> contributions <strong>of</strong> successful TPM initiatives towards<br />

competitive manufacturing", Journal <strong>of</strong> Quality in Maintenance Engineering, Vol. 14 Issue: 4 pp. 356 – 374<br />

5. Shams Rahman, Tritos Laosirihongthong, Amrik S. Sohal, (<strong>20</strong>10),"Impact <strong>of</strong> lean strategy on operational<br />

performance: a study <strong>of</strong> Thai manufacturing companies", Journal <strong>of</strong> Manufacturing <strong>Technology</strong><br />

Management, Vol. 21 Issue: 7 pp. 839 – 852<br />

6. Rakesh Narain, R.C. Yadav, Jiju Antony, (<strong>20</strong>04),"Productivity gains from flexible manufacturing:<br />

Experiences from India", International Journal <strong>of</strong> Productivity and Performance Management, Vol. 53 Issue:<br />

2 pp. 109 – 128<br />

7. G. Anand, Rambabu Kodali, (<strong>20</strong>08),"Selection <strong>of</strong> lean manufacturing systems using the PROMETHEE",<br />

Journal <strong>of</strong> Modeling in Management, Vol. 3 Issue: 1 pp. 40 – 70<br />

8. G. Anand, Rambabu Kodali, (<strong>20</strong>09),"Selection <strong>of</strong> lean manufacturing systems using the analytic network<br />

process - a case study", Journal <strong>of</strong> Manufacturing <strong>Technology</strong> Management, Vol. <strong>20</strong> Iss: 2 pp. 258 – 289<br />

9. Shahram Taj, Cristian Morosan, (<strong>20</strong>11),"The impact <strong>of</strong> lean operations on the Chinese manufacturing<br />

performance", Journal <strong>of</strong> Manufacturing <strong>Technology</strong> Management, Vol. 22 Iss: 2 pp. 223 – 240<br />

10. Zhi-Xiang Chen, Kim Hua Tan, (<strong>20</strong>11),"The perceived impact <strong>of</strong> JIT implementation on operations<br />

performance: Evidence from Chinese firms", Journal <strong>of</strong> Advances in Management Research, Vol. 8 Iss: 2<br />

pp. 213 – 235<br />

11. Bhim Singh, S.K. Garg, S.K. Sharma, (<strong>20</strong>09),"Lean can be a survival strategy during recessionary times",<br />

International Journal <strong>of</strong> Productivity and Performance Management, Vol. 58 Issue: 8 pp. 803 – 808<br />

12. Bhim Singh, S.K. Garg, S.K. Sharma,(<strong>20</strong>10) “Lean implementation and its benefits to production industry”,<br />

International Journal <strong>of</strong> Lean Six Sigma Vol. 1 No. 2, pp. 157-168<br />

13. Bhim Singh, S.K. Garg, S.K. Sharma,(<strong>20</strong>10),” Development <strong>of</strong> index for measuring leanness: study <strong>of</strong> an<br />

Indian auto component industry”, MEASURING BUSINESS EXCELLENCE VOL. 14 NO. 2, pp. 46-53,<br />

Emerald Group Publishing Limited, ISSN 1368-3047<br />

14. Bhim Singh, S.K. Garg, S.K. Sharma,(<strong>20</strong>10),” Scope for lean implementation: a survey <strong>of</strong> 127 Indian<br />

industries”, International Journal <strong>of</strong> Rapid Manufacturing, Vol. X, No. Y, pp1-11<br />

15. Bhim Singh & Suresh K. Garg & Surrender K. Sharma,(<strong>20</strong>10) “Value stream mapping: literature review and<br />

implications for Indian industry”, International Journal <strong>of</strong> Advance Manufacturing <strong>Technology</strong> DOI<br />

10.1007/s00170-010-2860-7 Published online on 10th August <strong>20</strong>10.<br />

16. Vikas Kumar,(<strong>20</strong>10), “ JIT Based Quality Management: Concepts and Implications in Indian Context”,<br />

International Journal <strong>of</strong> Engineering <strong>Science</strong> and <strong>Technology</strong> Vol.2(1), pp 40-50<br />

17. R. P. Mohanty, O. P. Yadav & R. Jain,(<strong>20</strong>06), “Implementation <strong>of</strong> Lean Manufacturing Principles in Auto<br />

Industry”, Vilakshan, XIMB Journal <strong>of</strong> Management pp1-32.<br />

18. Norani Nordin, Baba Md Deros and Dzuraidah Abd Wahab,(<strong>20</strong>10) “A Survey on Lean Manufacturing<br />

Implementation in Malaysian Automotive Industry”, International Journal <strong>of</strong> Innovation, Management and<br />

<strong>Technology</strong>, Vol. 1, No. 4, October <strong>20</strong>10 ISSN: <strong>20</strong>10-0248 Pp 374-380<br />

<strong>19</strong>. Vikas Kumar,Dixit Garg, N.P. Mehta,(<strong>20</strong>04) , “JIT practices: in Indian context”, Jouranal <strong>of</strong> scientific and<br />

Industrial research,Vol 63 pp 655-662.<br />

<strong>20</strong>. Job de Haan,, Masaru Yamamoto,(<strong>19</strong>99),”Zero inventory management: facts or fiction Lessons from Japan”,<br />

International Journal <strong>of</strong> Production Economics 59, (<strong>19</strong>99) 65Ð75<br />

21. Kakuro Amasaka, (<strong>20</strong>02) ‘‘New JIT:A new management technology principle at Toyota”, International<br />

Journal <strong>of</strong> Production Economics 80 135–144.<br />

22. Subhashish Samaddar,(<strong>20</strong>00),”The effect <strong>of</strong> set up time reduction on its variance”, The international Journal<br />

<strong>of</strong> Management <strong>Science</strong> , pp 243-247.<br />

23. FTS Chan, (<strong>20</strong>01),” Effect <strong>of</strong> Kanban size on Just-in-time manufacturing system”. Journal <strong>of</strong> materials<br />

processing technology 116, 146-160.<br />

24. Yu Cheng Wong* and Kuan Yew Wong,(<strong>20</strong>11) “Approaches and practices <strong>of</strong> lean manufacturing: The case<br />

<strong>of</strong> electrical and electronics companies”, African Journal <strong>of</strong> Business Management Vol.5 (6), pp. 2164-<br />

2174,<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

25. Yu Cheng Wong , and Kuan Yew Wong,(<strong>20</strong>11),” A Lean Manufacturing Framework for the Malaysian<br />

Electrical and Electronics Industry”,3rd International Conference on Information and Financial Engineering.<br />

26. Nitin Upadhye , S. G. Deshmukh,(<strong>20</strong>10), “Suresh Garg, Lean manufacturing system for medium size<br />

manufacturing enterprises: an Indian case”, International Journal <strong>of</strong> Management <strong>Science</strong> and Engineering<br />

Management, 5(5): 362-375,<br />

27. Yu Cheng Wong, Kuan Yew Wong, Anwar Ali,(<strong>20</strong>09), “A Study on Lean Manufacturing Implementation in<br />

the Malaysian Electrical and Electronics Industry”, European Journal <strong>of</strong> Scientific Research ISSN 1450-<br />

216X Vol.38 No.4, pp 521-535<br />

28. By Ms. Jami Kovach, Ms. Paris Stringfellow, Ms. Jennifer Turner, and Dr. B. Rae ChoThe House <strong>of</strong><br />

Competitiveness,(<strong>20</strong>05) “The Marriage <strong>of</strong> Agile Manufacturing, Design for Six Sigma, and Lean<br />

Manufacturing with Quality Considerations”, Journal <strong>of</strong> industrial technology, Volume 21, Number 3 - July<br />

<strong>20</strong>05 through September <strong>20</strong>05.<br />

29. Dr. Kenneth W. Stier,(<strong>20</strong>06). “ A Preliminary Manufacturing Competencies Study <strong>of</strong> Small and Medium-<br />

Sized Manufacturers in Illinois”, Journal <strong>of</strong> industrial technology, Volume 22, Number 2 - April <strong>20</strong>06<br />

through June <strong>20</strong>06.<br />

30. Flott, L. W.,(<strong>20</strong>02), "Industry in transition," in Metal Finishing, <strong>20</strong>02, pp. 77-82.<br />

31. Srinivasaraghavan, J. and Allada, V., (<strong>20</strong>06),"Application <strong>of</strong> mahalanobis distance as a lean assessement<br />

metric," International Journal <strong>of</strong> Advanced Manufacturing <strong>Technology</strong>, vol. 29, pp. 1159-1168.<br />

747


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

LEAN MANUFACTURING: ELEMENTS AND ITS BENEFITS FOR<br />

MANUFACTURING INDUSTRY<br />

Rakesh Kumar 1 , Vikas Kumar<br />

Research Scholar, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad-121006 (Haryana)<br />

Associate Pr<strong>of</strong>essor, Mechanical Engineering Department, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>,<br />

Faridabad-121006 (Haryana)<br />

e-mail: rakesh_siwach@yahoo.com<br />

Abstract<br />

In today’s competitive environment organizations needs to leverage the strength it has and must work to improve<br />

upon its weakness. Lean manufacturing has been recognized the key to improve competitiveness for manufacturing<br />

organizations over the globe. Lean manufacturing <strong>of</strong>fers a basket full <strong>of</strong> tools and techniques which can help in<br />

waste identification, reduction or elimination to enables manufacture product with superior quality, lower cost and<br />

on time with lesser efforts. Considering its potential <strong>of</strong> improving operational performance lean manufacturing is<br />

gaining popularity among manufacturing industries. Purpose <strong>of</strong> this paper is to present Lean Manufacturing<br />

elements, benefits, implementation strategy and obstacles in implementation for manufacturing industry.<br />

Keywords: Lean Manufacturing, Theory <strong>of</strong> Lean Manufacturing, Elements <strong>of</strong> Lean Manufacturing, Benefits and<br />

Lean Manufacturing implementation strategy.<br />

1. Introduction:<br />

Offering high quality product with competitive cost has always been a challenge for all manufacturing companies<br />

(2). This can be achieved by removing waste from the system by following certain practices called best practices.<br />

Many <strong>of</strong> the best practices in manufacturing have been originated by Toyota (10). Toyota got popularity in <strong>19</strong>80’s<br />

for efficient operations in all over the world by effectively implementation <strong>of</strong> JIT (just in Time) system. Brox and<br />

Fader, <strong>20</strong>02 defined just-in-time (JIT) production as a manufacturing philosophy that identifies and eliminates all<br />

forms <strong>of</strong> waste from the system and calls for continual improvement. In this philosophy non value adding activities<br />

are identified and either reduced or eliminated resulting in reduction <strong>of</strong> cost, productivity improvement, improved<br />

quality and delivery.<br />

In <strong>19</strong>90 a book written by Womack, Jones and Ross “The machine that changed the word” introduced a new concept<br />

called Lean Production or Lean Manufacturing (2, 14, and 17). In Past two decades Toyota Production System has<br />

been studied by many <strong>of</strong> researchers namely Adler,<strong>19</strong>93;Womack and Jones,<strong>19</strong>94;Liker ,<strong>19</strong>98;Sobek et al.<br />

<strong>19</strong>98;Spear and Bowen,<strong>19</strong>99;Mike Rother,<strong>20</strong>09.Although all <strong>of</strong> the lean Manufacturing principles studied by these<br />

researchers were not new to manufacturing system but it was observed that Toyota was able to sustain the better<br />

outcome <strong>of</strong> these principles with input <strong>of</strong> lesser resources (17). The acceptability <strong>of</strong> these principles increased<br />

because Japanese companies who adopted these principles were able to develop, manufacture and supply the product<br />

to customers with the lesser resources like material, machines, tools, human effort, capital investment, floor space,<br />

time and total expenses (Womack et al., <strong>19</strong>90). Ohno, <strong>19</strong>88; Shingo, <strong>19</strong>89; Womack et al.; <strong>19</strong>90, Monden <strong>19</strong>97;<br />

Mike Rother, <strong>20</strong>09 and other researcher made Lean Manufacturing approach popular among the industry.<br />

2. Theory <strong>of</strong> Lean Manufacturing:<br />

Lean Manufacturing is a philosophy that aims to maintain smooth production flow by continuously identifying and<br />

eliminating waste resulting in increasing value <strong>of</strong> activities in the production process (18). Lean manufacturing<br />

approach makes an organization able to sustain market competition by improving its competence for better quality;<br />

on time delivery with lower cost Lean Manufacturing aims for Identification and elimination <strong>of</strong> waste (any activity<br />

that does not add value to customer).<br />

Lean Manufacturing aims for the accomplishment <strong>of</strong> unidirectional and continuous material movement known as<br />

production flow (2, 9). Processes should be free from bottlenecks, waiting, disruption, and backflow. Lean<br />

manufacturing aims to produce only what is needed, when it is needed. Production is pulled by the downstream<br />

workstation so that each workstation should only produce what is requested by the next workstation. Lean<br />

2<br />

748


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Manufacturing focuses on defect free production lines (11). It aims for defects to be eliminated at the source and for<br />

quality inspection to be performed by the workers as part <strong>of</strong> the in-line production process. Lean Manufacturing<br />

requires striving for perfection by continually removing layers <strong>of</strong> waste as they are uncovered. This in turn requires a<br />

high level <strong>of</strong> worker involvement in the continual improvement process.<br />

3. Elements <strong>of</strong> Lean Manufacturing:<br />

To convert a conventional organization into a lean organization numerous and continual efforts are essential. Certain<br />

elements are discussed by researchers and are adopted by the manufacturing organizations to improve<br />

competitiveness in the market by reducing product manufacturing cost, reducing response time to customers and<br />

improving quality and productivity.<br />

Followings are the key elements which have been recognized in different research papers.<br />

Table1. Lean manufacturing elements<br />

Lean Manufacturing elements<br />

Attributed in reference<br />

SMED/setup time Reduction (5,10,11,15,16,18,24,26,27)<br />

Kanban (5,10,11,14,15,18,24,27)<br />

TPM (5,10,16,18,24,26,27)<br />

Batch Size Reduction /Single piece flow (5,10,16,18,24,26,27)<br />

Cellular Layout /Layout improvement (10,16,18,24,25,26,27)<br />

Poka yoke (5,11,16,18,24,26,27)<br />

Quality Circles/Quality at the Source (10,11,11,16,25,26)<br />

Kaizen (11,16,17,24,26,27)<br />

5 S’s (10,18,24,26,27)<br />

Employee involvement/development (10,16,17,18,25)<br />

Continuous improvements/PDCA (15,17,24,27)<br />

Standard Work (5,17,24,27)<br />

Visual Management (10,11,18)<br />

Value Stream Mapping (11,24,27)<br />

Production Leveling (Heijunka) (10,24,27)<br />

Group technology (16,27)<br />

Jidoka (24,27)<br />

Andon (24,27)<br />

Milk run (24)<br />

FIFO (24)<br />

3.1 SMED/setup time Reduction-Lean Manufacturing targets reduction <strong>of</strong> setup time and changeover time<br />

because it consumes critical working time and reduces proper utilization <strong>of</strong> machine and operator time. This can be<br />

achieved by sequenced and structured work instructions to perform the job. The operator will follow the instruction<br />

and should be able to finish the job within minimum possible time. The work instruction is based on time and motion<br />

study during changeover, analysis <strong>of</strong> the waste and modification with the aim to eliminate the waste.<br />

3.2 Kanban -Kanban is a shop floor tool which communicates customer requirement from downstream to<br />

upstream worker. Once product is withdrawn from finished goods against customer demands to replenish the moved<br />

quantity it is replaced with colored card (or electronically). This becomes a production order for the internal supplier<br />

in the upstream value chain.<br />

749


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3.3 Total Productive Maintenance -Total Productive Maintenance (TPM) promotes basic preventative<br />

maintenance job to operator itself so that break down time <strong>of</strong> machines is reduced. It also enhances operational<br />

efficiency <strong>of</strong> machine as worker does cleaning, lubricating, inspection, tightening activity <strong>of</strong> his machine.<br />

3.4 Batch Size Reduction -Lean Manufacturing calls for smaller batch size production. The word single piece<br />

flow means it tends to one part at a time to be produced when operating for various types <strong>of</strong> product. In practical<br />

case it is not possible in some cases so minimum possible batch size should be selected. It helps in reducing waiting<br />

inventory <strong>of</strong> part. Lesser idle inventory means lesser working capital requirement and better financial efficiency.<br />

3.5 Cellular Layout -In cellular production layouts, equipment and workstations are arranged into a large<br />

number <strong>of</strong> small tightly connected cells so that many stages or all stages <strong>of</strong> a production process can occur within a<br />

single cell or a series <strong>of</strong> cells. Cellular layout helps to achieve many <strong>of</strong> the objectives <strong>of</strong> Lean Manufacturing due to<br />

its ability to help eliminate many non value-added activities from the production process such as waiting times,<br />

bottlenecks, transport and works-in-progress. Another benefit <strong>of</strong> cellular manufacturing is that responsibility for<br />

quality is clearly assigned to the worker in a particular cell and he/she therefore cannot blame workers at upstream<br />

stages for quality problems.<br />

3.6 Poka Yoke -Poka Yoke means mistake pro<strong>of</strong>ing. This involves bringing a system which eliminate human<br />

mistakes in term <strong>of</strong> quality, safety and other process parameters to ensure quality and safety in the manufacturing<br />

lines.<br />

3.7 The Five S’s -The 5S is a lean tool which consists <strong>of</strong> five steps Seiri, Seiton, Seiso, Seiketsu, Shitsuke and<br />

taken from Japanese language which aims to improve work place efficiency.<br />

Seiri: It refers to the action <strong>of</strong> sorting out wanted and unwanted material in and around workplace. Unwanted<br />

material should throw away and material which needs with lesser frequency should be place near to workplace and<br />

material which is required more frequently must be kept at a defined place very near to point <strong>of</strong> use. Seiri ensures in<br />

reduction <strong>of</strong> material searching time waste.<br />

Seiton: Seiton or set in order means every object (material, tool or instrument) must have a designated place to keep<br />

and every place have is the same object. The correct place, position, or holder for every tool, item, or material must<br />

be chosen carefully in relation to how the work will be performed and who will use them<br />

Seiso: Seiso, is the third step in "5S", speaks about clean and shine. Everybody is caretaker <strong>of</strong> its workstation and<br />

should see to clean all the commodities in and around workplace and make it shine.<br />

Seiketsu: The forth S <strong>of</strong> "5S", is seiketsu, it means standardization. It consists <strong>of</strong> defining the standards by which<br />

personnel must measure and maintain 'cleanliness'. Color coding can be used for standardization which can enable to<br />

visualize between current level and desired level.<br />

Shitsuke: The S <strong>of</strong> "5S" is Shitsuke, which means 'Self Discipline.' It stands for promise to maintain the first 4 S as a<br />

way <strong>of</strong> life. The importance <strong>of</strong> shitsuke is taking away <strong>of</strong> bad habits <strong>of</strong> disorderliness and regular practice <strong>of</strong> good<br />

ones.<br />

3.8 Quality at the Source-Quality at the Source means that quality should be built into the production process<br />

in such a way that defects are identified and eliminated at the source. The main responsibility for quality inspection<br />

is done in-line by workers, not by separate quality inspectors who inspect sample lots. In lean manufacturing primary<br />

job <strong>of</strong> a quality control team is to troubleshoot the root cause <strong>of</strong> defects, implement preventive measures and provide<br />

training to workers to make sure that the defects are not produced.<br />

3.9 Worker Involvement -In Lean Manufacturing, workers are assigned clear responsibility to identify sources<br />

<strong>of</strong> non value-added activities and to propose solutions to those. Lean Manufacturers typically believe that the<br />

majority <strong>of</strong> useful ideas for eliminating non value-added activities typically originate with workers involved in those<br />

processes. In order to ensure that ideas for eliminating non value-added activities are acted upon, the power to decide<br />

on changes to the production processes are pushed down to the lowest level possible (i.e. normal workers) but any<br />

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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

such changes are required to meet certain requirements. For example, at Toyota workers are encouraged to<br />

implement improvements to the production processes but the improvement must have a clear logic which is in<br />

accordance with the scientific method, the improvement must be implemented under the supervision <strong>of</strong> an authorized<br />

manager and the new process must be documented in a high level <strong>of</strong> detail covering content, sequence, timing and<br />

improvement is effective, Toyota will implement the change across its manufacturing operations.<br />

3.10 Continual Improvement -A company can never be perfectly efficient. Lean Manufacturing requires a<br />

commitment to continual improvement, and preferably a systematic process for ensuring continuous improvement,<br />

whereby the company constantly searches for non value-added activities and ways to eliminate those. The focus <strong>of</strong><br />

continual improvement should be on identifying the root causes <strong>of</strong> non value-added activities and eliminating those<br />

by improving the production process.<br />

3.11 Kaizen –Kaizen means small improvement. To maintain continuous improvement activities throughout the<br />

organization Kaizen culture should be created and maintained. Kaizen is done by the individuals mainly by operators<br />

for improvement in working condition, safety, quality , productivity, set up time reduction or any other small<br />

change for betterment.<br />

3.12 Standard Work -Standardized work means defining work and process instructions are well defined with<br />

full details <strong>of</strong> operation or process and parameters. It will reduce variation in repeated work cycles All the work<br />

instructions should contain standard worker movement, actions, checkpoints for quality, safety along with machine<br />

time, standard inventory.<br />

3.13 Visual Management-Visual Management facilitate everyone to be known about manufacturing targets,<br />

current status, deviations etc. It makes information available for all regarding status <strong>of</strong> production lines, down time<br />

and also controls the process by defining limits <strong>of</strong> tolerance. Good and not good parts are also defined with different<br />

colors .Location <strong>of</strong> not good parts are generally defined by red color.<br />

3.14 Value Stream Mapping -Value stream mapping is a set <strong>of</strong> methods to visually display the flow <strong>of</strong><br />

materials and information through the production process. The objective <strong>of</strong> value stream mapping is to identify<br />

value-added activities and non value-added activities. Value stream maps should reflect what actually happens rather<br />

than what is supposed to happen so that opportunities for improvement can be identified. Value Stream Mapping is<br />

<strong>of</strong>ten used in process cycle-time improvement projects since it demonstrates exactly how a process operates with<br />

detailed timing <strong>of</strong> step-by-step activities. It is also used for process analysis and improvement by identifying and<br />

eliminating time spent on non value-added activities.<br />

3.15 Production Leveling (Heijunka) -Production leveling, also called production smoothing, aims to<br />

distribute production volumes and product mix evenly over time so as to minimize peaks and valleys in the<br />

workload. Any changes to volumes should be smoothed so that they occur gradually and therefore in the most nondisruptive<br />

way possible. This will also allow the company to operate at higher average capacity utilization while also<br />

minimizing changeovers. A key element <strong>of</strong> production leveling is that the person(s) responsible for placing orders to<br />

the factory floor should have a system for automatically smoothing out the orders so that any increases or decreases<br />

are gradual and not disruptive. This makes it easier to correctly allocate the necessary equipment and people.<br />

4. Benefits <strong>of</strong> Lean manufacturing implementation:<br />

Lean manufacturing focus on waste reduction, lowering cycle time, reducing defects and reduction <strong>of</strong> response time<br />

and work in progress inventory. These all positively impacts the performance <strong>of</strong> the organization. Some <strong>of</strong> the<br />

benefits are observed during study.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 2. Benefits <strong>of</strong> Lean Manufacturing<br />

Benefits <strong>of</strong> Lean Manufacturing Attributed in reference<br />

Reduced cost (2,3,11,15,16,17,27)<br />

Reduced lead time (2,3,5,15,17,26,27)<br />

Waste reduction (3,5,11,16,17,27)<br />

Improved productivity (2,3,16,17,26,27)<br />

Reduced work in progress (WIP) Inventory (2,16,17,26,27)<br />

Reduced Defects/Improved quality (2,3,11,16,26)<br />

Lower Cycle Times (2,3,5,17,26,)<br />

Improved Flexibility (11,16,26,27)<br />

Enhanced pr<strong>of</strong>it (3,16,27)<br />

Multi skill worker (3,11,17)<br />

Better Utilization <strong>of</strong> equipment and space (26)<br />

4.1 Reduced cost: By implementation <strong>of</strong> Lean Manufacturing organizations can achieve reduced cycle times,<br />

increased labor productivity and elimination <strong>of</strong> bottlenecks and reduced machine downtime can be achieved, and<br />

companies can generally significantly increased output with reduced cost from their existing facilities.<br />

4.2 Reduced lead time: With the effect <strong>of</strong> reduced cycle time and work in progress inventory lead time to<br />

manufacture and deliver the product is drastically reduces.<br />

4.3 Waste reduction: Waste identification and reduction is one <strong>of</strong> the main functions <strong>of</strong> Lean Manufacturing<br />

implementation plan. All the form <strong>of</strong> waste i.e. overproduction, defect, transportation, work in progress inventory,<br />

over processing, waiting and motion are reduced with Lean manufacturing implementation.<br />

4.4 Improved productivity - Improve labor productivity, both by reducing the idle time <strong>of</strong> workers and ensuring<br />

that when workers are working, they are using their effort as productively as possible (including not doing<br />

unnecessary tasks or unnecessary motions).<br />

4.5 Reduced work in progress (WIP) Inventory - Minimize inventory levels at all stages <strong>of</strong> production,<br />

particularly works-in-progress between production stages. Lower inventories also mean lower working capital<br />

requirements.<br />

4.6 Lower Cycle Times - Reduce manufacturing lead times and production cycle times by reducing waiting times<br />

between processing stages, as well as process preparation times and product/model conversion times.<br />

4.7 Improved Flexibility - Have the ability to produce a more flexible range <strong>of</strong> products with minimum changeover<br />

costs and changeover time.<br />

4.8 Multi skill worker – Involvement <strong>of</strong> worker in various Lean tools i.e. quality circles, kaizen circle, layout<br />

improvement; value stream mapping, set up time reduction etc. creates better understanding <strong>of</strong> processes, machines,<br />

material flow among the team and improves core competencies <strong>of</strong> worker.<br />

4.9 Better Utilization <strong>of</strong> equipment and space - Use equipment and manufacturing space more efficiently by<br />

eliminating bottlenecks and maximizing the rate <strong>of</strong> production though existing equipment, while minimizing<br />

machine downtime<br />

4.10 Reduced Defects - Reduce defects and unnecessary physical wastage, including excess use <strong>of</strong> raw material<br />

inputs, preventable defects, costs associated with reprocessing defective items, and unnecessary product<br />

characteristics which are not required by customers.<br />

5. Lean Manufacturing Implementation strategies:<br />

Lean manufacturing is a philosophy which cannot be implemented instantly so it requires tolerantly developing<br />

understanding within the organization about lean, starting with smaller projects <strong>of</strong> lean at tool level, taking<br />

guidelines <strong>of</strong> an expert, making and following the strategy with due course correction in strategy while implementing<br />

lean throughout the organization. Some <strong>of</strong> the steps are as follows:<br />

5.1 Senior Management Involvement-For any major change, support and commitment from top management is<br />

vital. It is very much possible that problems will arise when lean implementation will progress and these issues must<br />

be understood and solved by top management without effecting lean implementation process.<br />

5.2 Initiate with smaller projects - Initial project must be small so that more resources are utilized and more<br />

chances are for better results with lesser risk moreover people working on project and around will learn while doing<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

project. The results will motivate other to follow the same and people will start having faith in lean techniques. So<br />

recommendation is to start with smaller project at tool level.<br />

5.3 Start with limited execution – Lean implementation should be within limited area during start so that it can be<br />

monitored, corrected and directed for further implementation starting lean all-around the organization will reduce<br />

control and mentoring <strong>of</strong> people involved in lean implementation. Once movement is gained it should be spread in<br />

other areas.<br />

5.4 Employ a pr<strong>of</strong>essional –Services <strong>of</strong> a pr<strong>of</strong>essional mentor should be taken at least at the start. During<br />

conversion <strong>of</strong> a conventional organization to a lean organization lots <strong>of</strong> issue will arise and should be handled<br />

pr<strong>of</strong>essionally they can be taken care with the use <strong>of</strong> expert.<br />

6. Obstacles in Lean Manufacturing implementation:<br />

The following may be some obstacles in Lean manufacturing implementation:<br />

6.1 Lack <strong>of</strong> management support: the reason can be pressure from customer side; competitor is following lean<br />

practices or others. In this case management just starts and does not propel further this results only superficial lean<br />

and neither lean is implemented nor does it get benefit.<br />

6.2 Lack <strong>of</strong> training: Another reason is lack <strong>of</strong> clear understanding about lean throughout the organization. The<br />

organization where knowledge <strong>of</strong> lean lacks it cannot be implemented.<br />

6.3 Communication – Lack <strong>of</strong> communication is one <strong>of</strong> the prime obstacles in lean manufacturing implementation.<br />

6.4 Resistance to Change – Resistance to change is very common phenomena as it increases fear <strong>of</strong> failure, initial<br />

cost so many <strong>of</strong> routine liking people doesn’t want to change and hence it stops the progress <strong>of</strong> lean implementation.<br />

6.5 No direct financial advantage – Lean does not produces any direct financial benefits but it helps in<br />

identification and elimination <strong>of</strong> waste hence reduction <strong>of</strong> cost. Lean does not have any financial measure in terms <strong>of</strong><br />

input and output so sometimes lean idea is superseded by other organizational priorities.<br />

6.6 Past failures – In case <strong>of</strong> poor launching <strong>of</strong> Lean is itself big obstacle. Lack <strong>of</strong> implementation strategy may lead<br />

to lack <strong>of</strong> faith in whole philosophy.<br />

5. Conclusions:<br />

Lean Manufacturing has been broadly accepted over the globe by manufacturing sector and in some areas it has deep<br />

penetration resulting in improvement in operational performance <strong>of</strong> the organization. Many researchers has studied<br />

and documented their view on lean manufacturing so it is observed that there is no short and snappy definition for<br />

lean manufacturing. Common understanding about lean manufacturing is mainly waste reduction, continual<br />

improvement, process improvement and improving supplier customer relationship by reducing lead time. Lean<br />

manufacturing <strong>of</strong>fers an extensive list <strong>of</strong> tools to improve manufacturing and generate the desired advantage to<br />

survive in today’s competitive scenario. Selection <strong>of</strong> tools depends upon understanding about lean manufacturing,<br />

focus area for improvement, current condition etc. Smaller lot size results in lesser work in process inventory and<br />

reduces blockage <strong>of</strong> cash finally making organization able to release that capital for working asset. Improved<br />

flexibility by reduction <strong>of</strong> changeover time results in reduced inventory and reduced response time to customer.<br />

Implementation strategy <strong>of</strong> lean manufacturing is very important aspect. It should be carefully prepared and followed<br />

otherwise investment <strong>of</strong> resource for lean manufacturing implementation will go waste it may result into cost impact<br />

and demoralized employees. For effective implementation obstacles must be taken care <strong>of</strong> before initiation and<br />

should be backed with action plan to overcome them. Finally lean Manufacturing is not one time activity which can<br />

bring all the benefits right away but it should be taken as a way <strong>of</strong> life for improving manufacturing to make the<br />

organization more productive, pr<strong>of</strong>itable, and customer oriented which is the call for <strong>of</strong> the day.<br />

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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

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Emerald Group Publishing Limited, ISSN 1368-3047<br />

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and implications for Indian industry”, International Journal <strong>of</strong> Advance Manufacturing <strong>Technology</strong> DOI<br />

10.1007/s00170-010-2860-7 Published online on 10th August <strong>20</strong>10.<br />

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Industry”, Vilakshan, XIMB Journal <strong>of</strong> Management pp1-32.<br />

18. Norani Nordin, Baba Md Deros and Dzuraidah Abd Wahab,(<strong>20</strong>10) “A Survey on Lean Manufacturing<br />

Implementation in Malaysian Automotive Industry”, International Journal <strong>of</strong> Innovation, Management and<br />

<strong>Technology</strong>, Vol. 1, No. 4, October <strong>20</strong>10 ISSN: <strong>20</strong>10-0248 Pp 374-380<br />

<strong>19</strong>. Vikas Kumar,Dixit Garg, N.P. Mehta,(<strong>20</strong>04) , “JIT practices: in Indian context”, Jouranal <strong>of</strong> scientific and<br />

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Japan”, International Journal <strong>of</strong> Production Economics 59, (<strong>19</strong>99) 65Ð75<br />

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<strong>of</strong> Management <strong>Science</strong> , pp 243-247.<br />

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<strong>of</strong> electrical and electronics companies”, African Journal <strong>of</strong> Business Management Vol.5 (6), pp. 2164-<br />

2174,<br />

25. Yu Cheng Wong , and Kuan Yew Wong,(<strong>20</strong>11),” A Lean Manufacturing Framework for the Malaysian<br />

Electrical and Electronics Industry”,3rd International Conference on Information and Financial<br />

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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

26. Nitin Upadhye , S. G. Deshmukh,(<strong>20</strong>10), “Suresh Garg, Lean manufacturing system for medium size<br />

manufacturing enterprises: an Indian case”, International Journal <strong>of</strong> Management <strong>Science</strong> and Engineering<br />

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in the Malaysian Electrical and Electronics Industry”, European Journal <strong>of</strong> Scientific Research ISSN 1450-<br />

216X Vol.38 No.4, pp 521-535<br />

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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

CRITICALITY OF SUPPLY CHAIN IN INDIAN AUTO INDUSTRY<br />

Dharamvir Mangal 1 , Tarun Gupta 2<br />

1 Mechanical Engineering Department, The Technological Institute <strong>of</strong> Textile and <strong>Science</strong>s, Bhiwani (127021), Haryana,<br />

India<br />

2<br />

Mechanical Engineering Department, NGF College <strong>of</strong> Engineering and <strong>Technology</strong>, Palwal, Haryana, India<br />

e-mail: mangaldharamvir1@rediffmail.com<br />

Abstract<br />

Demanding competition in today’s global markets, introduction <strong>of</strong> products with short life cycles, and the discriminating<br />

expectations <strong>of</strong> customers have forced business enterprises to invest in, and focus attention on their supply chains.<br />

Supply chain management has increasingly become an inevitable challenge to most companies to be continuously<br />

survived and prospered in the global chain-based competitive environment. The current challenges <strong>of</strong> the Indian<br />

automotive world, their implications on supply chain are summarized and analyzed in this paper. In this competitive era<br />

<strong>of</strong> ‘LPG’ i.e. Liberalization, Privatization and Globalization, modern marketing systems, introduction <strong>of</strong> products with<br />

short life cycles, and the discriminating expectations <strong>of</strong> customers have enforced business enterprises to invest in and<br />

focus attention on their Supply Chains (SCs) in order to meet out the level <strong>of</strong> customer’s satisfaction and to survive in the<br />

competitive market. In fact, many <strong>of</strong> trends in the auto industry are reinforcing the need to redefine supply chain<br />

strategies layouts, and operations etc. Many manufacturing operations are designed to maximize throughput and lower<br />

costs with modest considerations for the crash on inventory levels and distribution capabilities. The new age customers<br />

want customized products according to their tastes like automobile color, interior, audio system, etc. This customer<br />

behavior implies that dealers and manufacturers have to maintain adequate inventory to satisfy the customer. To<br />

improve pr<strong>of</strong>itability and efficiency, automotive players are seeking ways to achieve operational excellence, reduce<br />

operating cost and enhance customer service through efficient supply chain management.<br />

Keywords: Automotive Industry, Supply chain, Challenges, market potential<br />

1. Introduction<br />

The term supply chain management refers to cooperative management <strong>of</strong> materials and information flows between<br />

supply chain partners, to reach goals that cannot be achieved acting individually (Eric Sucky, <strong>20</strong>05). The purpose <strong>of</strong><br />

supply chain management is to improve trust and collaboration among supply chain partners, thus improving inventory<br />

visibility and the velocity <strong>of</strong> inventory movement (Choi and Hong, <strong>20</strong>02). Emergence <strong>of</strong> new technologies and the everincreasing<br />

intensity <strong>of</strong> competition are forcing organizations, firms and industries to reexamine how they do business,<br />

meet new customer-driven challenges, companies are re-thinking, restructuring and re-investing their supply chains in<br />

order to survive, succeed, excel and even in some specific cases targeting to spearheading competitiveness (Drucker,<br />

<strong>19</strong>98). Indian Automotive industry has been facing major challenges due to fierce competition, increasing operational<br />

complexity, technology changes, shortened product lifecycle and frequently changing customer needs. Despite high<br />

stocks, the performance <strong>of</strong> the supply chain has failed to meet customer expectations in terms <strong>of</strong> delivering the exact<br />

specification desired within an acceptable timescale. Today Indian automotive industry is completely capable <strong>of</strong><br />

producing various kinds <strong>of</strong> vehicles and can be divided into three broad categories: two-wheelers, cars and heavy<br />

vehicles. Vast scope exists for Indian automobile and auto component manufacturers to reduce their logistics costs with<br />

the implementation <strong>of</strong> SCM solutions. As India is a developing country, and fascinatingly, there has been an upward<br />

trend <strong>of</strong> realization <strong>of</strong> supply chain optimization. SCM solution market has been making inroads in India and it is being<br />

established widely by many automobile industries in the country, particularly manufacturing ones where inventory<br />

carrying cost is very high. Several automobile manufacturers in India have taken positive actions to manage their<br />

logistics cost and get better customer services and measures have been undertaken by Indian companies to develop their<br />

supply chain (Kamala and Doreswamy, <strong>20</strong>07). Auto manufacturers in India and all tiers <strong>of</strong> the supply chain have<br />

immense opportunities to enhance their entire supply chain process with the successful implementation <strong>of</strong> SCM solution.<br />

At present there are 15 manufacturers <strong>of</strong> passenger cars & multi utility vehicles, 9 manufacturers <strong>of</strong> commercial vehicles,<br />

16 <strong>of</strong> 2/3 wheelers and 14 <strong>of</strong> tractors besides 5 manufacturers <strong>of</strong> engines. Total turnover <strong>of</strong> the Indian automobile<br />

industry is expected to grow from USD 34 Billion in <strong>20</strong>06 to USD 122 Billion in <strong>20</strong>16 (Ministry <strong>of</strong> heavy industries and<br />

public enterprises Government <strong>of</strong> India, <strong>20</strong>06). The automotive industry is today a key sector <strong>of</strong> the Indian economy and<br />

a major foreign exchange earner for the country. Today, India is the 2nd largest tractor and 5th largest commercial<br />

vehicle manufacturer in the world. Hero Honda with 3.9 million motorcycles a year is now the largest motorcycle<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

manufacturer in the world. With the growth <strong>of</strong> transportation system the automotive industry <strong>of</strong> India is also growing at<br />

rapid speed, occupying a vital place on the ‘canvases <strong>of</strong> Indian economy. By exploring Indian automobile sector, it has<br />

been found that uncertainties like demand and lead-time have direct impact on managing inventories and managers are<br />

facing great difficulties while controlling these parameters (Srinivas and Shekhar, <strong>19</strong>97). Customer satisfaction and cost<br />

reduction are again the key issues to be handled effectively and efficiently. To improve pr<strong>of</strong>itability and efficiency,<br />

automotive players are seeking ways to achieve operational excellence, reduce operating cost and enhance customer<br />

service through efficient supply chain management. Efficient and effective supply chain management plays a very<br />

important role in the auto industry. The automotive industry is changing its business model with innovative supply chain<br />

to reduce cost, create customer buying experience and quality. Mahindra & Mahindra has implemented one <strong>of</strong> the most<br />

efficient supply chain systems in use by Dealers today, though it still stands room for improvement.<br />

2. Indian Automotive Industry Scenario<br />

On the canvas <strong>of</strong> the Indian economy, auto industry occupies a prominent place. Due to its deep forward and backward<br />

linkages with several key segments <strong>of</strong> the economy, automotive industry has a strong multiplier effect and is capable <strong>of</strong><br />

being the driver <strong>of</strong> economic growth. A sound transportation system plays an essential role in the country’s speedy<br />

economic and industrial development. The well-developed Indian automotive industry skillfully fulfils this catalytic role<br />

by producing a broad variety <strong>of</strong> vehicles: passenger cars, light, medium and heavy commercial vehicles, multi-utility<br />

vehicles such as jeeps, scooters, motorcycles, mopeds, three wheelers, tractors etc. India’s quest to become a worldwide<br />

auto-manufacturing hub has made the world’s top automakers increasingly turn to India for their vehicle.<br />

components. Riding this achievement and capitalizing on the strengthening demand from domestic auto companies, the<br />

Indian auto industry is intensifying the demand and is emerging as one <strong>of</strong> fastest growing manufacturing sectors, and a<br />

worldwide competitive one (Kamala and Doreswamy, <strong>20</strong>07) . However, there is still a lack <strong>of</strong> noteworthy study <strong>of</strong><br />

supply chain practices and its presentation in developing countries, in general and India, in particular (Austin, <strong>19</strong>90).<br />

Many dominant factors affect decisions made in the automotive world. Consumer preferences decide the current styles,<br />

consistency, and presentation standards <strong>of</strong> vehicles. Government trade, safety, and environmental regulations found<br />

incentives and requirements for upgrading and change in design or production. Competitive rivalries and corporate<br />

strategies provide equally important momentum for research, design innovations, and changes in the manufacturing<br />

process. All automakers are continually under pressure to recognize consumer preferences, national biases, and new<br />

market segments where they can sell vehicles and gain market share. Their capability to be stretchy enough to quickly<br />

react to all these pressures is determining their prospect in the industry. The implications <strong>of</strong> these factors are enormous<br />

and propagate along the supply chain <strong>of</strong> the automakers in India. The Indian Automotive industry is growing with pace<br />

domestically as well as internationally with remarkable milestones. Below figure shows the growth <strong>of</strong> an Indian<br />

Automotive Sector.<br />

2.1 Domestic Market<br />

Commercial vehicles segment registered growth <strong>of</strong> 49.77 percent in April-July <strong>20</strong>10 as compared to the same period last<br />

year similarly during this period the Medium & Heavy Commercial Vehicles (M&HCVs) registered growth at 74.<strong>19</strong><br />

percent and Light Commercial Vehicles grew at 32.87 percent. During April-July <strong>20</strong>10, three wheelers sales recorded a<br />

growth rate <strong>of</strong> 18.08 percent, while passenger carriers grew by <strong>20</strong>.87 percent and goods carriers grew at 7.24 percent in<br />

this period. Two wheelers registered a growth rate <strong>of</strong> 28.31 percent in April-July <strong>20</strong>10.<br />

2.2 Exports<br />

In April-July <strong>20</strong>10, overall automobile exports registered a growth rate <strong>of</strong> 54.46 percent. Passenger vehicles, two<br />

wheelers, commercial vehicles and three wheelers segments grew by 9.01 percent, 61.52 percent, 95.31 percent and<br />

141.97 respectively in April-July <strong>20</strong>10 over April-July <strong>20</strong>09.<br />

2.3 Factors/Uncertainties explored by supply chain<br />

One <strong>of</strong> the major issues in a supply chain is ensuring hassle free and suave functioning <strong>of</strong> inventory and so the role <strong>of</strong><br />

inventory as a cushion against uncertainties and unforeseen oddities has been established for a long time (Gupta and<br />

Maranas, <strong>20</strong>03). Figure 1 represents the uncertainties that are explored and solved by successful implementation <strong>of</strong><br />

supply chain.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Demand Lead-time Suppliers’<br />

Internal<br />

problems<br />

conflicts<br />

Uncertainties<br />

Market<br />

trends<br />

Product<br />

life cycle<br />

Informatio<br />

n flow<br />

Governme<br />

nt policies<br />

Figure 1. Uncertainties affecting inventory control.<br />

To reduce the impact <strong>of</strong> these inventory uncertainties, supply chain managers must first understand their sources, the<br />

targeted market size, researched feasibility outcomes and the magnitude <strong>of</strong> their impact. Surprisingly many supply chains<br />

do not document and track these variables which may result into over-stock or under-stock, miscalculation <strong>of</strong> the leadtime<br />

and invest in the wrong resources for performance improvement (Tsiakis et al. <strong>20</strong>01). Besides these factors SCM<br />

covers inventory planning, replenishment planning, production scheduling, warehouse management, transportation and<br />

logistics management in auto sector.<br />

3. Conclusion/Theme <strong>of</strong> the paper<br />

Indian automobile and auto components industry is on a roll and there is a massive scope for improvement and<br />

augmentation <strong>of</strong> supply chain in this sector. India has become a most sought after destination for foreign companies to<br />

establish their facilities and form alliances with domestic companies. The Indian economy is now gaining momentum in<br />

the world <strong>of</strong> free trade and liberal movements <strong>of</strong> goods and services between countries. Low cost <strong>of</strong> manufacturing and<br />

conducive government support have been the major drivers for foreign companies investing in India. Therefore<br />

efficiency in supply chain will be critical for India’s automobile success.<br />

References<br />

Austin, J.E., <strong>19</strong>90. Managing in developing countries. Free Press, New York, NY.<br />

Choi, T.Y., Hong, Y., <strong>20</strong>02. Unveiling the structure <strong>of</strong> supply network: Case studies in Honda, Acura, and<br />

DaimlerChrysler. Journal <strong>of</strong> Operations Management <strong>20</strong>, 469-493.<br />

Drucker, P.F., <strong>19</strong>98. Management’s new paradigms. Forbes, 152-177.<br />

Eric Sucky, <strong>20</strong>05. Inventory problem in supply chains: A bargaining problem. International Journal <strong>of</strong> Production<br />

Economics 93-94, 253-262.<br />

Gupta, A., Maranas, C. D., <strong>20</strong>03. Managing demand uncertainty in supply chain planning. Computer and Chemical<br />

Engineering 27, 12<strong>19</strong>-1227.<br />

Kamala, T.N., Doreswamy, A.G., <strong>20</strong>07. Strategies for Enhancing Competitiveness <strong>of</strong> Indian Auto Component Industries.<br />

Indian Institute <strong>of</strong> Management Kozhikode.space.iimk.ac.in/bitstream/2259/478/1/215-2<strong>20</strong>+.pdf.<br />

Ministry <strong>of</strong> Heavy Industries & Public Enterprises Government <strong>of</strong> India, (<strong>20</strong>06). Draft automotive mission plan.<br />

dhi.nic.in. http://www.dhi.nic.in/ draft automotive_ mission_plan.pdf (retrieved 26.11.<strong>20</strong>09).<br />

Srinivas, V., Shekhar, B., <strong>19</strong>97. Applications <strong>of</strong> uncertainties based mental models in organizational learning: A case<br />

study in the Indian automobile industry. Accounting Management and Information <strong>Technology</strong> 7 (2), 87-112.<br />

Tsiakis, P., Shah, N., Pantelides, C. C., <strong>20</strong>01. Design <strong>of</strong> multi-echelon supply chain networks under demand uncertainty.<br />

Industrial Engineering in Chemical Research 40, 3585.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

INTENSITY OF CRITICAL FACTORS EFFECTING TECHNICAL<br />

INSTITUTION EVALUATION- AN ANP APPROACH<br />

Victor Gambhir 1 , N.C. Wadhwa 2 , and Dr. Sandeep Grover 3<br />

1 Pr<strong>of</strong>essor and Pro Vice Chancellor, Manav Rachna International <strong>University</strong><br />

2 Vice Chancellor, Manav Rachna International <strong>University</strong><br />

3<br />

Pr<strong>of</strong>essor, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, India<br />

e-mail: victorgambhir@rediffmail.com<br />

Abstract<br />

In a pursuit <strong>of</strong> excellence in technical education, it is increasingly important to identify critical factors affecting<br />

it. The technical education system in an attempt to react to the demands and ever increasing pressures from its<br />

stakeholders, finds itself in a market-oriented environment, with internal and external customers; wherein,<br />

“satisfying the customer”, is the rule for survival in the long run.With the change <strong>of</strong> education policy in <strong>19</strong>91,<br />

more and more technical institutions are being set up in India. Some <strong>of</strong> these institutions are providing quality<br />

education, but others are merely concentrating on quantity. Because <strong>of</strong> this stake holders are in a state <strong>of</strong><br />

confusion about the decision to select the best institute for their higher study. Although various agencies<br />

including print media are providing ranking <strong>of</strong> these institutions every year, but these seems to be contradictory<br />

and biased. In this paper, the authors have made an endeavor to find the critical factors for technical institution<br />

evaluation from literature survey. An Analytical Network Process (ANP) approach has been applied to find the<br />

intensity <strong>of</strong> the factors for evaluation. This will not only help the stake holders in taking right decision but will<br />

also help the management <strong>of</strong> institutions in benchmarking for identifying the most important critical areas to<br />

improve upon. This will in turn help Indian economy.<br />

Keywords: Critical factors, Technical Institution Evaluation, Analytical Network Process (ANP)<br />

1) Introduction<br />

Over the recent years, technical education in India has gone through rapid, radical and even revolutionary<br />

changes. This has generated opportunities to open technical institutions with business orientation. Thousands <strong>of</strong><br />

technical institutions have come into existence since <strong>19</strong>92 in India. Some <strong>of</strong> these institutions are very good and<br />

have realized the importance <strong>of</strong> quality but there are many for which only quantity matters. So students are in a<br />

great confusion to select the best institution for their higher study. Every year entrance exams are conducted in<br />

India and students has lot <strong>of</strong> options in terms <strong>of</strong> institution according to their ranks. Although many agencies<br />

provide ranking <strong>of</strong> the institutions every year but these ranking are contradictory and instead <strong>of</strong> solving the<br />

problem, alleviate it. Moreover these rankings seem to be influenced or biased. An engineer with the thorough<br />

knowledge places a great role in Indian economy than to an engineer holding just a graduate degree. Even the<br />

technical institution themselves want to benchmark with the peers for improvement. So the problem <strong>of</strong> technical<br />

institution evaluation is important for everyone and has great role to play in everyone’s life because everybody is<br />

associated with education in one or other way. Seeing the importance <strong>of</strong> the problem, the authors have made an<br />

endeavor to find the critical factors for technical institution evaluation from literature survey. Many researchers<br />

in the past have identified many factors for institution evaluation but as per authors’ knowledge no literature<br />

review has been attempted in the past to collect all critical factors at a single place. An ANP approach has been<br />

applied to find the intensity <strong>of</strong> the critical factors. ANP finds the importance <strong>of</strong> critical factors by evaluating their<br />

interdependence and generates weights for every factor.<br />

In this paper a total <strong>of</strong> 35 quality research papers have been reviewed to find the critical factors. To find the<br />

good papers all the leading search engines as well as renowned publishing houses like Elsevier, Taylor &<br />

Francis, Inderscience, Springer & Emerald have been searched. The remaining paper is organized as follows.<br />

Section 2 deals with identification <strong>of</strong> critical factors. Section 3 discusses ANP and conclusion is provided at the<br />

end.<br />

2) Literature Review<br />

This section identifies the critical factors affecting the tecnical educaion and also discusses the application <strong>of</strong><br />

ANP.<br />

i. Identification <strong>of</strong> Critical Factors<br />

Table 1 lists the critical factors with the name <strong>of</strong> the contributors. 40 factors were identified but with the opinion<br />

<strong>of</strong> experts and academicians these were reduced to 23, because other factors were either similar or they seems to<br />

have less importance.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 1. List <strong>of</strong> Critical Factors for Technical Institution Evaluation<br />

Critical Factors<br />

Contributors<br />

1. A well accepted vision and mission Lisensky (<strong>19</strong>88), Sherr and Tecter (<strong>19</strong>91), Nadeau (<strong>19</strong>93), The<br />

Conference Board (<strong>19</strong>93), Downey et al. (<strong>19</strong>94), Finch (<strong>19</strong>94),<br />

Lewis and Smith (<strong>19</strong>94), Burkhalter (<strong>19</strong>96), Frazier (<strong>19</strong>97),<br />

Madhavan (<strong>19</strong>97)<br />

2. Clearly defined and specific goals Seldin (<strong>19</strong>88), Lawton (<strong>19</strong>94), Billing (<strong>19</strong>96)<br />

3. Effective and efficient leadership Reid et al. (<strong>19</strong>87), Teauber (<strong>19</strong>87), Scheerens (<strong>19</strong>89,<strong>19</strong>92),<br />

Lezotte (<strong>19</strong>89), Rossow (<strong>19</strong>90), West-Burnham (<strong>19</strong>92),<br />

Nadeau (<strong>19</strong>93), Oakland (<strong>19</strong>93), The Conference Board<br />

(<strong>19</strong>93), Finch (<strong>19</strong>94), Dahlagaard et al. (<strong>19</strong>95), Spanbaurer<br />

(<strong>19</strong>95), Lozier and Tecter (<strong>19</strong>96), William (<strong>19</strong>96), Frazier<br />

(<strong>19</strong>97), Scheerens and Bosker (<strong>19</strong>97), Tang Zairi (<strong>19</strong>98)<br />

4. Clear & specific policies & procedures Tang and Ziari (<strong>19</strong>98)<br />

5. Strategic & operational planning Shirley (<strong>19</strong>88), Lisensky (<strong>19</strong>88), Binney (<strong>19</strong>92), Finch (<strong>19</strong>94),<br />

Frazier (<strong>19</strong>97), Owlia and Aspinwall (<strong>19</strong>97), Tamg and Zairi<br />

(<strong>19</strong>94)<br />

6. Clear organizational structure and West Burnham(<strong>19</strong>92), Downey et al.,(<strong>19</strong>94), Lewis and<br />

design<br />

Smith(<strong>19</strong>94)<br />

7. Delegation <strong>of</strong> authority/ power<br />

Developed by self<br />

distribution<br />

8. Budget priorities-proactive &<br />

Finch (<strong>19</strong>94)<br />

objective driven<br />

9. Well defined curriculum design Adapted by Frazier (<strong>19</strong>97)<br />

10. Suitability & relevance <strong>of</strong> curriculum Adapted by Frazier (<strong>19</strong>97)<br />

content<br />

11. Curriculum planning, design,<br />

Frazier (<strong>19</strong>97)<br />

periodic review<br />

12. Instructional competence-Expertise Trethowan (<strong>19</strong>87), also adapted from Pratt and Steanning<br />

and adequacy<br />

(<strong>19</strong>89)<br />

13. Instructional arrangement – class Developed by self<br />

size, adequate infrastructure & facilities<br />

14. Adaptive recourse allocation Developed by self<br />

15. Adequate and competent<br />

Adapted from Owlia and Aspinwall(<strong>19</strong>98)<br />

administrative staff/ support staff.<br />

16. Trustworthiness amongst all Owlia and Aspinwall(<strong>19</strong>98)<br />

17. Well defined channels <strong>of</strong><br />

Murgatroyd and Morgan (<strong>19</strong>93), the conference board(<strong>19</strong>93),<br />

communication<br />

Oakland and Oakland (<strong>19</strong>98), Gurnani (<strong>19</strong>99)<br />

18. Customer focus/ need based Binney (<strong>19</strong>92), Marchington (<strong>19</strong>92), West Burnham(<strong>19</strong>92),<br />

Downey et al.,(<strong>19</strong>94), Dahlgaard et al.(<strong>19</strong>95),<br />

Spanbauer(<strong>19</strong>95), Lozier and Teeter(<strong>19</strong>96), Owlia and<br />

Aspinwall(<strong>19</strong>98), Sirvanci(<strong>19</strong>96), Boaden(<strong>19</strong>97),<br />

Frazier(<strong>19</strong>97), Madhavan (<strong>19</strong>97), Gurmami(<strong>19</strong>99)<br />

<strong>19</strong>. Reward policy and Incentives<br />

Schemes<br />

<strong>20</strong>.clear and well defined values and<br />

norms<br />

21. Differentiation- adaptive service for<br />

its customers<br />

22.Emphasis on training and<br />

development for all<br />

Binney(<strong>19</strong>92), the conference board (<strong>19</strong>93), Raisbeck(<strong>19</strong>94),<br />

Gurnani (<strong>19</strong>99)<br />

Rutter et al.,(<strong>19</strong>79)<br />

Horne and Pierce(<strong>19</strong>96), Scheerners and Boasker (<strong>19</strong>97)<br />

The conference board (<strong>19</strong>93), Raisbeck (<strong>19</strong>94), Spanbauer<br />

(<strong>19</strong>95),Lozier and Teeter(<strong>19</strong>96), Boaden (<strong>19</strong>97), Owlia and<br />

Aspinwall(<strong>19</strong>97), Oakland and Oakland (<strong>19</strong>98), Gurnani(<strong>19</strong>89)<br />

23.Collaborative decision making Lewis and Smith(<strong>19</strong>94), Pashiardis (<strong>19</strong>98)<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

These 23 factors are further divided into four clusters by consulting with experts, which are shown in Fig.1.<br />

Figure 1.<br />

Institution<br />

Evaluation<br />

and detailed<br />

Technical<br />

clusters<br />

criteria<br />

ii.<br />

Analytical Network Process (ANP)<br />

ANP is a general form <strong>of</strong> AHP. AHP was first proposed by Saaty (<strong>19</strong>80a & <strong>19</strong>80b). The AHP is a widely used<br />

MADM based on the representation <strong>of</strong> a decision making problem by a hierarchical structure where elements are<br />

independent and unidirectionally linked. By considering both qualitative and quantitative aspects <strong>of</strong> a decision<br />

and through a pairwise comparison, it allows to set priorities among the elements and make the best decision.<br />

Decision problems are not always structured in a hierarchal way i.e. they may have interrelations among the<br />

elements at the same level. To overcome this difficulty, ANP was introduced by Saaty in <strong>19</strong>96. ANP<br />

simultaneously takes into account both feedback and dependence. ANP generalizes the AHP by allowing<br />

networks with or without hierarchal structure. ANP makes the best decision by allowing feedback within<br />

elements <strong>of</strong> a cluster (inner dependence) or between clusters (outer dependence). ANP methodology is explained<br />

in Saaty’s book (Saaty, <strong>20</strong>05). A brief description is given here because <strong>of</strong> space limitation. The ANP comprises<br />

<strong>of</strong> the following major steps:<br />

Step 1: Model construction through networks<br />

Decision problem should be structured into networks by using appropriate methods or through brainstorming.<br />

Step 2: Pairwise comparison and priority vectors<br />

Decision makers are asked to compare clusters through a series <strong>of</strong> questions for inner and outer dependence to<br />

achieve the goal. The relative importance values are determined on the scale <strong>of</strong> 1-9. Where a score <strong>of</strong> 1<br />

represents the equal importance among the elements and a score <strong>of</strong> 9 represents the extreme importance <strong>of</strong> one<br />

element over the other (Meade & Sarkis , <strong>19</strong>99). A reciprocal value is assigned to the inverse comparison i.e.<br />

b ij =1/b ji . Local priority vectors are derived similar to AHP. This step is done to derive the eigenvectors and to<br />

form a supermatrix.<br />

Step 3: Supermatrix formation<br />

The outcome <strong>of</strong> step 2 is unweighted supermatrix. Supermatrix is actually a partitioned matrix. Its columns<br />

represent priorities derived from the pairwise comparison <strong>of</strong> the elements. As unweighted supermatrix may not be<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

column stochastic, so as to obtain one, multiply each block with cluster priority obtained in the step 2. This<br />

stochastic matrix is known as weighted supermatrix. To obtain a convergence on the importance <strong>of</strong> weights, the<br />

supermatrix is raised to large powers and the resulted matrix is known as limit matrix. Priorities can be directly<br />

obtained from the limit matrix.<br />

3) Application <strong>of</strong> ANP to find the intensity <strong>of</strong> critical factors<br />

The factors reported by the selected articles were extracted and presented in a Table 1. The factors that were<br />

recommended by the authors for effective evaluation were included in the ANP approach. The priority matrix<br />

obtained from ANP analysis <strong>of</strong> factors by using s<strong>of</strong>tware Superdecision 2.0.8 is presented in Tables 2. The top<br />

five factors from priority matrix are Instructional competence-Expertise and adequacy (3.4%) , Adaptive recourse<br />

allocation (2.98%), A well accepted vision and mission (2.86%), Adequate and competent administrative staff/<br />

support staff (2.74%), Effective and efficient leadership (2.71%).<br />

Table 2. Priority Matrix<br />

Critical Factors Normalized Limiting Intensity<br />

1. A well accepted vision and mission 0.286 0.05 3<br />

2. Clearly defined and specific goals 0.134 0.02 13<br />

3. Effective and efficient leadership 0.271 0.04 5<br />

4. Clear & specific policies & procedures 0.138 0.02 12<br />

5. Strategic & operational planning 0.17 0.03 10<br />

6. Clear organizational structure and design 0.49 0.04 7<br />

7. Delegation <strong>of</strong> authority/ power distribution 0.139 0.01 17<br />

8. Budget priorities-proactive & objective driven 0.068 0.01 22<br />

9. Well defined curriculum design 0.114 0.01 18<br />

10. Suitability & relevance <strong>of</strong> curriculum content 0.189 0.02 14<br />

11. Curriculum planning, design, periodic review 0.046 0.01 <strong>19</strong><br />

12. Instructional competence-Expertise and adequacy 0.34 0.06 1<br />

13. Instructional arrangement – class size, adequate infrastructure &<br />

facilities 0.041 0.01 <strong>20</strong><br />

14. Adaptive recourse allocation 0.298 0.05 2<br />

15. Adequate and competent administrative staff/ support staff. 0.274 0.04 4<br />

16. Trustworthiness amongst all 0.103 0.01 21<br />

17. Well defined channels <strong>of</strong> communication 0.388 0.02 11<br />

18. Customer focus/ need based 0.229 0.01 15<br />

<strong>19</strong>. Reward policy and Incentives Schemes 0.<strong>19</strong>3 0.01 16<br />

<strong>20</strong>.clear and well defined values and norms 0.087 0.01 23<br />

21. Differentiation- adaptive service for its customers 0.182 0.04 6<br />

22.Emphasis on training and development for all 0.173 0.04 8<br />

23. Collaborative decision making 0.16 0.03 9<br />

Conclusion<br />

Technical institution evaluation is important for stakeholders, management as well as for strong economy <strong>of</strong><br />

India. Critical factors have been identified from literature survey and ANP approach has been applied to now the<br />

intensity <strong>of</strong> these factors in evaluation. The ANP approach shows that instructional competence-expertise and<br />

adequacy is the most important factor. This seems to be right because if the institution has enough instructural<br />

competence and expertise, then it can have freedom to make future policies <strong>of</strong> modernisation. The second<br />

important factor comes out to be adaptive resource allocation i.e. optimium resource allocation, this will save<br />

time and money and will help the instituion in best utilization <strong>of</strong> its resources. The third factor in the ranking is<br />

well accepted mision and vision, if vision and policies <strong>of</strong> the top management are correct and in the best interest<br />

<strong>of</strong> stakeholders and institution then definitely everyone will be beneficial. The fourth important factors come out<br />

to be Adequate and competent administrative staff/ support staff, which is the pillar <strong>of</strong> any good technical<br />

institution The fifth important factors comes out is effective and efficient leadership, which is another most<br />

critical factor because a good leadership will take any institution to the top and will help to make right policies.<br />

762


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

References<br />

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Journal <strong>of</strong> Marketing, 57-71.<br />

[2] Brady, M. C. (<strong>20</strong>01). Some new thoughts on conceptualizing perceived service quality: a hierarchical<br />

approach. Journal <strong>of</strong> Marketing, 65, 34-49.<br />

[3] Chaston, I. (<strong>19</strong>94). Are British universities in a position to consider implementing TQM Higher Education<br />

Quality, 48(2).<br />

[4] Cheng, Y. (<strong>19</strong>96). The Pursuit <strong>of</strong> School Effectiveness: Theory, Policy and Research. The Hong Kong<br />

Institute <strong>of</strong> Educational Research, The Chinese <strong>University</strong> <strong>of</strong> Hong Kong, Hong Kong.<br />

[5] Cronin, J. T. (<strong>20</strong>02). Measuring service quality: a re-examination and extension. Journal <strong>of</strong> Marketing, 56,<br />

56-58.<br />

[6] Elmuti, D. K. (<strong>19</strong>96). Are total quality management programmers in higher education worth the effort<br />

International Journal <strong>of</strong> Quality & Reliability Management, 13(6), 29-44.<br />

[7] Eriksen, S. (<strong>19</strong>95). TQM and the transformation from an elite to a mass system <strong>of</strong> higher education in the<br />

UK. Quality Assurance in Education, 3(1), 14-29.<br />

[8] Green, d. (<strong>19</strong>94). What is quality in higher education Concepts, policies and practice", in Green, D.<br />

(Eds),What is Quality in Higher Education SRHE and Open <strong>University</strong> Press, Buckingham, 3-<strong>20</strong>.<br />

[9] Haywood-Farmer, J. (<strong>19</strong>88). A conceptual model <strong>of</strong> service quality", International Journal <strong>of</strong> Operations &<br />

Production Management. 8(6), <strong>19</strong>-29.<br />

[10] Killedar, M. (<strong>20</strong>07). Model for Total Quality’ <strong>of</strong> the Open and Distance Education System. Total Quality<br />

Management, 8, 402-415.<br />

[11] Levinson, H. B.-J. (<strong>19</strong>96). Managing quality improvement on a development pilot line. Quality<br />

Management Journal, 3(2), 16-35.<br />

[12] Madu, C. K. (<strong>19</strong>94). 56, 375-390.<br />

[13] Madu, C. K. (<strong>19</strong>94). TQM in the university: a quality code <strong>of</strong> honor. Total Quality Management, 56, 375-<br />

390.<br />

[14] Meade, L. M., & Sarkis , J. (<strong>19</strong>99). Analyzing Organizational Project Alternatives for Agile Manufacturing<br />

Processes-Ananalytical Network Approach. International Journal <strong>of</strong> Production Research, 37(2), 241-261.<br />

[15] Michael, R. S. (<strong>19</strong>97). A comprehensive model for implementing TQM in higher education. Benchmarking<br />

for Quality Management and <strong>Technology</strong>, 4(2).<br />

[16] Mukhopadhay, M. (<strong>20</strong>01). Total Quality Management in Education, National Institute <strong>of</strong> Educational<br />

Planning and Administration. New Delhi.<br />

[17] Mukhopadhyay, M. (<strong>20</strong>05). Total quality management in higher education. International Journal <strong>of</strong><br />

Educational Management, 5(5), 4-9.<br />

[18] Owlia, M. A. (<strong>19</strong>98). A framework for measuring quality in engineering education. Total Quality<br />

Management, 9(6), 501-518.<br />

[<strong>19</strong>] Parasuraman, A. Z. (<strong>19</strong>85). SERVQUAL: a multiple-item scale for measuring consumer perceptions <strong>of</strong><br />

service quality. Journal <strong>of</strong> Retailing, 64(1), 12-40.<br />

[<strong>20</strong>] Pfeffer, N. C. (<strong>19</strong>91, november 24). Is Quality Good For You A Critical review <strong>of</strong> Quality Assurance in<br />

the Welfare Services. Institute <strong>of</strong> Public Policy Research TQM in Education, pp. 64-65.<br />

[21] Reeves, C. B. (<strong>19</strong>94). Defining quality: alternatives and implications. Academy <strong>of</strong> Management Review,<br />

<strong>19</strong>(3), 4<strong>19</strong>-445.<br />

[22] Saaty, T. L. (<strong>19</strong>80a). The Analytic Hierarchy Process-Planning, Priority Setting, Resource. New York: Mc-<br />

Graw Hill.<br />

[23] Saaty, T. L. (<strong>19</strong>80b). The Analytic Hierarchy Process. New York: Mc-Graw Hill.<br />

[24] Saaty, T. L. (<strong>19</strong>96). Decision Making with Dependence and Feedback: The Analytic Network Process.<br />

Pittsburgh: RWS Publications.<br />

[25] Saaty, T. L. (<strong>20</strong>05). Theory and Applications <strong>of</strong> the Analytic Network Process. Pittsburgh: RWS<br />

Publications.<br />

[26] Sahney, S. B. (<strong>20</strong>04). Customer requirement constructs: the premise for TQM in education: a comparative<br />

study <strong>of</strong> select engineering and management institutions in the Indian context. International Journal <strong>of</strong><br />

Productivity and Performance Management, 53(6), 499-5<strong>20</strong>.<br />

[27] Sallis, E. (<strong>19</strong>93). Total Quality Management in Education. Kogan Page, 45-47.<br />

[28] Spanbauer, S. (<strong>19</strong>95). Reactivating higher education with total quality management: using quality and<br />

productivity concepts, techniques and tools to improve higher education. Total Quality Management, 6(5).<br />

[29] Tobin, L. (<strong>19</strong>90). The new quality landscape: total quality management. Journal <strong>of</strong> System Management,<br />

41, 10-14.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[30] Walsh, A. H. (<strong>20</strong>02). Total quality management continuous improvement: is the philosophy a reality<br />

Journal <strong>of</strong> European Industrial Training, 26(6), 299-307.<br />

[31] Willis, P. (<strong>19</strong>99). Total quality management: some thoughts. Higher Education, 25(3), 373-375.<br />

[32] Zeithaml, V. P. (<strong>19</strong>85). Problems and strategies in services marketing. Journal <strong>of</strong> Marketing.<br />

764


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

EFFECTS OF ROAD TRAFFIC NOISE ON TRAFFIC CONSTABLE IN<br />

GHAZIABAD REGION<br />

Rakesh V.Mishra 1 , Sachin Rathore 2 , Nitin Sharma 2 , D.D.Johri 3 , Z Mallick 4<br />

1 M.tech. scholar, Department <strong>of</strong> Mechanical Engineering, AFSET Faridabad (Haryana)<br />

2 Assistant Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, KIET Gzb (U.P.)<br />

3 Associate Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, KIET Gzb (U.P.)<br />

4<br />

Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, JMI, New Delhi<br />

Email: mishrarv@gmail.com<br />

Abstract:<br />

Over the past decades there had been a rapid change in the population <strong>of</strong> Ghaziabad (U.P.). This has lead to a<br />

significant change in the traffic density in the commercially developed cities. This traffic growth has made the noise<br />

level on the roads beyond the prescribed limits. We have put an effort for the measurements <strong>of</strong> noise levels in this<br />

paper, under traffic conditions over different time span in Ghaziabad region, to estimate, whether these levels<br />

exceeds permissible limits, (65 dB (A)) prescribed by the Central Pollution Control Board, New Delhi. This paper is<br />

an attempt for the measurements <strong>of</strong> noise levels under traffic conditions over different time span in Ghaziabad<br />

region, to estimate, whether these levels exceeds permissible levels, (65 dB(A)) prescribed by the Central Pollution<br />

Control Board (CPCB) New Delhi, the variation in discomfort <strong>of</strong> road traffic Police constable was assessed by<br />

means <strong>of</strong> a questionnaire. Finally results reveal that higher road traffic noise levels led to the increase <strong>of</strong> discomfort<br />

<strong>of</strong> traffic Police constable.<br />

Keywords: Road traffic noise; Traffic Police constable; Discomfort; Questionnaire<br />

I. Introduction<br />

Ergonomics (or human factors) is the scientific discipline concerned with understanding <strong>of</strong> the interactions among<br />

humans and other elements <strong>of</strong> a system. It is also concerned with the pr<strong>of</strong>ession that applies theory, principles, data<br />

& methods to design, in order to optimize human well-being and overall system performance. People in systems<br />

operate within an environment and environmental ergonomics is concerned with how they interact with the<br />

environment from the perspective <strong>of</strong> ergonomics. Environmental ergonomics is provided in terms <strong>of</strong> the effects <strong>of</strong><br />

heat and cold, vibration, noise and light on the health, comfort and performance <strong>of</strong> people [15]. Nowadays, noise<br />

pollution is considered as one <strong>of</strong> the main problems <strong>of</strong> urban communities which has many hazardous effects on the<br />

urban environment and may result in a great deal <strong>of</strong> costs on the society [13][8]. The major contributor to the noise<br />

level increase is the traffic density in large cities [12]. According to the researches, noise pollution caused by traffic<br />

is one <strong>of</strong> the major problems in the southern large cities <strong>of</strong> Sweden [14] [7]. In another research conducted in <strong>20</strong>04<br />

in the same country, in addition to mentioning the problems <strong>of</strong> noise pollution in the big cities <strong>of</strong> Sweden, the<br />

researchers have demonstrated that noise effects will limit the episodic memory [9]. The traffic policemen in<br />

metropolises are the most affected groups exposed to this dangerous factor during their working hours and in their<br />

leisure time. Ingleet al.have been measured the level recorded for this group as 88 dB (A) and, in some cases, it has<br />

been observed up to 100 dB (A) [11]. Statistic results published by Organization for Economic Co-Operation and<br />

Development (OECD) in <strong>19</strong>94 specified that more than 17 million people in France are exposed to sounds louder<br />

than 55 dB (A) during 8-<strong>20</strong> hours <strong>of</strong> their lives, whereas the minimum standard noise for noise pollution in the<br />

environment is 55 dB (A) [4] [5]. The central pollution control board (CPCB) <strong>of</strong> India in its notification on ambient<br />

air quality standard for noise, which has been included as an air pollutant under section <strong>20</strong> <strong>of</strong> Amended air act <strong>of</strong><br />

<strong>19</strong>87 and has laid down the ambient noise standards. Moreover, it was concluded that the noise in some parts <strong>of</strong><br />

these cities is so much that can lead to long-lasting and irrecoverable effects on the citizens and in places like<br />

masonry workshops and may increase above 100 dB (A). Regarding to the sound standards (less than 55 dB (A))<br />

determined by World Health Organization (WHO), studying <strong>of</strong> the urban environmental noise became significant<br />

765


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[5]. Guite et al.studied the effects <strong>of</strong> urban environment over the public health and well being and they concluded<br />

that the environmental noise can affect the mental health [10].<br />

The major objective <strong>of</strong> the study was to enumerate the spatial and temporal distribution <strong>of</strong> urban traffic noise in the<br />

city <strong>of</strong> Ghaziabad and develop suitable noise maps for evaluation <strong>of</strong> impact.<br />

The investigations were conducted with the intention <strong>of</strong> assessing and quantify the extent <strong>of</strong> road traffic noise<br />

distribution pattern under the urban environment. Following objectives will be attained in this study:<br />

• Improve noise management practices in the study area;<br />

• Assist in planning for upcoming developments in the city;<br />

• Increase awareness among the local population to recognize their existing noise environment and<br />

• The potential for use as an benchmark for other cities, particularly in the Indian subcontinent and elsewhere<br />

to produce city noise maps<br />

2. MATERIALS & METHODS<br />

A. Study area<br />

Ghaziabad, an urban-industrial city and part <strong>of</strong> NCR zone situated in Uttar Pradesh state <strong>of</strong> India, with an area <strong>of</strong><br />

1548 km 2 and a population density <strong>of</strong> 3954/ km 2 has witnessed a sharp growth in vehicular population in the last<br />

five years, ensuing a significant, unrestrained noise pollution across the area The impact identification and<br />

quantification due to such exposure to road traffic noise has been done in such preceding works and it has been<br />

observed that such noise levels in the area are much above the prescribed limits .The situation demands through<br />

investigation, identification and assessment <strong>of</strong> the cause-effect chain due to traffic generated noise exposure. This is<br />

responsible movement <strong>of</strong> heavy and medium vehicles across the main road and throughout the day resulting in high<br />

noise emissions. Regarding to the number <strong>of</strong> vehicles and the traffic load among the rich habitants <strong>of</strong> the NCR region<br />

and by means <strong>of</strong> traffic organization and traffic police center data <strong>of</strong> the mentioned region, the traffic situation and<br />

the number <strong>of</strong> traffic policemen residing in the area were identified and their location were spotted. Then, the places<br />

that the measurement was supposed to carry out were located by means <strong>of</strong> available municipal maps taken from the<br />

traffic organization & from the internet. The traffic volume was assessed in terms <strong>of</strong> Passenger Car Units (PCU). It is<br />

the scale to convert all vehicles into one category, i.e., passenger car. The PCU values for two wheelers, three<br />

wheelers, light commercial vehicles, buses, and heavy commercial vehicles are 0.75, 2, 2.5, 3 and 3, respectively<br />

[16].<br />

B. Data collection<br />

Noise measurement was done at selected locations as shown in fig.1 with the help <strong>of</strong> A digital sound level meter<br />

(IEC651, ANSI S1.4) with frequency range <strong>of</strong> 31.5Hz to 8,000Hz and measuring level range between 35–130 dB<br />

was used for the study. All reading were taken on the ‘A-weighting’ frequency network, at a height <strong>of</strong> about 1.5 m<br />

from ground level and on the ‘Fast’ range time weighting. The ‘A’ weighting characteristic and ‘Fast’ range is<br />

simulated as ‘human ear listening’ response. Sound data were recorded at interval <strong>of</strong> 15 sec for a continuous<br />

sampling period <strong>of</strong> 1 minute during working days and under normal climatic conditions. The data collected from<br />

field were recorded in MS excel worksheet and later transferred to Noise Mapping (Get Data and Surfer) s<strong>of</strong>tware for<br />

further analysis. All noise values were expressed in dB (A) units. For the proper assessment and analysis <strong>of</strong> the<br />

results, the following noise indices were computed: L eq : A-weighted equivalent sound level during sampling period,<br />

L max and L min : Maximum and minimum noise level during sampling period. Equivalent sound level, ‘L eq ’ is<br />

computed using following equation:<br />

N<br />

L eq (dB (A)) = 10 × log 10 [(1/N) ∑i=1 10<br />

Li/10 ] (1)<br />

Where, L i is the noise level <strong>of</strong> the i th reading and ‘N’ denotes total number <strong>of</strong> recorded samples. Such data were<br />

generated for time intervals (8.00 am– 8.00 pm).<br />

766


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

In the present study, the general characteristics <strong>of</strong> selected locations are given in Table 1.<br />

Figure1. Map showing location <strong>of</strong> the study area<br />

Table 1. General features <strong>of</strong> all selected locations<br />

S.N.<br />

Name <strong>of</strong><br />

locations<br />

Nature <strong>of</strong><br />

locations<br />

Traffic characteristics<br />

Dominance <strong>of</strong><br />

Road vehicles<br />

Road conditions<br />

1 Hapur more Commercial<br />

Heavy traffic flow with<br />

traffic jam<br />

2 Old bus stand Commercial Heavy congested<br />

3 Chadhary more Commercial<br />

4<br />

5<br />

Hapur chungi<br />

more<br />

Delhi Meerut<br />

more<br />

Commercial<br />

Commercial<br />

Heavy traffic flow with<br />

traffic jam<br />

Heavy with frequent traffic<br />

jam<br />

Heavy with frequent traffic<br />

congestion<br />

Two wheelers,<br />

three wheelers,<br />

four wheelers<br />

& Heavy<br />

vehicles<br />

Narrow and poorly<br />

maintained<br />

Narrow and<br />

overcrowded<br />

Broad and<br />

maintained but<br />

overcrowded<br />

Broad and<br />

maintained but<br />

overcrowded<br />

Broad and<br />

maintained<br />

In the preparation <strong>of</strong> noise contour maps, GET DATA and Surfer version 8 and version 10 s<strong>of</strong>tware were used. The<br />

base map <strong>of</strong> the study area was taken from the Google map and saved in the document exchange format (DXF) for<br />

easy integration with the other s<strong>of</strong>twares used for the study. Positional coordinates <strong>of</strong> sampling locations were<br />

accurately collected using Get Data s<strong>of</strong>tware. The noise contour maps were created in Surfer-8 and surfer-10. Maps<br />

were created using interpolation (ordinary kriging) method. Kriging is a flexible geostatistical gridding method that<br />

has been proven useful and popular in many fields. This method produces visually appealing contour and surface<br />

plots from irregularly spaced data.<br />

There are some practical benefits <strong>of</strong> noise mapping. In some respects the benefits achieved are as much dependant on<br />

the vision <strong>of</strong> those having control <strong>of</strong> the noise mapping system as the capabilities <strong>of</strong> the system itself [2][3].<br />

• The very existence <strong>of</strong> a noise map can act as a catalyst for raising the pr<strong>of</strong>ile <strong>of</strong> noise with pr<strong>of</strong>essionals,<br />

politicians, and the public.<br />

• It can be used as a useful tool to minimize the extent <strong>of</strong> noise pollution <strong>of</strong> a noisy place.<br />

767


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

• It can predict the future status <strong>of</strong> noise pollution on the basis <strong>of</strong> noise producing source evaluation and<br />

monitoring.<br />

Furthermore a questionnaire, as shown in Table 2, was distributed amongst the elected policemen <strong>of</strong> sample size <strong>of</strong><br />

50 containing questions about their personal characteristic and the various factors that affect their task performance<br />

during the traffic conditions. The questionnaire was designed based on literature survey and discussion with traffic<br />

constable about their physical, mental and their behavior during performing the task [1].<br />

Table 2.The evaluation questionnaire <strong>of</strong> traffic policemen<br />

Noise level:- [ ] dB (A) Location: ………….………..<br />

Temperature & Relative humidity:- ( ) 0 C, ( ) % No <strong>of</strong> Vehicle/hr:-…………<br />

Age:- ( ) Years Avg. speed/hr:-……………...<br />

Sex:- ( ) M/F<br />

S.N.<br />

1<br />

2<br />

Questions<br />

Which one <strong>of</strong> hazards is the most<br />

important in your duty<br />

Which one <strong>of</strong> noise pollution source is the<br />

most important for you<br />

3 When you are most tensed<br />

4 When are you most relaxed<br />

5 When you feel most fatigue<br />

Answers/Options<br />

A B C D<br />

Air pollution Noise pollution<br />

Long term<br />

standing<br />

Accidents<br />

Traffic Crowd Car horns Others<br />

Morning (6-11<br />

am)<br />

Morning (6-11<br />

am)<br />

Morning (6-11<br />

am)<br />

Afternoon (12-4<br />

pm)<br />

Afternoon (12-4<br />

pm)<br />

Afternoon (12-4<br />

pm)<br />

Evening (5-9<br />

pm)<br />

Evening (5-9<br />

pm)<br />

Evening (5-9<br />

pm)<br />

Both a &<br />

c<br />

Both a &<br />

c<br />

Both a &<br />

c<br />

3. Results and Discussion<br />

The results <strong>of</strong> the study and interpretation are given in this section. Table 5.1 summarizes the traffic noise parameters<br />

used in the study. Fig.5.1 represents typical road noise maps based on traffic data across five different types <strong>of</strong><br />

locations. Based on the computed data as shown in Table 2 and the developed noise maps, it is observed that all the<br />

five location have the highest average Leq values which are significantly above the specified guidelines <strong>of</strong> Central<br />

Pollution Control Board, New Delhi (CPCB) and WHO specification. Their guidelines are summarized below in<br />

table: 3 [5][6].<br />

Table 3.National and International Noise Standards<br />

S.N. Organization Standard Noise Level (dB(A))<br />

1 CPCB 65<br />

2 WHO 55<br />

3 EUROPEAN UNION (EU) 55<br />

Based on the Leq values and the other noise computed parameters, it can be mentioned that noise values are<br />

significantly higher, both during day and night time, than the prescribed safe limits. Near intersections, especially the<br />

Old Bus Stand on Ambedkar Road and Hapur Chungi near Income Tax Collectorate <strong>of</strong>fice have very elevated traffic<br />

volumes and accounts for extremely high noise levels in and around the site. This area can be categorized as a high<br />

noise risk zone and is significant in the sense that residential and health establishments are within 100 m radius. The<br />

768


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

high noise prone identified areas included Hapur more (junction), Chaudhary more and Delhi-Meerut more. The<br />

roads passing across through these areas is the G. T. Road, Ambedkar road, Hapur Road, NH-58 (National Highway<br />

No. 58) all being arterial roadways <strong>of</strong> the city. As represented in Fig. 2 to 6, the noise levels are much higher near the<br />

roadways and fade outwards according to the local topography. Open areas with relatively less traffic movement<br />

show reduced noise levels. The Lmax is the highest at the Old Bus Stand and Hapur chungi more near collectorate<br />

<strong>of</strong>fice as these locations being an industrial, residential, and corporate <strong>of</strong>fice are always presented vulnerable to high<br />

levels <strong>of</strong> occupational noise exposure. A continuous exposure may lead to hearing loss and noise induced permanent<br />

threshold shift (NIPTS). Although the average traffic flow/hr is in the moderate to high range, but instantaneous<br />

noise produced mostly by heavy vehicles is significantly high. In the mixed zone areas that consist <strong>of</strong> two or more<br />

land use type, like residential-commercial or commercial-sensitive, etc. the two-wheeler class was the most<br />

accounted type and is one <strong>of</strong> the annoyance causing groups.<br />

The percentage <strong>of</strong> heavy goods vehicles, which includes the trucks, dumpers, trailers, buses, etc. ranges from 0 % to<br />

29.72 %. This group is the most significant factor for generation <strong>of</strong> traffic noise. Locations where heavy vehicular<br />

movement was lower had less noise levels. This is due to not only they produce noise directly, but also hamper the<br />

smooth flow <strong>of</strong> the traffic and causes frequent jams. The commercial and business establishments are <strong>of</strong> many types<br />

and varieties, including single establishments, clusters <strong>of</strong> shops and designated areas in the form <strong>of</strong> supermarkets,<br />

markets, shopping complexes, malls, etc. These establishments are lined alongside <strong>of</strong> 75% <strong>of</strong> all the major and<br />

secondary roadways <strong>of</strong> the city. The lack <strong>of</strong> proper footpaths and pavements causes the pedestrians to sprawl on the<br />

roads, which causes frequent traffic congestions and significant high noise environment. The noise levels in these<br />

zones varied between 71.1 to 102.2 dB (A) during study period (Between 8.00 am to 8.00 pm) as shown in Table 2.<br />

The noise contour maps given in the Fig 2 to 6 shows the mapped Leq noise levels in terms <strong>of</strong> Space and time based<br />

on collected data. This measure <strong>of</strong> noise gives an idea about the annoyance <strong>of</strong> exposed population due to traffic<br />

movements.<br />

Table 4. Summarized mean noise level for each specified locations<br />

S.N<br />

.<br />

Locations<br />

Measured value <strong>of</strong><br />

noise levels(dB<br />

(A))<br />

L eq L min L max<br />

Two<br />

wheelers<br />

Volume <strong>of</strong> vehicle per hour (%)<br />

Three<br />

wheelers<br />

Light<br />

vehicles<br />

Heavy<br />

vehicles<br />

Total no. <strong>of</strong><br />

vehicle per<br />

hours<br />

1 Hapur more 89.1 71.1 91.5 7.74 4.95 58.82 29.721 4845<br />

2 Old Bus stand<br />

100.<br />

3<br />

74<br />

102.<br />

2<br />

26.13 5.57 55.75 12.54 4305<br />

3 Chadhary more 84.5 72.9 88.3 21.6 8.9 48.87 <strong>20</strong>.63 4135.56<br />

Hapur Chungi<br />

101.<br />

4<br />

96.3 76.4<br />

28.8 7.54 52.34 11.32 3554.8<br />

more<br />

7<br />

Delhi Meerut<br />

5<br />

87.9 72.7 96.8 18.75 6.76 51.8 22.69 4154.8<br />

more<br />

Locations<br />

Hapur<br />

more<br />

South<br />

Distance<br />

(m)<br />

Table 5. Sound Level Data measured at Hapur More<br />

08:00 a.m. to 10:00 02:00 p.m. to 04:00<br />

a.m.<br />

p.m.<br />

dB (A)<br />

dB (A)<br />

06:00p.m. to 08:00 p.m.<br />

dB (A)<br />

L avg L max L avg L avg L max Lmax<br />

5 93.05 96.2 84.01 90.2 87.96 94.0<br />

10 86.63 92.3 83.05 86.5 88.76 95.5<br />

<strong>20</strong> 87.26 89.6 81.08 85.4 91.71 91.2<br />

769


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

30 85.33 90.3 80.06 84.5 89.96 92.2<br />

40 85.0 89.1 78.96 83.2 86.70 95.2<br />

North 5 92.17 95.3 83.02 89.5 85.85 93.1<br />

10 90.53 96.3 82.05 87.5 85.79 101.3<br />

<strong>20</strong> 87.15 93.1 80.05 86.4 91.73 92.03<br />

30 87.57 91.6 79.8 83.1 89.25 90.25<br />

40 85.65 92.6 74.5 82.7 89.53 93.3<br />

East 5 91.7 96.2 85.5 88.5 88.24 100.5<br />

10 89.23 94.7 84.5 89.2 92.51 92.3<br />

<strong>20</strong> 86.64 92.6 83.2 88.9 91.48 89.1<br />

30 86.83 90.1 80.0 85.5 87.57 87.5<br />

40 83.58 93.4 78.9 84.3 89.84 90.4<br />

West 5 94.0 94.6 86.0 90.2 95.67 97.2<br />

10 87.31 96.2 85.3 88.9 87.92 89.5<br />

<strong>20</strong> 86.99 92.5 82.34 86.5 87.<strong>19</strong> 94.4<br />

30 87.46 93.4 83.1 87.4 85.9 87.7<br />

40 86.14 89.3 84.2 88.3 90.03 90.5<br />

Locations<br />

Hapur<br />

more<br />

South<br />

Distance<br />

(m)<br />

Table 6. Sound Level Data measured at Hapur More<br />

08:00 a.m. to 10:00 02:00 p.m. to 04:00<br />

a.m.<br />

p.m.<br />

dB (A)<br />

dB (A)<br />

06:00p.m. to 08:00 p.m.<br />

dB (A)<br />

L avg L max L avg L avg L max Lmax<br />

5 85.2 95.6 88.6 93.8 98.2 96.5<br />

10 87.7 92.0 85.2 90.1 93.2 94.2<br />

<strong>20</strong> 89.2 89.1 81.6 86.4 89.2 99.2<br />

30 86.3 87.2 82.7 87.3 89.66 92.4<br />

40 84.5 88.9 81.8 89.1 85.4 92.3<br />

North 5 89.7 93.2 88.3 90.3 96.7 102<br />

10 87.5 92.5 85.0 97.7 90.1 94.3<br />

<strong>20</strong> 81.6 91.4 90.2 99.3 89.53 103.5<br />

30 79.9 89.6 83.7 93.6 88.53 105<br />

40 87.9 90.7 82.1 90.8 99.9 113.5<br />

East 5 88.9 93.3 91.4 95.7 89.9 96.8<br />

10 89.4 94.7 85.2 93.0 90.9 96.6<br />

<strong>20</strong> 87.8 90.6 84.3 95.2 92.3 99<br />

30 84.7 93.2 83.2 92.6 87.85 100.1<br />

40 80.6 89.4 81.7 94.5 84.42 88.7<br />

West 5 90.1 94.6 87.28 93.1 91.6 98.4<br />

10 87.8 94.9 86.50 91.1 99.24 105.2<br />

<strong>20</strong> 88.4 90.9 88.<strong>19</strong> 95.2 91.1 95.3<br />

30 85.5 96.7 83.<strong>20</strong> 92.1 87.6 92.3<br />

40 80.7 95.9 86.00 90.3 85.1 99.7<br />

The Noise maps shown in fig 2 to 6 based data collected at selected location as shown in the Table 5 to Table 6.The<br />

Noise map indicates that the selected locations are exposed to high level <strong>of</strong> noise pollution which are well above the<br />

safe limits prescribed by National and International standards.<br />

770


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 2. Noise Map <strong>of</strong> Hapur Figure 3. Noise Map <strong>of</strong> Old Bus stand Figure 4. Noise Map <strong>of</strong> Hapur<br />

Chungi<br />

More for L avg for L avg for L avg<br />

`Figure 5. Noise Map <strong>of</strong> Chaudhary More for L avg<br />

Figure 6. Noise Map <strong>of</strong> Meerut More for L avg `<br />

The questionnaire was pre-tested to determine various aspects <strong>of</strong> response <strong>of</strong> traffic constable to noise and its effects<br />

on their health and personal characteristics. There were the final results <strong>of</strong> the effects <strong>of</strong> noise pollution on traffic<br />

policemen. The final results <strong>of</strong> the biggest traffic-related problem that can be harmful for health are shown in Fig.<br />

7.The policemen were asked “What is the most important source <strong>of</strong> noise pollution in the cities” The results are<br />

shown in Fig.8. The 23 % <strong>of</strong> the traffic policemen suffered from the effects <strong>of</strong> noise pollution. Furthermore, 72 % <strong>of</strong><br />

the policemen have suffered from insomnia problem. More than 50 % <strong>of</strong> the traffic policemen had problem in work<br />

because <strong>of</strong> the noise pollution. 60 % <strong>of</strong> the policemen complained about buzzing sounds in their ears after a noisy<br />

workday. This showed the primary effects <strong>of</strong> noise in their ears. For a self-evaluation <strong>of</strong> the mood characteristics, the<br />

final results are shown in Fig. 9. Like any other large cities in the world, the main streets <strong>of</strong> Ghaziabad are also<br />

loaded with traffic flow, shopping centers and other activities which lead the residents suffer from noise pollution<br />

caused by the traffic. Urban management should pay special attention to metropolises noise pollution and its control<br />

methods. The results showed that the street traffic level affects the noise pollution. The traffic policemen thought <strong>of</strong><br />

noise pollution as the main environmental problem <strong>of</strong> their job and moreover, many <strong>of</strong> the residents <strong>of</strong> the mentioned<br />

area have considered the noise problem as the most important one <strong>of</strong> their district. The results achieved in the present<br />

research show that environmental noise can cause insomnia and this is more vivid in the less experienced traffic<br />

policemen.<br />

771


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Responses (%)<br />

25<br />

<strong>20</strong><br />

15<br />

10<br />

5<br />

0<br />

12<br />

Air<br />

Pollution<br />

23<br />

Noise<br />

Pollution<br />

15<br />

Long<br />

term<br />

standing<br />

11<br />

Accident<br />

Responses (%)<br />

25<br />

<strong>20</strong><br />

15<br />

10<br />

5<br />

0<br />

21<br />

Traffic<br />

horn<br />

18<br />

15<br />

Crowd Car horn<br />

8<br />

etc<br />

Figure 7.The most important hazards for traffic<br />

Policemen in Ghaziabad<br />

25<br />

Responses (%)<br />

<strong>20</strong><br />

15 12<br />

10<br />

5<br />

21<br />

Figure 8.The percentage <strong>of</strong> answers to the question<br />

“Which <strong>of</strong> noise pollution sources is the most<br />

important for you”<br />

16<br />

11<br />

0<br />

Very<br />

Patient<br />

Patient Nervous<br />

Very<br />

Nervous<br />

Figure 9. The results <strong>of</strong> Self-evaluation <strong>of</strong> mental characteristics in traffic policemen<br />

4. CONCLUSION<br />

The study reveals the spatio-temporal distribution <strong>of</strong> noise, generated by urban traffic, by means <strong>of</strong> monitoring,<br />

mapping and questionnaire as a tool for evaluation <strong>of</strong> impact. The quantified data shows that the city is exposed to<br />

noise levels ranging mostly from the moderate to extremely high levels in comparison to the national standards.<br />

Immediate administrative and technological mitigative measures should be adopted at the earliest to prevent auditory<br />

and non-auditory health impacts on the local population. Control methodologies can include control <strong>of</strong> noise at<br />

source <strong>of</strong> generation. Control in the transmission path by installation <strong>of</strong> barriers between noise source and receiver<br />

can attenuate the noise levels. The barrier may be either close to the source or receiver. The design <strong>of</strong> the building<br />

along with the use <strong>of</strong> suitable noise absorbing material for wall/door/window/ceiling will reduce the noise levels.<br />

Other measures include raising the awareness among local community, locating more No Horn zones and strict<br />

enforcement <strong>of</strong> laws.<br />

The results can be considered as not being acquainted with the environmental noise. However, it was demonstrated<br />

that this phenomena had some effects on the personal characteristics and nervousness <strong>of</strong> the individuals as social<br />

consequences. Therefore importance <strong>of</strong> noise controlling management should be taken into considerations. As a<br />

solution to all the harmful problems caused by the traffic noise, it is necessary for these people to undergo periodical<br />

checkups to eliminate late diagnosis <strong>of</strong> hearing capability loss and problems in the mental and nerve systems.<br />

Finally, the municipal management must have special noise management planning in metropolises like Ghaziabad;<br />

constructing shopping centers & entertainment venues with appropriate and equal costs at diversified location so that<br />

traffics for shopping & entertainment purposes would decrease; making e-commerce popularized; optimizing public<br />

transportation system with adequate capacity. The induction <strong>of</strong> batteries operated vehicles will also lead to reduce the<br />

noise level.<br />

772


References<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[1] M. U. Onuu. Road traffic noise in Nigeria: measurements, Analysis and evaluation <strong>of</strong> nuisance, International Journal <strong>of</strong> Sound and Vibration<br />

(<strong>20</strong>00) 233(3), 391-405.<br />

[2] Banerjee, D.; Chakraborty, S. K., (<strong>20</strong>05). Ambient noise quality around sensitive areas in Asansol City, West Bengal, India. Indian J. Environ.<br />

Ecoplan, 10 (3), 907-910 (4 pages).<br />

[3] Banerjee, D.; Chakraborty, S. K.; Bhattacharyya, S.; Gangopadhyay, A., (<strong>20</strong>08a). Evaluation and analysis <strong>of</strong> road traffic noise in Asansol: An<br />

industrial town <strong>of</strong> eastern India. Int. J. Environ. Res. Public Health, 5 (3), 165-171 (7pages).<br />

[4] CPCB, (<strong>20</strong>01). Central pollution control board, noise pollution regulation in India, CPCB, New Delhi.<br />

[5] Banerjee, D. S., Chakraborty, K., Bhattacharyya, S. and Gangopadhyay, A. (<strong>20</strong>09). Appraisal and mapping the spatial-temporal distribution <strong>of</strong><br />

urban road traffic noise. Int. J. Environ. Sci. Tech., 6(2), 325-335.<br />

[6] Barrigon Morillas, J. M., Gomez Escobar, V., Mendez Sierra, J.A., Vilchez Gomez, R. and Trujillo Carmona, J. (<strong>20</strong>02). An environmental<br />

noise study in the city <strong>of</strong> caceres, Spain. Appl. Acoust., 63 (10), 1061-1070.<br />

[7] Bjork, J., Ardo, J., Stroh, E., Lovkvist, E., Ostergren, P. and Albin, M. (<strong>20</strong>06). Road traffic noise in southern Sweden & its relation to<br />

annoyance, disturbance <strong>of</strong> daily activities and health, Scand. J. Work Environ. Health, 32(5), 392-401.<br />

[8] Chien, M. K. and Shih, L. H. (<strong>20</strong>07). An empirical study <strong>of</strong> the implementation <strong>of</strong> green supply chain management practices in the electrical<br />

and electronic industry and their relation to organizational performances. Int. J. Environ. Sci. Tech. 4 (3), 383 –394.<br />

[9] Enmarker, I. (<strong>20</strong>04). The effects <strong>of</strong> meaningful irrelevant speech and road traffic noise on teacher’s attention, episodic and semantic memory.<br />

Scand. J. Psychol., 45(5), 393-405.<br />

[10] Guite, H.F., Clark, C. and Ackrill, G. (<strong>20</strong>06). The impact <strong>of</strong> the physical and urban Environmental on mental well-being. J. Public Health,<br />

1<strong>20</strong>(12), 1117-1126. Int. J. Environ. Res., 3(4):645-652,Autumn <strong>20</strong>09 651.<br />

[11] Ingle, S.T., Pachpande, B.G., Wagh, N.D. and Attarde, S.B. (<strong>20</strong>06). Noise exposure and hearing loss among the traffic policemen working at<br />

busy streets <strong>of</strong> jogaon urban centre. Transport. Res, 10, 69-75.<br />

[12] Jamrah, A., Al-Omari, A. and Sharabi, R. (<strong>20</strong>06). Evaluation <strong>of</strong> traffic noise pollution in Amman, Jordan. Environ. Monitor. Assess., 1<strong>20</strong>,<br />

499–525.<br />

[13] Martin, M.A., Tarrero, M.A., Gonzalez, A. and Machimbarrena, M. (<strong>20</strong>06). Exposure–effect relationships between road traffic noise<br />

annoyance and noise cost valuations in Valladolid, Spain. J. Appl. Acoust., 67 (10), 945-958.<br />

[14] Skanberg, A. and Ohrstrom, J.F. (<strong>20</strong>02). Adverse health effects in relation to urban residential sound scopes. J. Sound Vib. 250(1), 151-155.<br />

[15] K.C. Parsons, Environmental ergonomics: a review <strong>of</strong> principles, methods and models, International Journal <strong>of</strong> Applied Ergonomics, vol. 31,<br />

pp. - 581-594, <strong>20</strong>00.<br />

[16] Nirjar RS, Jain SS, Parida M, Katiya VS, Mittal N. A study <strong>of</strong> transport related noise pollution in Delhi. J Inst Eng (India) <strong>20</strong>03; 84:1-15.<br />

773


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

OPTIMIZATION OF INVENTORY MODEL FOR DECAYING ITEM<br />

WITH VARIABLE HOLDING COST AND POWER DEMAND<br />

Ankit Prakash Tyagi 1 , Rama Kant Pandey 2 , Shivraj Singh 3<br />

1 Dayanand Brijendra Swarup (PG) College, Dehradun, Uttarakhand, India<br />

2 Department <strong>of</strong> mathematics, Dayanand Brijendra Swarup (PG) College, Dehradun, Uttarakhand, India<br />

3<br />

Department <strong>of</strong> mathematics, D.N. (PG) College, Meerut (UP), India<br />

e-mail: ankitprakashtyagi88@gmail.com<br />

Abstract<br />

In inventory control phenomena, holding cost is an integral part <strong>of</strong> total cost <strong>of</strong> every inventory system. This is<br />

determined from the investment in physical stocks and storage facilities for items during a cycle. In most <strong>of</strong> the<br />

inventory research papers with power demand pattern, holding cost rate per unit time for perishable inventory is<br />

assumed as constant. However, this is not necessarily the case when items in stock are decaying. In the present<br />

work, paying better attention on the holding cost, we present a deteriorating inventory model in which the unit<br />

holding cost is based on the deterioration <strong>of</strong> the inventory with the time the item is in stock. The deterioration is<br />

assumed Weibull distributive. The power pattern <strong>of</strong> demand is considered in this paper. Shortages are allowed<br />

and partial backlogged. The partial backlogging rate is a continuous inverse function <strong>of</strong> waiting time in<br />

purchasing the item during stock out period. By using classical optimization technique, conditions for uniquely<br />

existence <strong>of</strong> global minimum value <strong>of</strong> the average total cost per unit time are discussed. Numerical illustration<br />

and sensitivity analysis are presented.<br />

Keywords: Inventory, Deterioration, Shortage, Weibull Distribution, Power demand, variable holding cost.<br />

1 Introduction<br />

Food items, drugs, pharmaceuticals and agricultural products are few examples <strong>of</strong> essentially required items to<br />

fulfill our daily requirements. In practice, appreciable deterioration can take place during the normal storage<br />

period <strong>of</strong> such items and consequently this loss must be taken into account when making plan <strong>of</strong> our<br />

consumption. Therefore, in many inventory models, the effect <strong>of</strong> deterioration is very important assumption. To<br />

the best <strong>of</strong> our knowledge, an EOQ model for an inventory with variable proportion <strong>of</strong> the on-hand inventory<br />

deteriorates with time have first been developed by Ghare and Schrader [1]. Later, many prominent researcher<br />

papers on inventory control have been considered by Covert and Philip [2], Misra [3], Shah [4] etc. In their<br />

investigations, the market demand for the item is considered to be constant. As time progressed, several other<br />

researchers developed inventory models with decaying items and time dependent demand rates. In this<br />

connection, works done by Mandal and Pal [5], Wu et al. [6], Teng et al. [7], Rau et al. [8], etc. are noteworthy.<br />

Datta and Pal [9] investigated an inventory system with power demand pattern for items with variable rate <strong>of</strong><br />

deterioration.<br />

In some situations <strong>of</strong> inventory control, demand before ending season exists and the inventory has mostly<br />

consumed through joint effect <strong>of</strong> the demand and the deterioration. This type <strong>of</strong> situations laid the foundation <strong>of</strong><br />

stock out phenomena. Consequently, when stock out state occurs, some customers are willing to wait for<br />

backorder and others would turn to buy from other sellers. Many researchers such as Park [10], Hollier and Mak<br />

[11] and Wee [12] considered the constant partial backlogging rates during the shortage period in their inventory<br />

models. In most <strong>of</strong> inventory systems, the length <strong>of</strong> the waiting time for the next replenishment would decide<br />

whether the backlogging will be accepted or not. Therefore, the backlogging rate is variable and dependent on<br />

the waiting time for the next replenishment. Chang and Dye [13] investigated an EOQ model allowing shortage<br />

and partial backlogging. They assumed in their inventory model that the backlogging rate is variable and<br />

dependent on the length <strong>of</strong> the waiting time for the next replenishment. Many researchers have modified<br />

inventory policies by considering the ‘‘time-proportional partial backlogging rate’’ such as Abad [14],<br />

Papachristos and Skouri [15], Wang [16], Papachristos and Skouri [17], Yang et al. [18] etc.<br />

In the cited inventory researcher papers above, holding cost per unit time is taken as constant. Inventory decision<br />

maker generally has to face the major concern to hold the decaying items. For smooth running <strong>of</strong> business<br />

inventory should be available for whole cycle time in good condition. So inventory holding cost is an integral<br />

term <strong>of</strong> total cost function <strong>of</strong> inventory and for better demonstrating the real life situations, holding cost per unit<br />

should be more general as possible. Weiss [<strong>19</strong>] noted that variable holding costs are appropriate when the value<br />

<strong>of</strong> an item decreases the longer it is in stock; Ferguson et al. [<strong>20</strong>] recently indicated that this type <strong>of</strong> model is<br />

suitable for perishable items in which price markdowns or removal <strong>of</strong> aging product are necessary. Goh [21] first<br />

774


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

considered a stock-dependent demand model with variable holding costs, and assumed that the unit holding cost<br />

is a nonlinear continuous function <strong>of</strong> the time the item is in stock or a nonlinear continuous function <strong>of</strong> the<br />

inventory level. Giri and Chaudhuri [22] extended this model to account for perishable products. Roy [23]<br />

developed an inventory model for deteriorating items with time varying holding cost and demand is price<br />

dependent. Mishra and Singh [24] developed the inventory model for deteriorating items with time dependent<br />

linear demand and holding cost.<br />

In these inventory models for deteriorating item with variable holding cost assumption, demonstration <strong>of</strong> holding<br />

cost per unit time is not closely satisfied by real aspects. So, to extend and to introduce more general holding<br />

cost function, we have presented an Economic Quantity Model (EOQ) for decaying items. To give better fitness<br />

to this model, we introduce deterioration governed variable holding cost. The rate <strong>of</strong> deterioration is considered<br />

as Weibull distributed. The demand <strong>of</strong> item is assumed in power pattern. Shortages are allowed and partially<br />

backlogged at next replenishment length dependent rate. Finally, numerical example is presented to demonstrate<br />

the developed model and sensitivity analysis is also provided.<br />

2 Notations<br />

The following notation is used throughout the paper:<br />

I()<br />

t The inventory level at any time t , t ≥ 0 ;<br />

T Constant prescribed scheduling period or cycle length (time units);<br />

I Maximum inventory level at the start <strong>of</strong> a cycle (units);<br />

max<br />

S Maximum amount <strong>of</strong> demand backlogged per cycle (units);<br />

t Duration <strong>of</strong> inventory cycle when there is positive inventory;<br />

1<br />

Q Order quantity (units/cycle);<br />

c Cost <strong>of</strong> the inventory items ($);<br />

1<br />

c Fixed cost per order ($/order);<br />

2<br />

c Shortage cost per unit back-ordered per unit time ($/unit/unit time);<br />

3<br />

c Opportunity cost due to lost sales ($/unit);<br />

4<br />

*<br />

ATC ( t ) Average total cost per cycle.<br />

1<br />

3 Assumptions<br />

In developing the mathematical model <strong>of</strong> the inventory system, the following assumptions are made:<br />

1. The inventory system involves only one item and the cycle length is given and finite.<br />

2. The replenishment occurs instantaneously at an infinite rate.<br />

3. Lead time is negligible.<br />

4. The distribution <strong>of</strong> time until deterioration <strong>of</strong> the item follows a two-parameter Weibull distribution.<br />

5. Deterioration occurs as soon as items are received in to inventory.<br />

6. There is no replacement or repair <strong>of</strong> deteriorating items during the period under consideration;A brief<br />

introduction to the rate <strong>of</strong> deterioration is given as follows: t product life (time to deterioration), t > 0; f () t<br />

probability density function <strong>of</strong> product life (p.d.f.); F()<br />

t cumulative distribution function <strong>of</strong> product life<br />

(c.d.f); R()<br />

t reliability (probability <strong>of</strong> survivorship by time t ); Z()<br />

t instantaneous rate <strong>of</strong> deterioration. From<br />

reliability theory, one has<br />

R() t = 1 − F()<br />

t , (1)<br />

f () t<br />

Z()<br />

t = , (2)<br />

R()<br />

t<br />

and R (0) = 1.<br />

If the product life t is assumed to follow a two-parameter Weibul distribution, its p.d.f. f () t is<br />

β 1 αt<br />

β<br />

f () t αβt − e<br />

−<br />

= , (3)<br />

where α is the scale parameter, α > 0 , and β the shape parameter, β > 0 , using the former definition, one has<br />

β<br />

− αt<br />

R() t = 1 − F()<br />

t = e . (4)<br />

Substituting Eqs. (3) and (4) into Eq. (2), one has<br />

775


β−1<br />

−α<br />

β<br />

t<br />

αβt<br />

e<br />

β −1<br />

= = αβt<br />

, 0<br />

− α<br />

β<br />

t<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Z()<br />

t<br />

t > . (5)<br />

e<br />

Eq. (5) will be used in the model development in this chapter. When β > 1, deteriorating rate increase with<br />

time;<br />

when β < 1deteriorating rate decreases with time; and when β = 1, deteriorating rate is constant.<br />

1−n<br />

1<br />

n<br />

n<br />

7. The demand up to time t is assumed to be D()<br />

t = dt nT . Where d is the demand size during the fixed<br />

cycle time T and n ∈(1, ∞)<br />

is the pattern index. Such pattern in the demand rate is called power demand<br />

pattern.<br />

8. During the shortage period, the backlogging rate is variable and is dependent on the length <strong>of</strong> the waiting time<br />

for the next replenishment. We have defined the backlogging rate to be11 + δ ( T −t)<br />

where inventory is<br />

negative. The backlogging parameter δ is a positive constant, t 1<br />

≤t ≤ T .<br />

4 Model developments<br />

The inventory system during a given cycle is depicted in Fig.1. At t = 0 , an initial replenishment <strong>of</strong><br />

Inventory<br />

Level<br />

I<br />

max<br />

Q<br />

0 t T time<br />

1<br />

Lost sale<br />

Figure 1. Inventory system for Weibull distribution deteriorating items with partial backorder<br />

Q units are made, <strong>of</strong> which S units are delivered towards backorders, leaving a balance <strong>of</strong> I max<br />

units in the initial<br />

inventory. From t = 0 to t 1<br />

= 0 time units, the inventory level depletes due to both demand and deterioration. At t 1<br />

,<br />

the inventory level is zero. During the time ( T − t ) part <strong>of</strong> the shortage is backlogged and part <strong>of</strong> it is lost sales.<br />

1<br />

Only the backlogging items are replaced by the next replenishment.<br />

The differential equation describing I()<br />

t over the length t 1<br />

is given as follow:<br />

dI () t<br />

β 1<br />

+ αβt −<br />

It () = − Dt () ; 0 ≤t ≤ t .<br />

1<br />

dt<br />

(6)<br />

The boundary conditions are:<br />

I(0)<br />

= I and I( t ) = 0.<br />

max<br />

1<br />

The approximate solution <strong>of</strong> eqs. (6) by neglecting higher order term <strong>of</strong>α is<br />

1 1<br />

⎡<br />

+ β + β<br />

n n ⎤<br />

d 1 n 1 n α ( t − t )<br />

1<br />

t<br />

β<br />

− α<br />

I() t = ⎢( t − t ) +<br />

⎥e<br />

; 0 ≤t ≤ t . (7)<br />

1 n 1<br />

1<br />

T ⎢<br />

(1 + nβ<br />

) ⎥<br />

⎢⎣<br />

⎥⎦<br />

Now, again taking the first two terms <strong>of</strong> the exponential series and neglecting the terms containingα 2<br />

the<br />

equation (7) becomes<br />

776


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

1 1<br />

⎡<br />

+ β + β<br />

n n ⎤<br />

d 1 n 1 n<br />

β α ( t − t )<br />

1<br />

I( t) = ⎢( t −t )(1 − αt<br />

) +<br />

⎥ ; 0 ≤t ≤ t<br />

(8)<br />

1 n 1<br />

1<br />

T ⎢<br />

(1 + nβ<br />

) ⎥<br />

⎢⎣<br />

⎥⎦<br />

So, the maximum inventory level for each cycle can be obtained as<br />

1<br />

⎡<br />

+ β<br />

n ⎤<br />

d 1 n αt1<br />

I = I(0)<br />

= ⎢t<br />

+ ⎥<br />

(9)<br />

max 1 n 1<br />

T ⎢ (1 + nβ<br />

) ⎥<br />

⎢⎣<br />

⎥⎦<br />

During the shortage interval [ t , T<br />

1<br />

] , the demand at timet is partially backlogged at the fraction11 + δ ( T − t ) .<br />

Thus, the differential equation governing the amount <strong>of</strong> demand backlogged is as below.<br />

1−nn<br />

dI dt<br />

−<br />

1 n<br />

dt nT { 1 + δ ( T −t<br />

)}<br />

; t ≤t ≤ T<br />

(10)<br />

1<br />

with the boundary condition I( t ) = 0. The solution <strong>of</strong> equation (10) by neglecting higher order term <strong>of</strong> δ is<br />

1<br />

1 1<br />

d ⎡<br />

1 1<br />

1 n 1 n δ<br />

+ +<br />

n n<br />

⎤<br />

I( t) = − (1 δT)( t t ) ( t t ) ;<br />

1 n<br />

1 1<br />

T<br />

⎢ − − + −<br />

(1 + n)<br />

⎥ t ≤t ≤ T . (11)<br />

1<br />

⎣<br />

⎦<br />

Let t = T in (11), we obtain the maximum amount <strong>of</strong> demand backlogged per cycle as follows.<br />

1 1<br />

d ⎡<br />

1 1<br />

1 n 1 n δ<br />

+ +<br />

n n<br />

⎤<br />

S = − I( T) = (1 δT)( t t ) ( t t )<br />

1 n<br />

1 1<br />

T<br />

⎢ − − + −<br />

(1 + n)<br />

⎥<br />

⎣ ⎦ . (12)<br />

Hence, the order quantity per cycle is given by<br />

1<br />

⎡<br />

+ β<br />

n<br />

1 1 ⎤<br />

d<br />

1 1<br />

1 n αt<br />

1 n 1 n δ<br />

+ +<br />

n n<br />

Q = I + S = ⎢t + + (1 −δT)( T − t ) + ( T −t<br />

) ⎥. (13)<br />

max 1 n 1 1 1<br />

T ⎢ (1 + nβ<br />

) (1 + n)<br />

⎥<br />

⎣<br />

⎦<br />

The order cost per cycle is<br />

OC = c 2<br />

.<br />

The deterioration cost per cycle is<br />

t1<br />

β 1<br />

DC c αβt −<br />

I () t dt<br />

1<br />

0<br />

= ∫ ,<br />

1<br />

cdα<br />

1<br />

1<br />

+ β<br />

n<br />

=<br />

t . (14)<br />

1 n<br />

1<br />

T (1 + nβ<br />

)<br />

The shortage cost per cycle is<br />

T<br />

SH = ∫ c ( − I ( t )) dt ,<br />

t1<br />

3<br />

1 1<br />

1<br />

⎡<br />

+ 1 + 2<br />

+ 2<br />

1 2<br />

n<br />

1<br />

⎤<br />

n<br />

n<br />

cd<br />

3 2 1 n (1−<br />

2 δT ) + nT 2n δT<br />

δt<br />

n<br />

1<br />

= ⎢( δT − T)<br />

t + t + − + ⎥ . (15)<br />

1 n<br />

1 1<br />

T ⎢<br />

(1 + n) (1 + n) (1 + n)(1+ 2 n) (1+<br />

2 n)<br />

⎥<br />

⎢⎣<br />

⎥⎦<br />

The opportunity cost per cycle is<br />

T<br />

⎡ 1 ⎤<br />

OPC = ∫ c 1 ()<br />

4 ⎢ −<br />

D t dt<br />

t1<br />

{1 + δ ( T −t)}<br />

⎥ ,<br />

⎣<br />

⎦<br />

1 1<br />

+ 1 + 1<br />

n<br />

n<br />

c δ d<br />

4<br />

nT t<br />

= ⎢ + −<br />

1 n<br />

T<br />

⎡<br />

⎢ (1 + n) (1 + n)<br />

⎣<br />

1<br />

n<br />

1<br />

t<br />

⎤<br />

T⎥. (16)<br />

⎥<br />

⎦<br />

4.1 Holding cost<br />

we have assumed that holding cost is continuous variable and consists <strong>of</strong> two terms first the fixe rent R <strong>of</strong><br />

rental warehouse or depreciation <strong>of</strong> own warehouse; and second handling charges H variable with storage period<br />

and environment or perish ability. Handling charges <strong>of</strong> an item may vary with the time for which the item is in<br />

stock and deteriorating nature <strong>of</strong> item. So we have considered that the increasing rate <strong>of</strong> handling charges with<br />

storage period is exponentially governed by deterioration rate θ () t .Thus, the holding cost per unit per unit time<br />

t ( t )<br />

is ( R + He θ<br />

) , where t is the storage period <strong>of</strong> an item.<br />

Holding cost per cycle in this scenario is<br />

777


t1 t t<br />

β −1<br />

αβ<br />

= ∫ ( R + He ) I () t dt .<br />

0<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

1 1<br />

⎡<br />

+ 1 + β + 1<br />

n<br />

n ⎤<br />

d ( R+ H) t αβ ( R+<br />

2 H)<br />

t<br />

1 1<br />

= ⎢<br />

+<br />

⎥. (17)<br />

1<br />

⎢<br />

n<br />

(1 + n) ( β + 1)(1 + n+<br />

nβ)<br />

⎥<br />

T ⎢⎣<br />

⎥⎦<br />

Thus, the average total cost ATC ( t ) <strong>of</strong> inventory cycle is<br />

1<br />

1 1 1 1<br />

⎡ 1 1<br />

n ⎡ + + β+ n n ⎤<br />

+ β<br />

n<br />

d c T ( R+ H) t αβ ( R+<br />

2 H)<br />

t cαt<br />

2 1 1 1 1<br />

ATC ( t ) = ⎢ + ⎢ + ⎥+<br />

1 1 n<br />

T ⎢ d ⎢ (1 + n) ( β + 1)(1 + n+ nβ) ⎥ (1 + nβ)<br />

⎢⎣<br />

⎢⎣ ⎥⎦<br />

1 1<br />

⎡<br />

+ 2 + 1<br />

1 1 1<br />

2<br />

1 2<br />

n<br />

n ⎤<br />

2 (1−<br />

2 δT ) + δ + 2n δT nT<br />

n n n<br />

+ c ⎢( δT − T)<br />

t + t + t − + ⎥<br />

3 1 1 1<br />

⎢<br />

(1 + n) (1+ 2 n) (1+ 2 n)(1 + n) (1 + n)<br />

⎥<br />

⎣<br />

⎦<br />

1<br />

1<br />

⎡ + 1<br />

+ 1<br />

n<br />

n<br />

1 ⎤⎤<br />

nT t1<br />

n<br />

δ ⎢<br />

Tt ⎥⎥<br />

4 1<br />

+ c + − . (18)<br />

⎢ (1 + n) (1 + n)<br />

⎥⎥<br />

⎢⎣<br />

⎥⎥ ⎦⎦<br />

In this model, the objective is to determine the optimal values <strong>of</strong> shortage point t 1<br />

in order to minimize the<br />

average total cost ATC ( t ) per unit time. The optimal solutions * 1<br />

t need to satisfy the following equation.<br />

1<br />

1<br />

− 1<br />

n<br />

dt<br />

1 1<br />

dATC ( t )<br />

= f ( t ) = 0<br />

(<strong>19</strong>)<br />

1 1<br />

dt<br />

+ 1<br />

1<br />

n<br />

nT<br />

β + 1<br />

αβ ( R+<br />

2 H)<br />

t1<br />

β<br />

2 2<br />

Where f ( t ) = ( R+ H) t + + cαt + c ( δT T) (1 2 Tδ) t δt c δ( t T)<br />

1 1 1 1 3<br />

⎡ − + − +<br />

1 1<br />

⎤+ −<br />

4 1<br />

(1 + β )<br />

⎣<br />

⎦<br />

Theorem 1. If δT < ( c + δc ) c and β > 1 then the solutions to (<strong>19</strong>) not only exists but also is unique (i.e., the<br />

3 4 3<br />

optimal values t * is uniquely determined).On the other hand, if δT > ( c + δc ) c and β > 1 then the minimum<br />

1<br />

3 4 3<br />

point is t = = .<br />

*<br />

t 0<br />

1 1<br />

Pro<strong>of</strong>: From Eq. (<strong>19</strong>), it is easily verified that, when δT < ( c + δc ) c ,<br />

3 4 3<br />

lim f ( t ) < 0 and<br />

lim f ( t ) > 0. Furthermore, taking first derivative <strong>of</strong> f ( t ) with respect to t<br />

t T<br />

1<br />

1<br />

1<br />

∈ (0, T)<br />

, we get df ( t ) dt > 0.So,<br />

1 1<br />

1→<br />

*<br />

f ( t ) is a strictly increasing function <strong>of</strong> t<br />

1<br />

1<br />

∈ (0, T)<br />

. It implies that the Eq. (<strong>19</strong>) is verified at t = t ,<br />

1 1<br />

*<br />

with 0 < t < T , which is the unique root <strong>of</strong> f ( t ) = 0. On the other hand, when δT > ( c + δc ) c , the Eq. (<strong>19</strong>)<br />

1<br />

3 4 3<br />

1<br />

*<br />

vanishes at only t = = , with 0 < t < T . This completes the pro<strong>of</strong>.<br />

*<br />

t 0<br />

1 1<br />

1<br />

Theorem 2. IfδT < ( c + δc ) c and β > 1 the average total cost per unit time ATC ( t ) is convex and reaches<br />

3 4 3<br />

1<br />

its global minimum at point t * . 1<br />

Pro<strong>of</strong>: From Eq. (<strong>19</strong>), ifδT < ( c + δc ) c , we have<br />

3 4 3<br />

2<br />

1 1 1<br />

d ATC ( t 2 1 1<br />

1<br />

) d ⎡ 1<br />

− −<br />

n n<br />

d<br />

−<br />

⎛ ⎞ ⎤ ⎡ ⎤<br />

n<br />

= 1<br />

2 1 ⎢⎜<br />

− ⎟t1 f ( t1) + t1 f ′( t1) ⎥ = t<br />

1 ⎢ 1<br />

f ′( t1) ⎥ > 0. It<br />

dt<br />

+ 1 ⎝ n ⎠<br />

+ 1<br />

1<br />

nT<br />

⎣ ⎦<br />

nT<br />

⎣ ⎦<br />

*<br />

t1=<br />

t1 n * n<br />

*<br />

t1= t1 t1=<br />

t1<br />

*<br />

implies, t corresponds to the global minimum <strong>of</strong> convex ATC ( t ). This completes the pro<strong>of</strong>.<br />

1<br />

1<br />

By using t * , we can obtain the optimal maximum inventory level and the minimum average total cost per unit<br />

1<br />

time from equations (9) and (18), respectively (we denote these values by I<br />

* and<br />

max<br />

*<br />

( )<br />

1<br />

t1<br />

→0<br />

ATC t ). Furthermore, we<br />

can also obtain the optimal order quantity (we denote it by Q *<br />

) from equation (13).<br />

5 Numerical Examples<br />

As an illustration <strong>of</strong> developed model, a numerical example is presented for a single product. To perform the<br />

numerical analysis, data have been taken from the literature in appropriate units.<br />

Example 1: We consider an inventory system which verifies the assumptions described above. The input data <strong>of</strong><br />

parameters are T = 6, α = 0.3, β = 2, δ = 0.1, n = 4, d = 60, c = 8, c = 1, c = 9, R = 0.5, H = 0.4 and c<br />

1 2 3<br />

4<br />

= 2 . By<br />

1<br />

778


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

using MATHEMATICA 8.0, the minimum Average Total Cost ATC ( t )( = 46.2925) along with the optimal<br />

1<br />

value <strong>of</strong> t * ( = 2.493338) is calculated. The Optimal Order Quantity * 1<br />

Q ( = 67.6846) are also calculated.<br />

6 Sensitivity Analyses<br />

To discuss the effect <strong>of</strong> changes <strong>of</strong> model parameters TRH , , , α, β, c,<br />

cand c<br />

1 3 4<br />

on the optimal value <strong>of</strong> shortage<br />

*<br />

*<br />

point ( t = 2.493338) , Average Total Cost ( ATC ( t ) = 46.2952) and the optimal value <strong>of</strong> Order Quantity per<br />

1<br />

1<br />

*<br />

cycle ( Q = 67.6846) ; the different values <strong>of</strong> these parameter according to ± 5% and ± 10% change in each have<br />

taken and its effect on t * , TAC ( t *<br />

) and *<br />

1 1<br />

Q are presented in the following Table 1.<br />

Table 1. Sensitivity Analysis<br />

% change in the values <strong>of</strong><br />

*<br />

*<br />

*<br />

Parameters t Q ATC ( t )<br />

1<br />

1<br />

*<br />

*<br />

*<br />

t Q<br />

ACT ( t )<br />

T = 6<br />

2.564140 67.5363 47.0572 +2.83 -0.22 +1.64<br />

2.53<strong>20</strong>87 67.6478 46.7259 +1.55 -0.05 +0.93<br />

2.448025 67.6508 45.7646 -1.82 -0.04 -1.15<br />

2.3962<strong>19</strong> 67.5499 45.1328 -3.89 -0.<strong>20</strong> -2.51<br />

1<br />

1<br />

R = 0.5<br />

H = 0.4<br />

2.479873 67.5408 46.5896 -0.54 -0.21 +0.63<br />

2.486578 67.6124 46.4428 -0.27 -0.11 +0.32<br />

2.500152 67.7576 46.1469 +0.27 +0.11 -0.32<br />

2.507021 67.8314 45.9978 +0.54 +0.22 -0.64<br />

2.476663 67.5044 46.6062 -0.67 -0.27 +0.67<br />

2.484950 67.5950 46.4513 -0.34 -0.13 +0.34<br />

2.501827 67.7756 46.1380 +0.34 +0.13 -0.34<br />

2.510432 67.8680 45.9795 +0.67 +0.27 -0.68<br />

α = 0.3<br />

2.406391 67.6889 47.8088 -3.49 +0.006 +3.27<br />

2.448649 67.6891 47.0681 -1.79 +0.006 +1.67<br />

2.540706 67.6748 45.4872 +1.90 -0.014 -1.74<br />

2.591042 67.6588 44.6409 +3.92 -0.038 -3.14<br />

β = 2<br />

2.334117 66.78<strong>20</strong> 47.8<strong>19</strong>9 -6.38 -1.33 +3.29<br />

2.410022 67.2257 47.0841 -3.34 -0.68 +1.70<br />

2.584863 68.1561 45.4493 +3.67 +0.70 -1.83<br />

2.685423 68.6362 44.5428 +6.61 +1.40 -3.78<br />

c = 8<br />

1<br />

2.423686 66.9477 47.5844 -2.79 -1.09 +2.78<br />

2.457836 67.3069 46.9501 -1.42 -0.56 +1.41<br />

2.530275 68.0823 45.6186 +1.48 +0.59 -1.46<br />

2.568732 68.5017 44.9<strong>19</strong>0 +3.02 +1.<strong>20</strong> -2.97<br />

c = 9<br />

3<br />

2.589155 68.7264 48.8123 +3.84 +1.54 +5.44<br />

2.542135 68.2111 47.5731 +1.96 +0.78 +2.76<br />

2.442632 67.1465 44.9763 -2.03 -0.79 -2.85<br />

2.389868 66.5959 43.6138 -4.15 -1.61 -5.79<br />

c = 2<br />

4<br />

2.496735 67.7210 46.3717 +0.14 +0.05 +0.16<br />

2.495038 67.7028 46.3335 +0.07 +0.03 +0.08<br />

2.491634 67.6664 46.2569 -0.07 -0.02 -0.08<br />

2.489928 67.6481 46.2185 -0.14 -0.05 -0.15<br />

779


Observations:<br />

1. From Table 1 it is clear that<br />

TRH , , , , ,<br />

α c cand β ,c<br />

1 3<br />

4<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

ATC t increases with increase in the values <strong>of</strong> model parameters<br />

*<br />

( )<br />

1<br />

*<br />

. The obtained results show that ATC ( t ) is highly sensitive to changes<br />

in T, α, β,<br />

c and c<br />

3 1<br />

and less sensitive to changes in RHand , c 4<br />

. From results <strong>of</strong> the table above, the average<br />

total cost per unit time increases with increasing the values <strong>of</strong> deterioration’s parameters. This result<br />

demonstrates the fact that deterioration cost increase as deterioration <strong>of</strong> item increases. And, due to increase in<br />

the deterioration <strong>of</strong> item, its handling charges increase. Therefore, the holding cost and the average total cost<br />

per unit time increase.<br />

*<br />

2. From Table 1 it is clear that ATC ( t ) decreases with decrease in the values <strong>of</strong> model.<br />

1<br />

*<br />

parameters TRH , , , α , c,<br />

cand β ,c . The obtained results show that ATC ( t ) is highly sensitive to changes<br />

1 3<br />

4<br />

1<br />

in T, α, β,<br />

c and c<br />

3 1<br />

and less sensitive to changes in RHcand , , c<br />

3 4<br />

.<br />

7 Conclusions<br />

In this model, we study an inventory model in which the inventory is depleted not only by power pattern <strong>of</strong><br />

demand but also by Weibull distributed deterioration, holding cost per unit time is considered a continuously<br />

variable function depends upon item’s deterioration. Shortages are allowed and partially backlogged. Conditions<br />

for existence and uniqueness <strong>of</strong> the optimal solution are also provided. Therefore, the proposed model can be<br />

used in inventory control <strong>of</strong> certain deteriorating items such as food items, electronic components, and<br />

fashionable commodities, and others. Moreover, the advantage <strong>of</strong> the proposed inventory model is illustrated<br />

with example. On the other hand, as is shown by Table 1, the optimal average total cost per unit time is highly<br />

sensitive to changes in the value <strong>of</strong> deterioration parameters, holding cost and shortage cost. This represents the<br />

reality touch <strong>of</strong> this model because as deterioration parameters increase the deterioration cost and holding cost<br />

due to increased deterioration rate increase. Consequently, the average total cost per unit time increases. In<br />

future, this paper may be extended with stochastic demand and permissible delay <strong>of</strong> payment.<br />

References<br />

[1] P.M. Ghare, G.H. Schrader, A model for exponentially decaying inventory system, International Journal <strong>of</strong> Production<br />

Research 21 (<strong>19</strong>63) 449-460.<br />

[2] R. P. Covert, G. C. Philip, An EOQ model for items with Weibull distribution deterioration, AIIE Transactions 5 (<strong>19</strong>73)<br />

323-326.<br />

[3] R. B. Misra, Optimum production lot size model for a system with deteriorating inventory, International Journal <strong>of</strong><br />

Production Research 13 (<strong>19</strong>75) 495-505.<br />

[4] Y.K. Shah, An order-level lot size inventory model for deteriorating items, AIIE Transactions 9 (<strong>19</strong>77) 108–112.<br />

[5] B. Mandal A. K., Pal, Order level inventory system with ramp type demand rate for deteriorating items, Journal <strong>of</strong><br />

Interdisciplinary Mathematics 1 (<strong>19</strong>98) 49-66.<br />

[6] J. W. Wu, C. Lin, B. Tan, W. C. Lee, An EOQ inventory model with time-varying demand and Weibull deterioration with<br />

shortages, International Journal <strong>of</strong> Systems <strong>Science</strong> 31 (<strong>20</strong>00) 677-683.<br />

[7] J.T. Teng, H.L Yang, Deterministic economic order quantity models with partial backlogging when demand and cost are<br />

fluctuating with time, Journal <strong>of</strong> the Operational Research Society 55(5), (<strong>20</strong>04) 495-503.<br />

[8] H. Rau, B.C. Ouyang, A general and optimal approach for three inventory models with a linear trend in demand.<br />

Computers and Industrial Engineering 52(4), (<strong>20</strong>07) 521-532.<br />

[9] T.K. Datta, A.K. Pal, Order level inventory system with power demand pattern for items with variable rate <strong>of</strong><br />

deterioration, Indian Journal <strong>of</strong> Pure and Applied Maths. <strong>19</strong>(11) (<strong>19</strong>88) 1043-1053.<br />

[10] K.S. Park, Inventory models with partial backorders, International Journal <strong>of</strong> Systems <strong>Science</strong> 13 (<strong>19</strong>82) 1313–1317.<br />

[11] R.H. Hollier, K.L. Mak, Inventory replenishment policies for deteriorating items in a declining market, International<br />

Journal <strong>of</strong> Production Research 21 (<strong>19</strong>83) 813–826.<br />

[12] H.M. Wee, A deterministic lot-size inventory model for deteriorating items with shortages and a declining market,<br />

Computers & Operations Research 22 (<strong>19</strong>95) 345–356.<br />

[13] H.J. Chang, C.Y. Dye, An EOQ model for deteriorating items with time varying demand and partial backlogging,<br />

Journal <strong>of</strong> the Operational Research Society 50 (<strong>19</strong>99) 1176–1182.<br />

[14] P.L. Abad, Optimal lot size for a perishable good under conditions <strong>of</strong> finite production and partial backordering and lost<br />

sale, Computers & Industrial Engineering 38 (<strong>20</strong>00) 457–465.<br />

[15] S. Papachristos, K. Skouri, An optimal replenishment policy for deteriorating items with time-varying demand and<br />

partial exponential type-backlogging, Operations Research Letters 27 (<strong>20</strong>00) 175–184.<br />

[16] S.P. Wang, An inventory replenishment policy for deteriorating items with shortages and partial backlogging,<br />

Computers & Operations Research 29 (<strong>20</strong>02) <strong>20</strong>43–<strong>20</strong>51.<br />

[17] S. Papachristos, K. Skouri, An inventory model with deteriorating items, quantity discount, pricing and time-dependent<br />

partial backlogging, International Journal <strong>of</strong> Production Economics 83 (<strong>20</strong>03) 247–256.<br />

[18] H. L. Yang, J. T. Teng, M. S. Chern, An inventory model under inflation for deteriorating items with stock-dependent<br />

consumption rate and partial backlogging shortages, International Journal <strong>of</strong> Production Economics 123 (<strong>20</strong>10) 8–<strong>19</strong>.<br />

780<br />

1


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[<strong>19</strong>] H.J. Weiss, Economic order quantity models with nonlinear holding costs, European Journal <strong>of</strong> Operational Research, 9<br />

(1) (<strong>19</strong>82) 56–60.<br />

[<strong>20</strong>] M. Ferguson, V. Hayaraman, G.C. Souza, Note: An application <strong>of</strong> the EOQ model with nonlinear holding cost to<br />

inventory management <strong>of</strong> perishables, European Journal <strong>of</strong> Operational Research 180 (1) (<strong>20</strong>07) 485–490.<br />

[21] M. Goh, EOQ models with general demand and holding cost functions, European Journal <strong>of</strong> Operational Research 73 (1)<br />

(<strong>19</strong>94) 50–54.<br />

[22] B.C. Giri, K.S. Chaudhuri, Deterministic models <strong>of</strong> perishable inventory with stock-dependent demand rate and<br />

nonlinear holding cost, European Journal <strong>of</strong> Operational Research 105 (3) (<strong>19</strong>98) 467–474.<br />

[23] A. Roy, an inventory model for deteriorating items with price dependent demand and time varying holding cost,<br />

Advanced Modeling and Optimization 10 (<strong>20</strong>08) 25–37.<br />

[24] V.K. Mishra, L.S. Singh, Deteriorating inventory model for time dependent demand and holding cost with partial<br />

backlogging, International Journal <strong>of</strong> Management <strong>Science</strong> and Engineering Management 6 (4) (<strong>20</strong>11) 267-271.<br />

781


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Application <strong>of</strong> Graph Theory: a Review<br />

Ravi Kalra 1 , Sunil Kumar 2 , Kamal Jangra 3<br />

1 JCD college <strong>of</strong> Engineering, Sirsa, Haryana *<br />

2 Yadavindra College <strong>of</strong> Engineering, Guru Kashi Campus, Talwandi Sabo, Bathinda, Punjab<br />

3 <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad, Haryana<br />

* Email:ravikalra24@gmail.com<br />

Abstract<br />

This paper presents the application <strong>of</strong> graph theory in manufacturing and industrial systems. Graph theory is a<br />

systematic and logical approach that has been successfully implemented in various fields <strong>of</strong> engineering. The<br />

main advantage <strong>of</strong> graph theory over other techniques is that it includes even qualitative factors along with<br />

quantitative factors for modeling the process. In graph theory, a numeric index is proposed which is a<br />

performance index to evaluate the various considered factors in a system.<br />

Keywords: Graph theory, manufacturing system<br />

1. Introduction<br />

Production <strong>of</strong> low cost and highly reliable components at high rate can be made possible if all components <strong>of</strong> a<br />

production system (i.e. machine tool operation, material flow, quality control, dispatching etc) works on<br />

optimized parameters. There are numerous tools and methodology for choosing optimal selection such as AHP<br />

(analytic hierarchy process), ANN (artificial neural network), DOE (design <strong>of</strong> experiment) and graph theoretic<br />

approach (GTA).<br />

The beginning <strong>of</strong> Graph theory is said to have in 1736 when EULER considered the Konigsberg bridge problem.<br />

Subsequently, the graph theory has been applied in various fields <strong>of</strong> engineering such as physics, chemistry,<br />

mathematics, electrical engineering, sociology, computer technology (net working), economics, operation<br />

research, linguistics etc.<br />

Graph theoretic approach (GTA) is a systematic methodology for conversion <strong>of</strong> qualitative factors to quantitative<br />

values and mathematical modeling gives an edge to the proposed technique over conventional methods like<br />

cause-effect diagrams, flow charts etc. Graph theory serves as a mathematical model <strong>of</strong> any system that includes<br />

multi relations among its constituent elements because <strong>of</strong> its diagrammatic representations and aesthetic<br />

aspects.GTAis a three stage unified systems approach (Deb, <strong>20</strong>00).<br />

i. Modeling <strong>of</strong> systems in terms <strong>of</strong> nodes and edges gives a structural representation to the system and<br />

results in a directed graph. This representation is suitable for visual analysis and understanding the<br />

interrelationships among various nodes.<br />

ii. For further analysis, digraph representation is converted to matrix form, which makes it suitable for<br />

computer processing. However the matrix representation is not unique as changing the labeling <strong>of</strong> nodes<br />

can change it.<br />

iii. Analysis <strong>of</strong> matrix model results in permanent function model, which is in the expression form. The<br />

permanent function model analyzes various combinations among the factors and interrelationships.<br />

Simplified permanent function expression is represented in terms <strong>of</strong> a single numerical index.<br />

Using graph theoretic approach, several attempts have been made to solve the industrial problems involving<br />

multi variables having interaction among them (Wani and Gandhi, <strong>19</strong>99; Rao and Gandhi, <strong>20</strong>02, <strong>20</strong>06; Grover et<br />

al., <strong>20</strong>04; Jangra et al., <strong>20</strong>11). The aim <strong>of</strong> this paper is to present the review on application <strong>of</strong> graph theoretic<br />

approach in different engineering fields.<br />

2. Application <strong>of</strong> Graph theory<br />

Application <strong>of</strong> graph theory has been widely spread into various fields <strong>of</strong> science and technology. Venkatasamy<br />

and Agrawal (<strong>19</strong>95) applied graph theoretical approach to evaluate and analyze the quality <strong>of</strong> the automotive<br />

vehicle by considering the characteristics <strong>of</strong> the vehicle. Twelve quality characteristics <strong>of</strong> a vehicle were<br />

identified. The various factors that affect these characteristics were also identified. Digraph representation,<br />

matrix representation and permanent function were developed for the quality characteristics. Evaluation <strong>of</strong><br />

vehicles was given in terms <strong>of</strong> vehicle quality index, which can be used to compare and rank vehicles in<br />

particular type.<br />

782


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Rao and Gandhi (<strong>20</strong>02) analyzed the failure causes <strong>of</strong> a machine tool using digraph and matrix methods. To<br />

develop machine tool failure casualty digraph, a machine tool failure cause, vibrations <strong>of</strong> a machine tool, was<br />

considered. Six important contributing events; machine tool leveling, type <strong>of</strong> cutting and cutting conditions,<br />

inhomogenities in the work material, disturbance in machine tool drives, cutting process and tool setting and job<br />

handling were analyzed. R.VenkataRao, O.P. Gandhi (<strong>20</strong>02) proposed a methodology which is used for selecting<br />

the best work-tool combination for a given machining operation. Unlike conventional methods which adopt only<br />

one <strong>of</strong> the machinability assessment criteria, the proposed method considers all the criteria simultaneously &<br />

gives the correct and complete evaluation <strong>of</strong> the machinability <strong>of</strong> work materials. The proposed universal<br />

machinability index evaluates and ranks work materials for the given machining operation.<br />

Grover et al. (<strong>20</strong>04) used the digraph approach to evaluate the total quality management (TQM) environment <strong>of</strong><br />

an industry. A mathematical model was developed for TQM environment by considering the several factors.<br />

These factors were broadly grouped into behavioral factors, non-behavioral factors, use <strong>of</strong> tools and techniques,<br />

human factors and functional factors. Numerical value was evaluated as a TQM index which is useful for<br />

comparison, ranking and optimum selection. In another paper Grover et al. (<strong>20</strong>06) presented digraph and matrix<br />

approach for evaluation <strong>of</strong> extent <strong>of</strong> human aspects present in an organization. The ‘human factors’ in total<br />

quality management (TQM) environment was determined in terms <strong>of</strong> a single numerical index by considering<br />

their inheritances and interactions. In this paper, interaction among identified human factors is represented<br />

through digraph, matrix model and a multinomial.<br />

Mohan et al. (<strong>20</strong>05) developed a mathematical model using graph theory and matrix method to evaluate the<br />

performance <strong>of</strong> a steam power plant. For developing a system structure graph, sub-systems for boiler viz. air<br />

system, water system, combustion chamber/furnace, flue gas system and superheated steam system and their<br />

interactions were considered. The methodology converts a real life steam power plant into a block representation<br />

and then to a graph theoretic representation. The permanent function <strong>of</strong> the boiler system at a particular level <strong>of</strong><br />

hierarchy represents all possible combinations <strong>of</strong> its subsystems.<br />

Sushma Kulkarni (<strong>20</strong>05) introduced a methodology in graph theoretic approach to evaluate the performance<br />

index and ranks the various industries practicing TQM for a given time. To identify and compare various TQM<br />

performances in industry, performance index is to be used. This approach presents a rank to different industries<br />

and other organization practicing TQM or other quality program.<br />

Rao and Padamabhan (<strong>20</strong>06) presented digraph and matrix method for evaluation <strong>of</strong> alternative industrial robots.<br />

A robot selection index was proposed that evaluate and ranks robots for a given application. Purchase cost, load<br />

capacity, velocity, repeatability, number <strong>of</strong> degrees <strong>of</strong> freedom and man-machine interface were considered as<br />

the robot selection attributes for digraph generation. In another paper, Rao (<strong>20</strong>06) introduced a graph theoretic<br />

approach for Machine group selection in a flexible manufacturing cell. Flexible Manufacturing Cells (FMCs)<br />

represent a class <strong>of</strong> highly automated systems. The FMC relates to highly automated manufacturing systems to<br />

evaluate highly flexible manufacturing system. This paper presents a methodology for machine group selection<br />

in FMC. Here a performance index is to be made to evaluate and ranks for grouping <strong>of</strong> machine with their<br />

attributers and feature.Rao and Padmanabhan (<strong>20</strong>07)proposed a methodology forselection <strong>of</strong> a rapid prototyping<br />

process selection index to evaluate the ranking order for a given product. The proposed method is a general<br />

method and considers any number <strong>of</strong> quantitative and qualitative RP process selection approach.<br />

Faisal et al. (<strong>20</strong>07) introduce a digraph and matrix approach to evaluate Quantification <strong>of</strong> risk mitigation<br />

environment <strong>of</strong> supply chains .This paper present a model between various variables associated with risk<br />

mitigation environment along with their interdependencies. Using graph theory risk mitigation environment can<br />

be quantified for supply chain. Also it provides an opportunity to integrate new variables which could impact the<br />

overall supply chain risk mitigation environment.<br />

Thakkar et al.(<strong>20</strong>08) introduced a methodology to evaluate the buyer-supplier relationships using an integrated<br />

mathematical approach <strong>of</strong> interpretive structural modeling (ISM) and graph theoretic matrix. The main purpose<br />

<strong>of</strong> this paper is to evaluate and compare supply chain relationships, specifically when, small and medium scale<br />

enterprise is considered. To evaluate the net pool <strong>of</strong> buyer-supplier relationship on focal small and medium scale<br />

automotive component manufacturing industry, coefficient <strong>of</strong> similarity and dissimilarity are to be identified.<br />

Also the paper discussed the supply chain relationships and the reasons behind their present failures and<br />

establishes the criteria for win-win partnership.<br />

Singh and Agrawal (<strong>20</strong>08)introduced a mathematical model which characterized the structure <strong>of</strong> the<br />

manufacturing system and identify the various structural patterns for manufacturing system. The model may<br />

783


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

serve as a framework for developing various dimensions <strong>of</strong> performance i.e. flexibility, responsiveness etc.<br />

Different alternative structures may be compared, ranked and finally selected for system wide optimization.<br />

Yadav et al. (<strong>20</strong>10) introduced a methodology for selection <strong>of</strong> power plant using graph theoretic approach to<br />

evaluate and rank the various type <strong>of</strong> power plant, a universal evaluation index on the basis <strong>of</strong> operational<br />

characteristics has been proposed. In order to study the impact <strong>of</strong> attributes over the desired outcome, sensitivity<br />

analysis <strong>of</strong> the attributes has been used.<br />

Saha and Grover (<strong>20</strong>11) applied the graph theory to evaluate the quality dimension for web 2.0 environment with<br />

quantitative approach. Also the purpose <strong>of</strong> this paper is to represent the effect <strong>of</strong> ‘website quality dimension in<br />

web 2.0 environment’ in terms <strong>of</strong> a single numerical index by considering their inheritances and interactions.<br />

The practical approach is to find out the key quality attributes which affects overall website quality.<br />

Jangra et al. (<strong>20</strong>11) applied the graph theory to evaluate the performance <strong>of</strong> carbide compacting die<br />

manufactured by wire EDM. They considered surface characteristics and dimensional accuracy as the important<br />

performance attribute <strong>of</strong> a compacting die. Die performance indexes were determined under the combination <strong>of</strong><br />

different factors and sub-factors which evaluate the influence <strong>of</strong> considered factors. In another paper Jangra et al.<br />

(<strong>20</strong>11) evaluated the machinability <strong>of</strong> tungsten carbide composite with wire EDM using graph theoretic<br />

approach. Material removal rate is considered as an attribute for evaluating the machinability index.<br />

Malhota et al. (<strong>20</strong>11) applied the graph theoretic approach to evaluate the barriers affecting the reconfigurable<br />

system. Twelve barriers were identified and a mathematic model was developed to evaluate the extent <strong>of</strong> these<br />

barriers. Table 1 summarizes the application <strong>of</strong> GTA.<br />

Sr.<br />

No<br />

1<br />

2<br />

3<br />

Table 1: Application <strong>of</strong> Graph Theoretic Approach in Numerous Fields<br />

Areas <strong>of</strong> Application<br />

Quantitative Evaluation <strong>of</strong> Website Quality Dimension for<br />

Web 2.0 Environment<br />

Digraph and matrix method to evaluate the machinability<br />

<strong>of</strong> tungsten carbide composite with wire EDM<br />

Digraph and matrix method for the performance evaluation<br />

<strong>of</strong> carbide compacting die manufactured by wire EDM<br />

Researchers<br />

Saha and Grover (<strong>20</strong>11)<br />

Jangra et al.(<strong>20</strong>11)<br />

Jangra et al.(<strong>20</strong>11)<br />

4 Customer sensitivity and risk in supply chains Faisal et al. (<strong>20</strong>11)<br />

5<br />

Operational- Economics Based Evaluation And<br />

Selection <strong>of</strong> A Power Plant Using Graph Theoretic<br />

Yadav et al.(<strong>20</strong>10)<br />

Approach<br />

6<br />

Modeling And Analysis <strong>of</strong> Simple Open Cycle Gas<br />

Turbine Using Graph Networks<br />

Yadav et al.(<strong>20</strong>10)<br />

7 Optimization <strong>of</strong> single product flow line configuration <strong>of</strong> RMS Dou et al. (<strong>20</strong>09)<br />

8<br />

Evaluation <strong>of</strong> buyer-supplier relationships using an integrated<br />

mathematical approach <strong>of</strong> interpretive structural modeling<br />

(ISM) and graph theoretic matrix: The case study <strong>of</strong> Indian<br />

automotive SMEs<br />

Thakkar et al.(<strong>20</strong>08)<br />

9<br />

10<br />

Structural modeling and integrative analysis <strong>of</strong> manufacturing<br />

systems using graph theoretic approach<br />

Singh and aggrawal (<strong>20</strong>08)<br />

Quantification <strong>of</strong> risk mitigation environment <strong>of</strong> supply chains<br />

using graph theory and matrix methods Faisal et al. (<strong>20</strong>07)<br />

11 Selection and comparison <strong>of</strong> industrial robots Rao and Padmanabhan (<strong>20</strong>06)<br />

12 Role <strong>of</strong> human Factors in TQM Grover et al. (<strong>20</strong>06)<br />

13<br />

Machine group selection in a flexible manufacturing cell using<br />

digraph and matrix methods<br />

784<br />

R. VenkataRao (<strong>20</strong>06)


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

14 Human Resource performance index in TQM Environment Grover et al. (<strong>20</strong>05)<br />

15<br />

Graph theory and matrix approach for performance evaluation<br />

<strong>of</strong> TQM in Indian industries<br />

SushmaKulkarni (<strong>20</strong>05)<br />

16 Performance evaluation <strong>of</strong> TQM in Indian industries. Kulkarni (<strong>20</strong>05)<br />

17 TQM evaluation <strong>of</strong> an industry Grover et al. (<strong>20</strong>04)<br />

18 Coal based steam power plant Mohan et al (<strong>20</strong>03)<br />

<strong>19</strong> Failure cause analysis <strong>of</strong> machine tools Rao and Gandhi (<strong>20</strong>02)<br />

<strong>20</strong> Machinability evaluation <strong>of</strong> work materials Rao and Gandhi (<strong>20</strong>02)<br />

21<br />

Digraph and matrix methods for the machinability evaluation<br />

<strong>of</strong> work materials<br />

Rao and Gandhi (<strong>20</strong>02)<br />

22 Graph theoretic approach to group technology Mukhopadhyay et. al (<strong>20</strong>00)<br />

3. Limitations <strong>of</strong> graph theory<br />

• Using graph theoretic approach, numerical index is evaluated by developing an equation for permanent<br />

function. For the processing <strong>of</strong> large number <strong>of</strong> variables, computer s<strong>of</strong>tware is required.<br />

• Inheritance <strong>of</strong> sub-barriers and their interdependencies are based on the opinions <strong>of</strong> experts which may be<br />

erratic in some cases.<br />

4. Conclusions<br />

This paper presents the state <strong>of</strong> graph theory and matrix approach in various engineering fields. This method is<br />

well suitable to solve the problems involving multi-variables including qualitative as well as quantitative which<br />

are interdependent in nature. Application <strong>of</strong> graph theory can be extended in industrial engineering which<br />

involves large number <strong>of</strong> variables, from raw material to the supply <strong>of</strong> finished goods.Modelling <strong>of</strong> suchsystems<br />

can be easily done using graph theory.<br />

References<br />

J.Thakkar, A. Kanda, S.G. Deshmukh, (<strong>20</strong>08) "Evaluation <strong>of</strong> buyer-supplier relationships using an integrated<br />

mathematical approach <strong>of</strong> interpretive structural modeling (ISM) and graph theoretic matrix: The case study<br />

<strong>of</strong> Indian automotive SMEs", Journal <strong>of</strong> Manufacturing <strong>Technology</strong> Management, Vol. <strong>19</strong> (1), pp.92 – 124.<br />

K. Jangra, S. Grover and A. Agrawal (<strong>20</strong>11), “Digraph and matrix method to evaluate the machinability <strong>of</strong><br />

tungsten carbide composite with wire EDM”, International Journal <strong>of</strong> Advance manufacturing <strong>Technology</strong>,<br />

vol.56, pp.959-974.<br />

K. Jangra, S. Grover, F.T.S. Chan and A. Agrawal (<strong>20</strong>11), “Digraph and matrix method for the performance<br />

evaluation <strong>of</strong> carbide compacting die manufactured by wire EDM”, International Journal <strong>of</strong> Advance<br />

manufacturing <strong>Technology</strong>,vol.54, pp.579-591.<br />

M.N. Faisal, D.K. Banwet and R. Shankar (<strong>20</strong>11), “Quantification <strong>of</strong> Risk mitigation Environment <strong>of</strong> supply<br />

chains using graph theory and matrix methods”, European Journal <strong>of</strong> Industrial Engineering, vol.1, no.1,<br />

pp.22-39.<br />

M Mohan, O P Gandhi and V P Agrawal (<strong>20</strong>05), “Real-time efficiency index <strong>of</strong> a steam power plant: a systems<br />

approach”, Proc. I Mech E Part A: J. Power and Energy Vol. 2<strong>20</strong>.<br />

R. VenkataRao (<strong>20</strong>06), “Machine group selection in a flexible manufacturing cell using digraph and matrix<br />

methods”, international journal <strong>of</strong> industrial and systems Engineering, vol.1, no.4, pp.502-518<br />

R.V. Rao and K.K. padmanabhan (<strong>20</strong>06), “Selection, identification and comparison <strong>of</strong> industrial robots using<br />

digraph and matrix methods”, Robotics and Computer-Integrated manufacturing, vol. 22 pp. 373-383.<br />

R. Venkatasamy and VP. Agrawal (<strong>19</strong>95), “System and Structure analysis <strong>of</strong> an automobile vehicle-a graph<br />

theoretic approach”, InternationalJournal <strong>of</strong> vehicle Design, vol.16, pp.477-505.<br />

R.V. Rao and K.K. padmanabhan (<strong>20</strong>07), “Rapid prototyping process selection using graph theory and matrix<br />

approach”, Journal <strong>of</strong> materials processing <strong>Technology</strong>, vol.<strong>19</strong>4, pp. 81-88.<br />

R.VenkataRao and O.P. Gandhi (<strong>20</strong>02), “Digraph and matrix methods for the machinability evaluation <strong>of</strong> work<br />

materials”, International Journal <strong>of</strong> machine tools & manufacture, vol.42 pp.321-330.<br />

785


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

R.VenkataRao and O.P. Gandhi (<strong>20</strong>02), “Failure causes analysis <strong>of</strong> machine tools using digraph and matrix<br />

method”, International Journal <strong>of</strong> Machine Tools & Manufacture, vol.42, pp.521-528.<br />

S. Grover, V.P. Agrawal and I.A. Khan (<strong>20</strong>06), “Role <strong>of</strong> Human Factors in TQM: A Graph Theoretic<br />

Approach”, Bench Marking: An International Journal, vol.13, no.4, pp.447-468.<br />

S. Grover, V.P. Agrawal and I.A. Khan (<strong>20</strong>04), “A Digraph approach to TQM evaluation <strong>of</strong> an industry”,<br />

International Journal <strong>of</strong> production <strong>of</strong> Residual, vol.42, no.<strong>19</strong>, pp.4031-4053.<br />

S.Kulkarni (<strong>20</strong>05), "Graph theory and matrix approach for performance evaluation <strong>of</strong> TQM in Indian industries",<br />

The TQM Magazine, Vol. 17 no.6, pp.509 – 526<br />

V. Singh and V.P. Agrawal (<strong>20</strong>08), “Structural modeling and integrative analysis <strong>of</strong> manufacturing systems<br />

using graph theoretic approach”, Journal <strong>of</strong> manufacturing technology management vol.<strong>19</strong>, no.7, pp.844-870.<br />

786


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

EVALUATION OF IDEAS FOR PANEL BODY ASSEMBLY BY<br />

DECISION MATRIX<br />

Narender Kumar a* and Vineet Jain b<br />

a Department <strong>of</strong> Mechanical Engineering, Dronacharya College <strong>of</strong> Engineering Farukh Nagar, Gurgaon<br />

Email: narenderiitd@gmail.com<br />

b Department <strong>of</strong> Mechanical Engineering, Deep institute <strong>of</strong> engineering and <strong>Technology</strong>, Gurgaon,<br />

Email: vjdj<strong>20</strong>04@gmail.com<br />

ABSTRACT<br />

Evaluation phase aims at development <strong>of</strong> value alternatives which is accomplished by careful appraisal and<br />

creative judgment to the ideas which were listed during creativity phase. During the process <strong>of</strong> development, we<br />

should ensure that the product is not cheapened or degrade i.e. there is no reduction in product quality,<br />

performance, reliability, maintainability or other aspects below the requirements <strong>of</strong> customer. In this technique,<br />

decision matrix method is used to find out the performance score for different alternatives and then value score<br />

with the help <strong>of</strong> the cost <strong>of</strong> the alternatives. This comparison will give the team best workable solution for the<br />

problem at lowest cost without degrading the quality or value or the product.<br />

1. INTRODUCTION<br />

The evaluation <strong>of</strong> alternatives can be done on multiplicity <strong>of</strong> attributes- both tangible and intangible. The<br />

decision matrix approach is very effective way <strong>of</strong> multi-criteria evaluation and to find the ranking <strong>of</strong> the<br />

proposals. The attributes / factors for each assembly / component are given in their respective functional<br />

worksheets.<br />

In this technique, decision matrix method is used to find out the performance score for different alternatives and<br />

then value score with the help <strong>of</strong> the cost <strong>of</strong> the alternatives. This comparison will give the team best workable<br />

solution for the problem at lowest cost without degrading the quality or value or the product.<br />

In this first decision matrix for attributes is made by paired comparison <strong>of</strong> attributes. To decide the importance<br />

<strong>of</strong> a function following weight factor are considered and allotted to the function depending on the difference<br />

between them as explained in function phase previously. Once the attributes and their weights have been<br />

established, the next task is to use them in evaluating the alternatives selected from the feasibility ranking and<br />

comparison technique. At this point, it is assumed that all ideas that have survived i.e. accepted meet all minimal<br />

basic functions <strong>of</strong> the user.<br />

The criteria elements are entered on the top <strong>of</strong> the evaluation matrix their weight <strong>of</strong> importance just below. The<br />

following steps are used to rank the alternatives:<br />

(i) Find the percentage weights <strong>of</strong> the relevant attributes for each function by paired comparison.<br />

(ii) Rank the acceptable alternatives by comparing with each other for each attribute selected in step 1.<br />

(iii) Multiply the ranks <strong>of</strong> each alternative with weight for each attribute calculated in step 2 and subtotal it<br />

as performance score.<br />

(iv) Fine the value score by dividing performance score by cost <strong>of</strong> alternative.<br />

(v) Select the alternative with highest value score as the most optimal solution.<br />

Following the above procedure the evaluation worksheet for all poor value functions is made and given below as<br />

decision matrix. Attribute used in decision matrix are given by the following alphabets:<br />

A = Ease <strong>of</strong> implementation E = Safety<br />

B = Ease <strong>of</strong> maintenance F= Reliability<br />

C = Ease <strong>of</strong> operation<br />

G = Productionisation<br />

D = Endurance (Life)<br />

H = Ruggedness<br />

Functional development worksheets have only one acceptable alternative and these alternatives have direct cost<br />

saving besides the following advantages:<br />

(i) Simple design<br />

(ii) Ease <strong>of</strong> maintenance<br />

(iii) Spares readily available<br />

(iv) Life <strong>of</strong> the component is as good as the existing<br />

787


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

DECISION MATRIX 1<br />

Function: Joint parts<br />

ATTRIBUTES:<br />

A = Ease <strong>of</strong> Implementation<br />

B = Ease <strong>of</strong> Maintenance<br />

C = Ease <strong>of</strong> operation<br />

F = Reliability<br />

B C F Total Weight Adjusted Weight % Weight<br />

A B2 C2 F1 0 1 8.33<br />

B C1 B1 3 4 33.33<br />

C C1 4 5 41.67<br />

F 1 2 16.67<br />

8 12 100<br />

ALTERNATIVES<br />

Existing<br />

Use plastic Spacer<br />

Use L- Bkt.<br />

a<br />

b<br />

c<br />

Attribute ‘A’ “Ease <strong>of</strong> Implementation”<br />

b c TS Adj TS<br />

a a a 2 3<br />

b b 1 2<br />

c 0 1<br />

Attribute ‘B’ “Ease <strong>of</strong> Maintenance”<br />

b c TS Adj TS<br />

a<br />

a c 1 2<br />

b c 0 1<br />

c 1 2<br />

788


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Attribute ‘C’ “Ease <strong>of</strong> Operation”<br />

b c TS Adj TS<br />

a<br />

a a 2 3<br />

b b 1 2<br />

c 0 1<br />

Attribute ‘F’ “Reliability”<br />

b c TS Adj TS<br />

a a a 2 3<br />

b c 0 1<br />

c 1<br />

2<br />

Attributes<br />

A B C F Performance<br />

Value<br />

Alternatives<br />

Score<br />

Cost<br />

Score<br />

%Wt 8.33 33.33 41.67 16.67<br />

a (Existing) 8.33х3 33.33х2 41.67х3 16.67х3 141.66 55 2.57<br />

B 8.33 х2 33.33 х1 41.67 х2 16.67 х1 150 35 4.28<br />

C 8.33 х1 33.33 х2 41.67 х1 16.67 х2 116.66 48 2.43<br />

RANKING FOR ALTERNATIVES PROPOSED<br />

From the above ranking <strong>of</strong> alternatives <strong>of</strong> various creative ideas, alternative ‘b’ “Use plastic spacers” is<br />

having maximum value score 4.28 hence, it is selected as best design option.<br />

DECISION MATRIX 2<br />

Function: Provide support & facilitate maintenance<br />

ATTRIBUTES<br />

A = Ease <strong>of</strong> Implementation<br />

B = Ease <strong>of</strong> Maintenance<br />

E = Safety<br />

F = Reliability<br />

789


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

B E F Total Weight Adjusted Weight % Weight<br />

A B2 E2 F3 0 1 7.14<br />

B B1 F1 3 4 28.57<br />

E F1 2 3 21.43<br />

F 5 6 42.86<br />

8 14 100<br />

ALTERNATIVES<br />

Existing<br />

Use plastic mesh wire<br />

Reduce the length <strong>of</strong> welding structure<br />

Use only one lock for both doors<br />

a<br />

b<br />

c<br />

d<br />

Attribute ‘A’ “Ease <strong>of</strong> Implementation”<br />

b c d TS Adj TS<br />

a a a d 2 3<br />

b b d 1 2<br />

c d 0 1<br />

d 3 4<br />

Attribute ‘B’ “Ease <strong>of</strong> Maintenance”<br />

b c d TS Adj TS<br />

a a a a 3 4<br />

b b d 1 2<br />

c d 0 1<br />

d 2 3<br />

790


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Attribute ‘E’ “Safety”<br />

b c d TS Adj TS<br />

a a c a 2 3<br />

b c d 0 1<br />

c d 2 3<br />

d 2 3<br />

Attribute ‘F’ “Reliability”<br />

b c d TS Adj TS<br />

a b a a 2 3<br />

b b b 3 4<br />

c d 0 1<br />

d 1 2<br />

Attributes<br />

A B E F Performance<br />

Value<br />

Alternatives<br />

Score<br />

Cost<br />

Score<br />

%Wt 7.14 28.57 21.43 42.86<br />

a (Existing) 7.14х3 28.57х4 21.43х3 42.86х3 328.57 750 0.43<br />

B 7.14 х2 28.57 х2 21.43 х1 42.86 х4 264.29 225 1.17<br />

C 7.14 х1 28.57 х1 21.43 х3 42.86 х1 142.86 1<strong>20</strong> 1.<strong>19</strong><br />

D 7.14 х4 28.57 х3 21.43 х3 42.86 х2 264.28 130 2.03<br />

791


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

RANKING FOR ALTERNATIVES PROPOSED<br />

From the above ranking <strong>of</strong> alternatives <strong>of</strong> various creative ideas, alternative ‘d’ “Use only one lock for both<br />

doors” is having maximum value score 2.03 hence, it is selected as best design option.<br />

DECISION MATRIX 3<br />

Function: Provide cooling<br />

ATTRIBUTES<br />

A = Ease <strong>of</strong> Implementation<br />

B = Ease <strong>of</strong> Maintenance<br />

F = Reliability<br />

E = Safety<br />

B F E Total Weight Adjusted Weight % Weight<br />

A B3 A2 E1 3 4 30.76<br />

B E1 B1 4 5 38.46<br />

F A1 0 1 7.69<br />

E 2 3 23.07<br />

9 13 100<br />

ALTERNATIVES<br />

Existing<br />

Use one fan<br />

Eliminate fan tray<br />

Change the design <strong>of</strong> louver panel<br />

a<br />

b<br />

c<br />

d<br />

Attribute ‘A’ “Ease <strong>of</strong> Implementation”<br />

b c d TS Adj TS<br />

a a a a 3 4<br />

b b b 2 3<br />

c c 1 2<br />

d 0 1<br />

792


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Attribute ‘B’ “Ease <strong>of</strong> Maintenance”<br />

b c d TS Adj TS<br />

a a a a 3 4<br />

b b c 1 2<br />

c c 2 3<br />

d 0 1<br />

Attribute ‘F’ “Reliability”<br />

b c d TS Adj TS<br />

a b c d 0 1<br />

b b c 2 3<br />

c d 3 2<br />

d 2 3<br />

Attribute ‘E’ “Safety”<br />

b c d TS Adj TS<br />

a a a d 2 3<br />

b c d 0 1<br />

c c 2 3<br />

d 2 3<br />

793


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Attributes<br />

A B F E Performance<br />

Value<br />

Alternatives<br />

Score<br />

Cost<br />

Score<br />

%Wt 30.76 38.46 7.69 23.07<br />

a (Existing) 30.76х4 38.46х4 7.69х1 23.07х3 353.78 1<strong>20</strong>0 0.29<br />

b 30.76х3 38.46х2 7.69х3 23.07х1 215.34 390 0.55<br />

c 30.76х2 38.46х3 7.69х2 23.07х3 261.49 470 0.56<br />

d 30.76х1 38.46х1 7.69х3 23.07х3 161.50 270 0.60<br />

RANKING FOR ALTERNATIVES PROPOSED<br />

From the above ranking <strong>of</strong> alternatives <strong>of</strong> various creative ideas, alternative ‘c’ “Eliminate fantray” is having<br />

maximum value score 0.60 hence, it is selected as best design option.<br />

References<br />

1. Cooper R, Slagmulder R. (<strong>19</strong>97), “Target costing and value engineering” Portland, OR Productivity<br />

Press.<br />

2. D. Hannan. (<strong>20</strong>00), “Value methodology, creative problem solving strategies and TRIZ”, Engineering<br />

International Conference, SAVE International.<br />

3. Ghosh P. “Function Heart <strong>of</strong> value Engineering” proceeding, the international conference on value<br />

engineering in Nineties<br />

4. Mudge A.E.( <strong>19</strong>71),”Value Analysis a systematic Approach”, Mc-Graw hill<br />

5. Jay Mandelbaum and Danny L.Read <strong>20</strong>06, “Value engineering Handbook”,<br />

6. Miles L.D. (<strong>19</strong>72), “Techniques <strong>of</strong> Value Analysis and Engineering”, Mc-Graw Hill, New York.<br />

7. Gupta A.D. (<strong>19</strong>91), “LCC- a System Approach”, Proceedings international conference on Value<br />

Engineering in the Nineties<br />

8. Chari K.R. (<strong>19</strong>93), “Value Engineering-An introduction to concept and Applications, N.P.C new Delhi<br />

9. INVEST, Value Engineering Guide”, Eastern Zonal Chapter, Jamshedpur<br />

10. Miles L.D. (<strong>19</strong>62), “Reducing cost through Value Engineering and Analysis Techniques”.<br />

794


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

LEAN MANUFACTURING STRATEGY –A REMEDY FOR TOUGH<br />

TIMES<br />

Naveen Kumar 1 and S.K Sharma 2<br />

1<br />

Assistant Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, Faculty <strong>of</strong> Engineering and <strong>Technology</strong>,Manav<br />

Rachna International <strong>University</strong>,Faridabad, India<br />

2 Pr<strong>of</strong>essor in Department <strong>of</strong> Mechanical Engineering, NIT, Kurukshetra<br />

Email:goelnavin_07@yahoo.co.in<br />

Abstract<br />

Lean is a management methodology that provides the perfect medicine for surviving and thriving during bleak<br />

trading conditions as well as optimizing shrunken budgets. Japan in <strong>19</strong>50s.in a country rebuilding its shattered post<br />

war economy, the Toyota motor company developed a production system that has underpinned the company’s<br />

success and given rise to the lean movement. Toyota production system rejected the belief that productivity could be<br />

raised by working longer, harder and faster and presented the just in time alternative. This focused on delivery the<br />

right products to the right place at the right time anything not involved in achieving that objective was deemed<br />

suspect waste.<br />

The purpose <strong>of</strong> this paper is to discuss a survival strategy for industry in tough time by means <strong>of</strong> lean principles and<br />

philosophies. Tough time is the time for industries to follow lean guidelines and to look in to their business chain<br />

from raw material to end customer in order to remove all types <strong>of</strong> waste. The paper provides some real help as to<br />

how to survive in recession as there is little published research on this topic. This paper addresses a framework for<br />

studying lean thinking, as well as principles <strong>of</strong> lean production, strategy for lean implementation and the 8 types <strong>of</strong><br />

waste.<br />

Keywords: Lean thinking, waste, customer focus.<br />

Introduction<br />

Lean is defined as "a strategy for achieving significant continuous improvement in performance through the<br />

elimination <strong>of</strong> all wastes <strong>of</strong> resources and time in the total business process .It evolved from Toyota after world war<br />

2nd as a business strategy due to the limited resources available in Japan, in contrast to the vast resources available to<br />

manufacturers in the united state. Its principles apply to nearly all business operations, from administration and<br />

product design to hardware production. Lean manufacturing focuses on eliminating all sources <strong>of</strong> waste(Examples <strong>of</strong><br />

waste in manufacturing include overproduction, over processing, waiting, unnecessary part movement, excess<br />

inventory and defects) by applying the following strategies. (1) One piece workflow, (2) Takt time, (3) Pull system.<br />

Lean identifies bottlenecks in design and development processes that add unnecessary delays and cost. It can help to<br />

create a more efficient system that reduces time to market without compromising on quality.<br />

Lean has a key role to play in new product development and the improvement <strong>of</strong> existing products, including idea<br />

creation, design for manufacture, assembly and test, rapid prototyping, product portfolio management, market and<br />

competitor analysis, risk management, sales forecasting, setting key performance indicators, and value analysis to<br />

reduce the cost <strong>of</strong> existing products.<br />

The concept <strong>of</strong> ‘LM’ is derived from the methods developed at the shop floor <strong>of</strong> Toyota, which are described in<br />

detail by authors like Taiichi Ohno and Shigeo Shingo. But, these concepts in the form <strong>of</strong> lean manufacturing system<br />

(LMS) got an international recognition, as a result <strong>of</strong> the book, ‘The Machine that changed the world’, written by the<br />

researchers (Womack and Jones, <strong>19</strong>90). According to Womack Jones, and Roos, lean manufacturing uses less <strong>of</strong><br />

everything compared to mass production- half the human effort in the factory, half the manufacturing space, half the<br />

investment in tools, and half the engineering hours to develop a new product. In addition, it requires keeping far less<br />

than half <strong>of</strong> the needed inventory on site, results in many fewer defects, and produces a greater and ever-growing<br />

variety <strong>of</strong> products. In short, it is called lean because it uses less, or the minimum, <strong>of</strong> everything required to produce<br />

a product or perform a service. (Singh and Sharma <strong>20</strong>09) discussed many benefits <strong>of</strong> lean manufacturing to Indian<br />

industry. (Singh et al <strong>20</strong>09) discussed the survival strategy for recessionary times by means <strong>of</strong> lean principles and<br />

795


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

philosophies. (Singh et al <strong>20</strong>10) developed leanness index by using fuzzy triangular function for measuring leanness<br />

<strong>of</strong> manufacturing industry. Womack and Jones describe lean thinking as “the antinodes” to muda, which is the<br />

Japanese word for waste and specifically “any human activity that absorbs resources but creates no value” (Womack<br />

and Jones, <strong>19</strong>96).<br />

Principles behind the lean thinking :<br />

• Customer focus: make sure that all the activities <strong>of</strong> the organization are driven by the customer needs and<br />

expectation.<br />

• Eliminate waste with the goal <strong>of</strong> creating value: elimination <strong>of</strong> waste throughout the value chain. I.e. those<br />

activities which does not add any value to goods or services in the eye <strong>of</strong> customers or for which the<br />

customer is not willing to pay.<br />

• Pursue knowledge driven enterprise transformation: utilize the ideas and skills <strong>of</strong> everyone in the<br />

organization to implement systemic changes.<br />

• Foster a dynamic process <strong>of</strong> change and capability building: pursue a proactive, relentless, process <strong>of</strong><br />

ongoing change and capability building to ensure the sustained competitive advantage. Table 1 gives the<br />

comparison <strong>of</strong> lean vs. traditional manufacturing<br />

The five steps involved in lean thinking:<br />

STEP1: Specifying value:- Womack and Jones state that value can only be defined by the ultimate consumer and is<br />

only meaningful when expressed in terms <strong>of</strong> a specific product with specific capabilities which meets the customer’s<br />

needs at a specific price at a specific time. The problem is that while value is defined by the consumer, it is created<br />

by the producer and many things get in the way when producers try to express how they provide value.<br />

STEP 2: Identifying the value stream: - value stream is defined as “all the specific actions required to bring a<br />

specific product (whether a good, a service) Identify all the steps across the whole value stream, tracing the<br />

sequence <strong>of</strong> processes from raw materials to finished goods that deliver customer value.<br />

STEP 3: Creating flow: - Make sure those steps flow better ensures actions, which create value flow properly and<br />

eliminate delays and interruption to create a smooth process.<br />

STEP 4: The concept <strong>of</strong> pull: - Pull in simplest terms means that no one upstream should produce a good or service<br />

until the customer downstream asks for it.” Because <strong>of</strong> its responsiveness, this form <strong>of</strong> small –lot, even single item,<br />

production means that the plant only makes what is ordered when it is ordered.<br />

Instead <strong>of</strong> pushing completed products at customers, customer orders pull newly produced products through the<br />

plant. The result is no finished stock inventory, no complex tracking system and no need to remainder unwanted<br />

goods.<br />

STEP 5: The hunt for perfection: - Strive for perfection by continually removing successive layers <strong>of</strong> waste, which is<br />

defined as anything that does not add value to a product <strong>of</strong> service.<br />

Lean manufacturing principles include:<br />

• Pull processing: products are pulled from the consumer end (demand), not pushed from the production end<br />

(Supply)<br />

• Perfect first-time quality: quest for zero defects, revealing & solving problems at the source.<br />

• Waste minimization: eliminating all activities that do not add value & safety nets, maximize use <strong>of</strong> scarce<br />

resources (capital, people and land)<br />

• Continuous improvement: reducing costs, improving quality, increasing productivity and information<br />

sharing.<br />

• Flexibility: producing different mixes or greater diversity <strong>of</strong> products quickly, without sacrificing efficiency<br />

at lower volumes <strong>of</strong> production.<br />

• Building and maintaining a long-term relationship with suppliers through collaborative risk sharing, cost<br />

sharing and information sharing arrangements<br />

To implement lean manufacturing five primary elements need to be worked upon:<br />

• Manufacturing flow: concerns with the uninterrupted flow <strong>of</strong> material from the store through to value<br />

addition processes to the shipping.<br />

796


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

• Organization: deals with people’s roles and responsibility and to train them in new ways <strong>of</strong> thinking,<br />

working and communication.<br />

• Process controls: concerns with all that is required to monitor, control and improve discrete manufacturing<br />

process steps.<br />

• Metrics: it is the criteria to judge the success <strong>of</strong> lean manufacturing implementation, it establishes visible,<br />

results-based performance measures, determining targets for improvement and recognizing work teams for<br />

process improvements.<br />

• Logistics: it is the backbone <strong>of</strong> lean manufacturing. In case <strong>of</strong> working with minimum level <strong>of</strong> raw materials<br />

inventory, it becomes very important to ensure on time, correct, flexible and good quality supplies. The<br />

relations between supplier and customer take a very leading role. So, logistics concerns with the systems<br />

and mechanisms to ensure good supplies. It defines operating rules and mechanisms for the flow <strong>of</strong><br />

material.<br />

Importance <strong>of</strong> Lean Manufacturing Strategy:<br />

Sometimes companies cannot manage the competition and are forced to lower the charges and lose pr<strong>of</strong>it. While<br />

doing this, they might also lose clients so sometimes the strategies applied only lead to disaster. The most beneficial<br />

thing companies should do when they have problems in implementing lean manufacturing. The lean manufacturing<br />

strategy proved to be one <strong>of</strong> the greatest advantages when it comes to changing company's strategy. It is one <strong>of</strong> the<br />

most effective ways to decrease costs and increase pr<strong>of</strong>it on long term. Its philosophy is called "elimination <strong>of</strong> seven<br />

wastes.<br />

Business as usual<br />

Lean business<br />

Price - Cost = Pr<strong>of</strong>it<br />

Cost+ Pr<strong>of</strong>it = Price<br />

Strategies <strong>of</strong> Implementation <strong>of</strong> Lean Manufacturing:<br />

a) Senior Management Involvement -As for any significant process improvement project, the total commitment and<br />

support <strong>of</strong> the most senior management is essential for implementation <strong>of</strong> lean manufacturing. Problems will almost<br />

certainly arise during the implementation <strong>of</strong> lean production systems and those problems will likely only be solved if<br />

the senior management is fully committed to the successful implementation <strong>of</strong> lean.<br />

b) Start with a Partial Implementation <strong>of</strong> Lean - Some companies may initially implement only some <strong>of</strong> lean<br />

manufacturing and gradually shift towards a more complete implementation. In a <strong>20</strong>04, a survey <strong>of</strong> manufacturing<br />

companies in the U.S. by Industry Week Magazine, among companies which had commenced lean manufacturing<br />

programs, 39.1%reported implementing some aspects <strong>of</strong> lean, 55.0% reported implementing most aspects <strong>of</strong> lean and<br />

only 5.9% reported complete implementation <strong>of</strong> lean.<br />

Some simple first steps may include:<br />

• Measuring and monitoring machine capacity and output.<br />

• Creating more clearly defined production procedures.<br />

• Implementing the 5S system for shop floor housekeeping.<br />

• Streamlining the production layout.<br />

797


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

c) Start small - It is recommended that companies try to implement lean as a test case at a small part <strong>of</strong> their operations<br />

before applying it through their entire operations, especially for the shift from a push-based to a pull based system<br />

since this can potentially be disruptive. For example, the test case may be a single production line or a small series <strong>of</strong><br />

processes. This will help to minimize the risk <strong>of</strong> disruption, help educate the staff on the principles <strong>of</strong> lean while also<br />

serving to convince others <strong>of</strong> the benefits <strong>of</strong> lean.<br />

d) Use an Expert - It is recommended that for most private companies, it would be the best to use the services <strong>of</strong> a lean<br />

manufacturing expert to help them implement lean manufacturing systems. In particular, the shift from a push-based to<br />

a pull-based production system can potentially be quite disruptive so it is best to be guided by someone who has<br />

significant experience in this.<br />

e) Develop a Plan - The Company should develop a detailed and clear implementation plan before proceeding with the<br />

conversion to lean manufacturing. A list <strong>of</strong> issues to cover in the implementation plan can be downloaded from the<br />

article Building the Lean Machine from the September <strong>20</strong>00 issue <strong>of</strong> Advanced Manufacturing Magazine.<br />

f) Change Management-Lean Manufacturing is not implemented in a static corporate environment, but it is deployed in<br />

organizations under a change process imposed by the dynamic business landscape. In fact, Lean implementations could<br />

easily be limited to short-lived events interrupted in the short-term, if these implementations would not be organically<br />

aligned to the organizational change process phases. Based on empirical research in more than hundred companies<br />

along ten years, John Kotter, a Harvard researcher, identified the main phases necessary for an effective change process<br />

in the companies (Kotter, <strong>19</strong>96):The first change management phase consists <strong>of</strong> creating a ‘sense <strong>of</strong> urgency’ in the<br />

organization to motivate the change. For this purpose, it is necessary to analyze the current competitive position <strong>of</strong> the<br />

company and the technological trends, in order to confront this information with the actual performance <strong>of</strong> the<br />

organization.<br />

In the second phase, the successful companies in the change process created an integrated group <strong>of</strong> leaders<br />

committed to really improve the performance <strong>of</strong> the company.<br />

The third phase aims to define a clearly stated vision, an image <strong>of</strong> the desired future easily communicable to the<br />

company employees and investors, so that all involved understand which the company’s future trajectory is.<br />

In the fourth phase, the companies that successfully managed the change also communicated their vision effectively.<br />

This communication must be both broad and without contradictions. It is a broad communication, because it utilizes<br />

multiple complementary communication channels and non-contradictory, because it is also expressed in the behavior<br />

<strong>of</strong> the company leaders.<br />

In addition, in the fifth phase, the company identifies and removes the organizational obstacles blocking the<br />

implementation <strong>of</strong> the vision. The leaders gain the required credibility to obtain the commitment <strong>of</strong> the organization<br />

by demonstrating that they have effectively removed the main obstacles.<br />

In the sixth phase, the change process becomes tangible, due to the systematical planning and execution <strong>of</strong> actions<br />

for short-term results, in order to clearly show to the organization that, although the desired change requires a long<br />

and difficult trajectory, it is possible to obtain early improvements. Thus, the successful change process proves its<br />

legitimacy with fast results in indicators as, for example, productivity, market share, pr<strong>of</strong>itability or new products<br />

launching.<br />

In the seventh phase, the company searches for bigger goals to ensure that the performance remains improving<br />

beyond the achievement <strong>of</strong> short-term goals. By doing so, the organization does not interrupt the commitment with<br />

the new organizational systems, due to the false perception <strong>of</strong> having already reached the victory.<br />

Finally, in the eighth phase the organization incorporates the achieved changes into its culture, into the company’s<br />

dominant work stile. For this purpose, it is necessary to make evident that the achieved results are an effect <strong>of</strong> the<br />

undertaken changes and it is also necessary to show that the company leaders adopt entirely the new work approach<br />

resulting from the change process.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Lean Manufacturing Implementations:<br />

In general, the success <strong>of</strong> implementation <strong>of</strong> any particular management practice frequently depends upon<br />

organizational characteristics, and not all organization can or should implement the same set <strong>of</strong> practice. It describes<br />

three organizational context characteristics-unionization, plant age and plant size that may influence the<br />

implementation <strong>of</strong> manufacturing practices. A limited number <strong>of</strong> empirical studies suggest that implementation or<br />

adoption <strong>of</strong> a manufacturing practice is contingent upon specific organizational characteristic [Shah and Ward, (<strong>20</strong>03)].<br />

Lean Manufacturing (Womack and Jones, <strong>19</strong>96; Womack et al., <strong>19</strong>90) is an integrated system <strong>of</strong> multiple<br />

management practices, including just in time, quality controls, work teams, cellular manufacturing, supplier<br />

management (Shah and Ward, <strong>20</strong>02) and the Value Stream Map (Rother and Shook, <strong>19</strong>99).The success <strong>of</strong><br />

implementing Lean Manufacturing tools may depend on contextual issues as unionization and firm size. Based on a<br />

sample <strong>of</strong> 1748 Lean Implementations in USA, Shah and Ward (<strong>20</strong>03) found that unionized plants are less likely to<br />

implement Lean practices as cellular manufacturing, cross-functional work-force, cycle time reduction, maintenance<br />

optimization, process capability measurements, and self-directed work teams. In the other hand, the researchers also<br />

identified that large plants are likely to implement twenty Lean practices more extensively compared to small plants.<br />

Lean Manufacturing was created in the automobile sector. The manufacturing type is also an important driver for<br />

Lean adoption. Implementations <strong>of</strong> Lean Manufacturing have been less frequent in the process sector, due to the<br />

perception that the Lean techniques may not be applicable in process manufacturing. Abdulmalek and Rajgopal<br />

(<strong>20</strong>07) found that, in the steel industry the cellular manufacturing is probably not applicable, while setup reduction,<br />

just-in-time, production leveling and total productive maintenance are partially adapted for process manufactures.<br />

Moreover, 5S, value stream mapping, and visual systems are universally applicable.<br />

Another relevant factor influencing Lean Manufacturing deployments is the mix <strong>of</strong> Lean techniques that are<br />

implemented. A recent empirical research by Shah and Ward (<strong>20</strong>07) concluded that it is the complementary and<br />

synergistic effects <strong>of</strong> ten different inter-related elements <strong>of</strong> Lean Manufacturing that provides its ability to obtain<br />

multiple performance goals. This research identified that the main elements <strong>of</strong> sound Lean Manufacturing<br />

implementations are: supplier feedback, JIT delivery by suppliers, supplier development, customer involvement,<br />

pull, continuous flow, set up time reduction, total productive/preventive maintenance, statistical process control and<br />

employee involvement<br />

Conclusion:<br />

Lean manufacturing is discussed in detail including its principles, tools and technique, benefits to any industry and<br />

its scope. After going through all the facets <strong>of</strong> lean manufacturing in this paper, it has been concluded that lean<br />

manufacturing is a versatile strategy for identification and elimination <strong>of</strong> various types <strong>of</strong> industrial waste. It focuses<br />

on productivity improvement by reducing all types <strong>of</strong> non-value added activities. Further, after going through all the<br />

benefits <strong>of</strong> lean, it is understood that there is lot <strong>of</strong> scope for lean implementation in Indian industry.<br />

References:<br />

Abdulmalek FA, Rajgopal J (<strong>20</strong>07) analyzing the benefits <strong>of</strong> lean manufacturing and value stream mapping via<br />

simulation: a process sector case study. Int J Prod Econ 107(1):223–236 doi:10.1016/j.ijpe.<strong>20</strong>06.09.009<br />

B, Singh and S.K, Sharma, “Value stream mapping a versatile tool for lean implementation: an Indian case study <strong>of</strong> a<br />

manufacturing industry”, Journal <strong>of</strong> Measuring Business Excellence, Vol 13 No. 3, pp. 58-68, <strong>20</strong>09.<br />

B, Singh, S K, Garg, and S.K, Sharma, “Lean can be a survival strategy during recessionary times”, International<br />

Journal <strong>of</strong> Productivity and Performance Measurement, Vol. 58 No. 8, pp. 803-808, <strong>20</strong>09.<br />

B, Singh, S K, Garg, and S.K, Sharma, “Development <strong>of</strong> leanness index to measure leanness: a Case <strong>of</strong> an Indian<br />

auto component industry”, Journal <strong>of</strong> Measuring Business Excellence, Vol. 14 No. 2. Pp 46-53, <strong>20</strong>10.<br />

J.P Womack, D.T., Jones and D Roos, “The Machine That Changed The World: The Story <strong>of</strong> Lean Production”<br />

(Harper Collins Publishers, New York, USA), <strong>19</strong>90.<br />

J.P Womack, D.T., Jones, “Lean Thinking: Banish Waste and Create Wealth in Your Corporation (Simon &<br />

Schustes”, New York, USA), <strong>19</strong>96.<br />

Kotter, J. P. (<strong>19</strong>96). Leading Change. New York: Harvard Business School Press. 187.<br />

Rother M, Shook J (<strong>19</strong>99) learning to see: value stream mapping to add value and eliminate MUDA. The Lean<br />

Enterprise Institute, Brookline, MA<br />

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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Shah, R. and Ward, P. T. (<strong>20</strong>07), “Lean manufacturing: Context, practice bundles, and performance”, Journal <strong>of</strong><br />

operations management, 21 pp.129-149.<br />

Shah, R. and Ward, P. T. (<strong>20</strong>03), “Lean manufacturing: context, practice bundles, and performance”, Journal <strong>of</strong><br />

operation management 21, pp.129-149.<br />

Womack JP, Jones DT (<strong>19</strong>96) Lean thinking: banish waste and create wealth in your corporation. Simon & Schuster,<br />

New York<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

ENABLERS OF TECHNOLOGY MANAGEMENT: AN ISM<br />

APPROACH<br />

Sarvesh Kumar, Javed Khan, Abid Haleem<br />

Mechanical Engineering Department, Jamia Millia Islamia, New Delhi 110025, India<br />

e-mail: sarvesh0045@gmail.com<br />

Abstract<br />

The management <strong>of</strong> technology is acquiring a distinctive character and increasingly being recognized as an<br />

activity that complements other managerial functions in providing the necessary inputs to the decision-making<br />

process. Few factors which are helpers in the implementation <strong>of</strong> technology management which are known as<br />

enablers. The objective <strong>of</strong> this paper is to developed the relationships among the identified TM enablers. Further,<br />

this paper is also helpful to understand mutual influence <strong>of</strong> enablers and identify those enablers which support<br />

other enablers (driving enabler) and also those enablers which are most influenced by other enablers(dependent<br />

enabler ). The interpretive structure modeling (ISM) methodology is used to evolve mutual relationship among<br />

these enablers. TM enablers have been classified, based on their driving power and dependence power.<br />

Keywords:<strong>Technology</strong> Management (TM), Enablers, dependence power, driving power, Interpretive Structural<br />

Modelling (ISM).<br />

1- Introduction<br />

<strong>Technology</strong> management is a process, which includes planning, directing, control and coordination <strong>of</strong> the<br />

development and implementation <strong>of</strong> technological capabilities to shape and accomplish the strategic and<br />

operational objectives <strong>of</strong> an organization (Task Force on Management <strong>of</strong> <strong>Technology</strong>, <strong>19</strong>87). On the other hand,<br />

technology management includes: (1) planning for the development <strong>of</strong> technology capabilities; (2) identifying<br />

key technology and its related fields for development; (3) determining whether ‘to buy’ or ‘to make’, i.e.<br />

whether importation or self-development should be pursued; and (4) establishing institutional mechanisms for<br />

directing and coordinating the development <strong>of</strong> technology capabilities, and the design <strong>of</strong> policy measures for<br />

controls (Wang, <strong>19</strong>93). <strong>Technology</strong> management is the capacity <strong>of</strong> a firm, a group or a society to master the<br />

management <strong>of</strong> the factors that condition technical change with the purpose <strong>of</strong> improving its economic, social<br />

and cultural environment and increasing its wealth quotient.The overall process <strong>of</strong> technology management can<br />

be divided into the following eight phases (Khamba, Singh and Sushil, <strong>20</strong>01):<br />

• Forecasting and Assessment<br />

• Planning and Strategy<br />

• Acquisition and Development<br />

• Transfer<br />

• Adoption and Adaptation<br />

• Diffusion and Substitution<br />

• Utilization<br />

• Phasing – out.<br />

The aim <strong>of</strong> this paper is to develop the relationships among the identified enablers using interpretive structural<br />

modeling (ISM) and classify theses enablers depending upon their driving and dependence power. ISM is a well<br />

established methodology for identifying relationships among specific items which define a problem or an<br />

issue(A. Sage,<strong>19</strong>77, J. Warfield.,<strong>20</strong>05). The opinions from group <strong>of</strong> experts are used in developing the<br />

relationship matrix, which was later used in the development <strong>of</strong> the ISM model. These enablers are derived<br />

theoretically from various literature sources, and experts’ discussion (See Tab. 1).<br />

Table 1. <strong>Technology</strong> Management Enablers<br />

Enablers Number Enablers Description References<br />

1 <strong>Technology</strong> recipient characteristic<br />

( Absorptive Capacity , Recipient<br />

Collaborativeness )<br />

Cohen & Levinthal ,<strong>19</strong>90;Hamel,<strong>19</strong>91;Lyles&Salk,<strong>19</strong>96; Mowery et<br />

al., <strong>19</strong>96; Lane & Lubatkin, <strong>19</strong>98; Lane et al., <strong>20</strong>01 ; Gupta &<br />

Govindarajan,<strong>20</strong>00,Minbaeva et al.,<strong>20</strong>03;Minbaeva, <strong>20</strong>07;Pak<br />

&Park,<strong>20</strong>04 ;Yin& Bao,<strong>20</strong>06; Raduan Che Rose, Jegak Uli, Naresh<br />

Kumar, Sazali Abdul Wahab, <strong>20</strong>09; Escribano et al., <strong>20</strong>09;<br />

Keller,<strong>20</strong>02; Madanmohan et al.<strong>20</strong>04; Griffith et al. <strong>20</strong>04; Santangelo,<br />

<strong>20</strong>00; Levinson and Asahi, <strong>19</strong>95; Sushil,<strong>20</strong>01; Child & Faulkner,<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

<strong>19</strong>98; Inkpen, <strong>20</strong>00; Child &Faulkner, <strong>20</strong>06;<br />

2 <strong>Technology</strong> supplier characteristics<br />

( motivation ,partner transparency<br />

Disseminative capacity ,control, prior<br />

experience ,transferor’s commitment<br />

,articulated objective Source transfer<br />

capacity )<br />

3 Relationship characteristic<br />

(Relationship Quality and Mutual trust )<br />

Gupta & Govindranjan ,<strong>20</strong>00;Szulanski,<strong>19</strong>96, Simonin,<br />

<strong>19</strong>99a<strong>19</strong>99b,<strong>20</strong>04; Szulanski,<strong>19</strong>96, Inkpen,<strong>19</strong>98,<strong>20</strong>00, Lyles et al<br />

.,<strong>19</strong>99,Hamel ,<strong>19</strong>91,Minbaeva & Michailova,<strong>20</strong>04, Lyles et al .,<strong>20</strong>03<br />

Subramanian & Venkataraman ,<strong>20</strong>01Tsang et al.,<strong>20</strong>04 ,Lyles<br />

&Salk,<strong>19</strong>96;Inkpen <strong>20</strong>00,Szulanski, <strong>19</strong>96;Martin& Solomon,<strong>20</strong>03.<br />

Raduan Che Rose, Jegak Uli, Naresh Kumar, Sazali Abdul Wahab,<br />

<strong>20</strong>09;Doz&Hamel,<strong>19</strong>98. Child & Faulkner <strong>19</strong>98; Gupta, <strong>19</strong>87; Child&<br />

Fulkner,<strong>19</strong>98; Steensma&Lyles, <strong>20</strong>00; Dyer& Sing,<strong>19</strong>98.<br />

Raduan Che Rose, Jegak Uli, Naresh Kumar, Sazali Abdul Wahab,<br />

<strong>20</strong>09; Inkpen, <strong>19</strong>98a, <strong>20</strong>00, Szulanski, <strong>19</strong>96; Lin, <strong>20</strong>05; Dyer and<br />

Nobeoka, <strong>20</strong>00; Inkpen, <strong>19</strong>98a, <strong>20</strong>00; Inkpen& Dinur,<strong>19</strong>98;Inkpen &<br />

Beamish,<strong>19</strong>97; Inkpen,<strong>20</strong>00;<br />

Hamel,<strong>19</strong>91;Doz&Hamel,<strong>19</strong>98;Inkpen,<strong>20</strong>00; Gulati,<strong>19</strong>95; Glaister et<br />

al.,<strong>20</strong>03; Nahapiet & Ghoshal, <strong>19</strong>98; Kale, Singh & Perlmutter, <strong>20</strong>00;<br />

Steensma & Lyles,<strong>20</strong>00; Child & Faulkner,<strong>19</strong>98; Uzzi,<strong>19</strong>97; Dhanaraj<br />

et al., <strong>20</strong>04; Barney et al (<strong>19</strong>94; Bierly III and Gallagher, <strong>20</strong>07; Parise<br />

and Henderson, <strong>20</strong>01; Doz and Hamel, <strong>19</strong>98; Kauser and Shaw <strong>20</strong>04;<br />

A. Alawi, A. Marzooqi, Y. Mohammed,<strong>20</strong>07.<br />

4 Large and stable demand. Wei, <strong>19</strong>95; Stern, <strong>20</strong>07;Lewis, <strong>20</strong>07; Ockwell et al.,<strong>20</strong>08;Ribeiro and<br />

De Abreu, <strong>20</strong>08; Wang, <strong>20</strong>10; Zhang et al.,<strong>20</strong>09; Ana Pueyo, Rodrigo<br />

Garcia, Maria Mendiluce, Dario Morales, <strong>20</strong>11.<br />

5 Governmental policies and R&D<br />

Investment<br />

Nhan T. Nguyen , Minh Ha-Duong , Thanh C. Tran , Ram M. Shrestha<br />

, Franck Nadaud,<strong>20</strong>10; DIUS, <strong>20</strong>08; Dodgson, <strong>20</strong>00; Knight, <strong>19</strong>96;<br />

Pihkala et al., <strong>20</strong>02; Henry Mwanaki Alinaitwe, Kristian Widén,<br />

Jackson Mwakali and Bengt Hansson, <strong>20</strong>07; Astrid Szogs ,<strong>20</strong>10;<br />

Malik’s <strong>20</strong>02; Madu, <strong>19</strong>89; Santikaran, <strong>19</strong>81; Sushil,<strong>20</strong>01; Crawford,<br />

<strong>19</strong>87 a and b.<br />

6 Technological innovation J.M. Utterback,<strong>19</strong>74; Lundvall <strong>19</strong>92; Mellor <strong>19</strong>99; Dodgson, <strong>20</strong>00;<br />

Freeman and Soete <strong>19</strong>97; Porter, <strong>19</strong>87 Boyer and McDermott, <strong>19</strong>99;<br />

Lundvall et al.,<strong>20</strong>09; Muchie et al., <strong>20</strong>03; UNCTAD <strong>20</strong>07; UNDP,<br />

<strong>20</strong>05; Brundenius et al., <strong>20</strong>09; Chaminade et al., <strong>20</strong>09; Altenburg,<br />

<strong>20</strong>08; ChristianN.Madu,<strong>19</strong>89; Dr. Nimesh Chandra;<strong>20</strong>07; Lundvall et<br />

al., <strong>20</strong>09;Muchie et al., <strong>20</strong>03; Mytelka, <strong>19</strong>93; Ernst and Lundvall,<br />

<strong>19</strong>97; Arocena and Sutz, <strong>19</strong>99; Johnson and Segura-Bonilla, <strong>20</strong>01.<br />

7 Cross cultural training Black and Mendenhall ,<strong>19</strong>90; Julioo. De Castro,Williams.Schuze,<br />

<strong>19</strong>95; Cohen &Levinthal, <strong>19</strong>90; Dr. Richard Li-Hu, <strong>20</strong>10.<br />

3.1 Structural Self-Interaction Matrix (SSIM)<br />

Structural self interaction matrix is developed by the use <strong>of</strong> expert opinions. Pair wise comparison is done among<br />

the factors to know the direction <strong>of</strong> their relationship. Based on the opinion <strong>of</strong> experts Table 2 is developed. Four<br />

symbols are used to denote the direction <strong>of</strong> relationship between the criterion (i and j):<br />

V: criterion i will help to achieve criterion j;<br />

A: criterion i will be achieved by criterion j;<br />

X: criterion i and j will help to achieve each other<br />

O: criterion i and j are unrelated.<br />

Reachability matrix<br />

The SSIM has been converted into a binary matrix, called the reachability matrix by substituting X, A, V and O<br />

by 1 and 0. Then, its transitivity is checked. If factor i leads to factor j and factor j leads to factor k, then factor i<br />

would lead to factor k. By embedding transitivity, a modified reachability matrix is obtained. The situation may<br />

be shown as follows:<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

• if the entry in the SSIM is V, then (i, j) entry in the reachability matrix becomes 1 and the (j,i) entry becomes 0<br />

• if the entry in the SSIM is A, then (i, j) entry in the reachability matrix becomes 0 and the (j,i) entry becomes 1<br />

• if the entry in the SSIM is X, then (i, j) entry in the reachability matrix becomes 1 and the (j,i) entry becomes 1<br />

• if the entry in the SSIM is O, then (i, j) entry in the reachability matrix becomes 0 and the (j,i) entry becomes 0.<br />

Following these rules, an initial reachability matrix for the factors is prepared. This matrix is further iterated into<br />

a final reachability matrix and is shown in Table 3. The final reachability matrix is obtained by incorporating the<br />

transitivity . The transitivity <strong>of</strong> the contextual relation is a basic assumption made in ISM. It states that if an<br />

enabler A is related to B and B is related to C, then A is necessarily related to C. Table 4 shows the final<br />

reachability matrix with the transitivity.<br />

Level Partitioning<br />

Components <strong>of</strong> a structure can be aggregated into levels. A level is itself a set, composed <strong>of</strong> those factors that lie<br />

in the same relative position in a structure. This designation into levels is <strong>of</strong> great assistance when discussing the<br />

relationships in a hierarchy, using the hierarchy itself as a visual aid to the discussion. From the final reachability<br />

matrix (Table 4), the reachability set and antecedent set for each factor has been determined. The reachability set<br />

consisted <strong>of</strong> the factor itself and other factors, which it may help to achieve, whereas the antecedent set consists<br />

<strong>of</strong> the factor itself and the other factors, which may help in achieving it. Subsequently, the intersection <strong>of</strong> these<br />

sets is derived for all the factors. The factor for which the reachability and intersection sets were the same is the<br />

top-level factor in the ISM hierarchy. The top-level factor in the hierarchy would not help achieve any other<br />

factor above its own level. Once the top-level factor is identified, it is separated from the other factors. Then,<br />

with the same process, we find the next level <strong>of</strong> a factor. This process continues till the levels <strong>of</strong> each factor are<br />

identified. These identified levels help in building the digraph and hence the final model. In the present case, the<br />

factors along with their reachability set, antecedent set, intersection set and levels are shown in Tables 5–8. The<br />

process was completed in three iterations.<br />

In table 4, the driving power and dependence <strong>of</strong> each factor are also shown. Driving power for each factor is the<br />

total number <strong>of</strong> factors (including itself), which it may help achieve. On the other hand, dependence is the total<br />

number <strong>of</strong> factors (including itself), which may help in achieving it. An ISM model is thus generated by putting<br />

the factors according to their levels in a directed graph shown in Figure 1.The factors categorised at level I are<br />

put at the lowest hierarchy in the ISM model and the higher level factors are placed at higher hierarchy the<br />

model. The factors at the lowest level in the ISM are the factors with highest driving powers and the factors<br />

which are at the upper level in the ISM model are the factors with low driving power.<br />

From the ISM model it is observed that the factor technology innovation is highly dependent factors and it does<br />

not drive any other factor in the system, instead it is driven by other factors. This factor are totally dependent on<br />

other factors. On the other hand the factors like government policy,technology supplier charactericstic,cross<br />

culture training,relationship charactericstics are at the lower levels <strong>of</strong> hierarchy which means that they are highly<br />

driving factors, they do not depend on other factors and the drive all other factors in the system. The factors<br />

which are at the intermediate hierarchy level are the factors which are both dependent and driving in nature.<br />

Table 2. Structural Self-Interaction Matrix<br />

S.NO. FACTORS 7 6 5 4 3 2<br />

1 Government policy and investment O V V X V O<br />

2 <strong>Technology</strong> supplier Characteristics O V V X X<br />

3 Cross culture Training O V V V<br />

4 Relationship Characteristics O V V<br />

5 <strong>Technology</strong> recipient Charateristics O V<br />

6 <strong>Technology</strong> Innovation A<br />

7 Large and stable Demand<br />

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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 3. Initial Reachability Matrix<br />

Factors 1 2 3 4 5 6 7<br />

1 1 0 1 1 1 1 0<br />

2 0 1 1 1 1 1 0<br />

3 0 1 1 1 1 1 0<br />

4 1 1 0 1 1 1 0<br />

5 0 0 0 0 1 1 0<br />

6 0 0 0 0 0 1 0<br />

7 0 0 0 0 0 1 1<br />

Table 4: Final Reachability Matrix<br />

Factors 1 2 3 4 5 6 7 driving power<br />

1 1 1* 1 1 1 1 0 6<br />

2 1* 1 1 1 1 1 0 6<br />

3 1* 1 1 1 1 1 0 6<br />

4 1 1 1* 1 1 1 0 6<br />

5 0 0 0 0 1 1 0 2<br />

6 0 0 0 0 0 1 0 1<br />

7 0 0 0 0 0 1 1 2<br />

Dependence 4 4 4 4 5 7 1<br />

Table 5. levels <strong>of</strong> critical factors, iteration 1<br />

Reachability Set Antecedent set Intersection Level<br />

Factors<br />

1 1,2,3,4,5,6, 1,2,3,4 1,2,3,4<br />

2 1,2,3,4,5,6, 1,2,3,4 1,2,3,4<br />

3 1,2,3,4,5,6, 1,2,3,4 1,2,3,4<br />

4 1,2,3,4,5,6, 1,2,3,4 1,2,3,4<br />

5 5,6 1,2,3,4,5 5<br />

6 6 1,2,3,4,5,6,7 6 Level I<br />

7 6,7 7 7<br />

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Table 6: levels <strong>of</strong> critical factors, iteration 2<br />

Factors Reachability Set Antecedent set Intersection Level<br />

1 1,2,3,4,5, 1,2,3,4 1,2,3,4<br />

2 1,2,3,4,5 1,2,3,4 1,2,3,4<br />

3 1,2,3,4,5 1,2,3,4 1,2,3,4<br />

4 1,2,3,4,5 1,2,3,4 1,2,3,4<br />

5 5 1,2,3,4,5 5 Level II<br />

7 7 7 7 Level II<br />

Table 7: levels <strong>of</strong> critical factors, iteration 3<br />

Factors Reachability Set Antecedent set Intersection Level<br />

1 1,2,3,4, 1,2,3,4 1,2,3,4 Level III<br />

2 1,2,3,4 1,2,3,4 1,2,3,4 Level III<br />

3 1,2,3,4 1,2,3,4 1,2,3,4 Level III<br />

4 1,2,3,4 1,2,3,4 1,2,3,4 Level III<br />

Table 8: levels <strong>of</strong> factors<br />

Factors Reachability Set Antecedent set Intersection Level<br />

1 1,2,3,4, 1,2,3,4 1,2,3,4 Level III<br />

2 1,2,3,4 1,2,3,4 1,2,3,4 Level III<br />

3 1,2,3,4 1,2,3,4 1,2,3,4 Level III<br />

4 1,2,3,4 1,2,3,4 1,2,3,4 Level III<br />

5 5 1,2,3,4,5 5 Level II<br />

6 6 1,2,3,4,5,6,7 6 Level I<br />

7 7 7 7 Level II<br />

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6. <strong>Technology</strong> Innovation<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5. <strong>Technology</strong> Recipient<br />

Characteristics<br />

7. Large and Stable<br />

Demand<br />

1. Government<br />

Policy and<br />

Investment<br />

2.<strong>Technology</strong> Suppier<br />

Charactericstics<br />

3. Cross Culture<br />

Training<br />

4.Relationship<br />

Charactericstics<br />

Figure 1. ISM Model<br />

8<br />

7<br />

DP 6<br />

IV 1,2,3,4 III<br />

4<br />

3<br />

2<br />

I<br />

II<br />

1<br />

7 6<br />

1 2 3 4 5 6 7 8<br />

Dependence<br />

Table 9. Driving power and Dependence Ghraph<br />

Conclusion<br />

The levels <strong>of</strong> enablers are important in understanding <strong>of</strong> successful TM implementation government<br />

policy,technology supplier charactericstic,cross culture training,relationship charactericstics are the most<br />

important enablers due to its high driving power and low dependence among all the identified TM<br />

Enablers.These enablers are positioned at the lowest level in the hierarchy <strong>of</strong> the ISM-based model. The enabler<br />

technology innovation is at the highest level in the ISM-based model due to its high dependence power and low<br />

driving power. The model presented in this paper can provide management involved in technology management<br />

and decisions-makers to identify and classify the critical factors that have either strong dependence or strong<br />

driving power or both strong dependence and driving power that ultimately inhanced the productivity <strong>of</strong> any<br />

organization.<br />

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77. Glaister, K.W., Husan, R.& Buckley,P.J.(<strong>20</strong>03). Learning to Manage International Joint<br />

Venture.International Business Review,12(1):83-108.<br />

78. Nahapiet,J.& Ghoshal,S.(<strong>19</strong>98). Social Capital , Intectual Capital and the Organizational Advantage .<br />

Academy <strong>of</strong> Management Review,23(2):242-226.<br />

79. Kale p., Singh H. & Perlmutter H. (<strong>20</strong>00). Learning and Protection <strong>of</strong> Proprietary Assets in Strategic Alliance<br />

: Building Relational Capital , Strategic Management Journal,21 (3):217-37.<br />

80. Uzzi , B. (<strong>19</strong>97). Social structure and competion in interfirm networks: the paradox <strong>of</strong> embeddedness.<br />

Admnistrative science quartely,42:35-67.<br />

81. Dhanaraj , C., Lyles, M.A., Steensma ,H.K.&Tilhayi, L. (<strong>20</strong>04). Managing Tacit and Explicit Knowlegde<br />

Transfer in IJVs: The Role <strong>of</strong> Relational Embeddedness and the iImpact on Performance , Journal <strong>of</strong><br />

International Business Studies,35(5):428-42.<br />

82. Barney, J.B. (<strong>19</strong>91). Firm Resources and Sustainaned Competitive Advantage. Journal <strong>of</strong><br />

Management,17:151-166.<br />

83. Bierly III P E and Gallagher S (<strong>20</strong>07). “Explaining Alliance Partner Selection: Fit Trust and Strategic<br />

Expediency” Long Range Planning <strong>20</strong>07.<br />

84. Parise ,S and Hendorson,J.C.(<strong>20</strong>01) “Knowledge Resource Exchange in Strategic Allaince”IBM System<br />

Journal, Vol.40 pp.908-24.<br />

85. Haque,S.M.M.; Green,R; Keogh, W(<strong>20</strong>04) “Colloborative Relationship in the UK Upstream Oil and Gas<br />

Industry: Critical Success and Failure Factors” Problems & Perspective in Management,Issue 1,pp.44-51.<br />

86. Kauser, S and Shaw, V (<strong>20</strong>04) “The influence <strong>of</strong> behavioural and organizational characterstics on the success<br />

<strong>of</strong> international strategic alliance”, International Marketing Review;Volume:21 Issue:1.<br />

87. A. Alawi, A.Marzooqi, Y. Mohammed. Organizational Culture and Knowledge Sharing: Critical Success<br />

Factors. Journal <strong>of</strong> Knowledge Management,<strong>20</strong>07,11(2):22-42.<br />

88. Nimesh chandra,(<strong>20</strong>07). Small and medium enterprises in the national system <strong>of</strong> innovation: exploring the<br />

barriers to technology transfer.<br />

89. York, <strong>19</strong>77. A. Sage. Interpretive Structural Modeling: Methodology for Large-scale Systems, 91–164.<br />

McGraw-Hill, New york,<strong>19</strong>97.<br />

90. J. Warfield. Developing interconnection matrices in structural modeling. IEEE Transactionsons on Systems,<br />

Man and Cybernetics, <strong>20</strong>05, 4(1): 81–67.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

91. Task Force on Management <strong>of</strong> <strong>Technology</strong>, <strong>19</strong>87. Management <strong>of</strong> <strong>Technology</strong>: The Hidden Competitive<br />

Advantage. National Academy Press, Washington, DC, pp. 9.<br />

92. Wang, H., <strong>19</strong>93. <strong>Technology</strong> management in a dual world. International Journal <strong>of</strong> <strong>Technology</strong> Management<br />

8, 108–1<strong>20</strong>.<br />

810


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Establishing Time Standards for Fixing Body Side Panel to the Chassis in<br />

Assembly Line Using MOST<br />

Vikram K V 1 , Dr. D. N. Shivappa 2 , Jaganur Sangamesha 3<br />

1 PG Student, e-mail: vikramkv123@gmail.com<br />

2 Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, Sir M. Visvesvaraya Institute <strong>of</strong> <strong>Technology</strong>,<br />

Bangalore 562 157, India. e-mail: shivappadn@gmail.com<br />

3 Manager, Production Engineering Department, Mahindra Reva ElectricVehicles Pvt Ltd, Bangalore-560099,<br />

India. e-mail: jaganur.sangamesha@mahindrareva.com<br />

Abstract<br />

Mahindra Reva Electric Vehicles Pvt Ltd has established new assembly line to assemble Electric Car.The<br />

company has adopted a new concept <strong>of</strong> bonding methodology for the assembly <strong>of</strong> ‘Body Side Panel’ onto the<br />

chassis <strong>of</strong> Reva NXR vehicle at Stage 15, for this a special Bonding Fixture is used. To establish the new Time<br />

Standards for assembly activities <strong>of</strong> fixing Body Side Panel the ‘Maynard Operation Sequence Technique<br />

(MOST)’ is used. For each assembly processes the tools description, process description and existing MOST<br />

sheets were studied which provided detailed information about all the movements <strong>of</strong> assembly activities. It was<br />

identified that many movements <strong>of</strong> assembly activities were taking more time than required, using MOST,<br />

movements <strong>of</strong> some activities were modified and few were eliminated resulting in reduction <strong>of</strong> 41% in assembly<br />

time. In addition necessary changes in workplace were made which reduced the stress creating unproductive<br />

movements.<br />

Keywords:Body Side Panel, Bonding Fixture, Standard Time,MOST, Total Work Content, Work Measurement.<br />

Abbreviations<br />

MOST Maynard Operation Sequence Technique<br />

MTM Methods Time Measurement<br />

EST Established Standard Time<br />

TWC Total Work Content<br />

LH Left Hand<br />

RH Right Hand<br />

NVA Non-Value Added Activities<br />

TMU Time Measurement Unit<br />

1.Introduction<br />

Work measurement is a systematic procedure for the analysis <strong>of</strong> work and determination <strong>of</strong> time required to<br />

perform key tasks in processes,it is typically based on time standards for manual tasks. The release <strong>of</strong> the<br />

Methods Time Measurement (MTM) system in the <strong>19</strong>40s was an important step forward in predictive work<br />

measurement. It is defined as `a procedure which analyses any manual operation or method into the basic<br />

motions required to perform it.MTM assigns to each motion a predetermined time standard which is determined<br />

by the nature <strong>of</strong> the motion and the conditionsunder which it is made.<br />

One <strong>of</strong> the major problems in applying MTM to manufacturing operations is that it is extremely tedious and time<br />

consuming, since a work analyst must observe and document each movement in great detail. In addition, such an<br />

approach generates large amounts <strong>of</strong> data which must be managed. The development and release <strong>of</strong> the MOST in<br />

the <strong>19</strong>60s alleviated many <strong>of</strong> these problems, since it is much simpler and more efficient. It classifies all human<br />

movements into three basic categories, and the description <strong>of</strong> each category is done by assigning values to only a<br />

few standard parameters. It is the latest work measurement technique that can be easily implemented and<br />

practically maintained to not only estimate the standard time but also improve methods and maximize the<br />

resource utilization [1].<br />

2. Literature Review<br />

The first comprehensive work on MOST was published by Kjell B. Zandin [1]. Work measurement is largely<br />

concerned with human work output and includes a certain amount <strong>of</strong> allowance to provide for a worker’s<br />

personal needs, fatigue and unavoidable delays during the assembly operation they opine. The development <strong>of</strong><br />

manufacturing data is the first step in the work measurement and forms the basis for applying the time standards<br />

[2]. Authors have pointed out the difference between Engineered Standard and Non-Engineered Standard. By<br />

utilizing Engineering Standard, realistic and consistent engineered time standards the result <strong>of</strong> all the studies will<br />

811


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

be become more reliable. The predetermined time study forms the basis for the MOST work measurement<br />

technique [3]. They pointed out that estimating methods cannot determine accurate times,hence MOST is a<br />

standard method to determine the potential error which helps in minimising the time taken to perform a task or<br />

operation.<br />

Francesco Longoand others [4] pointed out that one <strong>of</strong> the most important approaches for studying line balancing<br />

is work measurement technique using MOST. They suggested that for designing an assembly line, both the line<br />

balancing as well as the work measurement technique has to be considered, which plays an important role for<br />

measuring the time standards in the assembly process. Ashish Thakre etal proposed that the MOST work<br />

measurement technique is used for minimization <strong>of</strong> non-productive activities in an assembly line. The study<br />

conducted using MOSTrevealed the excessive movements <strong>of</strong> the operators that significantly added to the basic<br />

work content [5].<br />

3. MOST Methodology<br />

The Maynard Operation Sequence Technique (MOST) is a work measurement technique that concentrates on the<br />

movement <strong>of</strong> objects. It is used to analyze work and to determine the normal time that it would take to perform a<br />

particular process/operation.<br />

MOST is used to:<br />

• Observe and document the methods <strong>of</strong> operation<br />

• Break down the sub-operation into logical activities<br />

• Select the appropriate sequence model for each activity<br />

• Select the appropriate ‘indices values’ for the parameters <strong>of</strong> the models, including their repetitions.<br />

• Synthesis the Standard Operation time <strong>of</strong> the activities.<br />

MOST focuses on three types <strong>of</strong> object movements:<br />

(i) General Move is applicable when objects are moved manually from one location to another freely through the<br />

air. To consider the various ways in which a General Move can occur, the activity sequence is made up <strong>of</strong> four<br />

sub-activities.<br />

A - Action distance<br />

B - Body motion<br />

G - Gain control<br />

P – Placement<br />

The sequence model defines the events or actions that always take place in a prescribed order when an object is<br />

being moved from one location to another. These sub-activities, or sequence model parameters, are then assigned<br />

time-related index numbers based on the motion content <strong>of</strong> the sub-activity. For each object moved, any<br />

combination <strong>of</strong> motions might occur, and using MOST, any combination may be analyzed.<br />

(ii) Controlled Move sequence is used to cover such activities as operating a lever or crank, activating a button or<br />

switch, or simply sliding an object over a surface. In addition to the A, B and G parameters from the General<br />

Move Sequence, the sequence model for a controlled move contains the following sub-activities:<br />

M: Move controlled<br />

X: Process time<br />

I:Alignment<br />

(iii) Tool Use sequence model covers the use <strong>of</strong> hand tools for such activities as fastening or loosening, cutting,<br />

cleaning, gauging, and recording. Also, certain activities requiring the use <strong>of</strong> the brain for mental processes can<br />

be classified as Tool Use, for e.g. reading and thinking. The Tool Use Sequence Model is a combination <strong>of</strong><br />

General Move and Controlled Move activities.<br />

4. Time Study <strong>of</strong> Body Side Panel Bonding Process<br />

The Body Side Panel Bonding process begins with pushing the chassis trolley to the body side panel bonding<br />

bay and locating the chassis using the foot operated pedal and attaching the front and rear locator to the chassis<br />

by inserting the dowel pin and toggle clamp. Attach static mixer at the tip <strong>of</strong> the Graco dispenser gun and<br />

dispense mixer's length <strong>of</strong> adhesive on the waste cloth to ensure uniform mixture and the apply the sealant on the<br />

RH side and LH side and fix the body side panel RH by locating and inserting the Tuflock Screws and firmly fix<br />

it to the chassis and repeat the same step for LH side.<br />

Bring in the body side panel fixture by using the switch control box and locate the bonding fixture above the<br />

chassis. Press the tackle down button to bring the fixture down until the ro<strong>of</strong> railing paddings will touch the ro<strong>of</strong><br />

812


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

area <strong>of</strong> the body side panel and apply pressure on it. Now press the cycle start switch for the fixture to<br />

automatically press the paddings. On reaching the curing time, remove the fixture by pressing the Cycle Stop<br />

Button and then Press the tackle up button to remove the fixture and move it away. Unclamp the locators and<br />

Remove the locators on front and bottom and remove the car from the body side panel fixture location to the<br />

transferring bay. Apply the protective coating around the body side panels LH and RH. The entire Body Side<br />

Panel Bonding area is as shown in Fig. 1.<br />

Fig. 1 Bonding Area in Assembly Line Stage 15<br />

4.1 Bonding Fixture<br />

The Bonding fixture shown in Fig.2 is basically made <strong>of</strong> a tubular structure comprising a base frame and two<br />

swing arms which swings sideways at the LH and RH side <strong>of</strong> the top frame. Eight sets <strong>of</strong> pneumatic actuators are<br />

mounted on each side <strong>of</strong> the swing arms <strong>of</strong> the fixture. These actuators are integrated and operated through a<br />

PLC program to enable auto cycling and fool pro<strong>of</strong>ing <strong>of</strong> manual errors through human, machine interfaces. The<br />

entire fixture assembly is hanged on to a super structure, which is mounted below an electric monorail that<br />

facilitates the movement <strong>of</strong> fixture from one station to another. This fixture is used for holding and fixing LH<br />

and RH Body Side Panel onto the chassis and it is controlled by Program Logic Control (PLC). Details <strong>of</strong> PLC<br />

are given below:<br />

• Power On the main supply to the fixture and Press ‘Trolley Left’ button to move the fixture to bonding<br />

station and place the two rough locators on chassis.<br />

• Press ‘Tackle Down’ button where in the fixture comes down and rests on the locators.<br />

• Press ‘Cycle Start’ where in the Pneumatic actuated fine locators align the fixture with chassis and the ro<strong>of</strong><br />

pads rests on the car ro<strong>of</strong> and wings <strong>of</strong> the fixture comes down simultaneously.<br />

• Press ‘Cycle Start’ again and all the pads start butting against the side panel one by one in prescribed order<br />

and after the pre-set bonding timer delay, all the pads retrieve one by one in prescribed order.<br />

• Press ‘Cycle Stop’ to retrieve both fine locators and ro<strong>of</strong> pads to home position.<br />

• Press ‘Tackle-Up’ and ‘Trolley-Right’ to take fixture back to the buffer station.<br />

Fig. 2 Bonding Fixture<br />

813


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5. MOST Application at Assembly Line<br />

The present study makes use <strong>of</strong> Basic MOST for the estimation <strong>of</strong> Total Work Content(TWC) for an <strong>of</strong>f-line<br />

stage <strong>of</strong> Bonding. The newest methodology <strong>of</strong> bonding assembly process was chosen to identify NVA activities<br />

and further to improve the layout.<br />

The study was carried out in three phases:<br />

(i) Existing TWC Calculations using Basic MOST,<br />

(ii) Basic MOST Analysis to Identify NVA Activities<br />

(iii)Elimination <strong>of</strong> the NVA Activities by making the necessary changes in work methods.<br />

(i) Existing TWC Calculations<br />

The activities at each workstation are broken down into distinctly identifiable and measurable sub-activities.<br />

Each sub-activity was further broken down into elements and these elements are then sequence modeled using<br />

the parameters and index values given in MOST Data Card. Unit sub-activities have common and same<br />

sequenced set <strong>of</strong> elements and occur frequently in many activities. The MOST estimation sheets are developed to<br />

sequence model the elements using the parameters and index values. MOST estimation sheet explains how an<br />

operation is broken down into sub-operations and activities. The cycle time (in seconds) for an element is<br />

calculated by adding the index values and then multiplying the sum by (0.36 * FRQ/DIV). FRQ (Frequency)<br />

represents the frequency <strong>of</strong> the repeated elements. DIV (Division) refers to the two or more elements done<br />

simultaneously by an operator, e.g., moving two trolleys simultaneously. Elemental cycle times are then added to<br />

obtain the cycle time <strong>of</strong> sub operation.The cycle times <strong>of</strong> sub-operations are further added to obtain the cycle<br />

time <strong>of</strong> sub-activity. Work content is then obtained by adding the cycle times <strong>of</strong> the sub-activities.<br />

The Body Side Panel Assembly activity was broken down into 42 sequence <strong>of</strong> operation by personally observing<br />

the workers movements. The parameters and index values in terms <strong>of</strong> TMU for each operation was identified<br />

using MOST Data Card. The operation time calculations based on parameters and index values are done for each<br />

operation. The time value for a sequence model in basic MOST is obtained by simply adding the index numbers<br />

for individual sub operation and multiplying the sum by 10 and then to convert TMU into seconds by multiply<br />

by 0.036.<br />

(ii) Basic MOST Analysis<br />

Using the MOST evaluation <strong>of</strong> operation time pertaining to 42 sequences <strong>of</strong> operations involved in Body Side<br />

Panel Bonding Process is carried out; details <strong>of</strong> establishing standard operation time for one activity “Dispensing<br />

Sealant” is discussed below.<br />

5.1 Established Standard Time for Dispensing Sealant<br />

Grasp (G1) the sealant gun within reach (A1) and dispense the sealant onto the cotton waste within reach (A1)<br />

by bending (B6) with light pressure (P3) by controlling the knob (M1) and return (A3) back 1 to 2 steps.<br />

The standard time in Seconds for the sequence <strong>of</strong> parameter A1 B6 G3 A1 P3 M1 A3 is,<br />

(A + B + G + A + P + M + A) * (0.36 * FRQ/DIV)<br />

(1 + 6 + 1 + 1 + 3 + 1 + 3)*(0.36 * 1/1) = 16*0.36 = 5.76 s.<br />

The index numbers for bending to dispense the sealant, applying pressure and returning back are 6, 3, 3<br />

respectively (B6 P3 A3). Higher index numbers indicate higher work content. Hence by personally observing the<br />

worker’s movement the higher index parameter is reduced from (B6) to no Bending (B0) in the process by fixing<br />

the Bin onto the super structure at a certain height in the assembly line.<br />

The standard time in seconds for revised sequence <strong>of</strong> parameter A1 B0 G3 A1 P3 M1 A3 is,<br />

(A + B + G + A + P + M + A) * (0.36 * FRQ/DIV)<br />

(1 + 0 + 1 + 1 + 3 + 1 + 3)*(0.36 * 1/1) = 10 * 0.36 = 3.6 sec.<br />

The time reduction for this activity is (5.76 – 3.6) = 2.16 sec.<br />

For other 41 activities, similar calculations were made to estimate work contents <strong>of</strong> each activity. TWC the sum<br />

<strong>of</strong> all work contents was found to be 9 minutes 56 seconds.<br />

814


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

(iii) Elimination <strong>of</strong> the NVA Activities by making the necessary changes in work methods<br />

Each <strong>of</strong> the 42 activities identified were critically examined to eliminate or reduce the NVA activity associated<br />

with that parameter. In each case, it was observed that, few small changes in the layout at the individual<br />

workstation lead to drastic reduction in the work content. For example, few changes in activity – Placement <strong>of</strong><br />

Front and Rear locators, operation time can be reduced by placing the front and rear locators nearer to the<br />

bonding bay and fixing it onto the super structure <strong>of</strong> the assembly line.<br />

Similar exercise was done for all the 42 activities associated with Existing Method. After evaluating the actual<br />

process it was identified that 5 activities were found to be taking more time than required, and 11 were identified<br />

as non-value added activities. By modification <strong>of</strong> 5 activities and elimination <strong>of</strong> 11 activities, total operation time<br />

<strong>of</strong> 3 minutes 58 seconds was reduced, thereby reducing the number <strong>of</strong> activities from 42 to 31. Hence the total<br />

operation time for Body Side Panel Bonding Process gets reduced to 5 minutes and 53 seconds from 9 minutes<br />

56 seconds. With the changes made in 5 activities and elimination <strong>of</strong> 11 activities there is a reduction <strong>of</strong> 41% <strong>of</strong><br />

operation time.<br />

6. Results and Analysis<br />

Before the new standards were established, an extensive and thorough analysis and review <strong>of</strong> each activity was<br />

conducted in Stage 15 <strong>of</strong> assembly line. The existing process had 42 activities and the time taken to complete the<br />

process was 9 minutes and 39 seconds. After evaluating the actual process it was identified that 5 activities were<br />

found to be taking more time than required, new time standards were established for these activities which are<br />

given Table 1.<br />

Table 1 Details <strong>of</strong> Operation Time Reduction<br />

Operation Name<br />

Existing<br />

Time in<br />

Seconds<br />

Modified<br />

Time in<br />

Seconds<br />

Reduction<br />

Time in<br />

Seconds<br />

Take the front locator 12.6 7.56 5.04<br />

Take the rear locator 12.6 7.56 5.04<br />

Insert rear bottom locator into the top locator 6.84 4.68 2.16<br />

Dispense adhesive 5.76 3.6 2.16<br />

Sealant Application Process time 126.72 86.4 40.32<br />

Total 164.52 109.8 54.72<br />

Table 2 Details <strong>of</strong> Operation Time Elimination<br />

Eliminated Operation Name<br />

Operation Time<br />

in Seconds<br />

Collect the body side panel 12.96<br />

Place the locators on the LH and RH panel 21.6<br />

Inspect the flushness and gap 6.48<br />

Adjust the fitness <strong>of</strong> the panel 4.32<br />

Disengage the Panel 9.36<br />

Place back the panels onto the storage Rack 17.28<br />

Use cotton cloth 0.72<br />

Using the Scuffing Tool 40.32<br />

Clean the scuffed area 57.6<br />

Get the Masking Tape 4.68<br />

Fix the masking tape onto the chassis 9.72<br />

Total 184.32<br />

815


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

And 11 were identified as non-value added activities as shown in Table 2with this, number <strong>of</strong> activities were<br />

reduced from 42 to 31. As given in Table 1 there is a reduction <strong>of</strong> operation time by 54.72 seconds and in Table<br />

2 there is an elimination <strong>of</strong> operation time by 3 minutes and 4 seconds, hence the total operation time for Body<br />

Side Panel Bonding Process gets reduced to 5 minutes and 53 seconds. With the changes made in 5 activities and<br />

elimination <strong>of</strong> 11 activities there is a reduction <strong>of</strong> 41% <strong>of</strong> operation time. Table 3 shows MOST estimation sheet<br />

with newly established standard time for Body Side Panel Bonding Process.<br />

7. Conclusion<br />

Study <strong>of</strong> existing set up for assembly <strong>of</strong> body side panel has revealed that there are 11 non-value added activities<br />

which have been removedthere by reducing the sequence <strong>of</strong> operations to 31 from 42. These 11 activities put<br />

together were taking assembly time <strong>of</strong> 3 minutes 4 seconds. And 5 activities were found to be taking more time<br />

than required i.e.; 54 seconds, for these activities new time standards were established. After modification <strong>of</strong> 5<br />

activities and elimination <strong>of</strong> 11 activities assembly time reduced to 5 minutes and 57 seconds from earlier 9 min<br />

56 seconds, a reduction <strong>of</strong> 41% in assembly time.<br />

This work has revealed that the three sequence models such as ‘General Move’, ‘Control Move’, and ‘Tool Use’<br />

used in MOST are found to be very effective in identifying unnecessary movements in assembly process. And<br />

these sequence models were effectively used in the present work to establish new standard times for certain<br />

activities and elimination <strong>of</strong> unnecessary movements.<br />

Acknowledgment<br />

The authors are grateful tothe Management <strong>of</strong> Mahindra Reva Electric Vehicles Pvt Ltd for providing permission<br />

to carry out the work.Sincere thanks are also due to Mr. Narayana Kutty, GM Production Engineering<br />

Department for helping our team in the Shop floor. The authors also thank Ms. Shaheen, Mr. Rajasekhar and Mr.<br />

Manokaranfor their help in research assistance.<br />

References<br />

[1] Kjell B. Zandin “MOST - Work Measurement Systems”, Maynard’s Industrial Engineering Handbook<br />

(New York: Marcel Dekker, INC, <strong>19</strong>90), 17.65 – 17.82.<br />

[2] Tew J D Manivannan, S Sadcwski D A and Seiia A F, “Development and Application <strong>of</strong> Realistic and<br />

Consistent Manufacturing Data as a Basis for Simulations”, Proceedings <strong>of</strong> the Winter Simulation<br />

Conference, Ed. Zandin, Kjell B, <strong>19</strong>94, 453-457.<br />

[3] Razmi, Jafar and Shakhs-Niyaee, Majid “Developing a specific predetermined time study approach: an<br />

empirical study in a car industry”, Production Planning & Control, <strong>19</strong>:5, <strong>20</strong>08, 454 — 460.<br />

[4] Francesco Longo, Giovanni Mirabelli, Enrico Pap<strong>of</strong>f “Effective Designing an Assembly Line Using<br />

Modeling and Simulation”, Dept. <strong>of</strong> Mechanical Engineering, <strong>University</strong> <strong>of</strong> Calabria, Rende (CS), Via P.<br />

Bucci, 87036, Italy, Proceeding <strong>of</strong> the Winter Simulation Conference, <strong>20</strong>06.<br />

[5] Ashish R. Thakre, Dhananjay A. Jolhe & Anil C. Gawande, “Minimization <strong>of</strong> Engine Assembly Time by<br />

Elimination <strong>of</strong> Unproductive Activities through ‘MOST’, Second International Conference on Emerging<br />

Trends in Engineering and <strong>Technology</strong>, ICETET-09.<br />

816


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Sl<br />

No.<br />

1<br />

2<br />

3<br />

4<br />

5<br />

6<br />

Sequence <strong>of</strong> Operation<br />

Apply pressure and push the chassis trolley about 5-7 steps to the body<br />

side panel bonding bay<br />

Locate it with adjustments and little resistance using the foot operated<br />

pedals on LH front area simultaneously by stamping on it<br />

Move 3-4 Steps and Bend and gain control <strong>of</strong> the front locator and<br />

attach it to the chassis crushing zone by inserting the dowel pin and<br />

toggle clamp with precision<br />

Move 3-4 Steps and bend to gain control <strong>of</strong> fixture rear locator and<br />

attach the top part by inserting it into the rear hatch fixing holes on the<br />

top side with precision<br />

Move 1-2 Steps and gain control <strong>of</strong> rear bottom locator and insert it into<br />

the top locator within reach and position it with precision<br />

Gain control <strong>of</strong> both the locators and loose fit the locking pin into the<br />

hole provided on both locators at their mating point<br />

Table 3 MOST Sheet with Established Standard Time for Body Side Panel Bonding Process<br />

Get Put Controlled Move Tool Action Return<br />

A B G A B P M X I F/L/C/S/M/R/T A<br />

817<br />

TMU<br />

Freq<br />

Established Standard<br />

Time (EST) in Seconds<br />

1 3 16 6 16 42 1 15.12<br />

1 3 3 7 1 2.52<br />

6 3 6 6 21 1 7.56<br />

6 3 6 6 21 1 7.56<br />

3 3 1 6 13 1 4.68<br />

1 1 3 5 1 1.8<br />

7<br />

Move 3-4 Steps and grasp the rear bottom locator and move 3-4 steps<br />

and with precision position the rear bottom locator using 2 toggle clamps<br />

with 2-3 revolutions at the bottom side <strong>of</strong> the chassis after butting the<br />

6 1 6 6 6 25 1 9<br />

surface against the chassis<br />

8<br />

Gain control <strong>of</strong> the Cloth within reach and with light pressure clean the<br />

bonding surface<br />

1 3 1 1 3 42 51 2 36.72<br />

9 Place the cotton within reach after completion 1 1 2 1 0.72<br />

10<br />

Move 3-4 Steps and Get LORD A/C Cartridge and sealant gun and insert<br />

in the sealant gun<br />

6 3 3 3 1 16 1 5.76<br />

11 Remove the caps 1 1 1 3 1 1.08<br />

12<br />

Grasp the Plungers within reach and Level the plungers by dispensing<br />

small amount <strong>of</strong> adhesive by pressing a button to ensure both sides are<br />

levelled<br />

1 1 1 1 1 5 1 1.8<br />

13 Place the static mixer at the tip and adjust onto the sealant gun 1 3 1 3 8 1 2.88<br />

14<br />

Dispense mixer’s length <strong>of</strong> adhesive on the cotton waste to ensure<br />

uniform mixture<br />

1 1 1 3 1 3 10 1 3.6<br />

Grasp the Sealant Cartridge within reach and apply sealant on the LH<br />

15<br />

1 1 3 3 8 4 11.52<br />

and RH side<br />

16 Process Time for Sealant Application in Straight Bead Pattern 6 6 3 15 16 86.4<br />

Move 3-4 Steps and collect the foam and immediately apply it in the<br />

17<br />

6 3 6 6 3 24 2 17.28<br />

Rear tub side bracket LH and RH<br />

18 Move 3-4 Steps and Gain control <strong>of</strong> the body side panel 6 3 6 3 6 24 2 17.28


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

<strong>19</strong><br />

Fix the body side panel LH and RH by small adjustments and locate it at<br />

Front and Rear <strong>of</strong> the Panel<br />

1 3 1 3 6 14 2 10.08<br />

Table 3 MOST Sheet with Established Standard Time for Body Side Panel Bonding Process (Continued)<br />

Sl<br />

No.<br />

Sequence <strong>of</strong> Operation<br />

Get Put Controlled Move Tool Action Return<br />

A B G A B P M X I F/L/C/S/M/R/T A<br />

TMU<br />

Freq<br />

Established Standard<br />

Time (EST) in Seconds<br />

<strong>20</strong> Move 3-4 Steps and Collect the Tuflock Screws 6 3 6 15 1 5.4<br />

21<br />

22<br />

23<br />

24<br />

25<br />

26<br />

27<br />

Grasp the Tuflock Screws within reach and Insert at points in four<br />

regions <strong>of</strong> the panel<br />

Move 3-4 Steps and grasp the switch control box and then Bring in the<br />

body side panel fixture by pressing "trolley left" switch and locate it<br />

above the chassis (it will automatically stop at that position)<br />

Press the tackle down button to bring the fixture down until the ro<strong>of</strong><br />

railing paddings will touch the ro<strong>of</strong> area <strong>of</strong> the body side panel and apply<br />

pressure on it<br />

Now press the cycle start switch for the fixture to automatically press the<br />

paddings<br />

On reaching the curing time, Move 3-4 Steps and grasp the Switch<br />

Control Box and press Cycle Stop Button to remove the fixture<br />

On Curing, Press the tackle up button to remove the fixture and move it<br />

away<br />

Move 3-4 Steps and Grasp the locators and then Unclamp the locators<br />

and Repeat the action for 5 Times<br />

1 1 1 3 3 9 4 12.96<br />

6 1 6 3 6 22 1 7.92<br />

1 1 3 5 1 1.8<br />

1 1 2 1 0.72<br />

6 1 1 8 1 2.88<br />

1 1 3 3 1 9 1 3.24<br />

6 1 6 3 1 17 5 30.6<br />

28 Grasp the locators within reach and then pull the locators from the Panel 6 1 1 3 1 12 4 17.28<br />

29 Gain control <strong>of</strong> the protective coating within reach 1 1 1 3 1 1.08<br />

30<br />

31<br />

Apply the protective coating all around the body side panels LH and RH<br />

using a knob with light pressure<br />

Move 3-4 Steps and Gain Control <strong>of</strong> the Car and then with Heavy<br />

Pressure push the car 10-13 steps from the body side panel fixture<br />

location to the transferring bay<br />

1 1 1 3 1 7 5 12.6<br />

6 3 10 6 24 49 1 17.64<br />

Total Time: 5 Minutes 57 Seconds 357.48<br />

818


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

ESTABLISHING TIME STANDARDS FOR ASSEMBLY ACTIVITY IN CHASSIS<br />

PREPARATION AREA USING MOST<br />

Harish.H 1 , D. N. Shivappa 2 , Jaganur Sangamesh 3<br />

1 PG Student, Department <strong>of</strong> Mechanical Engineering, Sir M. Visvesvaraya Institute <strong>of</strong> <strong>Technology</strong>, Bangalore 562 157, India<br />

2 Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, Sir M. Visvesvaraya Institute <strong>of</strong> <strong>Technology</strong>, Bangalore 562 157, India<br />

3. Manager, Production Engineering Department, Mahindra RevaElectricVehiclesPvtLtd, Bangalore, India<br />

e-mail: harish.me27@gmail.com<br />

Abstract:<br />

Paper presents development <strong>of</strong> time standards for all the assembly activities <strong>of</strong> Chassis Preparation Area in<br />

assembly line <strong>of</strong> Mahindra Reva Electric Vehicles Pvt Ltd. company using “Maynard Operation Sequence Technique<br />

(MOST)”. Initially thorough study <strong>of</strong> the chassis preparation area at stage I and II in assembly main line I was<br />

made. For each assembly process the bill <strong>of</strong> materials, tools description, and process description were studied which<br />

provided detailed information about all the movements <strong>of</strong> assembly activities. It was identified that many movements<br />

<strong>of</strong> assembly activities were taking more time than required; using MOSTmovements <strong>of</strong> these activities were modified.<br />

MOST sheets describing established time standards are developed for all the assembly activities <strong>of</strong> Stage I and II <strong>of</strong><br />

chassis preparation area.<br />

Keywords: Standard Time, MOST, Chassis preparation area, Rear Power Train, Front Suspension, Bundy Tubes,<br />

Steering Rack.<br />

Abbreviations<br />

EST Established Standard Time<br />

MOST Maynard Operation Sequence Technique<br />

RH Right Hand<br />

LH Left Hand<br />

RPT Rear Power Train<br />

TMU Time Measurement Unit<br />

1. Introduction<br />

In the organization under study, the excess work content in an assembly line <strong>of</strong> “Chassis Preparation Area” was the<br />

problem <strong>of</strong> concern, The current production system at Mahindra Reva NXR plant has some limitations which<br />

includes longer material handling, less labor productivity, more floor space, large work-in-process inventory and<br />

long setup time. In this work it is proposed to reduce the material handling time at chassis preparation area in stage I<br />

and II <strong>of</strong> the assembly line. For this purpose the highly practical efficient and cost effective time estimation<br />

technique MOST is used.<br />

2. Literature Review<br />

JafarRazmi [1] present the Standard Time Estimation <strong>of</strong> a project accomplished in the Iran-Khodro Car<br />

manufacturing Company. A particular predetermined time study approach is developed in this company which<br />

covers all bodyshopoperations.Then the MOST is employed to analyze each operation <strong>of</strong> standard routings to<br />

determine the associated standard time.<br />

Norashikin Binti Rahman’s [2] study was related to improvement <strong>of</strong> labor productivity utilizing Process Mapping<br />

and MOST. He proposed two approaches for productivity improvement; which are method study and time study.<br />

Thus, he used process mapping as the method study and MOST as the time study method. The aim <strong>of</strong> his research<br />

was to identify opportunities for improvement to current production system by performing work study on the manual<br />

operator’s activities, determining current Operator’s utilization as well as establish standard time for manual process.<br />

All this initiated by performing work study on the manual operators’ activities.<br />

Ashish R et al [3] highlights a methodology developed for minimization <strong>of</strong> non-productive activities in an assembly<br />

line. The case study was conducted in tractor manufacturing unit having a dedicated assembly line for tractor engine.<br />

The study conducted using MOST revealed the excessive movements <strong>of</strong> the operators that significantly added to the<br />

8<strong>19</strong>


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

basic work content. The necessary changes were suggested in workplace layout to minimize the stress creating<br />

unproductive movements.<br />

3. MOST Methodology<br />

MOST is the latest work measurement technique that can be easily implemented and practically maintained to<br />

estimate the standard time and also improve methods which maximize the resource utilization. It was originally<br />

developed by H. B. Maynard & Company Inc. and has three versions viz Basic MOST for the activities between <strong>20</strong><br />

sec to 2 min, Mini MOST for the activities shorter than <strong>20</strong> sec, and Maxi MOST for the activities above 2 min.<br />

MOST focuses on three types <strong>of</strong> object movements Such as General Move, Control Move, and Tool Use which are<br />

briefly explained hereunder<br />

(i) General Move: It represents the movement through the air from one point to another; this activity is represented<br />

by the following sequence <strong>of</strong> sub-activities or parameters –A B G A B P A,<br />

Where,<br />

A - Action Distance (Mainly Horizontal)<br />

B - Body Motion (Mainly Vertical)<br />

G - Gain Control<br />

P – Placement<br />

The variation in each sub-activity is indicated by an index value. For example, A6 B6 G1 A1 B0 P3 A0 represents,<br />

A6 - Walk three or four steps<br />

B6 - Bend and arise<br />

G1 - Simply grasp an object<br />

A1 - Move within reach<br />

B0 - No body motion<br />

P3 - Place object with adjustment<br />

A0 - No return move<br />

The common scale <strong>of</strong> index numbers for all MOST sequence models is 0, 1, 3, 6, 10, 16, 24, 32, 42 and 54. The time<br />

value for a sequence model in basic MOST is obtained by simply adding the index numbers for individual sub<br />

activity and multiplying the sum by 10. For instance the standard time in TMU for the sequence A6 B6 G1 A1 B0<br />

P3A0 is,<br />

(6 + 6 + 1 + 1 + 0 + 3 + 0)*10 =170 TMU,<br />

i. e., 170 * 0.036<br />

s = 6.12 s.<br />

(ii) Controlled Move: It represents theobject remains in contact with a surface or the object path is controlled. The<br />

move sequence model is A B G M X I A, in which,<br />

M: Move Controlled<br />

X: Process Time<br />

I: Alignment<br />

(iii) Tool Use:represents describing the manual tools (like wrenches, screw drivers, gauges, writing tools, etc.) these<br />

can be used during an operation. It also covers fingers and mental process. It is a combination <strong>of</strong> general move<br />

activities.<br />

The MOST has advantages that only one or two observations are needed to measure the work and the rating factor is<br />

inbuilt (in index time) [4]. The result does not deviate from analyst to analyst since the standard calculation sheet<br />

with standard motion sequence and index values are available. It is more accurate than other techniques and involves<br />

less paper work.<br />

4. Time study in chassis preparation area<br />

“Chassis Preparation Area” main line consists <strong>of</strong> 3 Stages, in Stage I assembly <strong>of</strong> “Rear Power Train” and “Front<br />

Suspension LH and RH” are carried out. In Stage II assembly <strong>of</strong> “Steering Rack”, “Proportionating Valves with three<br />

8<strong>20</strong>


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

way connectors” and “Bundy Tubes” is done, and finally in Stage III the chassis will drop onto the conveyor trolley<br />

using Pantograph I.<br />

In assembly main line stage I shown in Fig.1 the “RPT subassembly” is fixed to the chassis rear side. Initially the<br />

RPT will be on the subassembly fixture, with the help <strong>of</strong> decking fixture the RPT subassembly is carried to the rear<br />

side <strong>of</strong> chassis which is in horizontal position on special purpose machine (lift and tilt equipment). The Assembly <strong>of</strong><br />

the RPT to chassis is done by using necessary tools and hardware. The Rear Suspension both Left Hand and Right<br />

Hand which are parts <strong>of</strong> RPT are also assembled to the chassis. The pneumatic tools and sockets are used to<br />

assemble the parts kept separately in tool box which is 2 to 3 steps away from place <strong>of</strong> assembly (index parameter<br />

A6). The hardware such as bolts, washers and nut are kept in storage rack which is 3 to 4 steps away from place <strong>of</strong><br />

assembly (index parameter <strong>of</strong> A10).<br />

Figure 1. Assembly Main Line Stage I<br />

The RPT assembly activity is having 41 sequences <strong>of</strong> operations, standard time <strong>of</strong> these activities were noted from<br />

the existing MOST sheet. The parameters and index numbers in terms <strong>of</strong> TMU for each operation were identified<br />

using “activity having MOST Data Card”.The operation time (in seconds) calculations based on parameters and<br />

index numbers are done for each operation. The time for a sequence model in BasicMOST is obtained by adding the<br />

index numbers and then multiplying the sum by (0.36 * FRQ/DIV). FRQ represents the frequency <strong>of</strong> the repeated<br />

elements. DIV (division) refers to the two or more elements done simultaneously by an operator.<br />

Higher index numbers <strong>of</strong> the parameters lead to higher work contents. Hence, the parameters with higher index<br />

numbers (more than 2) were critically analyzed.<br />

Using the MOST estimation <strong>of</strong> operation pertaining to 41 sequences <strong>of</strong> operations involved in RPT Assembly is<br />

carried out; details <strong>of</strong> establishing standard operation time for one activity ‘move towards storage rack’is discussed<br />

below.<br />

4.1 Establish Standard Time for Move towards Storage Rack<br />

This operation involves move 3 to 4 steps towards storage rack by an operator for collecting the M12 bolt, M12 lock<br />

washer and M12 flat washer,for this motion index parameter is A6. The standard time in seconds for the sequence <strong>of</strong><br />

index parameter A6 is;<br />

(A) * (0.36 * FRQ/DIV)<br />

(6) * (0.36* 1/1) = 2.16 seconds<br />

The index number for walking towards storage rack is 6 (A6). This index number is relatively high; efforts were<br />

made to find the alternative movements to reduce this index number by personally observing the worker’s<br />

movements.<br />

821


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

By providing bins near to the place <strong>of</strong> assembly the operator movements reduced from 3 to 4 steps <strong>of</strong> walking<br />

distance to within reach <strong>of</strong> operator hand movement, hence this index number is reduced from A6 to A1.The revised<br />

standard time in Seconds for the sequence <strong>of</strong> index parameter A1 is;<br />

(A) * (0.36 * FRQ/DIV)<br />

(1) * (0.36* 1/1) = 0.36 seconds<br />

The time reduction for this particular activity is (2.16 – 0.36) = 1.8 seconds<br />

MOST was applied to remaining 40 activities <strong>of</strong> RPTAssembly. After evaluating the actual process it was identified<br />

that 10 operations were found to be taking more time than required in RPT Assembly,The new time standards were<br />

established for these activities which are shown inTable 1.<br />

Table 1. Details <strong>of</strong> Operation Time Reduction<br />

Existing<br />

Modified Reductio<br />

Operation Time<br />

Time n in Time<br />

Name (Seconds<br />

(Seconds) (Seconds)<br />

)<br />

Collect the<br />

Hardware<br />

2.16 0.36 1.8<br />

Insert Flat and<br />

Lock washers in 7.92 3.6 4.32<br />

Bolt<br />

Move towards<br />

Tool Box<br />

2.16 0.36 1.8<br />

Insert Socket in<br />

Tool and<br />

graspthe<br />

4.32 1.08 3.24<br />

pneumatic pipe<br />

Disengage the<br />

socket and tool<br />

3.24 0.36 2.88<br />

Movetowards<br />

Storage Rack<br />

2.16 0.36 1.8<br />

Insert Flat and<br />

Lock washers in 7.92 3.6 4.32<br />

Bolt<br />

move towards<br />

Tool Box<br />

2.16 0.36 1.8<br />

Place the Socket 4.32 1.08 3.24<br />

Disengage the<br />

Socket<br />

2.16 1.08 1.08<br />

Total 38.52 12.24 24.1<br />

Collect the Hardware: Move 3 - 4 steps towards storage rack for collect the M12 bolt, M12 lock washer and M12<br />

flat washer.<br />

Insert Flat and Lock washers in Bolt: Place M12 Lock washer and M12 flat washer into the M12 bolt and then<br />

return to place <strong>of</strong> assembly by 3 to 4 steps<br />

Move towards Tool Box: Move 3 to 4 steps towards Tool Box<br />

Insert Socket in Tool and grasp the pneumatic pipe: Put the socket inside the tool and move 1 to 2 steps towards<br />

super structure for grasp the pneumatic pipe<br />

Disengage the socket and tool and move towards tool box: Disengage the socket and tool and move 1 to 2 steps<br />

towards tool box<br />

Move towards Storage Rack: Move 3 - 4 steps towards storage rack to collect the M10 bolt, M10 lock washer and<br />

M10 flat washer<br />

822


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Insert Flat and Lock washers in Bolt: Place M10 Lock washer and M10 flat washer into the M10 bolt and then return<br />

to place <strong>of</strong> assembly by 3 to 4 steps<br />

Move towards Tool Box: Move 3 to 4 steps to collect tool and socket<br />

Place the Socket: Put the socket inside the tool<br />

Disengage the Socket: Disengage the socket and tool<br />

5. Establishing New Operation Time in Chassis Preparation Area<br />

The higher index parameter in operations <strong>of</strong> assembly activity represent higher time value which involve<br />

considerable amount <strong>of</strong> time during walking, bending, grasping, moving, control, placement, process time, etc. Such<br />

operations <strong>of</strong> Assembly activity indicate the higher probability <strong>of</strong> modification and reduction <strong>of</strong> time involved in<br />

existing chassis preparation area by following parameters.<br />

1) Movement from the place <strong>of</strong> assembly to the ‘Storage Rack’.<br />

2) Movement from the place <strong>of</strong> assembly to the ‘Tool Box’.<br />

3) Engaging and disengaging <strong>of</strong> ‘Pneumatic Tool’ and ‘Socket’ during assembly.<br />

The Modifications in operations can be made by proving facilities;<br />

(a) Providing Bins.<br />

(b) Providing hooks.<br />

(c) Keep separate Pneumatic Tools for the different sockets, both <strong>of</strong> them in engaged condition before the assembly.<br />

The bins provide on the decking fixtures <strong>of</strong> “Rear Power Train” and on “Front Suspension LH and RH” at Assembly<br />

Main Line stage I which avoids movement from place <strong>of</strong> assembly to the storage rack to procure hardware and return<br />

back. The bins are provided with partitions where hardware is kept which helps in easy identification and grasping <strong>of</strong><br />

the hardware.Similar Bins are provided on the “Pantograph I Arrest Arms” at the Assembly Main Line stage II.<br />

The hooks provided at legs <strong>of</strong> decking fixtures reduce the movements <strong>of</strong> tool box to assembly area. The pneumatic<br />

and sockets are placed on the hooks. The tool and sockets are assembled position instead <strong>of</strong> separately this<br />

alsoreduces the engaging and disengaging time <strong>of</strong> tool and socket. Hooks provided at legs <strong>of</strong> “Pantograph I Arrest<br />

Arms” reduce the movements <strong>of</strong> tool box to assembly area.<br />

The operations are modified by providing bins, hooks at the “Decking Fixtures” and “Pantograph I Arresting Arms”<br />

at the “Chassis Preparation Area”. The MOST is applied to modified chassis preparation area. The modified<br />

operation times for Assembly Main Line Stage I and Stage II are421.54 seconds (7.025 minutes) and 383.4 Seconds<br />

(6.39 minutes) respectively shown in Table 2.<br />

Table 2. Details <strong>of</strong> Established Standard Times<br />

Stage<br />

Assembly Operation<br />

Existing Standard Time<br />

(Sec)<br />

Established<br />

Time (Sec)<br />

Standard<br />

1<br />

2<br />

Rear power Train 166 139.3<br />

Front Suspension LH 150 99.72<br />

Front Suspension RH 146 95.76<br />

Anti-Roll Bar 125 86.76<br />

Total 587 421.54<br />

Steering Rack 142.5 105.8<br />

Proportionating valve<br />

and 3 - way 123.12 100.8<br />

Connector<br />

Bundy Tubes <strong>20</strong>9.1 176.7<br />

Total 474.72 383.3<br />

Table 3 shows MOST estimation sheet with newly established standard time for RPT Assembly operation. Similarly<br />

MOST is applied to remaining assembly activities in chassis preparation area and the new time standards were<br />

823


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

established. Due to space limitation details <strong>of</strong> EST for Front Suspension, Bundy Tubes, Steering Rack,<br />

Proportionating Valve and 3 way connectors are not presented in the paper.<br />

Conclusion<br />

The detailed study <strong>of</strong> operation time in chassis preparation area using MOST has identified that operation times for<br />

Assembly Main Line Stage I and Stage II are 587 seconds (9.79 min) and 474.48 seconds (7.9 min) respectively.<br />

These operation times were critically analyzed with respect to index numbers based on TMU. The operations are<br />

modified by providing bins, hooks at the ‘decking fixtures” and ‘pantograph I arresting arms” at the ‘chassis<br />

preparation area’. The modified operation times for assembly main line Stage I and Stage II are 421.54 seconds<br />

(7.025 minutes) and 383.4 seconds (6.39 minutes) respectively.<br />

This work has revealed that the MOST can be effectively utilized for all the three sequence models such as ‘General<br />

Move’, ‘Control Move’, and ‘Tool Use’. These models were effectively used in the present work to establish new<br />

standard times for certain activities and eliminate unnecessary movements.<br />

Acknowledgement<br />

The authors are grateful to the management <strong>of</strong> Mahindra Reva Electric vehicles Pvt Ltd for providing permission to<br />

carry out the work. Sincere thanks are also due to Mr. Narayana Kutty, GM Production Engineering Department for<br />

helping our team in the Shop floor.The authors also thank Ms. Shaheen for help in research work.<br />

Reference<br />

[1] Razmi, Jafar; Shakhs-Niyaee, Majid (<strong>20</strong>08) Developing a specific predetermined time study approach: an<br />

empirical study in a car industry. Volume <strong>19</strong>, pp. 454-460, (7)<br />

[2] Norashikin Binti Rahman, (<strong>20</strong>07). “Work Study for Labor Productivity Improvement Utilizing Process<br />

Mapping and MOST”., Dissertation <strong>University</strong> Teknikal, Malaysia Melaka.<br />

[3] Ashish R. Thakre, Dhananjay A. Jolhe, Anil C. Gawande, "Minimization <strong>of</strong> Engine Assembly Time by<br />

Elimination <strong>of</strong> Unproductive Activities through 'MOST'," icetet, pp.785-789, <strong>20</strong>09 Second International<br />

Conference on Emerging Trends in Engineering & <strong>Technology</strong>.<br />

[4] A. Abduelmula and C. Wagner., ’Design and Evaluation <strong>of</strong> Lean Manufacturing Cells: A Simulation Model’,<br />

Industrial Engineering Department, Visteon Corporation, Sterling Heights, Michigan 48310, USA.<br />

[5] Kjell B, Zandin, “MOST® Work Measurement Systems”, 3rd Edition, <strong>20</strong>08.<br />

824


Sl<br />

No.<br />

Sequence <strong>of</strong> operation<br />

Table 3 MOST Sheet with New Established Standard Time for Modified Rear Power Train Assembly<br />

GET<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

PUT<br />

CONTROLL<br />

ED MOVE<br />

A B G A B P M X I<br />

TOOL<br />

ACTION<br />

F/L/C/<br />

S/M/R<br />

/T<br />

RETUR<br />

N<br />

A<br />

T<br />

M<br />

U<br />

freq<br />

men<br />

Established<br />

Standard<br />

Time (EST)<br />

in sec<br />

1 Move 2 to 3 steps towards storage rack and Get the chain hooks and return 6 3 6 15 1 1 5.4<br />

2 place one end <strong>of</strong> chain hook to the hoist 1 6 1 8 1 1 2.88<br />

3 Place and align other end chain hooks to Seat on the power train 1 3 3 1 8 2 1 5.76<br />

4 Grasp the toggle switch within reach and push the button to lift the power train 1 1 10 12 1 1 4.32<br />

5<br />

Get power train within reach and move power train about 2 to 3 steps with<br />

resistance towards decking fixture and align on it<br />

1 3 3 1 8 1 1 2.88<br />

6<br />

Grasp the toggle switch within reach and push the button to down the power train<br />

on decking fixture<br />

1 1 10 12 1 1 4.32<br />

7<br />

Move decking fixture about 3 to 4 steps towards chassis rear side with high control<br />

along the guide path<br />

1 1 10 3 15 1 1 5.4<br />

8 Press the wheel lock in decking fixture 1 1 1 3 2 1 2.16<br />

9 Press 2 Up switch in decking fixture to lift the power train to the required height 1 1 1 3 2 1 2.16<br />

10 Get the trailing arm within 2 steps and align by putting into the chassis bracket 3 3 1 3 3 13 1 1 4.68<br />

11<br />

Move hand within reach towards Bin to collect the M12 bolt, M12 lock and M12<br />

flat washer<br />

1 1 1 1 0.36<br />

12 Grasp M12 bolt, M12 lock washer, M12 flat washer, M12 nut 1 3 1 5 2 1 3.6<br />

13 place M12 Lock washer and M12 flat washer into the M12 bolt and 1 3 1 5 2 1 3.6<br />

14<br />

Loose fit the bolt into the coupling hole <strong>of</strong> chassis bracket and trailing arm by wrist<br />

action<br />

1 3 6 10 2 1 7.2<br />

15<br />

Place the M12 nut into bolt and loose fit into bolt end (loose tight by 3 rev <strong>of</strong> wrist<br />

action)<br />

1 3 6 10 2 1 7.2<br />

16 move hand towards Tool Box within reach for get tool and socket 1 1 1 1 0.36<br />

17<br />

Get the Pneumatic Tool - LTV38 R70-13 with Socket - <strong>19</strong>x3/8" deep socket and<br />

spanner from the tool table<br />

1 3 1 5 3 1 5.4<br />

18 move 1 to 2 steps towards super structure for grasp the pneumatic pipe 3 3 1 1 1.08<br />

<strong>19</strong> Grasp the Pneumatic pipe from super structure and return to assembly area 3 1 6 10 1 1 3.6<br />

<strong>20</strong> Place pneumatic pipe to tool with socket (push with light pressure) 1 3 1 5 1 1 1.8<br />

825


Sl<br />

No.<br />

826<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 3 MOST Sheet with New Established Standard Time for Modified Rear Power Train Assembly (Continued)<br />

Sequence <strong>of</strong> operation<br />

GET<br />

PUT<br />

CONTROL<br />

LED MOVE<br />

TOOL<br />

ACTION<br />

RETURN<br />

T<br />

M<br />

U<br />

freq<br />

men<br />

Established<br />

Standard<br />

Time (EST)<br />

in sec<br />

A B G A B P M X I<br />

F/L/C/S<br />

/M/R/T<br />

A<br />

21 place the ring spanner on the M12 nuts by one hand 1 3 1 5 2 1 3.6<br />

22 Tighten the bolts by operating pneumatic tool (7 to 8 revolution) 1 3 16 1 21 2 1 15.12<br />

23 Disengage the Pneumatic pipe 1 3 1 5 1 1 1.8<br />

24 Place the Pneumatic pipe by moving 2 to 3 steps away 6 1 7 1 1 2.52<br />

25 Move hand within reach to place the tool with socket 1 1 1 1 0.36<br />

26 Place aside the tool and socket in tool box 1 3 1 5 1 1 1.8<br />

27 Return to lift and tilt equipment by 2 to 3 steps 6 6 1 1 2.16<br />

28<br />

Get the pan hard rod form the power train by moving 1 to 2 steps and place the<br />

Pan hard rod End to the chassis top joint bracket with precision alignment<br />

3 3 1 3 1 1 12 1 1 4.32<br />

29<br />

Move hand near Bin within reach collect the M10 bolt, M10 lock washer and<br />

M10 flat washer<br />

1 1 1 1 0.36<br />

30<br />

place M10 Lock washer and M10 flat washer into the M10 bolt and then Return<br />

to place <strong>of</strong> assembly by 3 to 4 steps<br />

1 3 1 5 2 1 3.6<br />

Grasp the bolt from pocket and Place the bolt at coupling point <strong>of</strong> Pan hard rod<br />

31 End and chassis top joint bracket with precision alignment and then loose tight 1 3 1 3 1 6 15 1 1 5.4<br />

by 3 turns <strong>of</strong> wrist action<br />

32 move hand within reach near hook to collect tool and socket 1 1 1 1 0.36<br />

33 Get the Pneumatic tool and socket from hooks provide near place <strong>of</strong> assembly 1 3 1 5 2 1 3.6<br />

34 1 to 2 steps towards super structure for grasp the pneumatic pipe 3 3 1 1 1.08<br />

35 Grasp the Pneumatic pipe from1 to 2 steps away and return 3 1 6 10 1 1 3.6<br />

36 Place pneumatic pipe to tool with socket (push with light pressure) 1 3 1 5 1 1 1.8<br />

37 Tighten the bolts by operating pneumatic tool (7 to 8 revolution) 1 3 16 1 21 1 1 7.56<br />

38 Disengage the Pneumatic pipe 1 3 1 5 1 1 1.8<br />

39 Place the Pneumatic pipe by moving 2 to 3 steps away 3 1 4 1 1 1.44<br />

40 move 1 to 2 steps towards tool box 3 3 1 1 1.08<br />

41 Place aside the tool and socket in tool box 1 3 1 5 1 1 1.8<br />

Total Time for Modified Rear Power Train Assembly 139.3


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

METAHEURISTIC DESIGNED FOR CALCULATING MAKESPAN OF<br />

COMPREHENSIVE SCHEDULING PROBLEMS<br />

Sunil Kumar 1 , Rajender Kumar Tayal 2<br />

1 Prannath Parnami Institute <strong>of</strong> Management &<strong>Technology</strong>, Hisar (Haryana)<br />

2 Government Polytechnic Sirsa (Haryana)<br />

e-mail: sunilchander<strong>19</strong>84@gmailmail.com<br />

Abstract:<br />

Scheduling is necessary to deal with internal and external disruption faced in real life manufacturing environments.<br />

Scheduling is a process <strong>of</strong> allocation <strong>of</strong> resources to tasks over a given time period. The objective <strong>of</strong> scheduling is to<br />

ensure maximum utilization <strong>of</strong> the plant at minimum cost. Main objective <strong>of</strong> the problem is to determine best job<br />

sequence that optimizes the makespan (C max ) i.e. total completion time <strong>of</strong> the job for a job shop problem . In addition<br />

to makespan various factors like completion time <strong>of</strong> the jobs on each machine, machine loading time, machine idle<br />

time among all these machines are also determined. An asexual reproduction genetic algorithm with mutation<br />

strategies is developed to solve the single-objective job shop scheduling with setup time. A source code is developed<br />

in MATLAB to solve the aforesaid problem and it is tested on various bench mark problems and other problems<br />

taken from literature. Results are compared with those available in the literature associated with this problem. The<br />

findings indicate that the source code developed in MATLAB using genetic algorithm can find good solutions within<br />

a very short computational time.<br />

Key Words: Job Shop Scheduling, Genetic Algorithm, Makespan.<br />

1. INTRODUCTION<br />

Scheduling is the process <strong>of</strong> deciding how to commit resources between varieties <strong>of</strong> possible tasks. It is a decisionmaking<br />

process in which allocation <strong>of</strong> resources to tasks over given time period [7]. Single machine shop, Parallel<br />

machine shop, Flow shop, Flexible flow shop, Job shop, Flexible job shop and Open shop are various types <strong>of</strong><br />

scheduling shop. In job shop the order in which jobs visits the machines is different and objective is to determine the<br />

order or sequence for processing a set <strong>of</strong> jobs through several machines in an optimal manner. Job shop scheduling<br />

problem received considerable attention in the literature and as a consequence a variety <strong>of</strong> scheduling algorithms or<br />

procedures for certain types <strong>of</strong> job shops were evolved.<br />

2. Literature review<br />

Various research work’s on scheduling were conducted by Indian and international scientists. Some <strong>of</strong> the basic<br />

literature papers have been collected for the study, these are mainly related to job shop scheduling problem. Sun et<br />

al. [13] addressed the job shop scheduling problem with release dates due dates and sequence dependent setup times<br />

with the scheduling objective to minimize the weighted sum <strong>of</strong> squared tardiness (maximum (lateness,0)). The<br />

problem is NP – hard whose optimal solution is difficult to obtain. Focacci et al. [17] addressed the job shop<br />

scheduling problem with sequence dependent setup times and alternative resources where optimization criteria are<br />

both make span and sum <strong>of</strong> setup times. Artigues and Roubellat [18] presented a Petri net approach for on-line and<br />

<strong>of</strong>f-line scheduling <strong>of</strong> a job shop with job release dates, sequence dependent family setup times and the maximum<br />

lateness objective. Cheung and Zhou [6] addressed the job shop problem with separable sequence dependent setup<br />

times. The objective <strong>of</strong> their problem was to minimize makespan, (i.e. the completion times <strong>of</strong> all jobs) they first<br />

described the problem with a mixed integer programming model. Marco Ballicu et al. [12] considered the classical<br />

representation job shop scheduling problems in terms <strong>of</strong> disjunctive graphs. Their objective was minimization <strong>of</strong><br />

makespan. Chan Choi and Dae-Sik Choi [9] considered job shop scheduling problem with alternative operations and<br />

sequence-dependent setups. Artigues et al. [<strong>19</strong>] proposed a new exact solution algorithm for the job shop problem<br />

with sequence-dependent setup times Balas et al. [5] deal with a variant <strong>of</strong> the job shop scheduling problem. Yaqin<br />

Zhou et al. [4] solved the job shop scheduling problems with setups using biological immune algorithm. Manikas<br />

and Chang [13] studied a multi-objective job shop scheduling problem with separable sequence-dependent setups.<br />

Aldakhilallab and Ramesh [<strong>20</strong>] proposed cyclic scheduling for a job shop manufacturing environment. Two efficient<br />

cyclic scheduling heuristic for job shop environments were developed. Each heuristic generate an efficient and<br />

feasible cycle production schedule for a job shop in which a single product was produced repetitively on a set <strong>of</strong><br />

machines was to determine an efficient and feasible cyclic schedule which simultaneously minimizes flow time and<br />

827


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

cycle time. Low et al. [2] investigated the benefits <strong>of</strong> lot splitting in job shop scheduling with setup. The objective is<br />

to determine a lot splitting strategy so that an optimal schedule can be obtained with the minimized make span.<br />

3. Problem Statement:<br />

We have considered a Static and Deterministic job shop scheduling problem with sequence dependent setup<br />

times .The objective is to minimize the make span (C max ) i.e. completion time <strong>of</strong> the last job including determine<br />

best job sequence for the problem using an asexual reproduction genetic algorithm, completion time <strong>of</strong> the jobs on<br />

each machine, machines loading time, idle time for each machine, percentage <strong>of</strong> machine utilization, illustrate the<br />

critical machines for the job shop problems.<br />

3.1 Assumptions<br />

• Machines never break down and are available throughout the scheduling period.<br />

• All the jobs and machines are available at time zero.<br />

• All processing time on the machine are known, deterministic and finite.<br />

• Setup times for operations are sequence dependent and are not included in processing times<br />

• Pre-emption is not allowed.<br />

• Each machine is continuously available for assignment, without significant division <strong>of</strong> the scale into<br />

shifts or days and without any breakdown or maintenance. The first machine is assumed to be ready<br />

whichever and whatever job is to be processed on it first.<br />

• Machines may be idle.<br />

• Splitting <strong>of</strong> job or job cancellation is not allowed.<br />

3.2 Parameter<br />

i =Index for machines i=1,2,3…m Cj=Completion time <strong>of</strong> job ‘j’<br />

j=Index for jobs j=1,2,3….n<br />

4. Genetic algorithm:<br />

Genetic Algorithm was introduced by John<br />

Holland. A genetic algorithm is a problem solving method that uses genetics as its model <strong>of</strong> problem solving [1]. It<br />

is a search technique to find approximate solutions for optimization and search problems. Genetic Algorithm (GA)<br />

is Just like as a machine which derives its behavior from the image <strong>of</strong> the processes in growth <strong>of</strong> nature [1]. GA<br />

handles a population <strong>of</strong> possible solutions. Each solution is represented through a chromosome coding and all the<br />

possible solutions into a chromosome. A reproduction operator is determined. Reproduction operators are applied<br />

directly on the chromosomes. Selection is done by using a fitness function. Selection is able to compare each<br />

individual in the population. Each chromosome has an associated value corresponding to the fitness function and<br />

used to perform mutations and recombinations over solutions [8].<br />

Genetic algorithm loop over an iteration process to develop the new population. Each iteration process consists <strong>of</strong><br />

the following steps:<br />

• Selection: The first step is consisting <strong>of</strong> selecting individuals for reproduction. This selection is done<br />

randomly with a probability depending on the relative fitness <strong>of</strong> the individuals so that best ones are chosen<br />

for reproduction than the poor ones.<br />

• Reproduction: In the second step, children are produced by the selected individuals. For generating new<br />

chromosomes, the algorithm can use both recombination and mutation.<br />

• Evaluation: Then the fitness <strong>of</strong> the new chromosomes is evaluated.<br />

• Replacement: During the last step, individuals from the old population are killed and replaced by the new<br />

ones.<br />

Genetic algorithm differs from other optimization and search procedures in following ways:<br />

• Working <strong>of</strong> genetic algorithm is according to the parameter set with the help <strong>of</strong> codes, not the parameters it<br />

selves.<br />

• Searching is takes place in genetic algorithm from a population <strong>of</strong> points, not for a single one.<br />

828


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

• Objective function information is used in genetic algorithm, not its derivatives.<br />

• Probabilistic transition rules are used only in genetic algorithm, so deterministic rules are not used.<br />

Genetic algorithm require the natural parameter for the set <strong>of</strong> the optimization problem to be coded as a finite-length<br />

string (similar to chromosomes in biological systems) containing characters, features (analogous to genes), taken<br />

from some finite-length alphabet. Usually, the binary alphabet that consists <strong>of</strong> only 0 and 1 is taken. Each feature<br />

takes on different values and may be located at different positions. The total package <strong>of</strong> strings is called a structure or<br />

population.<br />

Parameters Settings<br />

• Population Size (Ps): Population size refers to the search space i.e. algorithm has to search the specified<br />

number <strong>of</strong> sequences and larger the sequence, more the time is needed to execute the process <strong>of</strong><br />

genetic algorithm. As in flow shop scheduling number <strong>of</strong> possible sequences is equal to n! .Therefore, if the<br />

population size is equal to n! .Than application <strong>of</strong> genetic algorithm has no use. So, larger the initial<br />

population that is created, the more likely the best solution from it will be closer to optimal but at the cost <strong>of</strong><br />

increased execution time. So, in the present work it is set to 50 irrespective the size <strong>of</strong> problem to<br />

solve in a reasonable time.<br />

• Crossover function: Crossover is the breeding <strong>of</strong> two parents to produce a single child. That child<br />

has features from both parents and thus may be better or worse than either parent as per fitness<br />

function. Analogous to natural selection, the more fit the parent, the more likely the generation have.<br />

Different types <strong>of</strong> crossover have used in literature and after having experimental comparison , we have<br />

found that the order crossover(OX) provides the best results for the single objective problem<br />

considered among the partially matched crossover (PMX), Order crossover (OX), Cycle crossover<br />

(CX) and single point crossover (SPX). So, in the present work, we have applied the order crossover<br />

(OX).<br />

• Mutation function: For each sequence in the parent population a random number is picked and by<br />

giving this sequence a percent chance <strong>of</strong> being mutated. If this sequence is picked for mutation then a<br />

copy <strong>of</strong> the sequence is made and operation sequence procedure reversed. Only operations from<br />

different jobs will be reversed so that the mutation will always produces a feasible schedule. From the<br />

experiment, it is found that reciprocal exchange (RX) proves to be good with combination <strong>of</strong> order<br />

crossover (OX) and hence been used.<br />

• Crossover fraction: It is the fraction for which crossover has to perform on the parents as per population<br />

size in each generation. This is fixed to 0.8 i.e. crossover should be done on 80% <strong>of</strong> total population size.<br />

• Mutation Fraction: It is also used as fraction and specified for which process <strong>of</strong> mutation has to perform<br />

on the parents as per population size in each generation. This is fixed to 0.15 i.e. Mutation should be done<br />

on 15% <strong>of</strong> total population size.<br />

• Stopping condition: Stopping condition is used to terminate the algorithm for certain numbers <strong>of</strong><br />

generation. We have used time limit base stopping criteria. So, the algorithm stops when maximum time<br />

limit reaches n×m×0.25seconds.<br />

Job shop scheduling problem is NP-hard by nature. This complexity is further increased when additional<br />

constraints are added to solve the real world problem. The exact methods could solve only small size<br />

problems within acceptable time periods. Although they produce exact solution, they <strong>of</strong>ten simplify the<br />

instances. Meta-heuristics are semi-stochastic approaches that can produce near optimal solutions within<br />

less computational time. These approaches adapt to the problem situation. Among the meta-heuristic<br />

methods, genetic algorithms are techniques based on human evolution that were widely used to solve large<br />

optimization problems. The properties <strong>of</strong> genetic algorithms such as the use <strong>of</strong> a population <strong>of</strong> solutions,<br />

problem–independence enables them to be effectively used for job shop scheduling. Asexual<br />

reproduction genetic algorithm involves the formation <strong>of</strong> <strong>of</strong>fspring’s from a single parent. These<br />

methods always produce feasible solutions and consume very less computational time as compared<br />

to sexual reproduction methods. Therefore these properties <strong>of</strong> asexual reproduction methods enabled<br />

them to be effectively used for the complex job shop problem involved in this research<br />

829


5. Results and discussions<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

In Job shop problem, first <strong>of</strong> all by visualizing the Gantt chart calculate completion time <strong>of</strong> the jobs on each machine,<br />

idle time on each machine, loading time on each machine. Loading time is calculated by taking difference between<br />

completion time <strong>of</strong> the jobs on each machine and idle time <strong>of</strong> each machine.<br />

Job sequence for Scenario: J2-J1-J3-J4-J5-J6<br />

GANNT CHART for Scenario with total completion time =61<br />

In order to evaluate the effectiveness <strong>of</strong> the source code developed in MATLAB, it is first tested on the benchmark<br />

problem [15] and later on, on several other problems [16]. The experimentations with these problems confirmed<br />

that the source code developed in MATLAB is able to find good solutions <strong>of</strong> the addressed problem . Results<br />

lie between the limits <strong>of</strong> upper bound & lower bound values [15] which are stated in various literatures, related to job<br />

shop scheduling problems.<br />

Overall the results indicate that the source code developed for finding the performance <strong>of</strong> this job shop scheduling<br />

problem is able to generate the results which are comparable or better than the literature associated with this<br />

problem. Currently, the source code generates the schedule which lies within the lower bound and upper bound <strong>of</strong><br />

the bench mark instances [15] taken from the literature. Comparison chart shows that results (calculated values)<br />

lies between the limits <strong>of</strong> upper bound & lower bound values.<br />

Comparison chart for scenario:-<br />

830


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

6. Conclusions:<br />

In this work scheduling problem in a real time job shop environment is solved, for the single objective<br />

problem to minimize(optimization) the make span (C max ) . This objective is chosen because minimizing the make<br />

span results into minimizing the manufacturing lead time. An asexual reproduction genetic algorithm with mutation<br />

strategies is used to solve the scheduling problem.<br />

In order to evaluate the effectiveness <strong>of</strong> the source code developed in MATLAB, it is first tested on the benchmark<br />

problem [15] and later on, on several other problems [16]. The experimentations with these problems confirmed<br />

that the source code developed in MATLAB is able to find good solutions <strong>of</strong> the addressed problem . Results<br />

lie between the limits <strong>of</strong> upper bound & lower bound values [15] which are stated in various literatures, related to job<br />

shop scheduling problems.<br />

Overall the results indicate that the source code developed for finding the performance <strong>of</strong> this job shop scheduling<br />

problem is able to generate the results which are comparable or better than the literature associated with this<br />

problem. Currently, the source code generates the schedule which lies within the lower bound and upper bound <strong>of</strong><br />

the bench mark instances [15] taken from the literature.<br />

References<br />

[1] Falkenauer, E., and Bouffouix, S., (<strong>19</strong>91),” A Genetic Algorithm for the Job- Shop”, Proceedings <strong>of</strong><br />

the IEEE International Conference on Robotics and Automation, Sacremento, California, USA, pp. 824-<br />

829.<br />

[2] Low. C,Hsu, C.-M., Huang, K.I., <strong>20</strong>04. “Benefits <strong>of</strong> lot splitting in job-shop scheduling”, International Journal<br />

<strong>of</strong> Advanced Manufacturing <strong>Technology</strong> 24, 773–780<br />

[3] Artigues, C., Roubellat, F., <strong>20</strong>02 “An efficient algorithm for operation insertion in a multi-resource job-shop<br />

scheduling with sequence-dependent setup times”,Production Planning and Control 13, 175–186.<br />

[4] Yaqin,Zhou et al. <strong>20</strong>05. “Job shop scheduling problems with setups using biological immune algorithm”.<br />

[5] Balas, E., Simonetti, N., Vazacopoulos, A., <strong>20</strong>05. “Job shop scheduling with setup times,deadlines and<br />

precedence constraints”, In: Proceedings <strong>of</strong> the 2nd Multidisciplinary International Conference on Scheduling:<br />

Theory and Applications, New York, USA, July 18–21, <strong>20</strong>05, pp. 5<strong>20</strong>–532<br />

[6] Cheung, W., Zhou, H., <strong>20</strong>01. “Using genetic algorithms and heuristics for job shop scheduling with sequencedependent<br />

setup times”, Annals <strong>of</strong> Operations Research 107, 65–81.<br />

.[7 French, S., (<strong>19</strong>82), “Sequencing and Scheduling - An Introduction to the Mathematics <strong>of</strong> the Job-Shop”,<br />

John-Wiley and Sons, New York. 168, <strong>19</strong>90.<br />

[8] Camino, Ramiro., <strong>20</strong>08. “Proposed a hybrid algorithm called mimetic algorithm for job shop scheduling<br />

for job shop scheduling with setup times with the objective <strong>of</strong> make span minimization”.<br />

[9] Choi, I.C., Choi, D.S., <strong>20</strong>02. “A local search algorithm for jobshop scheduling problems with alternative<br />

operations and sequence-dependent setups”, Computers and Industrial Engineering 42, 43–58.<br />

[10] Ballicu, M., Giua, A., Seatzu, C., <strong>20</strong>02. “Job-shop scheduling models with set-up times”, Proceedings <strong>of</strong> the<br />

IEEE International Conference on Systems, Man and Cybernetics 5, 95–100.<br />

[11 Pinedo, M., (<strong>20</strong>01), “Scheduling: Theory, Algorithms, and Systems”, Prentice Hall, New York. Third<br />

edition.pp.18.<br />

[12] .Marco Ballicu , Alessandro Giua <strong>20</strong>02. “Studied the classical representation job shop scheduling problems in<br />

terms <strong>of</strong> disjunctive graphs”. Their objective was minimization <strong>of</strong> makespan.<br />

[13] Manikas , Chang <strong>20</strong>09. “Studied a multi-objective job shop scheduling problem with separable sequencedependent<br />

setups”.<br />

[14] Ali Allahverdi ,H.M.Soroush “A survey <strong>of</strong> scheduling problems about the significance <strong>of</strong> reducing setup times<br />

or costs”, European Journal <strong>of</strong> Operational Research 187 (<strong>20</strong>08) 978–984.<br />

[15] E.Taillard,<strong>19</strong>92. “Benchmarks for basic scheduling problems” Ecole Polytechnique Fdddrale de Lausanne,<br />

Departement de Mathmatiques, CH-1015 Lausanne,Switzerland.<br />

[16] Tsuyoshi Satake, Katsumi Morikawa, Katsuhiko Takahashi, Nobuto Nakamura <strong>19</strong>99, “Simulated annealing<br />

approach for minimizing the makespan<strong>of</strong> the general job-shop”.<br />

[17] Focacci et al “Solving scheduling problems with setup times and alternative resources”, In: Proceedings <strong>of</strong> the<br />

Fifth International Conference on Artificial Intelligence Planning and Scheduling, Breckenbridge, Colorado,<br />

USA, pp. 92–101.<br />

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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[18] Artigues, C., Roubellat, F., <strong>20</strong>01. “A Petri net model and a general method for on and <strong>of</strong>f-line multi-resource<br />

shop floor scheduling with setup times”, International Journal <strong>of</strong> Production Economics 74, 63–75..<br />

[<strong>19</strong>] Artigues, C., Belmokhtar, S., Feillet, D., <strong>20</strong>04. “A new exact solution algorithm for the job shop problem with<br />

sequencedependent setup times”, In: Regin, J.C., Rueher, M. (Eds.), 1st International Conference on Integration<br />

<strong>of</strong> AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, Lecture Note<br />

in Computer <strong>Science</strong>, vol. 3011. Springer, pp. 37–49.<br />

[<strong>20</strong>] Aldakhilallah, K.A., Ramesh, R., <strong>20</strong>01. “Cyclic scheduling heuristics for a re-entrant job shop manufacturing<br />

environment”,International Journal <strong>of</strong> Production Research 39, 2635–2657.<br />

832


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

AN EFFICIENT APPROACH OF GOOD MANUFACTURING<br />

FLEXIBILITY BY FMS AND RMS WITH MINIMIZING THE OVERALL<br />

WASTAGE BY JIT<br />

Virender Chahal<br />

Department Of Mechanical Engg.,HCTM, Kaithal<br />

e-mail: vchahal68@gmail.com<br />

Abstract<br />

Today, the customer demands a lot <strong>of</strong> flexibility and product to reconfigure operations for new challenges. As per the<br />

latest manufacturing, there are so many Flexible techniques. But with this Flexibility, quality <strong>of</strong> product is also<br />

required which is comes out by the JIT implementation. This paper study out the positive, negative and applications<br />

<strong>of</strong> FMS, RMS and also benefit <strong>of</strong> using the JIT in manufacturing. The latest inversions in reconfigurable<br />

manufacturing and FMS, affects our way <strong>of</strong> working. The paper is concluded with a present and future study on<br />

flexible and reconfigurable manufacturing system by implementing <strong>of</strong> JIT in these systems. JIT stands for producing<br />

necessary quantities as the necessary time. The ultimate aim <strong>of</strong> JIT is to concentrate on lot less, repetitive<br />

manufacturing, with only one unit <strong>of</strong> work in process and no stock <strong>of</strong> finished goods inventories with FMS AND<br />

RMS. In this paper, we focus on the way <strong>of</strong> manufacturing system by controlling with the help <strong>of</strong> Just In Time (JIT)<br />

control processes. We implement the JIT for better control.<br />

Keywords: Manufacturing systems, Self- evolution, Self- organization, Reconfigurablity, Flexibility, JIT<br />

1. Introduction:<br />

Manufacturing industries provides excellent manufacturing by Flexible and Reconfigurablity manufacturing systems.<br />

But today it is not possible to give customer satisfaction without company satisfaction. So at today the concept is<br />

used named as JIT (just in time). The ability to manage changes and quickly manufacturing and the reduce the<br />

wastage and improve quality <strong>of</strong> the product by JIT. This paper shows the flexibility in manufacturing by RMS and<br />

FMS and also readies the company for world level competition. Success in flexible manufacturing and in the<br />

production system by JIT and also the main purpose is to make a continuous improvement in product quality in<br />

development. Today, the companies must have more flexibility to make system smooth in working but during<br />

flexibility they compromise with the quality, time and wastage <strong>of</strong> raw material. World-class manufacturing<br />

companies have responded to these competitive demands by changing their traditional production system. To<br />

eliminate waste and improve quality, an best approach to production & inventory control called the Just-in-Time<br />

(JIT) system was developed by the Japanese-Taiichi Ohno, but it become famous throughout the world.Taiichi Ohno<br />

was considered to be the creator <strong>of</strong> the Toyota Production system and the father <strong>of</strong> the JIT system. After this<br />

implementation, number <strong>of</strong> companies follows this system for production control. And after it, first time the motor<br />

company FORD came in front <strong>of</strong> us by both <strong>of</strong> these systems : FMS and JIT. The efficiency <strong>of</strong> the production system<br />

is mostly dependent on the percent <strong>of</strong> flexibility as well as being able to reconfigure operations as per new demands.<br />

The flexible manufacturing system and reconfigurable manufacturing system techniques have an important role in<br />

manufacturing industries.<br />

2. Various Techniques in Manufacturing System<br />

There techniques are as follows:<br />

FMS: FMS is defined as a group <strong>of</strong> workstations (mostly comprising <strong>of</strong> NC and CNC machine tools), interconnected<br />

by means <strong>of</strong> an automated material handling and storage system, and controlled by computer integrated<br />

manufacturing system(CIM). The variety <strong>of</strong> product as well as volume is increased in this technique as clear from<br />

fig. 1. The FMS can be differentiated depending on peripherals present as:<br />

‣ Flexible manufacturing modules (FMM)<br />

‣ Flexible manufacturing group (FMG)<br />

‣ Flexible manufacturing cell (FMC)<br />

‣ Flexible manufacturing factory (FMF)<br />

RMS: A reconfigurable manufacturing system (RMS) is a system that is designed for cost-effective Response as per<br />

the manufacturing requirements. The motive <strong>of</strong> implementation <strong>of</strong> RMS is to be able to modify with random changes<br />

in production requirements through reconfiguration Reconfigurable manufacturing system focus on the customer<br />

833


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

requirements and there thinking about products and also take a proper action to fulfill their demands by modification<br />

<strong>of</strong> design etc. With the addition <strong>of</strong> FMS and RMS, both the customer satisfaction and variety <strong>of</strong> product will be<br />

increased as implemented in fig. 2<br />

Dedicated Equipment<br />

high<br />

FMS + RMS<br />

% <strong>of</strong><br />

Vol FMS customer<br />

Satisfaction<br />

FMS<br />

Stand alone nc/cnc<br />

low medium high low medium high<br />

Variety<br />

Figure 2. Application characteristics <strong>of</strong> FMS<br />

Variety<br />

Figure. 3. Implementation <strong>of</strong> FMS & RMS<br />

So these both systems create a lot <strong>of</strong> flexibility in manufacturing but made a successive action by also using the JIT.<br />

3. Technique <strong>of</strong> minimizing the wastage: JIT<br />

Just in time (JIT) is defined as focus attention on eliminating wastage by purchasing or manufacturing just enough <strong>of</strong><br />

right items just in time [2]. It is a Japanese philosophy applied in production which involves having the right item <strong>of</strong><br />

right quality and quantity in the right place and at right. The main pillars <strong>of</strong> JIT are shown in fig. 3<br />

JIT<br />

People Involvement Plant System<br />

Figure 3 Pillars <strong>of</strong> JIT<br />

According to the APICS (American Production and Inventory Control Society), JIT is a philosophy <strong>of</strong> manufacturing<br />

based on elimination <strong>of</strong> all waste and continuous improvement <strong>of</strong> productivity.<br />

The primary elements <strong>of</strong> zero inventories are:-<br />

‣ only required inventory when required<br />

‣ To maximize quality to zero defect<br />

‣ To reduce lead times by reducing set up times, queue length and lot sizes.<br />

The concept <strong>of</strong> JIT is extended to the whole system <strong>of</strong> production i.e-<br />

‣ To manufacture and deliver finished goods just in time to be sold<br />

‣ All assemblies just in time to be assembled into finished goods<br />

‣ Fabricated parts just in time to go into sub-assemblies<br />

‣ Raw material should be at right time<br />

The JIT philosophy is based upon two criteria:<br />

1. Just-in-time (JIT) refers to development and supply <strong>of</strong> needed parts when required.<br />

2. Another way is JI DOKA (self actuation) which means using the full capacity <strong>of</strong> the raw material/work<br />

piece.<br />

3.1 Goals <strong>of</strong> JIT<br />

The various goals <strong>of</strong> JIT are as follows:<br />

‣ Maximize organization ability to complete process<br />

834


‣ Maximize the degree <strong>of</strong> efficiency<br />

‣ Minimize the level <strong>of</strong> wastage <strong>of</strong> material<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3.2 Environmental concerns<br />

Some <strong>of</strong> the environmental concerns that are associated with JIT are given below:<br />

‣ Time: Every action should be at time<br />

‣ Inventory: Inventory should be as pr requirement<br />

‣ Scrap: Scrap must be minimize<br />

4. Types <strong>of</strong> flexibility <strong>of</strong> FMS<br />

There are 11 types <strong>of</strong> manufacturing systems flexibilities as given below:<br />

1. Machine flexibility: The number <strong>of</strong> operations performed without set-up <strong>of</strong> m/c change<br />

2. Process Flexibility: The set <strong>of</strong> part types that can be produced without major set-up changes.<br />

3. Transferring flexibility: Refers to flexibility in transferring various types and sizes <strong>of</strong> components.<br />

4. Routing Flexibility: Flexibility in part chosen and transfer a part from one place to another.<br />

5. Operation Flexibility: The different operation can done by interchanging m/c on work piece.<br />

6. Product Flexibility: Ease to ordering product place in an existing product mix.<br />

7. Actual Flexibility: It’s the ability to overcome concrete given changes.<br />

8. Potential Flexibility: It refers to capability <strong>of</strong> coping with an undefined universe <strong>of</strong> change.<br />

9. Volume Flexibility: The system should have economy <strong>of</strong> scope and not economy <strong>of</strong> scale.<br />

10. Expansion Flexibility: The ease to capable, when needed, through physical change to operational system.<br />

11. Control Program Flexibility: The capability to operate operation by intelligent machines tools and control<br />

s<strong>of</strong>tware system.<br />

4.1 Basic components <strong>of</strong> FMS:<br />

1. Computer controlled production equipment such as CNC machine.<br />

2. Automated material handling and storage system for transferring parts.<br />

3. Computer control to coordinate the activity <strong>of</strong> CNC machine and material handling.<br />

4.2 Advantages <strong>of</strong> Flexible manufacturing system:<br />

Following are the benefits <strong>of</strong> FMS:<br />

1. Increase machine utilization<br />

2. Increase production rate and Productivity<br />

3. Increase quality <strong>of</strong> work<br />

4. Reduce machine required<br />

5. Reduce floor space requirement<br />

6. Reduce inventory<br />

7. Reduce lead time<br />

8. Reduce direct labor requirements<br />

9. Greater responsiveness to change<br />

10. Opportunity for unattended production<br />

4.3 Disadvantages <strong>of</strong> Flexible manufacturing system:<br />

Following are the disadvantages <strong>of</strong> FMS:<br />

1. FMS systems are too costly.<br />

2. It is complicated than transfer lines.<br />

3. Skilled persons are required to operate.<br />

4. Skilled maintenance and repair <strong>of</strong> system required.<br />

4.4 Applications <strong>of</strong> FMS:<br />

The flexible automation is able to a variety <strong>of</strong> manufacturing operations. According to Yang, et al (<strong>20</strong>02), FMS<br />

technology is most rapidly and widely applied in machining operations. FMS is the technology <strong>of</strong> the transfer lines<br />

for high volume low variety work on the one side and stands alone CNC machines for mid to low volume high<br />

variety production on the other side.<br />

835


5. Reconfigurable Manufacturing System (RMS) :<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The reconfigurable manufacturing systems are prepared for specific way <strong>of</strong> manufacturing or modification (Rogers<br />

et al, <strong>20</strong>03).The reconfigurable manufacturing systems are those systems that are designed for Rapid change <strong>of</strong><br />

structure as well as hardware and s<strong>of</strong>tware components. In other words, the reconfiguration is the process <strong>of</strong><br />

changing the present configuration to a new one, which may involve changing the set <strong>of</strong> processes. .RMS goes<br />

beyond the objectives <strong>of</strong> FMS by permitting the reduction <strong>of</strong> Lead-time for realizing new systems and reconfiguring<br />

new systems. It has more flexibility in changing as per demands.<br />

5.1 Benefits <strong>of</strong> reconfigurable manufacturing system<br />

Following are the derived benefits <strong>of</strong> RMS<br />

1 Increased product quality<br />

2 Increased product varieties<br />

3 Minimize lead- time <strong>of</strong> realizing new system<br />

4 Ease prototype developments<br />

5 Providing more flexibility<br />

6 Fast in upgrading and quick action in new technology<br />

5.2 Disadvantages <strong>of</strong> reconfigurable manufacturing system<br />

1 Expensive system<br />

2 Expansive controls<br />

3 Difficult set up <strong>of</strong> machines<br />

4 Difficult selection <strong>of</strong> machine way <strong>of</strong> process and modules<br />

5 Difficult measurement or comparisons for changeability, reconfigurablity<br />

6 Difficult to prepare prototype model<br />

6. Different techniques <strong>of</strong> JIT, RMS and FMS:<br />

From the literature review and according to (Burbidge, et al.<strong>19</strong>91), Reconfigurablity and flexibility can be developed<br />

by adopting different techniques as follows:<br />

1 Control<br />

2 Measuring technique<br />

3 Estimating technique<br />

Minimize wastage <strong>of</strong> money, material, time and other…<br />

Increase production flexibility and customer satisfaction<br />

JIT<br />

FMS + RMS<br />

Provide only production flexibility<br />

FMS<br />

Figure 4. Process parameters <strong>of</strong> JIT, FMS & RMS<br />

7. Factors that affect the implementation <strong>of</strong> JIT, reconfigurable and flexible Systems design<br />

For design any manufacturing system, there are so many factors that can be in mind:<br />

1 Proper Implementation<br />

In the industry, it should be proper implementation for JUST-IN-TIME process and its working output.<br />

2 Cooperate<br />

836


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Its affects ability for reconfiguration <strong>of</strong> the transfer process if the possibilities to change suppliers minimize. Now, it<br />

will improve organization in product and process improvement that will improve capabilities to release high quality<br />

products.<br />

3 Motivations<br />

It provides the strength for doing best result and provides proper implementation <strong>of</strong> JIT, FMS and RMS.<br />

4 Basic roles <strong>of</strong> employees<br />

Employees are the first step for good and future development and overall improvements Future can be make better<br />

by JIT, FNS and reconfigurablity and motivation to employees. So they have a strong role.<br />

5 Short-term goals<br />

Short term goals shows the actual picture <strong>of</strong> organization. So these are important for continuous grouth in<br />

organization.<br />

6 Hy-tech and automatic manufacturing<br />

Hy-tech and automatic manufacturing provide some advantages in quality, product development and productivity.<br />

Still, more hy-tech and automated machinery is not very flexible in terms <strong>of</strong> reconfiguring the system.<br />

7 Standardization<br />

Standardization is very important for any <strong>of</strong> industry for best production.<br />

8. Conclusion:<br />

Today, the world is rapidly changed in manufacturing. The efficiency and performance <strong>of</strong> the manufacturing system<br />

is mostly depends on time <strong>of</strong> job completion or minimum wastage, percent <strong>of</strong> flexible as well as being able to<br />

reconfigure the system for current requirement. JIT provides us minimum wastage in raw material and FMS is an<br />

important area and continuous for future manufacturing. Sometimes, the customer does not satisfied with FMS<br />

because <strong>of</strong> some problems, including its lack <strong>of</strong> reconfigurablity. This research paper shows that use <strong>of</strong> JIT with<br />

FMS and RMS is a satisfactory way <strong>of</strong> satisfy customer needs with full fill their demands by minimizing wastage in<br />

material and other wastage.<br />

9. Future Researches<br />

The research area <strong>of</strong> FMS and RMS is too broad and has large areas for future research but with the JIT it will be<br />

smooth, time oriented and with minimum wastage. Few suggested areas are formulated.<br />

‣ To create advance future technology for evaluation when there is a requirement for flexibility and<br />

Reconfigurablity but with minimum wastage.<br />

‣ To measurement for analysis <strong>of</strong> flexibility and reconfigurablity in an existing manufacturing system with<br />

JIT by latest complementary methods.<br />

‣ To create methods with s<strong>of</strong>tware based with a user-friendly interface in industry.<br />

‣ To implement s<strong>of</strong>tware’s for control and change for better.<br />

References:<br />

[1]. V. malhotra, t. raj, a. arora, Excellent technics <strong>of</strong> manufacturing system: FMS and RMS, International<br />

Journal <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong> vol.2(3) <strong>20</strong>10, 137-142<br />

[2]. M.Mahajan, Statical Quality and Control, Dhanpat rai & co.<strong>20</strong>08<br />

[3]. Koren Y, Heisel U, Jovane F, Moriwaki T, Pritschow G, Ulsoy G, Van Brussel H (<strong>19</strong>99), Reconfigurable<br />

manufacturing systems. CIRP magazine 48(2), pp 527–540<br />

[4]. Maraghy, R, Ulay Y (<strong>20</strong>07), Reconfigurable manufacturing systems: key to future manufacturing. Journal<br />

<strong>of</strong> intelligent manufacturing, 11(4), pp 403–4<strong>19</strong><br />

[5]. Sethi AK, Sethi SP (<strong>19</strong>90), Flexibility in manufacturing, a survey. International journal <strong>of</strong> Flexible<br />

Manufacturing System, 2(2), pp 82–88<br />

[6]. Kouvelis, J.P, Moodie C.L (<strong>19</strong>99), Definition and classification <strong>of</strong> manufacturing flexibility types and<br />

measures. International journal Flexible Manufacturing System 10(3), pp 25–34<br />

[7]. Drucker, P (<strong>19</strong>90), The flexibility <strong>of</strong> manufacturing system, International journal <strong>of</strong> production research,<br />

7(4), pp 35–45<br />

[8]. Jackson, Tonchia S (<strong>20</strong>01), Manufacturing flexibility: a literature review. International journal <strong>of</strong><br />

production Reasearch, 36(6), pp 58–62 Burbidge, T, Yamada S, Vink P (<strong>19</strong>91), Manufacturing aspects <strong>of</strong><br />

intelligent machines, Journal <strong>of</strong> manufacturing systems, 2(1), pp 981–988<br />

[9]. Fujii, R.P. and Gambrell, C.C., (<strong>20</strong>00), Analysis <strong>of</strong> flexible systems, International Journal <strong>of</strong> Production<br />

Research, 5(2), pp 23-28.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[10] Rosenblatt, M. J. and Lee, H.L., (<strong>19</strong>97), Robustness Approach to Facilities Design, International Journal on<br />

Production Research, 25(4), pp 479-486.<br />

[11]Shore, R. H. and Tompkins, J.A., (<strong>20</strong>00), Flexible Facilities Design, AIIE Transactions, 12(2), pp <strong>20</strong>0-<strong>20</strong>5.<br />

[12]Yang, T. and Peters, B.A., (<strong>20</strong>02), Flexible Machine Design for Dynamic and Uncertain systems, European<br />

Journal <strong>of</strong> Operational Research, 10(8), pp 49-64.<br />

[13]D’Souza, E ,Benjaafar, S. (<strong>20</strong>00), Design <strong>of</strong> integrated systems, Flexible Automation an Intelligent<br />

Manufacturing, Proceeding <strong>of</strong> Ninth International FAIM Conference, pp. 425-427.<br />

[14] Cheng, C.H., Chen, Y. (<strong>20</strong>03), Autonomous intelligent manufacturing systems and its applications, Journal<br />

<strong>of</strong> Industrial Engineering, 31(1), pp. 409-412.<br />

a. Browne, T.L, Lee, G. H., (<strong>19</strong>96), Reconfigurablity Considerations in the Design <strong>of</strong> Component and<br />

Manufacturing Systems, International Journal <strong>of</strong> Advanced Manufacturing <strong>Technology</strong>, 13(5), pp 76-86.<br />

838


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

MODERN TRENDS, PROBLEMS, SOLUTIONS AND ETHICS IN<br />

MECHANICAL ENGINEERING<br />

Niranjan Lal Mangla,<br />

Associate Pr<strong>of</strong>essor, Mechanical Engineering Department, <strong>YMCA</strong>UST, Faridabad.<br />

email: niranjanmangla@gmail.com<br />

Abstract<br />

Modern trends like nano technology, computer aided manufacturing, spacecraft to Mars etc. seem interesting<br />

but have failed to solve unemployment, mental stresses, food and social problems that have sprung from<br />

industrialisation. Green technology is heard <strong>of</strong>, but global warming continues. In spite <strong>of</strong> more efficient<br />

combustion systems and new sources <strong>of</strong> energy, the energy crisis is spiralling. New management skills are being<br />

developed to manage resources in industries but vast natural resources like Yamuna’s mineral water are<br />

unavailable. The solution lies right in the vedic texts. The alternate technologies, that can generate employment,<br />

that are environmental friendly and sustainable and at the same time help in space exploration and solve most <strong>of</strong><br />

the above problems, have been discussed in light <strong>of</strong> the ancient Sanskrit literature on science and engineering.<br />

But this is for people who have human and pr<strong>of</strong>essional ethics. Some universal values have been revealed from<br />

the vedic texts on code <strong>of</strong> conduct.<br />

Modern Trends and the Problems<br />

Some <strong>of</strong> the modern trends which are important and <strong>of</strong> concern will be discussed one by one. The problems<br />

associated and their subtle causes will be highlighted.<br />

1. Efficient Thermal Power Plants, two and four stoke power engines<br />

Modern trend is to have pollution free thermal plants using tons <strong>of</strong> coal and fuel oil. The trend is also for<br />

efficient two stroke and four stroke engines used in motor cycles, cars, trucks etc. Research is towards using bi<strong>of</strong>uel<br />

or Hydrogen etc. The problem is that global warming is taking place. What is the reason Is carbon dioxide<br />

a problem It is probably not. There are four basic reasons. First is the release <strong>of</strong> “Amedhya” substance into<br />

the atmosphere. What is this “Amedhya” Ayurveda comes to our help. Sanskrit comes to our help. It literally<br />

means something that is not conducive to the analysing capacity <strong>of</strong> brain. But practically such a substance when<br />

released in atmosphere even in parts per million or billion will have an enormous effect on the atmosphere. Some<br />

seeding effect in the destruction <strong>of</strong> the ozone layer or the electromagnetic fields that protect our atmosphere from<br />

outside bombardment <strong>of</strong> hazardous substances or radiations takes place. Complete combustion <strong>of</strong> the fossil fuels<br />

or collecting carbon dioxide will not help, unless we trap the “Amedhya” contentst in the fossil fuels. These<br />

“Amedhya” substances are very difficult to be traced out. That is why the nature has buried the fossil fuels<br />

underneath so that with the passage <strong>of</strong> time their “Amedhya” content gets eliminated. How foolish it is on our<br />

part to dig the garbage out and burn it. That is why Lord “Manu” clearly instructs “Do not put “Amedhya” into<br />

fire” [1]. Just a simple instruction but <strong>of</strong> a great importance.<br />

The second reason is the excessive use <strong>of</strong> oxygen. The amount <strong>of</strong> oxygen needed in producing the energy from<br />

even complete combustion <strong>of</strong> the fossil fuels or bio- fuel or hydrogen is enormous. How The oxygen consumed<br />

in driving a car is 22.5 kg/hour which is 750 times the oxygen needed by a human being [2]. Now, millions <strong>of</strong><br />

automobiles and thousands <strong>of</strong> power plants are burning millions <strong>of</strong> tons <strong>of</strong> fossil fuels. Won’t the ozone layer<br />

and oxygen in the atmosphere get affected<br />

The third reason is the heat released in the atmosphere. The efficiency <strong>of</strong> the modified Rankine cycle used in<br />

steam power plants is around 37% for the given temperatures and pressures [3]. If the efficiency <strong>of</strong> the steam<br />

boilers is assumed to be 90 (on the higher side), the over all efficiency is around 33%. Similar figures are there<br />

for reciprocating engines. That means around 70% <strong>of</strong> the heat produced in burning fossil fuels is being<br />

transferred to the atmosphere or the water in the oceans. This is an alarming amount when figures are counted.<br />

The nuclear power plants are no exception to this reason. As a result, global warming is imminent.<br />

The fourth reason is the vibrations released into the atmosphere. A horse gallop is pleasing to listen. A fine<br />

tuned classical music gives a soothing effect to the body and mind. However the shrill noise <strong>of</strong> a reciprocating<br />

engine is certainly displeasing. It is not the displeasure that is disturbing. The after effects <strong>of</strong> this shrill noise on<br />

the atmosphere are disturbing. Modern trends are to reduce the noise level. One has to be careful here. Noise is<br />

839


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

something that can be heard by the human ears. But the vibrations that have been generated once, whether heard<br />

or not, produce an immediate effect on the environment. The subtle vibrations apart from the vibrations <strong>of</strong> the<br />

mass particle also have an effect. Slight meditation makes this clear. The enormous electromagnetic vibrations<br />

being generated for mass tele-communication are also having a detrimental effect. It is well known that the<br />

radiations from a mobile phone or the computer screen are harmful. Similarly the artificial electromagnetic<br />

waves travelling all around in the atmosphere are having a negative effect on the various natural protective and<br />

nourishing phenomenons taking place in the environment and the outer layers <strong>of</strong> the atmosphere.<br />

The above four reasons together are certainly responsible for the deteriorating environment on the earth. Time is<br />

running out and immediate action is needed. If there is catastrophe in the near future in the form <strong>of</strong> solar<br />

storms or earthquakes, it will not be because <strong>of</strong> the Mayan Calendar ending. It will be modern technology<br />

made.<br />

2. Computer Aided Design; Computer aided Manufacturing<br />

The computer aided automatised and fast machines are bringing out better and complicated designs and<br />

beating the traditional lathes in production. Jobs for computer and s<strong>of</strong>tware engineers have been generated.<br />

Money for the owners has been generated. But all this mass production has thrown out millions <strong>of</strong> people out <strong>of</strong><br />

job the world over. Slums in the overwhelming cities have come up. People have been uprooted from their<br />

villages and with that from their natural and social environment. Let us take some examples. There were<br />

thousands <strong>of</strong> weavers all over India. They were earning good livelihood before the advent <strong>of</strong> European<br />

machines. There were thousands <strong>of</strong> copper and brass utensil makers in towns. Similarly there were the<br />

shoemakers, blacksmiths etc. They have been almost all thrown out <strong>of</strong> jobs. The tractors used for ploughing the<br />

land have not only spoiled the land but have made the oxen, the farmers jobless. There is another angle to it and<br />

cause <strong>of</strong> the suicides by the farmers. A wealthy farmer, instead <strong>of</strong> working for eight hours on land finishes his<br />

task within say two hours. The remaining time is used in gossip, drinking or other non productive activities. This<br />

leads to mental and social problems. So it is a misunderstanding that industrialisation generates economy and<br />

employment. It is for the few and not for the masses. This is the cause <strong>of</strong> disparity and hence communism and<br />

capitalism have come into existence.<br />

3. Plastics and nano-technology<br />

Plastics have a long life as compared to wood. They do not rust as compared to iron. So, new and better<br />

plastics in various forms are coming to existence. More efficient moulding machines are taking birth. The<br />

problem in plastics is threefold. First the long continuous polymer chains do not have sufficient pores. So air<br />

etc cannot pass with ease. Thus these long artificially created molecules when go along with water or food clog<br />

the pores inside the human body or animal bodies. This is hazardous to health. This concept <strong>of</strong> non clogging <strong>of</strong><br />

arteries, veins and numerous other passages, meant for flow <strong>of</strong> liquids or air or electromagnetic fields (the<br />

“Prana”), is laid out in Ayurveda (“Vilekhanam”). One need not eat plastic for this. The bear contact <strong>of</strong> the water<br />

and food items with the containers entraps very minute particles <strong>of</strong> plastics not visible to normal eyes. Secondly,<br />

plastics are burnt by common man for heat or disposal. The same long polymers are now disposed <strong>of</strong> into the<br />

atmosphere and clog the respiratory systems. Apart from the long chained molecules, some “Amedhya”<br />

substances are also released. That is clear from the smell from the products <strong>of</strong> combustion. Thus pollution is<br />

many fold. The third problem is recycling. It is well established that plastic bottles, polythenes bags etc. take lot<br />

<strong>of</strong> time in getting back to the nature. Rivers and land seems to be strewn all over with plastics and polythene<br />

bags. Visit the villages, visit the cities and visit the rivers. You may not find them in England or America but<br />

visit their land fills.<br />

Similarly nano-technology products, because <strong>of</strong> non porosity, can be much more harmful to health and<br />

environment. For example, there is a saying that nano socks or pants will never get dirty. But look the poor<br />

man’s feet or legs will certainly be uncomfortable and deteriorate because <strong>of</strong> no contact with air. Porous<br />

comfortable cotton clothes are needed.<br />

4. The mission to mars and outer space and air travel<br />

Man is curious to land on Mars or explore the outer space. Rocket propulsion is a must to take the pay load out<br />

<strong>of</strong> the earth’s pull. Thousands <strong>of</strong> increasing number <strong>of</strong> planes are flying every day around 12 km high on our<br />

heads. Modern research is to come up with novel techniques that reduce drag and generate extra lift. Still<br />

millions <strong>of</strong> tons <strong>of</strong> aviation fuel is being consumed to produce high velocity jets to overcome drag and generate<br />

lift. The problems associated remain the same as discussed before: excessive oxygen consumption; heat and<br />

noise release to the atmosphere.<br />

840


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5. New management Techniques<br />

Production planning and control is an important activity in industrial engineering. Many skills for the<br />

management <strong>of</strong> resources and products are coming up. But, the plight <strong>of</strong> the rivers like the great Yamuna and the<br />

Ganges is not worth it. Just go and visit Yamuna in the summer and you will see the stinking black water where<br />

even a bird won’t dip. By putting in the sewage into these rivers, we have deprived the common man <strong>of</strong> the<br />

precious mineral water coming straight from the Himalayas. By allowing construction on the banks, a large<br />

forest cover is being destroyed. By installing big hydro-power plants, the water head that takes the water with<br />

sufficient momentum down the planes has been reduced. Isn’t it a big mismanagement The mechanical<br />

engineers should come out <strong>of</strong> their dens <strong>of</strong> factories to manage these large natural resources. The solution has<br />

been discussed ahead.<br />

Solutions<br />

The alternatives to the above trends in power, mobility on land, mass production machines, plastics, air and<br />

space travel etc. are being discussed now. These do not have the problems mentioned above associated with<br />

them. They are environmental friendly, use renewable sources <strong>of</strong> energy, human friendly and thus sustainable.<br />

1. Alternative to power and automotives<br />

There are two steps required to this problem. First is the use <strong>of</strong> the ox and the horse. A village properly<br />

planned as per Vedic engineering can support 1000 oxen. If one ox produces one 8 KWH <strong>of</strong> energy in a day, it<br />

makes 0.8 MWH for the village in a day. For one hundred thousand <strong>of</strong> villages this becomes 80,000MWH for<br />

one day. That is a large amount. The ox’s input is grass which is renewable. It does not pollute and uses<br />

minimum amount <strong>of</strong> oxygen. Instead its urine and excreta are also valuable fertilisers. Its body parts are also <strong>of</strong><br />

use after death. The horse is the most efficient engine with built in air bags, with vision and intelligence to stop<br />

or by pass the anticipated accident. Its input is again renewable grass. Minimum oxygen requirement and no<br />

pollution are its features. Solar power is also beaten by the ox and the horse. Efficiency <strong>of</strong> a good solar cell is<br />

around 15%. The efficiency <strong>of</strong> the grass or the plants to convert solar energy to food energy is more than 90%.<br />

The efficiency <strong>of</strong> the horse or the ox to convert this food energy into actual work energy is again more than 90%.<br />

No heat energy or the vibrations are emitted to the environment. Isn’t it foolish on the part <strong>of</strong> man to abandon the<br />

naturally available most efficient, non polluting, intelligent sustainable machines and feel proud that “I am<br />

technologically advanced”. Instead he should put a label “I am a demon who has come to destroy you and<br />

your environment”. Millions <strong>of</strong> people are dying or getting crippled due to accidents on roads. Certainly the<br />

figure will come down drastically with the ox and the horse. The other advantage is that man likes greenery and<br />

fresh air around him and not the concrete or steel jungle which has become necessary to boost the power and<br />

locomotive industry.<br />

The second necessary step is to reduce the energy requirement with proper village, town and city planning [4].<br />

The town planning at present is faulty. A lot <strong>of</strong> the energy and time is being wasted in travelling from the place<br />

<strong>of</strong> residence to the work place. Similar is the expenditure for movement within a city as it is too big. This has<br />

sprung from the foreign rulers who wanted to rule from the central fortified places. Industrialisation is also<br />

responsible. The vedic town planning (Vastu Sastra) limits the size <strong>of</strong> villages, towns and cities. The work place<br />

and residence are at one location. Travel within a village, town or city can be easily done on foot or the chariot<br />

[4]. The main roads run outside the towns and cities. This will bring down the energy expenditure, time wastage<br />

and the requirement for fast moving automobiles. Proper town planning also solves most <strong>of</strong> the law and order<br />

problems.<br />

It is the basic requirement <strong>of</strong> the Vedic town planning to take care <strong>of</strong> the health, wealth and character <strong>of</strong> the<br />

residents. The mechanical engineers have to rise from their factory planning <strong>of</strong> machines and layout to the town<br />

planning. Improper planning has given rise to so many health problems and criminal activities.<br />

2. Alternative to computer aided design and manufacturing<br />

Instead <strong>of</strong> big machines small man operated or animal operated machines should be used [5]. Man is an<br />

intelligent robot with vision, power <strong>of</strong> discretion and so many degrees <strong>of</strong> freedom. This will immediately<br />

generate millions <strong>of</strong> jobs the world over. Dignity <strong>of</strong> man will be restored. The worker feels proud <strong>of</strong> his<br />

indigenous work unlike the machine that frightens him <strong>of</strong> accident and his inability. Money and work places will<br />

get decentralised. He can work right at his place. The tillers (in the absence <strong>of</strong> tractors), the weavers, the<br />

cobblers, the potter makers, the smiths, the carpenters, the utensil makers, special designers etc. will all flourish<br />

841


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

and find a livelihood. They will not starve, they will not face uprooting and the polluted environment <strong>of</strong> the<br />

modern industries. Isn’t it foolish <strong>of</strong> the modern man to say I am technologically advanced and create miseries<br />

for the millions “What will the mechanical engineers do” One may say. Yes, there is lot <strong>of</strong> scope to design<br />

the proper functioning <strong>of</strong> these small man operated machines and tools. The metallurgy and reduction <strong>of</strong> friction<br />

etc. are all important. Journal bearings, wheels and springs for the chariots need to be designed and made.<br />

Recyclability and workability <strong>of</strong> the metals for utensils, surgical instruments, the plough etc. will have to be<br />

taken care <strong>of</strong>. That is why lord “Manu” has wisely said that avoid big machines [5]. He does not say eliminate<br />

machines altogether. A high level scope is being discussed in step 5.<br />

3. Alternative to plastics and nano products<br />

Natural degradable material available should be used instead <strong>of</strong> plastics. For example the re-usable<br />

cloth or natural fabric (like the jute) bags can easily replace the polythene bags. With proper forest cover,<br />

millions <strong>of</strong> cattle can be supported. The animal hide is another good alternative for containers. Even if the<br />

products are more costly or having less life, one must go for them to avoid the problems associated with plastics<br />

and nano products.<br />

4. Solution to air and space travel<br />

The present principle to generate lift and overcome drag in air planes and propulsion rockets for space<br />

is to generate a high velocity jet that produces sufficient thrust. The vedic texts have a different scientific<br />

principle for the working <strong>of</strong> the airplanes and the spacecrafts. There are only five fundamental particles and one<br />

<strong>of</strong> them is responsible for movement [6]. A delicately processed material called “Beejam” is implanted into the<br />

plane or spaceship. When heated, this material generates a field around it that gives motion against gravity [7].<br />

Probably it manipulates the fundamental particle responsible for motion. Apart from this it is also supposed to<br />

reduce drag to almost zero by eliminating the boundary layers responsible for the friction [8]. It is reusable and<br />

the payload ratio is high. The “pushpak vimanam” <strong>of</strong> Ramayana is not a myth but a fact [9]. Research should be<br />

immediately started on this front as many texts are still available that can help in the processing <strong>of</strong> this<br />

“Beejam”. Thus man can still travel in air and space without creating environmental problems.<br />

5. Management <strong>of</strong> Yamuna and the Ganges<br />

This needs two steps. First is to stop the sewage going into these rivers immediately. Lord Manu<br />

instructs that excreta and urine should not be thrown into water [10]. That is the key to the cleanliness <strong>of</strong> the<br />

rivers and the water problem. Soil should be used in the lavatories along with toilet paper and minimum <strong>of</strong><br />

water. The design <strong>of</strong> the toilet and disposal <strong>of</strong> the waste is now the job <strong>of</strong> the mechanical engineers. This way<br />

we shall not only save precious water, rivers and power but also develop a large amount <strong>of</strong> natural manure. This<br />

will increase the fertility <strong>of</strong> land instead <strong>of</strong> reducing it as done by the chemical fertilisers. The money spent on<br />

the chemical fertilisers will also be saved. The second step is to declare around three km <strong>of</strong> land on both sides<br />

<strong>of</strong> the rivers as reserved forest land. This will result in thousands <strong>of</strong> miles <strong>of</strong> dense forest on both the sides <strong>of</strong> the<br />

rivers. Water is already available there for trees and grass to come up. Millions <strong>of</strong> cows can be grazed there.<br />

Shortage <strong>of</strong> milk and butter will disappear. Many cow boys will get employed. Fresh air and mineral water will<br />

be available to the common man. Numerous men and women can practice Yoga and do exercises in these<br />

reserved forests. Natural cow dung cakes will be available for delicious cooking. The requirement for the<br />

cooking gas will come down. Smokeless cooking, using cow dung cakes, is another project for the engineers. Let<br />

the mechanical engineers apply their design and management skill here.<br />

Human Values and Pr<strong>of</strong>essional Ethics<br />

The advances advised above are for mechanical engineers who care for human values and pr<strong>of</strong>essional ethics.<br />

The question arises that what are those values and ethics which are universal to all like the scientific laws. Vedic<br />

texts specify them as the five “Yamas” and five “Niyamas” [11]. The five “Yamas” are: 1) “Ahimsa” (non<br />

killing), 2) “Satya” (speaking the truth), 3) “Asteya” (non stealing), 4) “Brahmacharya” (no sex before marriage<br />

and observance <strong>of</strong> the sex rules after marriage, 5) “Aparigraha” (non hoarding <strong>of</strong> any kind). The five “niyamas”<br />

are: 1) “Shaucha” (cleanliness), 2) “Santosha” (satisfaction), 3) “Tapah” (tolerating respect and insult, adverse<br />

and comfortable environment etc.), 4) “Swadhyaya” (meditation in the mornings and evenings daily and reading<br />

<strong>of</strong> the “Vedas”, 5) “Ishwar Pranidhanam” (firm belief in the all pervading and all powerful conscience entity<br />

called the God) [12]. This is in brief and encompasses all aspects <strong>of</strong> human life- personal, family, social,<br />

national, and pr<strong>of</strong>essional, etc. Properly observance <strong>of</strong> “Yamas” and “Niyamas” can take a person to the highest<br />

level <strong>of</strong> bliss and a nation to the peak.<br />

Conclusions<br />

842


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Some <strong>of</strong> the modern trends and advances in mechanical engineering have been discussed. The problems<br />

associated have been thrown light upon. The solutions with evidences from the vedic texts on science and<br />

technology have been given. If we want to save our planet from a big environmental catastrophe, the advances<br />

suggested must be immediately implemented. For a better human and ethical environment, the vedic texts on<br />

ethics are important to be followed. Sanskrit as a language, which is the key to the vedic texts, must be<br />

introduced in all educational institutions. Likewise, the course on human values and ethics is a must. The science<br />

and technology in the Sanskrit texts is <strong>of</strong> great relevance in modern times. There should be a separate department<br />

for that in the scientific and technical institutes.<br />

References<br />

1. “Manusmriti”, chapter 4, verse 53, Motilal Banarsidas, <strong>19</strong>83 edition.<br />

2. “Living Energies” Chapter 2, Fig. 2.1, Callum Coats.<br />

3. “Engineering Thermodynamics”, section 11.5, Rogers and Mayhew, <strong>19</strong>67 edition.<br />

4. “Samarangana Sutra Dhara”, chapter 10, verse 79-85, Gaekwad’s Oriental series no. 25, <strong>19</strong>66 edition.<br />

5. “Manusmriti”, chapter 11, verse 63, Motilal Banarsidas, <strong>19</strong>83 edition.<br />

6. “Vaisesika Darsanam Prasasta Pada Bhasyam”, concept <strong>of</strong> Vayuh.<br />

7. “Samarangana Sutra Dhara”, chapter 31, verse 95, 96, Gaekwad’s Oriental series no. 25, <strong>19</strong>66 edition.<br />

8. “Samarangana Sutra Dhara”, chapter 31, verse 97,98, Gaekwad’s Oriental series no. 25, <strong>19</strong>66 edition.<br />

9. “Valmikiya Ramayanam”, Yudha Kandam , Sarga 114, verses 9-14, Nag Publishers, <strong>19</strong>91.<br />

10. “Manusmriti”, chapter 4, verse 56, Motilal Banarsidas, <strong>19</strong>83 edition.<br />

11. “Manusmriti”, chapter 4, verse <strong>20</strong>4, Motilal Banarsidas, <strong>19</strong>83 edition.<br />

12. “Yoga Darsanam”.<br />

843


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

STRATAGEM PROGRESS OF LEAN MANUFACTURING<br />

IMPLEMENTATION IN SHOP FLOOR<br />

1 Pr<strong>of</strong>. <strong>YMCA</strong>UST, Faridabad<br />

2 Asstt. Pr<strong>of</strong>. AITM, Palwal<br />

1 Email: Navdeep_malhotra<strong>20</strong>01@yahoo.com<br />

Navdeep Malhotra 1 , Dharmender 2<br />

Abstract<br />

In the present business scenario competitiveness <strong>of</strong> the manufacturing companies is determined by their ability<br />

to meet and respond as swiftly as possible to the changing environment scenario and to produce and supply high<br />

quality products at lower cost as per demand <strong>of</strong> the customer. This can be achieved by proper planning and<br />

skillfulness, through the application <strong>of</strong> automation and innovative concepts, e.g. Lean manufacturing, JIT, and<br />

TQM. Among these innovative concepts, lean manufacturing is recognized by the manufacturing companies as a<br />

major driver to achieve world class capabilities. The implementation <strong>of</strong> lean manufacturing reduced the waste in<br />

the industry and enhances the pr<strong>of</strong>it and production.<br />

Keywords: Just in time (JIT), Total quality management (TQM), Lean Manufacturing<br />

1. Introduction<br />

Lean manufacturing derives its name from the manufacturing systems and processes <strong>of</strong> the Toyota production<br />

system that are so effective at producing at low cost and short cycle times. These systems are highly flexible and<br />

responsive to the customer requirements. Mean manufacturing is multi dimensional approach that encompasses a<br />

wid variety <strong>of</strong> management practices, including just in time, quality systems, work teams, cellular<br />

manufacturing, supplier management etc in an integrated system. The core thrust <strong>of</strong> lean production is that these<br />

practices can work synergistically to create a stream line high quality system that produces finished products at<br />

the pace <strong>of</strong> customer demand with little or no waste. Lean manufacturing , also called lean production is a set <strong>of</strong><br />

tools and methodologies that aims for the continuous elimination <strong>of</strong> all waste in the production processes<br />

Here a study has been undertaken in an organization, manufacturing camshafts. Various machinig and heat<br />

treatement operations are carried out on the material received from the suppliers. In this study various operations<br />

have been carefully observed and the records <strong>of</strong> the production have been analysed to find out root cause <strong>of</strong><br />

various types <strong>of</strong> wastes at different stages having determined the type and quantum <strong>of</strong> waste at every stage. It<br />

was ascertained as to how far the company is from the concept <strong>of</strong> lean manufacturing. Subsequently an action<br />

plan has been developed for step wose implementation <strong>of</strong> lean manufacturing which is primarily based on<br />

removing the root causes <strong>of</strong> various wastes.<br />

2. Methodology<br />

The steps employed in the qualitative modeling are as under:<br />

1. Identification <strong>of</strong> experts<br />

2. The summation <strong>of</strong> results <strong>of</strong> analysis to experts<br />

3. Generalization <strong>of</strong> the provision/controls identified under each <strong>of</strong> the above area, by experts<br />

4. Identification <strong>of</strong> factors and parameters influencing development <strong>of</strong> a generalized approach by brain<br />

storming and idea generation<br />

5. Collection <strong>of</strong> qualitative score to a quantitative score using the scoring scale and the number <strong>of</strong><br />

responses to a choice<br />

6. Listing the results <strong>of</strong> various generalizes provisions/control in reducing order <strong>of</strong> their cumulative scores<br />

separately for lean wastes.<br />

7. Using expert’s opinion for implementation <strong>of</strong> these provisions an deciding an order <strong>of</strong> priority to the<br />

four major areas studied.<br />

8. Formulation <strong>of</strong> phased implementation approach by picking up the provisions which have higher<br />

weighted scores in the lean wastes.<br />

3. Analysis<br />

Here a complete step by step analysis including data collection, calculation <strong>of</strong> various types <strong>of</strong> wastes, their root<br />

cause analysis and comparison with the requirements <strong>of</strong> lean manufacturing is carried out. A phased approach<br />

has then been developed for implementation <strong>of</strong> lean manufacturing in the organization. In the light machine<br />

shop, four type <strong>of</strong> camshaft are manufactured. Currently only conventional camshaft and modified camshaft are<br />

844


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

manufactured. They are made <strong>of</strong> alloy steel <strong>of</strong> 1<strong>20</strong> mm diameter weighing 106.5 kg. Various characteristics for<br />

camshafts are as shown in Table I<br />

3.1 Analysis <strong>of</strong> waste<br />

For the purpose <strong>of</strong> analysis, the waste has been categorized into six different types:<br />

1. Defects<br />

2. Excessive inventory<br />

3. Waste due to unnecessary material movement<br />

4. Delay due to waiting<br />

5. Overproduction<br />

6. Inappropriate processing<br />

The detailed analysis <strong>of</strong> each <strong>of</strong> above types has been presented in the next section.<br />

3.2 Root cause analysis <strong>of</strong> wastes<br />

A cause and effect diagram was developed to examine the factors that are contributing to the problem. The cause<br />

and effect diagram was developed through four steps, namely:<br />

a) Identify the problem’s characteristics<br />

b) Brain storms the reasons why the problem is occurring using a casual table also known as the why<br />

because technique<br />

c) Group the causes by relationship<br />

d) Create a cause and effect diagram<br />

The causes are grouped under the following headings: (1) Men (2) Machine (3) Material (4) method. The<br />

diagram makes it easy to see the many possible root causes <strong>of</strong> the issues that may be leading to defects.<br />

3.2.1 Defects<br />

845


3.2.2 Rework<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3.2.3 Excess inventory<br />

3.2.4 Delay due to waiting<br />

3.2.5 Excessive material movement<br />

3.2.6 Over processing<br />

846


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3.3. Gap analysis<br />

Following work has been carried out to identify GAP:<br />

1. Comparison <strong>of</strong> existing status with the requirements <strong>of</strong> lean manufacturing.<br />

2. Using expert opinion and clarify the gap as HIGH , MEDIUM, or LOW<br />

Where<br />

HIGH – very large gap, need immediate action.<br />

MEDIUM – Large gaps, urgent action required.<br />

LOW- insufficient gap does not require immediate action.<br />

Table II shows the gap between the existing status and requirements <strong>of</strong> lean manufacturing as per above<br />

classification.<br />

4. Development <strong>of</strong> generalized approach<br />

For developing a generalized approach, the cost associated with a provision has been taken as the most important<br />

input. In the development <strong>of</strong> approach experts play important role. Experts are employees <strong>of</strong> the organizations, in<br />

all , a total <strong>of</strong> ten experts consisting <strong>of</strong> two managers, three supervisors, three operators, one inspector and one<br />

mechanic were selected. The experts were briefed about the findings <strong>of</strong> the root cause <strong>of</strong> wastes for the purpose<br />

<strong>of</strong> getting their feedback.<br />

A. Factors and Parameters influencing Development <strong>of</strong> a Generalized Approach<br />

The experts after discussion and brain storming conversed on the following factors influencing development <strong>of</strong> a<br />

generalized approach.These qualities scores were then converted into quantative score using the scoring scale<br />

and the number <strong>of</strong> responses to a choice. The scoring scale is shown in table III<br />

Table IV depicts the summary <strong>of</strong> responses received from experts. In this table number <strong>of</strong> experts responding to<br />

a particular choice in a factor or parameter has been compiled from the individual responses <strong>of</strong> the experts.<br />

Number <strong>of</strong> responses to a particular choice has been, then, multiplied by the score <strong>of</strong> that choice in every factor<br />

as listed in table III. Those weighted scores have been summed up against each generalized control or provision<br />

and have benn listed in the last column <strong>of</strong> table IV. The highest score <strong>of</strong> a provision in the column, depicts that<br />

considering all the above eight factors and parameters, this generalized provision should be taken up for<br />

implementation.<br />

847


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5. Suggested Implementation Plan<br />

It was then decided to formulate a phase wise implementation approach by picking up the provisions which had<br />

higher weighted scores in the above seven major areas. For deciding the number <strong>of</strong> provisions taken up for<br />

implementation in a phase, out <strong>of</strong> the total provisions under a major area, the proximity or differences <strong>of</strong> scores<br />

around the cut<strong>of</strong>f were considered i.e. there should be a considerable differences between the score <strong>of</strong> the last<br />

provision in the phase 1 and the first provision has been divided into three phases as an order <strong>of</strong> priority for<br />

implementation in any diesel locomotive industry. The three phases <strong>of</strong> the suggested approach are presented in<br />

table V<br />

The provision or controls suggested to be implemented in phase 1 will in general be less costly, easy to<br />

implement and would have positive or complementary effect on many other areas in the organization.<br />

Phase 2 includes measures which are slightly more difficult to implement, involves reasonably higher cost,<br />

which may require some kind <strong>of</strong> budgetary provisions and approvals.<br />

Phase 3 includes provisions, which are more related with hardcore technical changes, machinery, equipment and<br />

tooling. Implementation <strong>of</strong> these provisions will involve substantial capital investment and may require a<br />

number <strong>of</strong> iterations and trials for implementation.<br />

6. Results <strong>of</strong> the study<br />

The following results were drawn from the study,<br />

• Average monthly rejection <strong>of</strong> part before the conduct <strong>of</strong> the study was 3.6%<br />

• The raw material usage is only 26% <strong>of</strong> the available inventory each month.<br />

• The company has a high WIP inventory which is 86% <strong>of</strong> what is actually required.<br />

• The finished goods stock inventory is as per requirement.<br />

• In the existing layout material movement is very high and will be reduced by at least 75% by changing<br />

to the new layout. In the new layout, the material movement distance has been reduced to 131.5 metres<br />

compared to 537.45 metres in the existing layout.<br />

848


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

• The cycle time will reduce by about 23% at each station.<br />

• The set up time will reduce by about 24% at each station.<br />

• The break down time will reduce by about 3% at each station.<br />

• The absenteeism will reduce by about 5% at each station.<br />

• The operator missing from work station will reduce by about 24% at each station.<br />

• Over production is not very common in this industry as the parts are made against actual order.<br />

• If the raw material diameter is reduced from 1<strong>20</strong> mm to 115 mm the saving in the raw material<br />

requirement is 59%.<br />

• 80% <strong>of</strong> the rework products are rejected.<br />

7. Conclusion<br />

The following control and provision are suggested to be undertaken for implementation in each <strong>of</strong> the three<br />

phases:-<br />

7.1 Concluding remarks<br />

It is generally agreed that for a lean manufacturing programe to be effective, it should include a set <strong>of</strong> tools and<br />

techniques or provisions to ensure management commitment, employee involvement, identification <strong>of</strong> wastes,<br />

development <strong>of</strong> controls for wastes and training and education for employees. These tools and techniques are<br />

said to be typical <strong>of</strong> any comprehensive lean manufacturing implementation programme. The implementation <strong>of</strong><br />

lean manufacturing reduced the waste in the industry and enhances the pr<strong>of</strong>it and production.<br />

References<br />

1. Abduelmula, A. and Wagner, C: “Design and Evaluation <strong>of</strong> Lean Manufacturing Cell” ; A Simulation<br />

Model, <strong>20</strong>00.<br />

2. Ansari, a., and Modarress, B., “The Potential Benefits <strong>of</strong> Just-In-Time Purchasing For U.S Manufacturing,”<br />

Production and inventory management journal, Second quarter, <strong>19</strong>86, PP.30-35.<br />

3. Aytac, Selim, Erdem: “Lean Manufacturing as a Human –Centered Approach for Manufacturing System<br />

Design”, <strong>20</strong>03.<br />

4. Shah Rachna & Ward Peter T.; “Lean Manufacturing; context, practice bundles, and performance <strong>20</strong>03”.<br />

(Journal <strong>of</strong> operations management).<br />

849


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

APPENDIX<br />

WASTE<br />

ROOT CAUSE <strong>of</strong><br />

Table IV Responses <strong>of</strong> Experts<br />

EASE OF<br />

COST<br />

REMOVAL<br />

EFFECT <strong>of</strong> OTHERS<br />

TOTA<br />

L<br />

S<br />

WASTE<br />

H M L E N D H M L H M L<br />

SCOR<br />

1 2 3 3 2 1 +3 +2 +1 -1 -2 -3<br />

E<br />

Improper machining and<br />

equipment<br />

Poor quality <strong>of</strong> inputs<br />

like materials, tools etc<br />

Human error on passing<br />

on instructions<br />

8 2 0 0 2 8 0 0 1 9 0 0 16<br />

0 8 2 7 3 0 0 0 1 1 1 7 26<br />

1 1 8 8 2 0 0 1 2 7 0 0 52<br />

Human error by workers 1 8 1 2 7 1 0 1 2 5 1 0 38<br />

DEFECT<br />

INVENT<br />

ORY<br />

Wrong setting and<br />

determination <strong>of</strong><br />

parameters <strong>of</strong> temp,<br />

pressure etc. and<br />

inefficient control<br />

system to maintain them<br />

Scraping <strong>of</strong> product, this<br />

deviates from drawing<br />

specifications but can be<br />

used.<br />

Arbitrary buying <strong>of</strong><br />

material.<br />

Buying gross<br />

requirement as per the<br />

matter production<br />

schedule, net<br />

requirement not<br />

calculated.<br />

For regular items<br />

techniques <strong>of</strong> inventory<br />

control not used.<br />

0 2 8 7 3 0 0 0 0 3 7 0 38<br />

0 3 7 8 2 0 0 2 7 1 0 0 65<br />

0 2 8 7 3 0 0 0 0 3 7 0 38<br />

0 3 7 8 2 0 0 0 1 7 2 0 34<br />

1 8 1 8 2 0 0 0 1 6 3 0 37<br />

Poor record keeping and 0 3 7 9 1 0 0 0 2 5 3 0 47<br />

850


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

retrieval.<br />

In balancing <strong>of</strong><br />

production lines.<br />

Inventory levels between<br />

work centers not worked<br />

out.<br />

Bottlenecks in the<br />

processes.<br />

Deliberate attempt by<br />

production people to<br />

keep higher inventories.<br />

7 2 1 0 7 3 0 0 0 3 7 0 14<br />

8 2 0 0 2 8 0 8 0 0 2 0 36<br />

7 3 0 1 2 7 0 0 0 1 1 8 16<br />

0 7 3 1 2 7 0 0 0 4 5 1 18<br />

Improper layout. 8 2 0 0 2 8 0 0 1 3 6 0 10<br />

EXCESS<br />

IVE<br />

MATERI<br />

AL<br />

MOVEM<br />

ENT<br />

DELAY<br />

DUE TO<br />

WAITIN<br />

Storage is away from the<br />

production shop.<br />

Old method or manual<br />

transportation system.<br />

Expansion <strong>of</strong> shops not<br />

properly planned<br />

resulting in too much<br />

excessive movement.<br />

Unaware <strong>of</strong> extent <strong>of</strong><br />

loss.<br />

Inability <strong>of</strong> top<br />

management to plan<br />

modernization.<br />

Poor understanding <strong>of</strong><br />

process flow for<br />

production.<br />

Large batch size, long<br />

lead-time and large<br />

storage area<br />

Workers present but not<br />

working deliberately<br />

because <strong>of</strong> negative<br />

2 7 1 2 7 1 0 1 7 2 0 0 47<br />

0 4 6 1 6 3 0 0 1 7 2 0 52<br />

8 2 0 0 2 8 0 1 4 5 0 0 25<br />

2 7 1 0 8 2 0 4 2 4 0 0 43<br />

8 2 0 8 2 0 0 0 0 3 7 0 36<br />

0 3 7 1 7 2 0 0 2 7 1 0 39<br />

2 7 1 1 8 2 0 0 1 2 7 0 25<br />

7 3 0 0 2 8 0 0 0 1 1 8 2<br />

851


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

G<br />

attitude, union effects,<br />

lack <strong>of</strong> motivation, low<br />

morale, no concern and<br />

lack <strong>of</strong> a accountability.<br />

Un-avoidable delays 4 5 1 0 4 5 0 2 1 7 0 0 32<br />

Shortages <strong>of</strong> materials 0 4 6 4 6 0 0 0 1 3 7 0 22<br />

Break downs <strong>of</strong><br />

machines and equipment<br />

Excessive time spent on<br />

setting because proper<br />

jigs and fixture are not<br />

used.<br />

8 2 0 2 8 0 0 0 1 2 7 0 <strong>19</strong><br />

0 4 6 3 6 1 0 0 6 4 0 0 50<br />

Absenteeism 7 3 0 4 6 0 0 0 0 4 6 0 21<br />

INAPPR<br />

OPRIAT<br />

E<br />

PROCES<br />

SING<br />

Product changes without<br />

process changes.<br />

Poor machine<br />

effectiveness.<br />

Trace customer<br />

requirement undefined.<br />

Over processing to<br />

accommodate downtime.<br />

Lack <strong>of</strong><br />

communications.<br />

0 6 4 2 7 1 0 0 4 5 1 0 42<br />

1 7 2 3 7 0 0 0 3 6 1 0 39<br />

0 4 6 4 6 0 0 0 2 7 1 0 43<br />

3 7 0 3 7 0 0 0 1 8 1 0 31<br />

1 6 3 4 6 0 0 0 3 7 0 0 42<br />

Careless workers. 0 7 3 0 7 3 0 0 2 6 2 0 32<br />

Extra copier/excessive<br />

information.<br />

0 3 7 6 4 0 0 3 6 1 0 0 64<br />

852


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

TOOLS AND TECHNIQUES FOR QUALITY MANAGEMENT IN<br />

MANUFACTURING INDUSTRIES<br />

Mohit Singh 1 , I.A. Khan 2 , Sandeep Grover 3<br />

1 Research Scholar, Dept. <strong>of</strong> Mech Engg., Faculty <strong>of</strong> Engg. & Tech., Jamia Millia Islamia, New Delhi, India<br />

2 Pr<strong>of</strong>essor, Dept. <strong>of</strong> Mech. Engg., Faculty <strong>of</strong> Engg. & Tech., Jamia Millia Islamia, New Delhi, India.<br />

3 Pr<strong>of</strong>essor & Head, Chariman-Mech. Engg. Dept., <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> Sci. & Tech., Faridabad (HR), India.<br />

e-mail: sinmohit@gmail.com<br />

Abstract:<br />

Globalization, intense competitive environment, customer awareness etc. forces the manufacturing industries to <strong>of</strong>fer<br />

higher product quality which is the main requirement to gain global market share. Satisfying the customer with high<br />

quality products in the shortest time possible at lowest cost is the key to success <strong>of</strong> any organization in the market.<br />

To cope up and retain the position in this environment, it is a necessary requirement for any manufacturing industry<br />

to keep focusing on quality management. Managing well quality management within the industry is not possible<br />

without adequate knowledge <strong>of</strong> quality tool and techniques. The main aim <strong>of</strong> this paper is to highlight all major<br />

quality tools and techniques used for quality management in a manufacturing industry. The tools and techniques are<br />

segregated under four headings and explained briefly.<br />

1. Introduction:<br />

Manufacturing Industries are under increasingly diverse and mounting pressures due to more sophisticated markets,<br />

changing customer choice and global competition. The market for products is becoming increasingly international<br />

(Dangayach and Deshmukh, <strong>20</strong>03). They must understand how changes in their competitive environment are<br />

unfolding. Industries should actively look for opportunities to exploit their strategic abilities, adapt and seek<br />

improvements in every area <strong>of</strong> the business, building on awareness and understanding <strong>of</strong> current strategies and<br />

successes (Papulova & Papulova, <strong>20</strong>06). Accordingly, measures <strong>of</strong> modern quality management aiming for<br />

sustainable success do not only mean to avoid the delivery <strong>of</strong> defective products to the customer but seek to establish<br />

maximum efficiency in the performance <strong>of</strong> all processes <strong>of</strong> the company. With such optimized procedures, products<br />

<strong>of</strong> high quality can be provided with minimum effort <strong>of</strong> time and costs (Werner & Weckenmann, <strong>20</strong>12). To achieve a<br />

positive ranking and thus assure a high level <strong>of</strong> perceived quality, the company has to find a suitable position in the<br />

triangle <strong>of</strong> conflicting requirements on quality, costs and time (W. Geiger, <strong>19</strong>94).<br />

Quality management theory has been influenced by the contributions made by quality leaders (Crosby, <strong>19</strong>79;<br />

Deming, <strong>19</strong>82; Ishikawa, <strong>19</strong>85; Juran, <strong>19</strong>88; Feigenbaum, <strong>19</strong>91). Table 1 shows the empirical studies leading to a<br />

scale <strong>of</strong> Quality management (Juan José Tarı́& Vicente Sabater, <strong>20</strong>04).<br />

Table 1. Empirical research <strong>of</strong> quality management<br />

Authors Purpose Critical factors identified<br />

Saraph et al.<br />

(<strong>19</strong>89)<br />

Flynn et al.<br />

(<strong>19</strong>94)<br />

Badri et al.<br />

(<strong>19</strong>95)<br />

Black and Porter<br />

(<strong>19</strong>95)<br />

Ahire et al.<br />

(<strong>19</strong>96)<br />

Grandzol and<br />

Gershon (<strong>19</strong>98)<br />

Develop an instrument for measuring critical<br />

factors <strong>of</strong> quality management<br />

Develop an instrument based on empirical and<br />

practitioner literature<br />

Additional assessment <strong>of</strong> instrument proposed<br />

by Saraph, Benson and Schroeder<br />

Identify a set <strong>of</strong> critical factors <strong>of</strong> TQM<br />

Identify constructs <strong>of</strong> TQM and develop scales<br />

for measuring these constructs<br />

Develop and test an instrument for use in TQM<br />

research<br />

853<br />

8 factors with 66 items<br />

7 major dimensions with 48 items<br />

8 factors with 66 items<br />

10 factors with 32 items<br />

12 factors with 50 items<br />

7 exogenous factors with 39 items<br />

and 6 endogenous factors with 23


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Authors Purpose Critical factors identified<br />

Quazi et al.<br />

(<strong>19</strong>98)<br />

Rao et al. (<strong>19</strong>99)<br />

Corroborate the results <strong>of</strong> the study developed<br />

by Saraph, Benson and Schroeder<br />

Develop a valid instrument for key dimensions<br />

<strong>of</strong> quality management in the international<br />

context<br />

items<br />

16 factors with 78 items<br />

13 factors with 62 items<br />

[source: Juan José Tarı́& Vicente Sabater, <strong>20</strong>04]<br />

2. Quality tools & techniques for quality management:<br />

A single tool is a device with a clear function, and is usually applied on its own, whereas a technique has a wider<br />

application and is understood as a set <strong>of</strong> tools (McQuater et al., <strong>19</strong>95). Thus, Ishikawa (<strong>19</strong>85) and McConnell<br />

(<strong>19</strong>89)have identified a list <strong>of</strong> seven TQM tools: flow charts, cause and effect diagrams, Pareto charts, histograms,<br />

run charts and graphs, X bar and R control charts and scatter diagrams. Also, Imai (<strong>19</strong>86), Dean and Evans<br />

(<strong>19</strong>94), Goetsch and Davis (<strong>19</strong>97), Dale (<strong>19</strong>99), and Evans and Lindsay (<strong>19</strong>99) have <strong>of</strong>fered a list <strong>of</strong> tools and<br />

techniques for quality improvement. For their part, Dale and McQuater (<strong>19</strong>98) have identified the tools and<br />

techniques most widely used by firms, as shown in Table 2.<br />

The seven basic quality<br />

control tools<br />

Table 2. Commonly used tools and techniques<br />

The seven<br />

Other tools<br />

management tools<br />

Techniques<br />

Cause and effect diagram Affinity diagram Brainstorming Benchmarking<br />

Check sheet Arrow diagram Control plan Departmental purpose<br />

analysis<br />

Control chart Matrix diagram Force field analysis Design <strong>of</strong> experiments<br />

Flow Chart Matrix data analysis Questionnaire Failure mode and effects<br />

analysis<br />

Histogram<br />

Process decision Sampling<br />

Fault tree analysis<br />

program chart<br />

Pareto diagram Relations diagram Poka yoke<br />

Scatter diagram Systematic diagram Problem solving<br />

methodology<br />

Quality costing<br />

Quality function<br />

deployment<br />

Quality improvement<br />

teams<br />

Statistical process control<br />

[source: Dale and McQuater, (<strong>19</strong>98)]<br />

854


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Top <strong>20</strong> Quality Tools & Techniques: Supplier–Customer Ranking<br />

Ranking<br />

SME (Supplier) a<br />

Large Firm (Customer) b<br />

1-<strong>20</strong> =Most to least used 1-<strong>20</strong> =Most to least used<br />

1 Brainstorming Process capability<br />

2 Barcharts Just in Time<br />

3 Improve internal Process Productivity improvement<br />

4 Check sheet Lean<br />

5 ISO 9001:<strong>20</strong>00 Statistical process control<br />

6 Flow charts ISO 9001:<strong>20</strong>00<br />

7 Lean Total Quality Management<br />

8 Process capability Self assessments<br />

9 Self assessments Material requirements planning<br />

10 Statistical process control Improve internal process<br />

11 Material requirements planning Kanban<br />

12 Plan, do, check, act, cycle Matrix data analysis<br />

13 Matrix data analysis Bar charts<br />

14 Just in time Plan, do, check, act, cycle<br />

15 Kanban Brainstorming<br />

16 Suggestion scheme Flowcharts<br />

17 Tally charts Suggestion schemes<br />

18 Productivity improvement Tally charts<br />

<strong>19</strong> Tree diagrams Check sheets<br />

<strong>20</strong> Total Quality Management Tree diagrams<br />

[source: Jones, Thomas & Thomas, <strong>20</strong>07]<br />

2.1 Seven basic quality tools<br />

• Cause and effect diagram: A Cause-and-Effect Diagram is a tool that helps identify, sort, and display possible<br />

causes <strong>of</strong> a specific problem or quality characteristic. It graphically illustrates the relationship between a given<br />

outcome and all the factors that influence the outcome. This type <strong>of</strong> diagram is sometimes called an "Ishikawa<br />

diagram" because it was invented by Kaoru Ishikawa, or a "fishbone diagram" because <strong>of</strong> the way it looks.<br />

• Check Sheet: The check sheet is a simple document that is used for collecting data in real-time and at the<br />

location where the data is generated. The document is typically a blank form that is designed for the quick, easy,<br />

and efficient recording <strong>of</strong> the desired information, which can be either quantitative or qualitative.<br />

• Control Chart: A control chart is a statistical tool used to distinguish between variation in a process resulting<br />

from common causes and variation resulting from special causes. It presents a graphic display <strong>of</strong> process<br />

stability or instability over time.<br />

• Flow chart: The Flow Chart provides a visual representation <strong>of</strong> the steps in a process or a diagram that uses<br />

graphic symbols to depict the nature and flow <strong>of</strong> the steps in a process.<br />

• Histogram: One uses this graph to show frequency distributions. It looks very much like a bar chart. This chart<br />

graphs data distributions. If you have numerical, variable, continuous data you can use this chart. The chart<br />

organizes and sorts the data. It shows the data in a pictorial format.<br />

• Pareto Diagram: A Pareto chart, named after Vilfredo Pareto, is a type <strong>of</strong> chart that contains both bars and<br />

a line graph, where individual values are represented in descending order by bars, and the cumulative total is<br />

represented by the line.<br />

A simple rule, pareto, <strong>20</strong> % issues causes 80 % results.<br />

This means, 80 % if problems come from <strong>20</strong> <strong>of</strong> reasons.<br />

80 % <strong>of</strong> results come from <strong>20</strong>% <strong>of</strong> work. 80% <strong>of</strong> cost comes from <strong>20</strong>% <strong>of</strong> spent area...and so on.<br />

855


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

• Scatter diagram: It is used to determine if there is a relationship or correlation between two variables. It is<br />

used to display what happens to one variable when another variable changes in order to test a theory that the two<br />

variables are related. The data displayed on the scatter diagram clearly show if there is a positive, negative or no<br />

relationship between the two variables.<br />

2.2 The seven management tools<br />

• Affinity diagram: An Affinity Diagram is a tool that gathers large amounts <strong>of</strong> language data (ideas, opinions,<br />

issues) and organizes them into groupings based on their natural relationships. The Affinity process is <strong>of</strong>ten used<br />

to group ideas generated by Brainstorming. It may be used in situations that are unknown or unexplored by a<br />

team, or in circumstances that seem confusing or disorganized, such as when people with diverse experiences<br />

form a new team, or when members have incomplete knowledge <strong>of</strong> the area <strong>of</strong> analysis.<br />

• Arrow diagram: The arrow diagram shows the required order <strong>of</strong> tasks in a project or process, the best schedule<br />

for the entire project, and potential scheduling and resource problems and their solutions. The arrow diagram lets<br />

you calculate the “critical path” <strong>of</strong> the project. This is the flow <strong>of</strong> critical steps where delays will affect the<br />

timing <strong>of</strong> the entire project and where addition <strong>of</strong> resources can speed up the project.<br />

• Matrix diagram: The matrix diagram shows the relationship between two, three or four groups <strong>of</strong> information.<br />

It also can give information about the relationship, such as its strength, the roles played by various individuals or<br />

measurements.<br />

• Matrix data analysis: A complex mathematical technique for analyzing matrices, <strong>of</strong>ten replaced in this list by<br />

the similar prioritization matrix. One <strong>of</strong> the most rigorous, careful and time-consuming <strong>of</strong> decision-making<br />

tools, a prioritization matrix is an L-shaped matrix that uses pairwise comparisons <strong>of</strong> a list <strong>of</strong> options to a set <strong>of</strong><br />

criteria in order to choose the best option(s).<br />

• Process decision: The process decision program chart (PDCP) systematically identifies what might go wrong in<br />

a plan under development. Countermeasures are developed to prevent or <strong>of</strong>fset those problems. By using PDPC,<br />

you can either revise the plan to avoid the problems or be ready with the best response when a problem occurs.<br />

• Relations Diagrams: These are drawn to show all the different relationships between factors, areas, or<br />

processes. Just as importantly, the process <strong>of</strong> creating a relations diagram helps a group analyze the natural links<br />

between different aspects <strong>of</strong> a complex situation.<br />

• Systematic diagram: The tree diagram also known as systematic diagram starts with one item that branches<br />

into two or more, each <strong>of</strong> which branch into two or more, and so on. It looks like a tree, with trunk and multiple<br />

branches. It is used to break down broad categories into finer and finer levels <strong>of</strong> detail. Developing the tree<br />

diagram helps you move your thinking step by step from generalities to specifics.<br />

2.3 Other tools<br />

• Brainstorming: Brainstorming is a simple way for a group to generate multiple ideas such as possible solutions<br />

to a known problem. When you need as many ideas as possible. The classic method <strong>of</strong> round-the-table<br />

suggestions helps solve process improvement problems.<br />

• Control Plan: It is a management tool to identify and monitor the activity required to control the critical inputs<br />

or key outputs for a process so the process will continually meet its product or service goals. Control plans are<br />

usually monitored at least by Quality Assurance, departments using inspection procedures and sometimes using<br />

quality function deployment methods. Control charts are typically used in a control plan to monitor items.<br />

• Force Field Analysis: It is a useful decision-making technique. It helps us in making a decision by analyzing<br />

the forces for and against a change, and it helps you communicate the reasoning behind your decision.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

• Questionnaire: It is a list <strong>of</strong> questions designed to collect specific information. A questionnaire is a research<br />

instrument consisting <strong>of</strong> a series <strong>of</strong> questions and other prompts for the purpose <strong>of</strong> gathering information from<br />

respondents. Although they are <strong>of</strong>ten designed for statistical analysis <strong>of</strong> the responses, this is not always the<br />

case.<br />

• Sampling: A process used in statistical analysis in which a predetermined number <strong>of</strong> observations will be taken<br />

from a larger population. The methodology used to sample from a larger population will depend on the type <strong>of</strong><br />

analysis being performed, but will include simple random sampling, systematic sampling and observational<br />

sampling.<br />

2.4 Techniques<br />

• Benchmarking: Benchmarking is a self-improvement tool for organisations. It allows them to compare<br />

themselves with others, to identify their comparative strengths and weaknesses and learn how to improve.<br />

Benchmarking is a way <strong>of</strong> finding and adopting best practices.<br />

• Departmental Purpose Analysis: Department purpose analysis (DPA) is a process for applying the concepts<br />

and principles <strong>of</strong> management in a practical way. It is designed to ensure that a department, team or group is<br />

achieving goals that contribute to the company's strategy and overall goals, and that the department's activities<br />

add value. A key step in the process is a clear focus on agreeing, measuring and meeting customer (internal and<br />

external) requirements.<br />

• Design <strong>of</strong> Experiments: DOE is a systematic approach to investigation <strong>of</strong> a system or process. A series <strong>of</strong><br />

structured tests are designed in which planned changes are made to the input variables <strong>of</strong> a process or system.<br />

The effects <strong>of</strong> these changes on a pre-defined output are then assessed.<br />

• Failure Mode Effect Analysis: Failure Modes and Effects Analysis (FMEA) is a systematic, proactive method<br />

for evaluating a process to identify where and how it might fail and to assess the relative impact <strong>of</strong> different<br />

failures, in order to identify the parts <strong>of</strong> the process that are most in need <strong>of</strong> change.<br />

• Fault Tree Analysis: Fault tree analysis (FTA) is a top down, deductive failure analysis in which an undesired<br />

state <strong>of</strong> a system is analyzed using Boolean logic to combine a series <strong>of</strong> lower-level events. This analysis<br />

method is mainly used in the field <strong>of</strong> safety engineering and Reliability engineering to determine the probability<br />

<strong>of</strong> a safety accident or a particular system level (functional) failure.<br />

• Poka Yoke: Poka Yoke is any process that can stop mistakes being created, thereby ensuring that there are no<br />

defects within the production process. So if a machine is designed to stop or at least sound a warning signal if it<br />

is not aligned correctly then this is ‘Poka Yoke’ in action. The operator will be alerted to the fact that the<br />

machine has not been correctly aligned and instead <strong>of</strong> faulty goods being created, or the machine continuing and<br />

then perhaps breaking down the operator will take the necessary steps to ensure that the problem is resolved<br />

before the faulty goods are created or before the machine breaks down.<br />

• Problem Solving Methodology: The process <strong>of</strong> working through details <strong>of</strong> a problem to reach a solution.<br />

Problem solving may include mathematical or systematic operations and can be a gauge <strong>of</strong> an individual's<br />

critical thinking skills.<br />

• Quality Costing: Quality Costing provides pragmatic advice on how to set about introducing and developing a<br />

quality costing system and using the data that emerges. Quality costs help to show the importance <strong>of</strong> qualityrelated<br />

activities to management; they demonstrate the cost <strong>of</strong> nonquality to an organization; they track the<br />

causes and effects <strong>of</strong> the problem, enabling the working out <strong>of</strong> solutions using quality improvement teams, and<br />

then monitoring progress (Dale & Plunkett, <strong>19</strong>99).<br />

• Quality Function Deployment: Quality Function Deployment is a systematic approach to design based on a<br />

close awareness <strong>of</strong> customer desires, coupled with the integration <strong>of</strong> corporate functional groups. It consists in<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

translating customer desires (for example, the ease <strong>of</strong> writing for a pen) into design characteristics (pen ink<br />

viscosity, pressure on ball-point) for each stage <strong>of</strong> the product development (Rosenthal, <strong>19</strong>92).<br />

• Quality Improvement Teams: Quality improvement teams provide a mean <strong>of</strong> participation for employees in<br />

quality decision – making. They aids in employee development, leadership, problem solving skills and lead to<br />

quality awareness which is essential for organizational change.<br />

• Statistical Process Control: Statistical Process Control is a scientific visual method used to monitor, control<br />

and improve processes by eliminating special cause variation from manufacturing, service and financial<br />

processes. SPC is a key continuous improvement tool.<br />

3.0 conclusions<br />

The use <strong>of</strong> tools and techniques is a vital component <strong>of</strong> any successful improvement process. These tools and<br />

techniques can only be beneficial for any manufacturing industry after the proper training <strong>of</strong> their employees so that<br />

they understand these tools effectively. Therefore, the use <strong>of</strong> tools and techniques for quality improvement is<br />

necessary for quality improvement. The weakness <strong>of</strong> certified firms is a lack <strong>of</strong> support for and commitment towards<br />

the use <strong>of</strong> tools and techniques for quality improvement, mainly regarding the basic tools; on the other hand, it must<br />

also be admitted that there are some companies that have not benefited from and improved their performance by<br />

using these techniques and tools. The solution can be found in a higher managerial commitment, promoting their use<br />

among all the employees, together with a planning and training process covering teamwork methods and the use <strong>of</strong><br />

these tools and practices. In other words, managers may encourage a higher number <strong>of</strong> employees to use these<br />

techniques in a way that benefits the whole firm. The paper describes all major quality tools and techniques<br />

necessary for quality management in manufacturing industry.<br />

4.0 References:<br />

1. G.S Dangayach, S.G Deshmukh (<strong>20</strong>03). Evidence <strong>of</strong> manufacturing strategies in Indian industry: a survey,<br />

International Journal <strong>of</strong> Production Economics. Vol. 83, No. 3, 279-298.<br />

2. Papulova, E., Papulova Z. (<strong>20</strong>06), Competitive strategy and competitive advantages <strong>of</strong> small and midsized<br />

manufacturing enterprises in Slovakia, E-Leader, international leadership and networking conference, Slovakia.<br />

3. Teresa Werner, Albert Weckenmann (<strong>20</strong>12). Sustainable quality assurance by assuring competence <strong>of</strong> employees,<br />

Measurement. Vol. 45, No. 6, Pages 1534-1539.<br />

4. W. Geiger, Qualitätslehre, Vieweg, Braunschweig, <strong>19</strong>94.<br />

5. P.B. Crosby (<strong>19</strong>79). Quality is Free, the Art <strong>of</strong> Making Quality Certain. Hodder & Stoughton, New York.<br />

6. W.E. Deming (<strong>19</strong>82). Quality, Productivity and Competitive Position. MIT Center for Advanced Engineering,<br />

Cambridge, MA.<br />

7. K. Ishikawa (<strong>19</strong>85). What is Total Quality Control The Japanese Way. Prentice-Hall, London.<br />

8. J.M. Juran (<strong>19</strong>88). On Planning for Quality. Collier Macmillan, London.<br />

9. A.V. Feigenbaum (<strong>19</strong>91). Total Quality Control. McGraw-Hill, New York.<br />

10. Juan José Tarı́, Vicente Sabater (<strong>20</strong>04). Quality tools and techniques: Are they necessary for quality<br />

management, International Journal <strong>of</strong> Production Economics. Vol. 92, No. 3, 267-280.<br />

11. R.E. McQuater, C.H. Scurr, B.G. Dale, P.G. Hillman (<strong>19</strong>95). Using quality tools and techniques successfully, The<br />

TQM Magazine. Vol. 7, No. 6, 37–42.<br />

12. J. McConnell (<strong>19</strong>89). The Seven Tools <strong>of</strong> TQC, 3rd edition. The Delaware Group, NSW.<br />

13. M. Imai (<strong>19</strong>86). Kaizen, the Key to Japan's Competitive Success. McGraw-Hill, New York .<br />

14. J.W. Dean, J.R. Evans. Total Quality, Management, Organization and Strategy. West Publishing Company, St.<br />

Paul, MN.<br />

15. D.L. Goetsch, S.B. Davis (<strong>19</strong>97). Introduction to Total Quality, Quality Management for Production, Processing,<br />

and Services. Prentice-Hall, Englewood Cliffs, NJ.<br />

16. B.G. Dale (<strong>19</strong>99). Managing Quality. Blackwell Publishers, Oxford.<br />

17. J.R. Evans, W.M. Lindsay (<strong>19</strong>99). The Management and Control <strong>of</strong> Quality. South-Western College Publishing,<br />

Cincinnati, OH.<br />

18. B.G. Dale, R. McQuater (<strong>19</strong>98). Managing Business Improvement & Quality Implementing Key Tools and<br />

Techniques. Blackwell Business, Oxford.<br />

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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

<strong>19</strong>. Rowland-Jones R., Page-Thomas K., Thomas P.T. (<strong>20</strong>07). 'Quality Management' Tools & Techniques: Pr<strong>of</strong>iling<br />

SME use & Customer Expectations, International Journal <strong>of</strong> Quality and Standards. Vol. 1, No -1, 163 – 179.<br />

<strong>20</strong>. Barrie G. Dale and J.J. Plunkett (<strong>19</strong>99). Quality Costing, Third Edition, Gower Publishers. 978-0-566-08260-3.<br />

21. Rosenthal, Stephen R (<strong>19</strong>92). Effective product design and development, How to cut lead time and increase<br />

customer satisfaction, Business One Irwin, Homewood, Illinois 60430.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

SIMULATION BASED ANALYSIS OF THE BULLWHIP EFFECT UNDER<br />

DIFFERENT INFORMATION SHARING STRATEGIES<br />

B. A.MIR, A. JAYANT, A. SINGH<br />

Department <strong>of</strong> Mechanical Engineering, Sant Longowal Institute <strong>of</strong> Engg. & <strong>Technology</strong>, Longowal, Sangrur,<br />

Punjab – 148106 (INDIA) (Deemed <strong>University</strong> Est. by Govt. <strong>of</strong> India)<br />

E-mail ID: arvindjayant@rediffmail.com<br />

Abstract<br />

In this paper we are simulating a three-stage supply chain that is based on the Stock-to-Demand inventory type.<br />

The aim <strong>of</strong> the simulation is to investigate the well-known phenomenon <strong>of</strong> the bullwhip effect, and identify the<br />

parameters that affect it. To investigate and measure this impact, a simulation model is developed using Arena<br />

11 s<strong>of</strong>t-ware package for a three-stage supply chain, consisting <strong>of</strong> a single retailer, wholesaler, and a<br />

distributor. Since the bullwhip effect is based on an interrelated network <strong>of</strong> parameters, the model will be<br />

changed to affect the change in these parameters on the variance amplification <strong>of</strong> orders. It has been observed<br />

that how lack <strong>of</strong> information, lack <strong>of</strong> transparency throughout the supply chain and a disconnect between<br />

production and real-time supply chain information result in increasing lost sales, bad customer service, high<br />

inventory levels and unrealized pr<strong>of</strong>its. Simulation modeling, presented in this work allows the user to analyze<br />

the performance <strong>of</strong> the three tier supply chain network and to understand the complex relationship between the<br />

parties involved. The findings from the simulation suggest that the model calculates customer service levels, total<br />

cost, waiting times, inventories and demands at every stage in a predictable manner.<br />

Keyword: Bullwhip effect, simulation modeling, Information sharing, business performance<br />

1. Introduction<br />

The bullwhip effect describes the phenomena <strong>of</strong> the amplification <strong>of</strong> demand order variability’s as they moved<br />

up the supply chain. The distortion <strong>of</strong> information throughout a supply chain can lead to tremendous<br />

inefficiencies. The underlying causes for the bullwhip effect are multiple and a thorough understanding can help<br />

counteract upon it. This cannot be over emphasized, since the supply chain system is inherent to its cause; the<br />

underlying demand characteristics and replenishment lead times The global market increasing competition, the<br />

product life cycle reduction and the more demanding customer had forced enterprises and businesses to pay<br />

more attention to supply chain management. The order information transmitted along supply chain appears scaleup<br />

effect, named bullwhip effect. It consumedly increased operation cost <strong>of</strong> supply chain and reduced its<br />

efficiency. Therefore, the study <strong>of</strong> bullwhip effect in supply chain and its restraining method is <strong>of</strong> great<br />

important. That enhancement <strong>of</strong> connection and cooperation between supply chain various nodes, and the<br />

information sharing degree, being seamless joint driven by customer demand, are the key to reduce the supply<br />

chain cost, restrain bullwhip effect and enhance supply chain management effectively. For that, we analyzed the<br />

reason <strong>of</strong> bullwhip effect development and the alleviation countermeasure, established a three-echelon supply<br />

chain simulation model base on that, implemented information sharing at upstream nodes and quantitatively<br />

analyzed the restrain effect <strong>of</strong> information sharing to bullwhip effect.<br />

This paper is arranged as follows: After reviewing some <strong>of</strong> the most relevant literature on multi-echelon supply<br />

chains in Section 2, a detailed description <strong>of</strong> problem formulation presented, the Arena simulation model and<br />

assumptions are given in Section 3. Section 4 & 5 discusses the simulation experiment presented in this paper<br />

and provides the simulation results. Finally the conclusions <strong>of</strong> this paper and future work to be done are<br />

summarized in Section 6.<br />

2. Literature review<br />

The Bullwhip effect research on information sharing in the supply chain was initiated by Forrester (<strong>19</strong>61) who<br />

demonstrated that information in a supply chain, such as orders, propagates upstream with increased volatility.<br />

He illustrated the effect in case studies and pointed out that it is a result <strong>of</strong> industrial dynamics or time varying<br />

behaviors <strong>of</strong> industrial organizations. Sahay and Mohan (<strong>20</strong>02) highlighted the bullwhip effect in the ‘beer<br />

distribution game’, in an inventory management context. He attributed this phenomenon as a result <strong>of</strong> a player’s<br />

systematic irrational behavior or ‘mis-perceptions <strong>of</strong> feedback’. Chase et al. (<strong>20</strong>03) identified the bullwhip effect<br />

to demand forecasting and order lead times, based upon a model. Its effects are extended to multiple supply<br />

chains with or without centralized customer demand information and demonstrate that the bullwhip effect can be<br />

reduced but not entirely eliminated, by centralizing demand information. They studied that the use <strong>of</strong> an<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

exponential smoothing forecast by the retailer can cause the bullwhip effect and contrasted these results with<br />

variability due to the use <strong>of</strong> a moving average forecast.<br />

Samuel and Mohanty (<strong>20</strong>02) have said that the ‘Demand Signal Processing’ (DSP) is one <strong>of</strong> the causes for the<br />

whiplash or bullwhip phenomenon. Updating <strong>of</strong> demand forecasts from downstream level to upstream level in a<br />

supply chain based on the signals <strong>of</strong> increase or decrease in demand is referred to as Demand Signal Processing.<br />

They have studied the impact <strong>of</strong> DSP on bullwhip effect and how information sharing can minimize this effect,<br />

with the help <strong>of</strong> decentralized supply chain model and alternative information sharing model. Tang et al. (<strong>20</strong>02)<br />

have developed a program called ‘Advance Booking discount (ABD) program to manage demand uncertainty for<br />

short life cycle products. This program entices customers to pre-commit their orders at a discount price prior to<br />

the selling season. however, such orders are filled during the selling season. The time between the placement<br />

and the fulfillment <strong>of</strong> these pre-committed orders provides an opportunity for the retailers to update demand<br />

forecasts by utilizing information generated from the pre-committed orders at the beginning <strong>of</strong> the selling<br />

season. Huang et al. (<strong>20</strong>07) develop models <strong>of</strong> a class <strong>of</strong> supply chain systems, including a multi-echelon supply<br />

chain system, a time-lag dynamic supply chain system, and a dual-channel supply chain with a B2B e-market,<br />

and analyze each <strong>of</strong> the bullwhip effects respectively. They address a new method for dynamic quantification<br />

and calculations <strong>of</strong> the bullwhip effect based on classical control theories and methods, and discuss the H control<br />

strategies <strong>of</strong> these systems under the worst fluctuation <strong>of</strong> demand. Finally, combined with the empirical practices<br />

<strong>of</strong> the most representative state-owned companies in China, they carry out three simulation experiments, and<br />

from the results have found that the bullwhip-effect coefficients <strong>of</strong> these three systems are all controlled and<br />

dampened with the H control method. Nienhaus and Ziegenbein (<strong>20</strong>06) describe the beer distribution game<br />

online, which is a web-based simulation <strong>of</strong> a supply chain with four tiers. Results <strong>of</strong> this simulation allow for the<br />

first time the analysis <strong>of</strong> how humans perform as a partner in a supply chain compared with simple agent-based<br />

strategies. A study by Lin and Lin (<strong>20</strong>06) examines the bullwhip effect caused by order variance from retailers.<br />

It shows that based on portfolio theory, supplier's demand variance can be reduced by adjusting the order<br />

quantities <strong>of</strong> retailers through co-ordination. The results indicate that this approach can be a useful means for<br />

alleviating the bullwhip effect.<br />

3. Problem explanation<br />

The main aim <strong>of</strong> this work is to compare the performance <strong>of</strong> the three tier supply chain with two types <strong>of</strong><br />

information strategies i.e. centralized and decentralized information. The research objectives <strong>of</strong> the present work<br />

are<br />

1. To study the existing supply chain (supply chain with decentralized information strategy) <strong>of</strong> the company<br />

ABC Ltd. and to identify the drawbacks.<br />

2. To study the two types <strong>of</strong> information sharing strategies in supply chain management i.e. centralized and<br />

decentralized and compare the supply chain performance associated with both.<br />

3. To find out the best information sharing strategy from the analysis which has reasonable cost and at the same<br />

time should capable enough to give the better performance.<br />

4. Design and development <strong>of</strong> simulation models (ARENA 11.0 simulation s<strong>of</strong>tware) <strong>of</strong> supply chain with<br />

Centralized and Decentralized information strategy in order to improve performance level.<br />

4. Models development to bullwhip effect reduction<br />

In the present work a multi echelon supply chain has been created in which entities are customers, retailers,<br />

distributors ,output buffer, input buffer and suppliers. At the beginning the customer will place order to the<br />

retailer, the retailer will hold this demand how long the earlier customers demand have been fulfilled. Then it<br />

will check its inventory stock, if available it will provide this product to customer if not it will order from<br />

distributor .The distributor will check its demand and if not available there is a loss <strong>of</strong> customer. Further the<br />

distributor will order from the output buffer <strong>of</strong> the plant, if not available will take from input buffer. The input<br />

buffer, if not having enough stock will order it from the supplier and the process goes like this .For supplier we<br />

have assumed that there is no demand loss. So, we are taking the two flows in our supply chain (demand flow<br />

and material flow).<br />

4.1 Model <strong>of</strong> Decentralized & Centralized Information Sharing<br />

In the present work two conceptual supply chain models has been developed for the analysis named as<br />

Centralized and Decentralized information sharing strategy .We have compared the performance parameters <strong>of</strong><br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

both these information strategy models in three tier supply chain environment. It has been observed that<br />

centralized information strategy is much more efficient than decentralized .The inventory levels in the<br />

decentralized information equipped supply chain is more than in supply chain with centralized information<br />

strategy. The conceptual models has been shown in figure 1 and figure 2.<br />

Customer demand Retailer Distributor output buffer<br />

plant input buffer supplier<br />

Orders<br />

Material flow<br />

Centralized information-All stages have access to end customer data<br />

Figure 1 Supply chain model with centralized information sharing strategy<br />

Customer demand Retailer Distributor output buffer<br />

plant input buffer supplier<br />

orders<br />

Material flow<br />

Decentralized information-All stages base their forecast on the direct customer’s demand<br />

Figure 2 Supply chain model with decentralized information sharing strategy<br />

4.2 Simulation Modeling <strong>of</strong> Bullwhip Effect<br />

The Arena Simulation approach has been used to study the difference in applying both the information sharing<br />

strategies in the working <strong>of</strong> the company. It has been noticed that the Centralized information is the best strategy<br />

to be adopted by the company ABC Ltd<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

customer demand<br />

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0<br />

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Figure 3 Simulation model with decentralized information (main model)<br />

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input buf f er<br />

input buf f er<br />

0 0<br />

assign input<br />

buf f er demand t o<br />

supplier<br />

supplier<br />

0<br />

dispose input<br />

buf f er demand<br />

0<br />

assign cust omer<br />

demand t o input<br />

budf f er<br />

assign cust omer<br />

demand t o<br />

supplier<br />

Figure 4 Simulation Model with centralized information (main model)<br />

4.3 Simulation Model Translation<br />

Models have been developed by using ARENA Simulation S<strong>of</strong>tware to study the functioning <strong>of</strong> the company<br />

and new model has been devised to make the system performance efficient. We have built models in such a<br />

manner that what we study about the system should be same what we have developed through models.<br />

Validation confirms about the realistic characteristics <strong>of</strong> the system. We have verified the model by the analysis<br />

<strong>of</strong> the predictions. We have gone through the following strategy<br />

1. Inspection <strong>of</strong> logic <strong>of</strong> simulation program<br />

2. Performing <strong>of</strong> simulation test runs with which we can inspect the correctness <strong>of</strong> the program logic<br />

3. Performing simple consistency checks<br />

Bullwhip Effect in the supply chain is quantified by using equation 1.<br />

………………….(1)<br />

M=Variance (O t<br />

)/Variance (D t<br />

)<br />

863


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Where,<br />

M=Measure <strong>of</strong> bullwhip effect<br />

O t<br />

= Order variance<br />

D t<br />

=Demand variance<br />

Verification concerns with the operational model (whether it is performing properly). It is done to ensure that:<br />

The model is programmed correctly. The model does not contain errors, oversights, or bugs. We have studied the<br />

given formula <strong>of</strong> calculating the Bullwhip Effect from Supply chain Research .To make assure that the results<br />

obtained are valid ,Let us take the result <strong>of</strong> the Replication N=90 for Centralized information, for it the order<br />

variance has been calculated by using mean and standard deviations for the order and demand. Order variance<br />

=57.81 and Demand variance = 58.59 So the value <strong>of</strong> M=57.81/58.59 i.e. 0.9866 which is 1 so<br />

Bullwhip effect is present.<br />

5. Results And Discussions<br />

In the present work simulation experiments carried out for N=70 replication and Run length has been taken as<br />

for 525600 minutes. The table 1, 2,3 and table 4 represents the results <strong>of</strong> simulation run during study. The<br />

inventory at different stages <strong>of</strong> the supply chain has been checked from the simulation results and it has been<br />

observed that the inventory at the decentralized information model is more as compared to the Centralized<br />

information sharing strategy. It is more efficient than the decentralized one. The order rate and the demand rate<br />

has also been analyzed and it has been seen that in Decentralized model, orders are more fluctuating than the<br />

demand, but in Centralized model order and demand are nearly comparable. The proposed supply chain with<br />

centralized information strategy has been developed for the company ABC Ltd, The proposed supply chain is<br />

practicing the Centralized information sharing strategy among all its supply chain partners. Figure 4 and 5<br />

clearly shows the fluctuation in demands and order with centralized and decentralized information sharing<br />

strategy in supply chain management.<br />

Table 1 Variation in Bullwhip Effect with No. <strong>of</strong> Replications (Decentralized Information)<br />

No <strong>of</strong><br />

Replications<br />

Demand<br />

variance<br />

Order variance Bullwhip effect=M=order<br />

variance/demand variance<br />

N<br />

90 46.00284 76.09645 1.6541>1<br />

70 44.836 63.7678 1.4222>1<br />

50 43.764 66.34 1.5158>1<br />

30 42.1713 65.85 1.5614>1<br />

10 41.42 64.68 1.5615>1<br />

Table 2 Variation in Bullwhip Effect with No. <strong>of</strong> Replications (Centralized Information)<br />

No <strong>of</strong> Replications Demand<br />

Order variance Bullwhip effect=M=order<br />

N<br />

variance<br />

variance/demand variance<br />

90 58.59 57.81 0.9866


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Performance parameters<br />

Existing supply chain<br />

Decentralized<br />

Proposed supply chain<br />

Centralized<br />

Percentage<br />

improvement<br />

Inventory levels at Retailer 50 47 4.47%<br />

Order at Supplier 82 76 6.59%<br />

Order at input buffer 90 74 17.82%<br />

Order at Distributor 80 52 34.74%<br />

Inventory at output buffer 57 55 2.<strong>19</strong>%<br />

Inventory at input buffer 72 70 2.00%<br />

Figure 5 Demand and order at Decentralized model<br />

Figure 6 Demand and order variation at centralized Model<br />

Table 4 Number <strong>of</strong> orders at various supply chain partners<br />

Replications Retailer Distributor Output buffer Input buffer Supplier<br />

10 76 93 100 102 103<br />

30 76 91 100 101 104<br />

50 76 92 100 100. 104<br />

70 76 91 100 103 106<br />

90 76 93 100 102 106<br />

The proposed model will enhance the company’s performance by analyzing the cost, inventory and order levels<br />

which can reduce the wastage. It has also been observed that in Decentralized information lost sales at retailer<br />

are <strong>20</strong> units and it has been reduced to 18 units in centralized information. The inventory levels for the<br />

distributor have been decreased from 53 units to 51units due to the Centralized sharing strategy Order at output<br />

buffer goes down from 100 to 74 in case using the centralized information system Inventory at input buffer has<br />

been shown going down from 72 to 70 which can improve the cost entities in the proposed supply chain Order at<br />

865


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Distributor comes down from 80 to 52 and for the input buffer the order level goes from 90 to 74 which is a<br />

considerable difference for any supply chain. Order level at Supplier decreases from 81 to 76 and the inventory<br />

for Retailer decreases 50 to 47, hence it has been concluded that the results obtained in Centralized models are<br />

far better than the existing Decentralized system.<br />

6. Conclusions & Future Scope<br />

The two different models designed in ARENA simulation s<strong>of</strong>tware for the information sharing strategies have<br />

provided the best results related to inventory, order, demand, number in , number out and various costs like<br />

usage cost ,busy cost. The variables like inventory ,waiting time, amount lost and order-demand have been<br />

compared for both the strategy and it has been found that the Centralized information is the best information<br />

sharing strategy than the Decentralized one. Centralized information model can be practiced in every industry<br />

and experts can also use this for the business purposes to minimize the loss. Graphs and tables have been used to<br />

show the performance and the stability <strong>of</strong> both the information sharing strategy that leads to the bullwhip effect<br />

in the Supply chain. Since research level has no end point, same can be incorporated that the research gaps are<br />

always there. More complex chains with multiple buyers, sellers and vendors can be included in it. To make<br />

ARENA language realistic visual basic tools which are advanced tools in ARENA can also be employed for<br />

complex supply chains<br />

References<br />

[1] Ameera Aly Ismail(<strong>20</strong>07) ‘A Simulation Model to Investigate Critical Factors Influencing the Bullwhip<br />

Effect in a Supply Chain’ Faculty <strong>of</strong> Management and Information Systems ,The French <strong>University</strong> in<br />

Egypt(<strong>20</strong>07)<br />

[2] Andar ,Bloco , Parque Tecnológico (<strong>20</strong>04) ‘Ideas for modeling and simulation <strong>of</strong> supply chain<br />

management by ARENA’ winter simulation conference.(<strong>20</strong>04)<br />

[3] Croson, R. and Donohue, K. (<strong>20</strong>04), Behavioral Causes <strong>of</strong> the Bullwhip Effect and the Observed Value<br />

<strong>of</strong> Inventory Information, OPIM Working Paper(<strong>20</strong>04)<br />

[4] D.Aprile ,A.C Garavelli(<strong>20</strong>07) ‘Bullwhip effect reduction: The impact <strong>of</strong> Supply chain flexibility’ The<br />

<strong>19</strong> th international conference on production research<br />

[5] Debabrata Das, Pankaj Dutta(<strong>20</strong>12) ‘A Simulation Study <strong>of</strong> Bullwhip Effect in a Closed-Loop Supply<br />

Chain with Fuzzy Demand and Fuzzy Collection Rate under Possibility Constraints’ International<br />

journal <strong>of</strong> Economics and management sciences .pp .296-303<br />

[6] Lee H, Padmanabham V and Whang S, Information Distortion in a Supply Chain: The Bullwhip Effect,<br />

Management <strong>Science</strong>, vol. 43, no.4, pp. 546-558,<strong>19</strong>97.<br />

[7] Lee H, Padmanabham V and Whang S, The bullwhip effect in supply chains, Sloan Management<br />

Review, vol. 38, no.2, pp. 93-102, <strong>19</strong>97.<br />

[8] Truong Ton Hien Duc, Huynh Trung Luong, Yeong-Dae Kim, A measure <strong>of</strong> bullwhip eect in supply<br />

chains with a mixed autoregressive-moving average demand process, European Journal <strong>of</strong> Operational<br />

Research, Vol.187, 243–256, <strong>20</strong>08.<br />

[9] Thomas Kelepouris, Panayiotis Miliotis, Katerina Pramatari, The impact <strong>of</strong> replenishment parameters<br />

and information sharing on the bullwhip effect: A computational study, Computers & Operations<br />

Research Vol.35, 3657-3670, <strong>20</strong>08.<br />

[10] So Young Sohn, Michael Lim, The effect <strong>of</strong> forecasting and information sharing in SCM for multigeneration<br />

products, European Journal <strong>of</strong> Operational Research, Vol.186, 276-287, <strong>20</strong>08.<br />

[11] U. W. Thonemann, Improving supply-chain performance by sharing advance demand information,<br />

European Journal <strong>of</strong> Operational Research Vol.142, 81-107, <strong>20</strong>02.<br />

[12] Huang Xiao-yuan, Wang Jing, Research Progress <strong>of</strong> the Bullwhip Effect Problem in Supply Chain:<br />

Existence, Quantification and Control, Information and Control vol. 33, no. 5, pp. 579-583, <strong>20</strong>04.<br />

[13] Zhang Qin, Da Qing-li, Shen Hou-cai, Bullwhip Effect and Assess <strong>of</strong> the Information Sharing Under<br />

ARIMA(0,1,1) Demand, Chinese Journal <strong>of</strong> Management <strong>Science</strong>, vol. 9, no. 6, pp. 1-6, <strong>20</strong>01.<br />

[14] Xu Bao-shou, et al, Simulation and PID control <strong>of</strong> bullwhip effect in supply chain, Proceedings <strong>of</strong> <strong>20</strong>07<br />

Chinese Control and Decision Conference, pp. 801-804.<br />

[15] Edgar Perea, et al, Dynamic Modeling and classical control theory for supply chain management,<br />

Computers and Chemical Engineering, vol. 24, pp. 1143-1149, <strong>20</strong>00.<br />

866


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

SUPPLIER MANUFACTURER RELATIONSHIP IN SUPPLY CHAIN<br />

MANAGEMENT: A REVIEW<br />

Vikramjeet Singh, Arvind Jayant<br />

Department <strong>of</strong> Mechanical Engineering, Sant Longowal Institute <strong>of</strong> Engineering and <strong>Technology</strong>, (Deemed<br />

<strong>University</strong>, est. by Govt. <strong>of</strong> India) Longowal, Punjab, INDIA.<br />

e-mail: arvindjayant@gmail.com<br />

Abstract:<br />

This paper investigates the current development in research and practice in supplier manufacturer relationship<br />

through content analysis <strong>of</strong> the published literature. We have used various web based search engines, books and<br />

conference proceedings to locate and review the literature. The review finds that research and practice in supplier<br />

manufacturer relationship are focused on all aspects <strong>of</strong> supplier manufacturer relationship—from literature. We<br />

position the contributions in a framework that takes the diversity <strong>of</strong> procurement situations in terms <strong>of</strong> complexity<br />

and importance into account and covers all phases in the supplier selection process from initial problem definition,<br />

over the formulation <strong>of</strong> criteria, the qualification <strong>of</strong> potential suppliers, to the final choice among the qualified<br />

suppliers. Conditions under which a manufacturer operating with a linear price contract reveals demands<br />

information truthfully with his supplier for the long term business relationship. We believe that review the <strong>of</strong> supplier<br />

manufacturer relationship provided here can help the researchers/practitioners to advance their work in the future.<br />

Keywords: Supplier-manufacturer relationship, Supply chain management, Decision Making, Information sharing.<br />

1. Introduction<br />

Supplier selection is one <strong>of</strong> the most critical activities <strong>of</strong> purchasing management in supply chain. Supplier selection<br />

is a complex problem involving qualitative and quantitative multi-criteria. A trade-<strong>of</strong>f between these tangible and<br />

intangible factors is essential in selecting the best supplier. In such circumstances decision making <strong>of</strong> purchasing<br />

management can play a key role in cost reduction. In today’s highly competitive environment, an effective supplier<br />

selection process is very important to the success <strong>of</strong> any manufacturing organization (Liu &Hai, <strong>20</strong>05).The global<br />

competition among manufacturers to co-ordinate and responds quickly the industry value chain from supplier to<br />

customer has made customer – supplier relationship management important in the new business era. In such<br />

circumstances the decision making in each business plays a key role in the cost reduction and supplier selection<br />

relationship management because doing business with appropriate supplier is beneficial for the organization to<br />

provide a sufficient production volume with good quality, very few manufacturer now own all the activities along the<br />

chain but integrate the supply network from various supplier networks and the ability to make fast and accurate<br />

decision <strong>of</strong>ten constitute to make other networks.<br />

• Support <strong>of</strong> improved business processes across the supply chain.<br />

• A next- generation architecture that can handle multi-enterprise processes.<br />

• Facilitation <strong>of</strong> rapid product cycle and new product introduction.<br />

Together this mechanism can drive competitive advantage through substantial reductions can in the true costs <strong>of</strong><br />

parts and materials, increased flexibility to respond to change in customer demand, and faster cycle times which can<br />

enhance customer satisfaction and increase market share. A common practice by manufacturer is to require their<br />

supplier to keep ample inventories <strong>of</strong> components, <strong>of</strong>ten as a condition for winning the supply contract. At the<br />

beginning <strong>of</strong> the <strong>20</strong>th century, inter-organizational transactions were the domain <strong>of</strong> marketing and distribution<br />

personnel. Because material specification was much more standard at this time, cost was the primary differentiator<br />

in transaction decision. Inter-organizational alliances or partnerships between generally not present among early <strong>20</strong>th<br />

century organization. The manufacturer in deciding the production quantities <strong>of</strong> all the product variants the<br />

corresponding order allocations among selected suppliers. In order to maintain the pr<strong>of</strong>it margin while increasing the<br />

quality level, it is essential for manufacturers to strengthen their own competitive edges by means <strong>of</strong> focusing their<br />

resources on the core competences. It is an increasing trend for manufacturers to build a close and collaborative<br />

relationship with their suppliers through outsourcing. These suppliers, through superior performance, can leverage<br />

the manufacturers to a higher level <strong>of</strong> competitiveness or success. By forming such link, a manufacturer becomes a<br />

867


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

customer-focused organization through collecting customer order and requirement and then subcontracting the order<br />

to appropriate suppliers to achieve total customer satisfaction. Hence, the selection <strong>of</strong> suppliers becomes a crucial<br />

factor for the manufacturer to become a successful out-sourced type company to get customer satisfaction in the<br />

business. Two most important questions regarding supplier-manufacturer relationships concern the nature <strong>of</strong> the<br />

commercial outcome and the nature <strong>of</strong> the interaction between the two parties. When we think about the commercial<br />

outcome <strong>of</strong> a supplier-manufacturer relationship, we can simply use the concept <strong>of</strong> surplus value provided by<br />

economics. The surplus value in a relationship between a manufacturer and a supplier can be broadly defined as the<br />

difference between the costs <strong>of</strong> production <strong>of</strong> the supplier (which, <strong>of</strong> course, includes normal pr<strong>of</strong>its) and the utility<br />

function <strong>of</strong> the buyer.<br />

2. Review methodology<br />

This paper reviews the literature on Supplier-manufacturer relationship in supply chain management that has been<br />

available in the various academic journals .The aim is to scrutinize the wide literature related to suppliermanufacturer<br />

relationship in supply chain management,thus to help the academicians develop the efficient supply<br />

chains. We adopted a structural survey methodology. Initially, we collected a wide range <strong>of</strong> papers containing<br />

supplier-manufacturer relationship, supply chain management. The aim <strong>of</strong> the paper is to help researchers to<br />

understand actually the hidden meaning <strong>of</strong> Supplier- manufacturer relationship in supply chain management as well<br />

as identifying the most prominent areas for future research. Table 1 present supplier-manufacturer relationship<br />

framework to compile the research on the topic.<br />

Table.1 Supplier Manufacturer Relationship Framework<br />

CONTENTS<br />

AUTHORS<br />

Modeling by AHP & ANP Farzad, Mohammad et al.(<strong>20</strong>08),Ali Nazeri,<br />

Hasi,Awaluddin(<strong>20</strong>11),,Sanjey,Neeraj(<strong>20</strong>09),<br />

MinWu(<strong>20</strong>07),Mahdi,<br />

Abbas(<strong>20</strong>09), Onur, Bahadir et al.(<strong>20</strong>11), Amanda et al.(<strong>20</strong>09), YanmoyTamal,<br />

Parnab(<strong>20</strong>11), Parthiban, Abdul, Swati(<strong>20</strong>11), Chaiu et al.(<strong>20</strong>11). Giuseppe et<br />

al. (<strong>20</strong>09).<br />

Bullwhip effect<br />

Information sharing<br />

Risk<br />

Uncertainty<br />

G erard, Taylor(<strong>20</strong>07), Buchmeister et al.(<strong>20</strong>08), Mehdi, Reza(<strong>20</strong>11), I.Alony,<br />

A. Munoz(<strong>20</strong>07).<br />

Nucharee (<strong>20</strong>08), Badrul, Suhaiza (<strong>20</strong>07), V.C. Pandey et al. (<strong>20</strong>10), Rashed et<br />

al. (<strong>20</strong>10), Jairo.R, Gloria.L. (<strong>20</strong>11).<br />

Christopher’s. (<strong>20</strong>06). Peter, Kevin (<strong>20</strong>09), Qing et al. (<strong>20</strong>08), Zhen in Yu et al.<br />

(<strong>20</strong>01).<br />

Arnaldo,Andrea,Enrico(<strong>20</strong>05),<br />

Patcharer,Damien(<strong>20</strong>10),S.Mehdi,Behrooz(<strong>20</strong>10), Mousa et al.(<strong>20</strong>11), Owen q,<br />

Hong chen(<strong>20</strong>03).<br />

3. Modeling by AHP & ANP<br />

3.1 Analytical Hierarchy Process<br />

The Analytic Hierarchy Process (AHP) is a structured technique for organizing and analyzing complex decisions.<br />

Based on mathematics and psychology, it was developed by Thomas L. Saaty in the <strong>19</strong>70s and has been extensively<br />

studied and refined since then. It has particular application in group decision making, and is used around the<br />

business, industry, healthcare, and education. Rather than prescribing a "correct" decision, the AHP helps decision<br />

makers find one that best suits their goal and their understanding <strong>of</strong> the problem. It provides a comprehensive and<br />

rational framework for structuring a decision problem, for representing and quantifying its elements, for relating<br />

those elements to overall goals, and for evaluating alternative solutions.<br />

868


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 1 AHP Modeling<br />

3.2 Analytic Network Process<br />

The analytic network process (ANP) is a more general form <strong>of</strong> the analytic hierarchy process (AHP) used in multicriteria<br />

decision analysis. AHP structures a decision problem into a hierarchy with a goal, decision criteria, and<br />

alternatives, while the ANP structures it as a network. Both then use a system <strong>of</strong> pairwise comparisons to measure<br />

the weights <strong>of</strong> the components <strong>of</strong> the structure, and finally to rank the alternatives in the decision. In the AHP, each<br />

element in the hierarchy is considered to be independent <strong>of</strong> all the others—the decision criteria are considered to be<br />

independent <strong>of</strong> one another and the alternatives are considered to be independent <strong>of</strong> the decision criteria and <strong>of</strong> each<br />

other. But in many real-world cases, there is interdependence among the items and the alternatives. ANP does not<br />

require independence among elements, so it can be used as an effective tool in these cases.<br />

Farzad & Mohamad et al,<strong>20</strong>08)They had used different selection methods concerning supplier selection are<br />

discussed and the advantages and disadvantages <strong>of</strong> selection methods, especially the Analytic Hierarchy Process<br />

(AHP), are illustrated and compared.(Ali,Hadi&Awaluddin,<strong>20</strong>11)They propose an integrated model that evaluates<br />

suppliers and allocates order to them. In the first step, they evaluate suppliers by qualitative criteria such as financial<br />

structure, services and loyalty with Fuzzy analytical hierarchy process (FAHP) and gain their weights.(Giuseppe et<br />

al,<strong>20</strong>11) They focuses on the use <strong>of</strong> AHP and its variants to solve different aspects <strong>of</strong> the problem. The results <strong>of</strong> the<br />

study allow individuating opportunities and open issues arising by the use <strong>of</strong> multi-criteria approaches. (Sanjay,<br />

Neeraj, <strong>20</strong>09)They adopted researched methodology for the synthesis <strong>of</strong> priorities and the measurement <strong>of</strong><br />

consistencies. A consistency ratio has also been calculated. Industries has been classifies into small scale, medium<br />

scale and large scale. After analysis <strong>of</strong> the results they found that for large scale industries, vendor reliability, product<br />

quality and vendor experience are the top three vendor selection problems that needs to be taken up on priority for<br />

effective vendor selection.(Min Wu,<strong>20</strong>07)There aiming for the supplier selection problem, they discusses a class <strong>of</strong><br />

AHP (analytical hierarchy process) technique—simulation approach, which is valuable in that it examines the<br />

uncertainty in AHP and helps to reduce the uncertainty in AHP to some extent. Then the approach is illustrated by<br />

solving a simplified supplier selection problem in SCM. (Mahdi, Abbas, <strong>20</strong>09)They developed a framework for: (1)<br />

information sharing within supply chain members, (2) improving decision making process, and finally (3) strategic<br />

management <strong>of</strong> the whole supply chain. This model the decision making process is based on four prominent aspects<br />

<strong>of</strong> customer satisfaction namely: price, lead time, quality, and service level. This framework can be used by strategic<br />

decision makers who need comprehensive models to guide them in efficient decision making that increases the<br />

pr<strong>of</strong>itability <strong>of</strong> the entire chain.(Our, Bahadir et al,<strong>20</strong>11)They had employed Analytic Network Process(ANP) <strong>of</strong><br />

multi-criteria decision making (MCDM) methods is employed for the selection <strong>of</strong> the best alternative among certain<br />

suppliers. They determined the criteria and the relations between them, made pairwise comparisons and rated<br />

alternatives with the help <strong>of</strong> an expert from the company. Finally the supplier with the highest rank is selected.<br />

869


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

(Amanda et al, <strong>20</strong>09)They propose an approach based on the Analytic Network Process (ANP) with Ratings for the<br />

final supplier selection. Ratings consist in assigning categories to previously defined criteria for alternatives<br />

selection. This approach reduces the number <strong>of</strong> judgments required for a decision and allows the analysis <strong>of</strong> cases<br />

with high number <strong>of</strong> alternatives.(Tanmoy,Tamal&Parnab,<strong>20</strong>11)They had adopted novel heuristic approach is<br />

adopted as an optimization technique to solve the abovementioned multi-criteria decision making (MCDM)<br />

problem.The simulation result is compared and shown to outperform the AHP result in terms <strong>of</strong> quality <strong>of</strong> the<br />

solution.(Parthiban, Abdul &Swati,<strong>20</strong>11)They showed that supplier selection procedure is a highly essential decision<br />

making process for companies. It is an endeavour to utilize ANP for ranking the potential suppliers and making the<br />

final selection. ANP - BOCR method is solved using Super Decision package.(Chaiu et al,<strong>20</strong>11) They proposed an<br />

integrated network model from the aspect <strong>of</strong> product development so that four business functions, i.e., design,<br />

purchasing, manufacturing, and marketing, and their activities can be identified.Some dependent relations<br />

areprocessed by analytic network process (ANP) with pair-wise comparison, and suitable alternatives will<br />

beselected. In the final section, the model is employed by one leading electronic company in Taiwan.<br />

4. Bullwhip effect<br />

The bullwhip effect occurs when the demand order variability’s in the supply chain are amplified as they moved up<br />

the supply chain. Distorted information from one end <strong>of</strong> a supply chain to the other can lead to tremendous<br />

inefficiencies. Companies can effectively counteract the bullwhip effect by thoroughly understanding its underlying<br />

causes.<br />

Four major causes <strong>of</strong> the bullwhip effect:<br />

1. Demand forecast updating<br />

2. Order batching<br />

3. Price fluctuation<br />

4. Rationing and shortage gaming<br />

(Gerard, Taylor,<strong>20</strong>07)They find that wholesale industries exhibit a bullwhip effect, but retail industries generally do<br />

not exhibit the effect, nor do most manufacturing industries. Furthermore, they observe that manufacturing industries<br />

do not have substantially greater demand volatility than retail industries in demand and changing. Based on<br />

theoretical explanations for observing or not observing demand amplification, they are able to explain a substantial<br />

portion <strong>of</strong> the heterogeneity in the degree to which industries exhibit the bullwhip effect. (Buchmeister et al,<br />

<strong>20</strong>08)They experimented with two cases stable demand with single 5% changing demand in periodic 10% increases<br />

and later in the same decreases. Two stock keeping policies for all stages in the chain have been studied to keep in<br />

stock (1) one and (2) two periods demand. The effect indicates a lack <strong>of</strong> synchronization among supply chain<br />

members because <strong>of</strong> corrupt key information about actual demand. (Mehdi, Reza, <strong>20</strong>11) They considered and<br />

compared the effects <strong>of</strong> various forecasting methods on the bullwhip effects. The effect <strong>of</strong> various forecasting<br />

methods, such as Moving Average, Exponential Smoothing, and Regression, in terms <strong>of</strong> their associated bullwhip<br />

effect, in a four echelon supply chain- including retailer, wholesaler, manufacturer, and supplier- are<br />

considered.Then, the bullwhip effect measure is utilized to compare the ineffectiveness <strong>of</strong> various forecasting<br />

methods. They generate two sets <strong>of</strong> demands in thetwo cases where the demand is constant (no trend) and has an<br />

increasing trend, respectively.(I.Alony, A. Munoz,<strong>20</strong>07)They examine the limitations <strong>of</strong> these methodologies and<br />

suggest a combined approach discrete event-continuous simulation modeling approach to further study this<br />

phenomenon in complex production supply chains.<br />

5. Impact <strong>of</strong> information sharing<br />

A supply chain partnership is a relationship formed between two independent members in supply channels through<br />

increased levels <strong>of</strong> information sharing to achieve specific objectives and benefits in terms <strong>of</strong> reductions in total costs<br />

and inventories. It promises a win-win situation for the members involved. Supply chain management emphasizes<br />

the overall and long time benefits <strong>of</strong> all parties on the chain through cooperation and information sharing. The<br />

partnerships are focused on the basis <strong>of</strong> different levels <strong>of</strong> information sharing between two adjacent partners on the<br />

chain. (Nucharee, <strong>20</strong>08) They studied forecast accuracy; market knowledge, negotiation power, and supplier<br />

relationship quality were considered as influencing factors <strong>of</strong> the sourcing performance.Structural equation modeling<br />

was performed. The results indicated that two dimensions <strong>of</strong> supplier relationship quality, joint planning and<br />

information sharing positively affected sourcing performance while forecast accuracy provided only marginal<br />

influence in positive direction.(Badrul, Suhaiza,<strong>20</strong>07)They introduce how information quality plays an important<br />

870


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

role in supply chain management, particularly in the buyer-supplier relationships particularly in the Malaysian<br />

context. The information sharing among the members <strong>of</strong> the chain, particularly between buyer and supplier, will<br />

result on the big impact to the partnership in term <strong>of</strong> the business performance.(V.C.Pandey et al,<strong>20</strong>10) They<br />

observed that information sharing has significant impact on the competitive strengths <strong>of</strong> the manufacturer in order<br />

winning parameters like cost effectiveness and service level.Statistical analysis has been done to identify the<br />

relationship with the type <strong>of</strong> information sharing and the competitive strengths <strong>of</strong> the manufacturing<br />

enterprises.(Rashed et al,<strong>20</strong>10) They focus on the combined consequence <strong>of</strong> information and knowledge sharing on<br />

supplier’s operational performance through supplier-buyer relationship. They collected data from 30 Bangladeshi<br />

Readymade Garments Industry were collected through interview and mail survey. The content validity, construct<br />

validity, and reliability are tested. They findings showed that information sharing is a prerequisite for knowledge<br />

sharing and the close supplier-buyer relationship is a vital factor for escalating the supplier’s operational<br />

performance. (Jairo R, Gloria L, <strong>20</strong>11) They devoted to the study <strong>of</strong> information sharing between the members <strong>of</strong> a<br />

supply chain in a dynamic context. They consider a typical make-to-order direct sell supply chain without finished<br />

products inventory, similar to the one implemented by Internet PC sellers. They compare various scheduling<br />

algorithms implemented to study different scenarios <strong>of</strong> information sharing among the members <strong>of</strong> the chain. A<br />

simulation study is developed in order to get some insights about the impact <strong>of</strong> information sharing on the<br />

performance <strong>of</strong> the chain.<br />

6. Risk in supplier manufacturer relationship<br />

Supplier risk management is an evolving discipline in operations management for manufacturers, retailers, financial<br />

services companies and government agencies where the organization is highly dependent on suppliers to achieve<br />

business objectives. Outsourcing, globalization, lean supply chain initiatives and supplier rationalization have<br />

contributed to a highly fragmented model, where control is <strong>of</strong>ten several steps removed from the corporation. While<br />

these models have allowed companies to reduce overall costs and expand quickly into new markets, they also expose<br />

the company to the risk <strong>of</strong> a supplier suddenly going bankrupt, closing operations or being acquired. (Christopher S,<br />

<strong>20</strong>06) They reviewed various quantitative models for managing supply chain risks. They also relate various supply<br />

chain risk management (SCRM) strategies examined in the research literature with actual practices.(Peter,<br />

Kevin,<strong>20</strong>09)They presents preliminary researchconceptsregardinganewapproachtotheidentification and prediction<br />

<strong>of</strong>supply risk. They asses and classify <strong>of</strong> suppliers is based on supplier’s attributes, performances and supply chain<br />

characteristics. The findings are explained with in the Contingency theory. (Qing et al, <strong>20</strong>08)They developed a new<br />

supply chain network model with multiple decision-makers associated at different tiers and with multiple<br />

transportation modes for shipment <strong>of</strong> the good between tiers.The models also incorporate the individual attitudes<br />

towards disruption risks among the manufacturers and the retailers, with the demands for the product associated with<br />

the retailers being random. They present the behavior <strong>of</strong> the various decision-makers, derive the governing<br />

equilibrium conditions, and establish the finite dimensional variation inequality formulation. (Zhen in Yu et al, <strong>20</strong>01)<br />

They illustrates the benefits <strong>of</strong> supply chain partnership based on in information sharing for a decentralized supply<br />

chain comprising a manufacturer and retailer and derive the members optimal inventory policies under different<br />

information sharing scenarios.<br />

7. Uncertainty in relationship<br />

Supply chain in <strong>19</strong>90, when issues related to the circulation material was formed, was introduced. These categories, a<br />

wide variety <strong>of</strong> press articles and various publications won, moreover, the issue <strong>of</strong> interest was a lot <strong>of</strong> teachers and<br />

pioneers In general , a supply chain consists <strong>of</strong> different activities including: logistics, inventory, supplying resources<br />

and purchasing, production planning, the relationship between and within the organization and measuring<br />

performance. Indeed, supply chain management is nothing but integration processes, supply chain from the supplier<br />

<strong>of</strong> the primary to the client end in order to create satisfaction for the consumer end. (Arnaldo, Andrea &Enrico,<br />

<strong>20</strong>05) They applied theory to model vertical inter-firm relationships and study risk sharing between manufacturers<br />

and first-tier suppliers in the Italian high-precision air conditioning (AC) industry. They use regression analysis to<br />

test the agency model on the supplier networks (respectively <strong>of</strong> 50 and 58 suppliers) <strong>of</strong> two leading Italian high<br />

precision AC manufacturers. The regression analysis shows that both the manufacturers absorb risk to a nonnegligible<br />

degree.(Paycharee, Damien,<strong>20</strong>06) They investigated the relationships between supply chain uncertainty,<br />

supply chain relationships and firm’s performance in product and service industries. They showed that in both<br />

industries, supply uncertainty is a more significant determinant <strong>of</strong> performance than demand uncertainty.A dyadic<br />

supply chain with uncertain supplier.(S. Mehdi, Behrooz,<strong>20</strong>10)They considered a dyadic supply chain with uncertain<br />

supplier and derive a good approximation for the total cost function <strong>of</strong> described system, as weighted mean costs <strong>of</strong><br />

871


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

the one-for-one ordering policy. By using simulation studies, they show that absolute errors are significantly<br />

ignorable.(Mousa et al,<strong>20</strong>11) They examined the qualitative factors which affect the supply chain management (e.g.<br />

plant location, supply chain uncertainty, and manufacturing practices) based on performance evaluation models and<br />

then give some solutions to improve the performance and show that petrochemical industry supply chain<br />

performance is being affected by plant location, supply chain uncertainty and manufacturing practices factors.(Owen<br />

Q, Hong Che,<strong>20</strong>03) They examine the relations between supply chain structures, product differentiation, and demand<br />

uncertainty and makes two contributions. First, the analytical marketing literature on channel structures to the supply<br />

chain literature on coordination under demand uncertainty. Second, they derive explicit equilibria <strong>of</strong> different supply<br />

chain structures, compare the implications <strong>of</strong> them, and examine the impact <strong>of</strong> demand uncertainty.<br />

8. Research gaps in the literature and suggested future research<br />

Despite pr<strong>of</strong>ound contributions by research scholars and academicians <strong>of</strong> national and international repute on the<br />

topic <strong>of</strong> supplier- manufacturer relationship. The literatures reviewed still have a wide range <strong>of</strong> gaps which are to be<br />

addressed in the upcoming years with focused dedication so as to enhance the concept <strong>of</strong> supplier-manufacturer<br />

relationship in order to bridge a gap between underdeveloped, developing and developed nations.<br />

a) The researchers will focus on qualitative criteria in the future rather than a combination <strong>of</strong> both qualitative and<br />

quantitative criteria with existing methods such as AHP.<br />

b) Furthermore, an issue regards the distance between the literature and firm’s reality. So, further definition and<br />

specification <strong>of</strong> the criteria are needed.<br />

c) For further research the criteria and sub-criteria can be modified with opinions <strong>of</strong> other experts and alsoother<br />

multi criteria decision making (MCDM) methods may be applied to the same problem.<br />

d) Novel heuristic approach could be practiced as an effective vendor rating technique and further be employed in<br />

more complex vendor selection problem by incorporating more conflicting criteria and sub-criteria such as risk<br />

management, supplier pr<strong>of</strong>ile etc.<br />

e) For any companies implementing green management; it indeed requires a systematic and more complete<br />

analysis approach to judge which direction is better for companies to develop in the future.<br />

f) For future study focus on different stock keeping policies at all stages <strong>of</strong> a supply chain. The investigation will<br />

be based on the spreadsheet simulation; the bullwhip effect will be measured by the standard deviation <strong>of</strong><br />

orders.<br />

g) Use simulation to develop theories on managerial behavior in complex supply chain environments from the<br />

strategic and tactical levels <strong>of</strong> management.<br />

h) Such as trust, commitment, and also other factors that are related to the collaboration can be considered as<br />

antecedents <strong>of</strong> supplier relationship quality. Also, as some details on marketing strategies and consumers<br />

behaviors that are omitted can be included in the future researches.<br />

i) Highlighting the gap between theory and practice, and hope to motivate researchers to develop new models for<br />

mitigating supply chain disruptions.<br />

j) For future research, constructing further comprehensive metrics in order to evaluate supply chain network<br />

performance.<br />

k) Main future work is a detailed study <strong>of</strong> especially the SC strategy and structure construct. Currently, only the<br />

variables SC type, supplier type, geographical dispersion and business structure are included.<br />

l) Investigating an integrated supply chain with multi-supplier is a valuable potential area for future researches,<br />

because using multi suppliers can reduce the expected total cost.<br />

9. Concluding remarks:<br />

This paper presents a comprehensive literature review <strong>of</strong> the journal papers on supplier-manufacturer relationship in<br />

supply chain management. Present literature review is based on the basis <strong>of</strong> the previous work done by reputed<br />

researchers and academicians for studying supplier-manufacturer relationship in supply chain management. Different<br />

authors had developed different models and frameworks for studying supplier manufacturer relationship in supply<br />

chain management. As stated at the outset <strong>of</strong> this paper, the literature on supplier manufacturer relationship to date<br />

has been weak in terms <strong>of</strong> establishing probable connections between supplier & manufacturer in operations and<br />

firm’s strategy, competitive environment and business performance. Unfortunately, different theories <strong>of</strong> supplier<br />

manufacturer relationship have led to diverse and separated application and so through this review paper we have<br />

tried our best to install convergence in such a vast topic so that more generalized research findings should come in<br />

the upcoming years by our world renowned supply chain experts, academicians and research scholars.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

References:<br />

[1] Liu, F.H. F. & H. L. Hai. (<strong>20</strong>05). ` the voting analytic hierarchy process method for selecting supplier’.<br />

International Journal <strong>of</strong> Production Economics Vol.97 No.3. pp. 308-317.<br />

[2] Farzad.T, Mohammed.R, et al (<strong>20</strong>08) `A review <strong>of</strong> supplier selection methods in manufacturing industries’.<br />

Journal science and technology Vol.15 No.3 <strong>20</strong>1-<strong>20</strong>8.<br />

[3] Ali.N, Hadi .M. etal (<strong>20</strong>11)` Supplier evaluation and selection in SCM using fuzzy AHP’. 3 rd international<br />

conference an advanced manufacturing science Vol.<strong>19</strong>.<br />

[4] Giuseppe et al. (<strong>20</strong>09) `the analytic hierarchy process in the supplier selection problem’.<br />

[5] Sanjay, Neeraj, Abid.H (<strong>20</strong>09) `Analytical hierarchy process applied to vendor selection problem. Small<br />

scale, medium scale and large scale industries’.Business intelligence journal.<br />

[6] Min Wu (<strong>20</strong>07) `Topsis AHP simulation model and its application to supply chain management’. World<br />

journal <strong>of</strong> modeling and simulation. Vol.3 No.3 pp <strong>19</strong>6-<strong>20</strong>1.<br />

[7] Mahdi.S, Abbas.H (<strong>20</strong>09) `A conceptual framework for supply chain coordination in fuzzy environment’.<br />

Journal <strong>of</strong> theoretical and applied information technology.<br />

[8] Amanda.C. et al (<strong>20</strong>09) ` ANP and rating model applied to supplier selection problem’. The international<br />

symposium on the AHP.<br />

[9] Onur.Y. et al (<strong>20</strong>11) ` Supplier selection <strong>of</strong> a textile company with AHP’. 15 th international research/expert<br />

conference.<br />

[10] Tanmoy.C, Tamal.G, Parnab.K (<strong>20</strong>11) `Application <strong>of</strong> analytic hierarchy process and heuristic algorithm in<br />

solving vendor selection problem’. Business intelligence journal, PP- 167-177.<br />

[11] Parthiban.P, Abdul.Z, Swati.K (<strong>20</strong>11) `A model for supplier selection using analytic network process’.<br />

[12] ChaiuChing.C (<strong>20</strong>11) `Using ANP for the selection <strong>of</strong> green supply chain management strategies’.<br />

[13] Gerard.P, et al. (<strong>20</strong>07) `In search <strong>of</strong> the bullwhip effect’. Manufacturing & service operations management,<br />

Vol.9, No-4, Page No-457-479.<br />

[14] Buchmeister.B, et al. (<strong>20</strong>08) `Bullwhip effects problem in supply chains’. Advances in production<br />

engineering & management PP.45-55.<br />

[15] Mehdi.N, Reza.Z (<strong>20</strong>11) `Bullwhip effects analysis in a supply chain’.<br />

[16] I.Alony, A. Munoz (<strong>20</strong>07) `the bullwhip effects in complex supply chains’. International symposium on<br />

communications technologies, PP.1355-1360.<br />

[17] Nucharee (<strong>20</strong>08) `the effects <strong>of</strong> supplier relationship and negotiation power on sourcing performance: A<br />

case <strong>of</strong> fashion accessories products’.<br />

[18] BadrulNizer, Dr.Suhaiza.Z (<strong>20</strong>07) `the effects <strong>of</strong> information quality on buyer-supplier relationship:<br />

Aconceptual framework’. 7 th global conference on business & economics.<br />

[<strong>19</strong>] V.C.Pandey, S.K.Garg, Ravi Shankar (<strong>20</strong>10) `Impact <strong>of</strong> information sharing on competitive strength <strong>of</strong><br />

Indian manufacturing enterprises’. Business process management journal, Vol-16, No-2, PP- 226-243.<br />

[<strong>20</strong>] Rashed.C.A, Azeem.A, Halim.Z (<strong>20</strong>10) `Effect on information and knowledge sharing on supply chain<br />

performance. A survey based approach’. Journal <strong>of</strong> operations and supply chain management .Vol.3 No.2,<br />

PP- 61-77.<br />

[21] Jario.R, Gloria.L (<strong>20</strong>11) `on the analysis <strong>of</strong> supplier manufacturer information sharing strategies for<br />

production scheduling’.<br />

[22] Christopher’s. Tang (<strong>20</strong>06) `Perspectives in supply chain risk management’. International journal<br />

production economics .Vol.103, PP. 451-488.<br />

[23] QiangQiang, Anna.N, (<strong>20</strong>08) `Modeling <strong>of</strong> supply chain risk disruptions with performance measurement<br />

and robustness analysis’.<br />

[24] Peter Trkman, Kevin Mccormack (<strong>20</strong>09) `Supply chain risk in turbulent environments- A conceptual model<br />

for managing supply chain network risk’. International journal production economics Vol.1<strong>19</strong>, PP. 247-258.<br />

[25] Zhenxin.Y, Hong Yen, T.C.Edwin (<strong>20</strong>01) ` Benefits <strong>of</strong> information sharing with supply chain partnerships’.<br />

Industrial management & data system Vol.101 No.3, PP.114-1<strong>19</strong>.<br />

[26] Arnaldo.C, Andrea.F, Enrico.R (<strong>20</strong>05) `Risk sharing in supplier relations: An agency model for the Italian<br />

air conditioning industry’.<br />

[27] Patchree.B, Damien.P (<strong>20</strong>10 `Impact <strong>of</strong> supply chain uncertainty on business performance and role <strong>of</strong><br />

supplier and customer relationship: comparison between product and service organization’.<br />

[28] S.Mehdi, Behrooz.P (<strong>20</strong>10) `an integrated supply chain model for the supply uncertainty problem’.<br />

International conference on industrial engineering and operations management.<br />

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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[29] Mousa.R, Shahram.G, Seyyed.J.M (<strong>20</strong>11) `the effect <strong>of</strong> positioning factors uncertainty and manufacturing<br />

practices on supply chain performance in Iranian industrials petrochemical’. Australian journal <strong>of</strong> basic and<br />

applied sciences vol.5 No. (9), PP 1554-1559.<br />

[30] Owen Q. Wu, Hong.C (<strong>20</strong>03) `Chain to chain competition under demand uncertainty’.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

A GENERIC MODEL OF MULTI-ECHELON REVERSE<br />

LOGISTICS NETWORK FOR PRODUCT RETURNS<br />

S. Bansal 1, A.Jayant 1 , P. Gupta 1 , S. K. Garg 2<br />

1 Department <strong>of</strong> Mechanical Engineering, Sant Longowal Institute <strong>of</strong> Engineering and <strong>Technology</strong>, Longowal,<br />

Sangrur – 148106<br />

2 Department <strong>of</strong> Mechanical Engineering, Delhi Technological <strong>University</strong>, Delhi-110042<br />

Abstract<br />

Rapid technology advances in turbulent Indian business environment have shortened the lifecycle <strong>of</strong> white<br />

goods, resulting in the increasing number <strong>of</strong> discarded products in recent years. Due to the growing<br />

environmental concerns, several state governments have passed new regulations in order to reduce the amount<br />

<strong>of</strong> waste stream generated by mass consumption <strong>of</strong> the products in the society, to divert the discarded/End-<strong>of</strong> –<br />

Life (EOL) products from landfills, and to dispose the retired electronic & mechanical assembly based products<br />

properly. As a result, an effective reverse logistics infrastructure is required to support the product recovery<br />

activities. In this research, a noble approach for designing reverse logistics infrastructure by privategovernment<br />

partnership model is presented. Finally, discussion, recommendation and insight information in<br />

operating reverse logistics real business environment is analyzed and provided.<br />

1. Introduction<br />

Supply chain management (SCM) can be considered as a key component <strong>of</strong> competitive strategy to enhance<br />

organizational productivity, performance and pr<strong>of</strong>itability [7]. In the recent past, there has been a surge in<br />

research that examined the impact <strong>of</strong> supply chain integration on firm performance. Most SCM publications<br />

concern mainly procurement production, extending the concept beyond the point <strong>of</strong> sale is rare. Recently,<br />

increased need has been recognized to extend SCM issues beyond the point <strong>of</strong> sale in industrial manufacturing.<br />

Hence, research field <strong>of</strong> managing supply chains has been enlarged by tasks referring to the product utilization<br />

phase (e.g. service, maintenance, and others) and to the end-<strong>of</strong>-life phase (e.g. product recovery, refurbishing or<br />

recycling). Conceptually speaking, these additional tasks have been complementary traditional supply chains to<br />

closed-loop supply chains [12].<br />

Sustainability initiatives brought increasingly growing number <strong>of</strong> countries across EU and Eastern Asia to enact<br />

legislations that would demand manufacturers to assume higher responsibilities on their end-<strong>of</strong>-life products<br />

[35]. Sustainability is becoming one <strong>of</strong> the most desired and highly prized goals <strong>of</strong> modern industrial operations<br />

and environmental management as the deterioration <strong>of</strong> natural environment becomes increasingly more<br />

concerned. International Union for the Conservation <strong>of</strong> Nature and Natural Resources, the Global Tomorrow<br />

Coalition, and the World Resources Institute establish sustainability as a desired goal <strong>of</strong> environmental<br />

management, development and international cooperation. The term, “sustainability,” issued in numerous<br />

disciplines and is defined in many ways according to the context to which it is applied and whether its use is<br />

based on an ecological, social, or economical perspective. IUCN defines sustainability as improving the quality<br />

<strong>of</strong> human life while living within the carrying capacity <strong>of</strong> supporting eco-systems. Although conceptualization <strong>of</strong><br />

sustainability may differ among different interest groups, the World Commission on Environment and<br />

Development defines sustainable development, as ‘development that meets the needs <strong>of</strong> the present without<br />

compromising the ability <strong>of</strong> the future generations to meet their own needs [6]. In many Western European<br />

countries, “Green” parties have been initiated to deliver environmental concerns due to industrial and operational<br />

wastes into public, social and political action. In response to globally growing concerns for sustainability,<br />

many durable product manufacturers began to launch programs that would both reduce operational wastes and<br />

advocate environmental safety. The intent <strong>of</strong> the ‘product take-back’ laws is to pressurize durable product<br />

manufacturers to pursue sustainable development and to transform it into business practices that would promote<br />

environmental welfare, while avoiding increasingly growing waste management cost charged by municipal<br />

governments. In addition, higher customer expectations on manufacturers’ environmental responsibility have<br />

also compelled manufacturers to assume increased responsibility with regards to placing their products on the<br />

market. ‘Product take-back’ targets a wide variety <strong>of</strong> manufacturers <strong>of</strong> batteries, automobiles, waste packaging,<br />

and electrical or electronic products. Instead <strong>of</strong> filling landfills, more manufacturers are urged to take back their<br />

products for reassembling, repackaging, remanufacturing, or component recycling before redistributing to the<br />

market. Value recovery process <strong>of</strong> returned products consists <strong>of</strong> several sequential activities: collection,<br />

evaluation, disassembly, capture <strong>of</strong> recyclable components, and disposal <strong>of</strong> residuals as hazardous wastes [11].<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. Need <strong>of</strong> economically and environmentaly viable rl frame work<br />

Despite growing participation within industries, most value recovery processes still remain small, independent<br />

and highly fragmented [34]. To strategize cost efficient product take-back plan, there has been growing interest<br />

in the development <strong>of</strong> reverse logistics that drives reverse flow <strong>of</strong> returned products from the end customers back<br />

to the original equipment manufacturers. Efficient planning and execution <strong>of</strong> reverse logistics would provide<br />

firms a competitive edge in the development <strong>of</strong> sustainable, yet pr<strong>of</strong>it-generating, business strategies. Sound<br />

strategy and execution <strong>of</strong> reverse logistics would promote not only economic, but also environmental benefits as<br />

value <strong>of</strong> returned products should be counted towards savings <strong>of</strong> raw material and labor. While reverse logistics<br />

do not promise guaranteed savings, many have reported noticeable benefits: 40% less overall cost, 33% less<br />

inventory usage, and 44% higher customer satisfaction .From environmental viewpoint, reverse logistics make<br />

significant contribution towards reduction <strong>of</strong> hazardous waste, alleviation <strong>of</strong> landfill saturation and preservation<br />

<strong>of</strong> scarce raw materials [12]. Reverse logistics take fundamentally different approach from forward logistics<br />

having characteristics <strong>of</strong> highly fragmented return quantities, multiple return channels, complex transportation<br />

routing, higher level <strong>of</strong> expected serviceability for multiple Clients and variety <strong>of</strong> disposition options. Due to<br />

such characteristics, realization or execution <strong>of</strong> reverse logistics <strong>of</strong>ten entail many new challenges. Two major<br />

challenges <strong>of</strong> reverse logistics network design would include cost <strong>of</strong> value recovery process and low return rates<br />

from customers. Recent research reported the cost <strong>of</strong> reverse logistics accounts for nearly 44% <strong>of</strong> entire product<br />

take-back process [41]. Additionally, Green peace’s survey in <strong>20</strong>07 revealed that many manufacturers struggle to<br />

achieve beyond <strong>20</strong> percent <strong>of</strong> product return rate. Challenges in product take-back processes entail careful<br />

evaluation <strong>of</strong> aforementioned two key issues <strong>of</strong> reverse logistics network design in order to minimize the total<br />

operating cost, while promoting higher customer product return frequency.<br />

However, the reverse flow <strong>of</strong> products from consumers to upstream business has not received much<br />

interest [13]. Yet, reverse logistics is a big business opportunity. According to the survey in <strong>19</strong>99 that reverse<br />

logistics executive council the cost <strong>of</strong> handling, transporting and determining the disposition <strong>of</strong> returned products<br />

was $35 billion annually for U.S firms [14]. In <strong>20</strong>00 remanufacturing in the U.S. was a #35 billion per year<br />

industry [15]. Up to now, rates are still increasing. In India e-waste generation from electronics and computers<br />

industries is approximate 1050 tons and if we count imported used products from developed countries then this<br />

figures goes up to three times. From abroad used computers and electronic goods send to India by illegal<br />

practices and received by big scrap dealers. The scrap dealers take outs useful components from used products<br />

like circuit boards, switches, condenser, capacitor, batteries, transformers, copper wires, aluminums wires and<br />

other precious metals by unscientific techniques and unsafe methods. By this process various dangerous gases<br />

and metal particle like cadmium, mercury, bromine flame, poly- chlorination, Bi-finials are mixed in the<br />

environment and causes for cancer, respiratory and brain related diseases in the society.<br />

3. SAFE HANDLING OF E-WASTE<br />

Today world is facing problem <strong>of</strong> e-waste. The life <strong>of</strong> this e-waste is very long and it is not biodegradable and<br />

remains in the environment for long period, Product life cycle has been very short and day to day companies are<br />

launching new advance products due to developments <strong>of</strong> advance technologies in the world. That is main reason<br />

for the creation <strong>of</strong> e-waste in the society. In India more than 10 million computers are under use and more than 2<br />

million computers are outdated. At present in our country here is no rule or directives from government<br />

regarding retreatment and recycling <strong>of</strong> e-waste. To save the environment and society there is need to develop an<br />

economically viable and safe practice <strong>of</strong> reverse logistics/recycling model. This model may be helpful to rescue<br />

<strong>of</strong> products/components in environment friendly manner. We hereby developed a conceptual holistic generic<br />

frame work <strong>of</strong> forward and reverse supply chain networks as shown in figure 1.<br />

3.1 Secondary Markets<br />

To generally conceptualize, reverse logistics is the process <strong>of</strong> retrieving the product from the end consumer for<br />

the purposes <strong>of</strong> capturing value or paper disposal. Activities include transportation, warehousing, distribution<br />

and inventory management. Transportation is usually the largest component <strong>of</strong> reverse logistics costs. Reverse<br />

logistics services include product returns, source reduction , recycling, materials substitution, reuse <strong>of</strong> materials,<br />

waste disposal, refurbishing, repair and remanufacturing [18] Reverse logistics -and reverse logistics researchhas<br />

traditionally emphasized green logistics i.e. the use <strong>of</strong> environmentally conscious logistics strategies [18,<strong>19</strong>].<br />

While environment aspects <strong>of</strong> reverse logistics are critically important, many firms are also recognizing the<br />

economic impact <strong>of</strong> reverse logistics [<strong>20</strong>] Practically all business must deal with returns <strong>of</strong> some natures because<br />

<strong>of</strong> issues such as marketing returns (i.e. customers change their minds or find the product unacceptable), damage<br />

or quality problems, overstocks, or, merchandise that is brought back for repairs, refurbishing, or<br />

remanufacturing. NOREK (<strong>20</strong>02) provides an indication <strong>of</strong> the sheer volume <strong>of</strong> returns generated in many<br />

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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

companies. He notes that returns range from 3% to as high as 50% <strong>of</strong> total shipments across all industries;<br />

various industry studies put the true costs <strong>of</strong> returns at 3-5% <strong>of</strong> sales [21].<br />

Suppliers/<br />

Raw<br />

Green<br />

Store<br />

(Spare<br />

OE<br />

Green<br />

Green Manufacturing<br />

Producti<br />

on<br />

Inventory<br />

( d<br />

Green<br />

Distribut<br />

Custom<br />

Secondar<br />

y<br />

Remanufactur<br />

Re-Assembly/reuse unit<br />

Defectives<br />

Waste<br />

Remanufactured<br />

Plant<br />

Figure 1 Conceptual Holistic Frame work <strong>of</strong> Generic Closed Loop Supply Chain<br />

Collection<br />

Centre/<br />

3PL<br />

Inspection<br />

/<br />

Uncontrolla<br />

ble<br />

In brief, the management <strong>of</strong> the reverse flows is an extension <strong>of</strong> traditional supply chains with used product or<br />

material either returning to reprocessing organizations or being discarded. Reverse supply chain management is<br />

defined as the effective and efficient management <strong>of</strong> the series <strong>of</strong> activities required to retrieve a product from a<br />

customer and either dispose <strong>of</strong> it or recover value. The importance <strong>of</strong> studying reverse supply chains has<br />

increased in recent years for several reasons:<br />

Sales opportunities in secondary and global markets have increased revenue generation from previously<br />

discarded products.<br />

1) End-<strong>of</strong>-life take-back laws have proliferated over the past decade both in the European Union and in the<br />

United States, requiring businesses to effectively manage the entire life <strong>of</strong> the product [22, 23].<br />

2) Consumers have successfully pressured business to take responsibility for the disposal <strong>of</strong> their products<br />

that contain hazardous waste [24].<br />

3) Landfill capacity has become limited and expensive. Alternatives such as repacking, Re-manufacturing<br />

and recycling have became more prevalent and viable [25, 26]<br />

In conclusion, become <strong>of</strong> effective reverse logistics in daily operations, firms can to foster a sustainable<br />

competitive advantage and increase revenues in a highly competitive market.<br />

4. Green supply chain management operation<br />

Some <strong>of</strong> the key challenges <strong>of</strong> GSCM such as integrating remanufacturing with internal operations,<br />

understanding the effects <strong>of</strong> competition among remanufacturers, integration product design, integrating<br />

remanufacturing and RL with supply chain design are discussed as under.<br />

4.1 Green manufacturing and remanufacturing operation<br />

This is a very important area within green operations. The techniques for minimum energy and resource<br />

consumption for flow systems in order to reduce the use <strong>of</strong> virgin materials are based on three fields <strong>of</strong> study:<br />

pinch analysis, industrial energy [10] and energy and lifestyle analysis. Logistics represent up to 95% <strong>of</strong> total<br />

costs (stock <strong>19</strong>98 in recycling. Automobile, electronic, and paper recycling are the most common examples <strong>of</strong><br />

product recovery the purpose <strong>of</strong> repair is to return used products to working order. The quality <strong>of</strong> repaired<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

products is generally lower than the quality <strong>of</strong> new products. The purpose <strong>of</strong> refurbishing is to bring used<br />

products up to a specified quality. Analysis <strong>of</strong> remanufacturing facilities for household appliances and<br />

automotive parts by [21] reveals that cleaning and repairing are the most critical steps in the re manufacturing<br />

process.<br />

4.2 Organizational Size and Environmental Practice<br />

It is seen whether resources and capabilities associated with different sized organizations play a role in adopting<br />

GSCM practices. Determining whether smaller organizations are adopting at greater, lesser one even equal rate<br />

as compared to medium and larger organizations for environmental practices sets the foundation for practical and<br />

research issues. D inferences among these organizations will influence different strategies that can be applied by<br />

supply chain and logistics partners, investors, pr<strong>of</strong>essional organizations and government policy makers to aid<br />

smaller or larger organizations or both when seeking to adopt these GSCM practices and innovations. For<br />

example, if larger organizations are adopting practices earlier than their smaller counterparts. Then a diffusion<br />

mechanism through collaborative partnerships with smaller organizations may be a policy that should be<br />

encouraged.Yet, if all organizations seem to be lagging in a particular GSCM practice adoption, supply chains,<br />

umbrella pr<strong>of</strong>essional groups or even regulatory agencies may play a larger role in diffusing these innovative<br />

practices.<br />

4.3 Recent trends and examples in GSCM<br />

In recent years, some organizations have begun relying on their supply chains to improve their business<br />

performance and create value for their end customers. Manufacturers also are calling on their suppliers more<br />

frequently to create innovative ideas that exploit new emerging technologies, and reduce costs during the design<br />

and development <strong>of</strong> their products [18]. In some instances, organizations are even relying on their suppliers to<br />

deliver state-<strong>of</strong>-the-art process technology that they cannot develop internally. Consequently, enterprises wishing<br />

to minimize their environmental impacts during product design are learning that their ability to do so <strong>of</strong>ten is<br />

dependent on their ability to manage their increasingly complex supplier relationships. For instance, in <strong>20</strong>02,<br />

Hewlett-Packard established its Supply Chain Social and Environmental Responsibility Policy. The company<br />

also instituted a supplier code <strong>of</strong> conduct. Combined, these efforts have extended Hewlett-Packard’s corporate<br />

social responsibility commitment by incorporating its global supply base and reducing its supply chain risks.<br />

4.4 Capabilities for Adopting GSCM<br />

There are numerous capabilities required to adopt GSCM, Organizations have to develop their knowledge-based<br />

competencies by guaranteeing the environmental quality <strong>of</strong> incoming goods.GSCM practices require<br />

organizations to have strong inventory control systems. These systems reduce redundant stock materials and<br />

unnecessary inputs in the production process. Organizations that rely on these systems should manage materials,<br />

productive capacity and other organizational information. At their core, GSCM rely on what on Deming’s (<strong>19</strong>86)<br />

continuous improvement model.GSCM practices leverage continual improvement processes that reduce the<br />

impact <strong>of</strong> supplier inputs on the organization’s final product. Collaboration across internal departments is<br />

essential to maintaining robust GSCM practices. For instance, in utilizing GSCM,an organization must<br />

coordinate its product design department with its marketing department and its suppliers in an effort to minimize<br />

waste and environmental impact at every node in the supply chain [18].However, traditional organizational<br />

structures generally are fragmented with purchasing departments operating separately from marketing and sales,<br />

and operations functioning independently from human resources, with each having their own goals.<br />

4.5 Top Antecedents <strong>of</strong> GSCM<br />

4.5.1Management Commitment<br />

Implementation <strong>of</strong> GSCM practices in any manufacturing environment is a strategic decision, as it requires<br />

significant amount <strong>of</strong> time, effort and resources. Min et al. [21] mentioned that one <strong>of</strong> the major obstacles for<br />

implementing environmental policies is the lack <strong>of</strong> top management support. Kroon [11] proposed top-level<br />

support as one <strong>of</strong> critical elements for the successful implementation <strong>of</strong> GSCM.Zsidisin and Siferd (<strong>20</strong>01),<br />

Trowbridge (<strong>20</strong>01), and Rice (<strong>20</strong>03) mentioned that top management must be committed to complete<br />

environmental excellence.Hu and Hsu (<strong>20</strong>06) demonstrated analytically that top management support is the most<br />

important item for the successful implementation <strong>of</strong> GSCM practice in the Taiwanese electrical and electronics<br />

industries.<br />

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4.5.2 Government’s Initiative<br />

Proceedings <strong>of</strong> the National Conference on<br />

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<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The government should ignite, encourage and promote the green activities carried out by the manufacturing<br />

supply chain.Zhu et al. (<strong>20</strong>05) mentioned that China has encouraged (pressured) GSCM practice adoption to help<br />

spur economic development. One can find literatures which also claim government regulation as the major driver<br />

<strong>of</strong> environment/green efforts <strong>of</strong> manufacturing companies (Green et al., <strong>19</strong>96; Handfield et al., <strong>19</strong>97; Walton et<br />

al., <strong>19</strong>98; Eagan and Kaiser, <strong>20</strong>02; Scupola, <strong>20</strong>03; Lin, <strong>20</strong>07; and Peng and Lin, <strong>20</strong>08).The government<br />

manufacturing companies should become role models to others. They should come out with transparent<br />

legislation for environmental responsibility. Environmental regulations such as EuP (Eco-Design <strong>of</strong> Energy-<br />

Using Products), REACH (Registration, Evaluation, and Authorization <strong>of</strong> Chemicals), ELV (End <strong>of</strong> life Vehicle<br />

Directive), WEEE (Waste from Electrical and Electronic Equipment) and RoHS (Restrictions on Hazardous<br />

Substances) <strong>of</strong> the European Union are putting pressure on the companies for adopting green practices. One can<br />

find similar types <strong>of</strong> laws in other countries like China, Taiwan, Korea, Japan and the US. Such laws compel the<br />

manufacturing companies to closely look into the production processes and supplier selections. Within a few<br />

years, products will be sold in most parts <strong>of</strong> world under such legislation. The government should apply pressure<br />

so as to compel the companies to become green without any compromise.<br />

4.5.3 External Pressures for Adopting GSCM<br />

GSCM may be considered complimentary management practices relate to the institutional pressures that<br />

encourage their adoption. Institutional pressures persuade organizations to undertake similar strategic actions<br />

(H<strong>of</strong>fman, <strong>19</strong>97; Scott, <strong>20</strong>01) to increase their external legitimization (DiMaggio and Powell, <strong>19</strong>83; H<strong>of</strong>fman<br />

and Ventresca, <strong>20</strong>02). Regulatory pressures are <strong>of</strong>ten associated with an organization’s decisions to adopt GSCM<br />

practices (Birett, <strong>19</strong>98). These pressures arise from threats <strong>of</strong> non compliance penalties and fines (Davidson and<br />

Worrell, <strong>20</strong>01) and requirements to publicly disclose information about toxic chemical releases(Konar and<br />

Cohen, <strong>19</strong>97).For instance, regulatory changes in automotive paints have pressed car manufacturers to require<br />

their suppliers to reduce their use <strong>of</strong> regulated chemicals in the production process(Geffen and<br />

Rothenberg,<strong>20</strong>00). In addition to regulatory pressures, Market Pressures may influence an organization’s<br />

decision to adopt on GSCM practices (Rao, <strong>20</strong>02; Gupta and Piero, <strong>20</strong>03). Over the last ten years, market actors<br />

have been placing greater pressures on organizations to consider their impacts on the natural environment<br />

(H<strong>of</strong>fman, <strong>20</strong>00). Overall, 15 percent <strong>of</strong> US consumers routinely pay more for green products, and another 15<br />

percent seek green products if they do not cost more (Ginsberg and Bloom, <strong>20</strong>04). While these findings suggest<br />

that markets are creating opportunities for environmental friendly organizations, the majority <strong>of</strong> consumers still<br />

are not influenced by a company’s proactive environment practices. However, these same customers may be<br />

persuaded to change their purchasing decisions if a company violates environmental laws or emits high levels <strong>of</strong><br />

toxins (Prakash, <strong>20</strong>00). As a consequence, EMS and GSCM adoption may provide a vehicle for organizations to<br />

‘signal’ to market participants that their environmental strategies adhere to or exceed generally accepted<br />

environmental standards. Doing so may lead to greater acceptance <strong>of</strong> the organization’s strategic approach<br />

(DiMaggio and Powell, <strong>19</strong>83) and insulate organizations from competitor’s criticisms (King and Lenox, <strong>20</strong>01).<br />

EMS and GSCM adoption also may help organizations develop an environmentally conscious reputation. Such a<br />

re-reputation may invite patronage from consumers and generate opportunities for business with other<br />

organizations that value these principles (Darnall and Carmin, <strong>20</strong>05). Finally, organizations are subjected to<br />

Pressures from the community that includes environmental groups, community groups, media, labor unions<br />

and industry associations (H<strong>of</strong>fman, <strong>20</strong>00). Each <strong>of</strong> these groups can marshal public support for or against an<br />

organization’s environmental performance (Clair, Milliman and Mitr<strong>of</strong>f, <strong>19</strong>95; Turcotte, <strong>19</strong>95).<br />

4.5.4 Green Procurement<br />

Green procurement is defined as an environmental purchasing consisting <strong>of</strong> involvement in activities that include<br />

the reduction, reuse and recycling <strong>of</strong> materials in the process <strong>of</strong> purchasing. Besides green procurement is a<br />

solution for environmentally concerned and economically conservative business, and a concept <strong>of</strong> acquiring a<br />

selection <strong>of</strong> products and services that minimizes environmental impact Supplier selection: (1) purchase<br />

materials or parts only from “Green Partners” who satisfy green partner environment quality standards and pass<br />

an audit process in following regulations for the environment-related substances (2) consider suppliers who<br />

acquire ISO 14000, OHSAS18000 and/ or RoHS directives(3) select suppliers who control hazardous substances<br />

in company’s standard lists and obtain green certificate achievements EPP is the act <strong>of</strong> purchasing products or<br />

services that have a less adverse effect on human health and the environment.<br />

4.5.5 Green Manufacturing<br />

Green manufacturing is defined as production processes which use inputs with relatively low environmental<br />

impacts, which are highly efficient, and which generate little or no waste or pollution. Green manufacturing can<br />

lead to lower raw material costs, production efficiency gains, reduced environmental and occupational safety<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

expenses, and improved corporate image. Activities in green manufacturing are: Hazardous substance control:<br />

(1) lead free-replace other substances such as bismuth, silver, tin, gold, copper (2) rinse parts with clean water<br />

instead <strong>of</strong> using chemicals and reuse water (3) quality control in inputs at vendor site and recheck before<br />

processing Energy-efficient technology: (1) reduce power consumption in products such as ramp load/unload<br />

technology in HDD (2) increase product lifespan resulting in higher efficiency and productivity.<br />

4.5.6 Green Distribution<br />

Green distribution consists <strong>of</strong> green packaging and green logistics. Packaging characteristics such as size, shape<br />

and materials have an impact on distribution because <strong>of</strong> their effect on the transport characteristics <strong>of</strong> the<br />

product. Better packaging along with rearranged loading patterns can reduce materials usage, increase space<br />

utilization in the warehouse and in the trailer, and reduce the amount <strong>of</strong> handling required. Activities in green<br />

distribution are Green packaging: (1) downsize packaging (2) use “green” packaging materials (3) cooperate<br />

with vendor to standardize packaging (4) minimize material uses and time to unpack (5) encourage and adopt<br />

returnable packaging methods (6) promote recycling and reuse programs. Green logistics/transportation: (1)<br />

deliver directly trouser site (2) use alternative fuel vehicles (3) distribute products together, rather than in smaller<br />

batches (4) change to modal shift.<br />

4.5.7 Reverse Logistics<br />

One <strong>of</strong> the collective solutions that industries have come up with is the development <strong>of</strong> the reverse logistics that<br />

focus on the value recovery <strong>of</strong> returned products for recycling or remanufacturing. Reverse logistics refers to the<br />

logistics management skills and activities involved in reducing, managing and disposing packages or products.<br />

Srivastava defines reverse logistics as “Integrating environmental thinking into supply chain management<br />

including product design, material sourcing and selection, manufacturing processes, delivery <strong>of</strong> the final product<br />

to the consumers as well as end-<strong>of</strong>-life management <strong>of</strong> the product after its useful life”. A growing responsibility<br />

towards the environment and governmental regulations, and increasing awareness <strong>of</strong> valuable commercial<br />

opportunities in collecting, recycling, and reusing products and materials stimulate the development. One <strong>of</strong> the<br />

obvious challenges <strong>of</strong> reverse logistics is reverse distribution <strong>of</strong> goods and information; which fundamentally<br />

differs from that <strong>of</strong> forward logistics in terms <strong>of</strong> direction <strong>of</strong> material and information flow and their respective<br />

volume. Due to its difficulties in handling, reverse logistics cost exceeds $35 billion dollars per year for US<br />

companies. For above reasons, many companies treat reverse-logistics as a non-revenue-generating process<br />

which would <strong>of</strong>ten result in a very few resources allocated to this part <strong>of</strong> the supply chain. However, more and<br />

more firms now realize that reverse logistics is a business process by itself with growing attention towards<br />

sustainability and environmental responsibility. Hawken et al. envision economic benefits <strong>of</strong> as much as 90%<br />

through reduction <strong>of</strong> energy and materials consumption. Practice <strong>of</strong> reverse logistics entails a series <strong>of</strong> tasks to<br />

capture value <strong>of</strong> products returned for recycling.<br />

Product acquisition to obtain the products from end-users<br />

• Transshipment from point <strong>of</strong> acquisition to a point <strong>of</strong> disposition<br />

• Testing, sorting, and disposition to determine products’ economic attractiveness<br />

• Refurbish to facilitate the most attractive economic options: reuse, repair, Remanufacture, recycle, or<br />

disposal<br />

• Remarketing to create and exploit secondary markets<br />

As reverse logistics fundamentally differ in many aspects <strong>of</strong> operations from forward logistics, strategic<br />

development <strong>of</strong> competitive reverse logistics entails careful evaluation, design, planning and control. Product<br />

acquisition would initiate at initial collection centers (ICPs) and consolidation would continue before reaching<br />

centralized return center (CRC) or manufacturer who would process remanufacturing.<br />

5. Industry response towards reverse logistics<br />

In many ways, industries have been focusing on maximizing financial or productive capital gain while<br />

consuming natural and social capital as needed. Global environmental awareness, however, have brought<br />

environment friendly or green initiatives in every aspect <strong>of</strong> product operations. Xerox’s accomplishment <strong>of</strong><br />

‘zero-waste to-landfill’ engineering can be a very good example <strong>of</strong> ‘cleaner production [15]. Increasingly many<br />

industries have adopted concepts <strong>of</strong> cleaner production and developed many strategic approaches and practices<br />

that increase re-manufacturability or recyclability <strong>of</strong> products or eliminate harmful wastes. Waste Electric and<br />

Electronic Equipment (WEEE) directive <strong>of</strong> the European Union; for instance, obliges manufacturers <strong>of</strong> electric<br />

and electronic equipment to assume extended responsibility by taking back equipments reached end-<strong>of</strong>-life state<br />

for re-processing and recovery.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Radical transformation did more than mere improvement <strong>of</strong> corporate images. The financial impact has been<br />

remarkable. 3M’s 3P (also known as Pollution Prevention Pays) project has saved the company more than $1<br />

billion in its first year by aggressively limiting harmful by-products and wastes. Kathy Reed <strong>of</strong> 3M noted<br />

“Anything not in a product in a product is considered a cost”. Timberland’s redesigned shoeboxes saved nearly<br />

15% <strong>of</strong> virgin packaging material. AMD’s modified ‘wet processing’ technology reduced the water usage from<br />

eighteen to less than now six gallons per minute. Besides many notable individual achievements, the<br />

sustainability issues must be dealt at supply chain managements’ level as today’s industries become more and<br />

more interdependent on one another in every aspect <strong>of</strong> product and service delivery. Efforts <strong>of</strong> environmental<br />

management and operations should no longer be limited to issues <strong>of</strong> localized product operations. Rather, it<br />

needs to be assessed in a higher level <strong>of</strong> Operations, which encompass production, transportation, consumption<br />

and post-disposal Disposition. Given such a significant and increasing level <strong>of</strong> attention toward issues related<br />

sustainable development, or sustainability, it is imperative to define sustainability on supply chain managements’<br />

level to discuss environmental as well as economic benefits as a whole.<br />

6. Government and industry partnership<br />

The problem <strong>of</strong> e-waste can be solved by joint efforts <strong>of</strong> industry and government. The government should<br />

ignite, encourage and promote the green activities carried out by the manufacturing supply chain. China has<br />

encouraged (pressured) GSCM practice adoption to help spur economic development. One can find literatures<br />

which also claim government regulation as the major driver <strong>of</strong> environment/green efforts <strong>of</strong> manufacturing<br />

companies. The government manufacturing companies should become role models to others. They should come<br />

out with transparent legislation for environmental responsibility. Environmental regulations such as EuP (Eco-<br />

Design <strong>of</strong> Energy Using Products), REACH (Registration, Evaluation, and Authorization <strong>of</strong> Chemicals), ELV<br />

(End <strong>of</strong> Life Vehicle Directive), WEEE (Waste from Electrical and Electronic Equipment) and RoHS<br />

(Restrictions on Hazardous Substances) <strong>of</strong> the European Union are putting pressure on the companies for<br />

adopting green practices. One can find similar types <strong>of</strong> laws in other countries like China, Taiwan, Korea, Japan<br />

and US. Such laws compel the manufacturing companies to closely look into the production processes and<br />

supplier selections. Within a few years, products will be sold in most parts <strong>of</strong> world under such legislation. The<br />

government should apply pressure so as to compel the companies to become green without any compromise.<br />

There is a need to make policies by the Indian government to handle the problem <strong>of</strong> huge e-waste generated by<br />

the producers/manufacturing industries. Municipalities can play lead role in the collection <strong>of</strong> waste/used/EOL<br />

products from the society with collaboration <strong>of</strong> industries and 3PL provider to optimize the use <strong>of</strong> EOL products.<br />

We hereby developed an integrated model <strong>of</strong> forward and reverse supply chain for efficient utilization <strong>of</strong> EOL<br />

products in India with the concept <strong>of</strong> government and private partnership strategy.<br />

The structure <strong>of</strong> the presentation was based on functions that could be considered as drivers within the<br />

green supply chain/closed loop supply chain. These are Procurement, in-bound logistics, production, distribution<br />

and out-bound logistics, and reverse logistics procedure with joint collaboration <strong>of</strong> government and private<br />

partnership model.<br />

7. Conclusion & Discussion<br />

The underlying aim in considering the end-<strong>of</strong>-life phase <strong>of</strong> a product’s life is to reduce impacts on the natural<br />

environment. The ultimate goal is sustainable development “meeting the needs <strong>of</strong> the present without<br />

compromising the ability <strong>of</strong> future generations to meet their own needs”. The perspective <strong>of</strong> this work is on<br />

manufacturer involvement in managing end-<strong>of</strong>-life products with the infrastructure support <strong>of</strong> local government<br />

like, municipal Corporations, Nagar Councils, Village Councils and Third Party Logistics Service (3PL)<br />

provider. This study focuses on the Original Equipment Manufacturers (OEM) relationship with government<br />

agencies to handle the product returns<br />

The generic model presented in the paper represents total perspective and look at the problem <strong>of</strong> used product<br />

return from an overall environmental or societal perspective. The strategic perspective to end-<strong>of</strong>-life<br />

management with government support has received very limited attention [12], especially the role <strong>of</strong><br />

manufacturers which is expected to grow [14]. Waste collectors can be municipalities, third parties, or logistics<br />

service providers. Depending on their location in the world, end users may have to pay to dispose <strong>of</strong> the product.<br />

From waste collection the product will be sent to a landfill, an incinerator, or a recycling facility. Incineration<br />

means that energy is recovered from the product, whereas recycling refers to recovering material value from the<br />

product [8]. From the recycling facilities the recovered materials may end-up back in the original supply chain <strong>of</strong><br />

the product or an alternative supply chain. Recycling facilities may in some cases be owned by manufacturers, as<br />

is frequently the case in Japan [10].<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The government should apply pressure so as to compel the companies to become green without any compromise.<br />

There is a need to make policies by the Indian government to handle the problem <strong>of</strong> huge e-waste generated by<br />

the producers/manufacturing industries. As per present model theme the municipalities can play lead role in the<br />

collection <strong>of</strong> waste/used/EOL products from the society with collaboration <strong>of</strong> industries and 3PL provider to<br />

optimize the use <strong>of</strong> EOL products. We hereby developed an integrated model <strong>of</strong> forward and reverse supply<br />

chain for efficient utilization <strong>of</strong> EOL products in India with the concept <strong>of</strong> government and private partnership<br />

strategy.<br />

References<br />

1. Amato-McCoy, D.M., <strong>20</strong>03. “Sears gets a return on returns”, Stores, Vol. 85 No. 7, pp.66.<br />

2. Bidwell, R. and Verfaillie, H.A., <strong>20</strong>00. Measuring Eco-efficiency: a Guide to Reporting Company<br />

Performance. Geneva: World Business Council for Sustainable Development.<br />

3. Bradbury, H. and Clair, J.A., <strong>19</strong>99. Promoting sustainable organizations with Sweden’s Natural Step.<br />

Academy <strong>of</strong> Management Executive, 13, 4, 63-74.<br />

4. Chopra, S. Meindl, P. Supply Chain Management 3rd edition Harvard Business Press Chung, Chun-Jen,<br />

Wee, Hui-Ming, <strong>20</strong>08. Green-component life-cycle value on design<br />

and reverse manufacturing in semi-closed supply chain, Int. J. Production Economics 113 (<strong>20</strong>08) 528-<br />

545<br />

5. Cooper, M.C. and Gardner, J.T., <strong>19</strong>93. Building good business relationships: More that Partnering or<br />

strategic alliances International Journal <strong>of</strong> Physical Distribution and Logistics Management 23, 6<br />

(<strong>19</strong>93), 14-26.<br />

6. Environmental Consequences in Reverse Manufacturing for the Computer Industry, Journal <strong>of</strong> Cleaner<br />

Production, 11/4 (<strong>20</strong>03): 445-458.<br />

7. Ginter, P.M., Starling, J.M., <strong>19</strong>78. “Reverse distribution channels for recycling,” California<br />

Management Review <strong>20</strong> (3), (<strong>19</strong>78) 72-82.<br />

8. Jurg M. and Egler, Haans-Peter, <strong>20</strong>03. “From cleaner production to sustainable Industrial production<br />

modes,” Swiss State Secretariat for Economic Affairs (SECO) Effingerstr.1, 3003, Bern, Switzerland.<br />

9. Guide Jr., V.D.R. and Harrison, Terry P., <strong>20</strong>03. The Challenge <strong>of</strong> Closed-loop Supply Chains.<br />

Interfaces Vol. 33, No. 6, November-December <strong>20</strong>03.<br />

10. Guide Jr., V.D.R., Van Wassenhove, L.N., <strong>20</strong>02. The reverse supply chain. Harvard Business Review<br />

80 (2), 25-26<br />

11. Guide Jr. V.D.R., Souza, Gilvan C., Wassenhove, Luk N., Blackburn, Joseph D., <strong>20</strong>06 Time Value <strong>of</strong><br />

Commercial product returns, Management <strong>Science</strong>, Vol. 52, No.8, August <strong>20</strong>06, pp.1<strong>20</strong>0-1214.<br />

12. Guide Jr., V.D.R., Jayaraman, V., Srivastava, R., Benton, W.C., <strong>20</strong>00. Supply chain Management for<br />

recoverable manufacturing systems. Interfaces 30(3), 125-142.<br />

13. Gland, Switzerland.|IUCN - The World Conservation Union, UNEP - United Nations Environment<br />

Programme, WWF - World Wide Fund for Nature.<br />

14. Jayaraman V, Patterson RA, Rolland E., <strong>20</strong>03. The design <strong>of</strong> reverse distribution Networks: models and<br />

solution procedures. European Journal <strong>of</strong> Operations research <strong>20</strong>03; 150(1):128-49.<br />

15. Krikke, H., van Harten, A., Schuur, P., <strong>19</strong>99. Business case Oce: reverse logistics network Re-design<br />

for copiers. OR Spectrum 21, 381-409.<br />

16. Kroon, L., Vrijens, G., <strong>19</strong>95. Returnable containers: An example <strong>of</strong> reverse logistics. International<br />

Journal <strong>of</strong> Physical Distribution and Logistics Management 25 (2), 56-68.<br />

17. Min, Hokey, Ko, Hyun Jeung, Ko, C.S., <strong>20</strong>06. A genetic algorithmic approach to Developing the multiechelon<br />

reverse logistics network for product returns Omega 34 (<strong>20</strong>06) 56-69<br />

18. Mitra, Subrata, <strong>20</strong>05. A Survey <strong>of</strong> the Third-Party Logistics (3PL) Service Providers in India, Indian<br />

Institute <strong>of</strong> Management Calcutta, WPS No. 562/ October <strong>20</strong>05.<br />

<strong>19</strong>. National Safety Council, “Electronic Product Recovery and Recycling Baseline Report: Recycling <strong>of</strong><br />

Selected Electronic Products in the United States,” (Washington, DC: National Safety Council, <strong>19</strong>99)<br />

<strong>20</strong>. O’Rourke, D., Connelly, L., Koshland, C., <strong>19</strong>96. “Industrial Ecology: A critical Review,” International<br />

Journal <strong>of</strong> Environment and Pollution, Vol. 6, Nos. 2/3, pp. 89-112.<br />

21. Sarkis, J., <strong>19</strong>95. Manufacturing strategies and environmental consciousness. Technovation 15 (2), 79-<br />

97.<br />

22. Senge, P.M., Carstedt G., <strong>20</strong>01. "Innovating Our Way to the Next Industrial Revolution." Sloan<br />

Management Review. Winter <strong>20</strong>01, Volume 42, Number 2, pp. 24-38. (Beckhard Prize Winner)<br />

23. Srivastava, S. K., <strong>20</strong>07. Green supply chain management: a state-<strong>of</strong>-the-art literature Review.<br />

International Journal <strong>of</strong> Management Reviews <strong>20</strong>07; 9(1):3-80.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

24. Srivastava, S. K., <strong>20</strong>08. Network design for reverse logistics, Indian Institute <strong>of</strong> Management, Lucknow<br />

226013, India, Omega 36 (<strong>20</strong>08) 535-548<br />

25. Stuart, Julie Ann, Low, Ming Kaan, Williams, David J., Turbini, Laura J., Ammons, Jane Chumleve,<br />

<strong>19</strong>98. IEEE Transaction on components, packaging, and manufacturing technology – part c, vol. 21,<br />

NO.3, July <strong>19</strong>98.<br />

26. Thierry, Martijn, Salomon, Mark, Nunen, Jo Van, and Wassenhove, Luk Van, <strong>19</strong>95. “Strategic Issues in<br />

Product Recovery Management,” California Management Review, 37/2 (Winter <strong>19</strong>95): 114-135.<br />

27. T<strong>of</strong>fel, Michael W., <strong>20</strong>03. “The Growing Strategic Importance <strong>of</strong> End-<strong>of</strong>-Life Product Management,”<br />

California Management Review, 45/3 (Spring <strong>20</strong>03): 102-129.<br />

28. Toktay, B., Wein, L., Stefanos, Z., <strong>20</strong>00. Inventory management <strong>of</strong> remanufacturable products.<br />

Management <strong>Science</strong> 46, 1412-1426.<br />

29. White, C.D., Masanet, E., Rosen, C.M., and Beckman, S., <strong>20</strong>01. “Product Recovery: An Overview <strong>of</strong><br />

Management Challenges” MIT Sloan management review, ISSN 1532-9<strong>19</strong>4, Vol. 42 No 2, pp. 24-38.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

SUPPLIER QUALITY ASSURANCE IN SUPPLY CHAIN<br />

MANAGEMENT (SCM) THROUGH QUALITY TOOLS AND<br />

TECHNIQUES<br />

P.P. Shah 1 , R.L. Shrivastava 2<br />

1 Acharya Shrimannarayan Polytechnic, Wardha(M.S.), India<br />

2 Yeshwantrao Chavan College <strong>of</strong> Engineering, Nagpur (M.S.), India.<br />

e-mail: pps<strong>19</strong>71@rediffmail.com<br />

Abstract:<br />

Fierce competition forces organizations to implement different business improvement methodologies to improve<br />

the business performance. A Supply chain is an association <strong>of</strong> different facilities and distribution channels that<br />

includes the procurement <strong>of</strong> raw materials, production, assembly and delivery <strong>of</strong> finish products or services to<br />

the final user i.e. customer. The management <strong>of</strong> supply chain and the role and responsibilities <strong>of</strong> various persons<br />

involved differ from industry to industry. Due to which Supply chain management (SCM) has become a vital<br />

issue for manufacturer, pr<strong>of</strong>essionals and researchers. It is felt that to manage the supply chain effectively,<br />

entire structure <strong>of</strong> supply chain must be understood properly. This paper attempts to provide a manufacturer,<br />

pr<strong>of</strong>essionals and researchers a complete picture <strong>of</strong> supply chain management and explains the role <strong>of</strong> supplier<br />

in supply chain, describes the various quality tools and techniques if implemented properly assurance the quality<br />

<strong>of</strong> suppliers.<br />

Keywords: Supply Chain Management, Quality Management System, Supply Chain Integration, ISO 9001<br />

Introduction:<br />

Industrial world over are trying to improve efficiencies in their operations. There is a need to re-evaluate<br />

business plans especially with respect to investments in new faculties, markets and products. Rising input<br />

resource prices and the economic uncertainty are forcing organizations to thing about the optimum utilization <strong>of</strong><br />

resources to maximize the productivity and the pr<strong>of</strong>it. However, achieving operational efficiencies requires more<br />

than reducing costs, high utilization mandates, strict inventory control and rationalizing capacity or manpower.<br />

There is a single objective <strong>of</strong> the supply chain – right product at the right place in the right quantity at the right<br />

time, which requires all operational units within the organization to be integrated through business processes and<br />

technological enablers.<br />

The aim <strong>of</strong> Supply Chain Management is to satisfy customers at the optimum cost. Due to globalization,<br />

liberalization and advancement in new technologies, supply chains have become more complex, more global and<br />

a more critical business function than ever before. At the same time, many leading firms have realized that a well<br />

run supply chain can be a source <strong>of</strong> distinct competitive advantage in the marketplace, and have been in the<br />

forefront in adopting practices that deliver superlative efficiencies in their supply chain functions.<br />

Supply Chain Management:<br />

The term “supply chain management” arose in the late <strong>19</strong>80s and came into widespread use in the <strong>19</strong>90s. Prior to<br />

that time, businesses used terms such as “logistics” and “operations management” instead. The one <strong>of</strong> the<br />

definition <strong>of</strong> a supply chain Management is given below:<br />

“Systemic, strategic coordination and cooperation <strong>of</strong> the usual business functions within a particular<br />

organization and across organizations within the supply chain, for the purposes <strong>of</strong> improving the performance <strong>of</strong><br />

the individual one and the supply chain which includes not only the manufacturer and suppliers, but also<br />

warehouses, transporters, retailers, and customers themselves as a whole .”<br />

There is a basic pattern to the practice <strong>of</strong> supply chain management. The Five Major Supply Chain Drivers are:<br />

1. Production— what products does the market want<br />

2. Inventory—what inventory should be stocked at each stage in a supply chain<br />

3. Location—where should facilities for production and inventory storage be located<br />

4. Transportation—how should inventory be moved from one supply chain location to another<br />

5. Information—how much data should be collected and how much information should be shared<br />

Every time company has to carry out the 5WH analysis for effective management <strong>of</strong> the supply chain drivers to<br />

enhance the utilization to maximize the productivity and pr<strong>of</strong>it. The right combination <strong>of</strong> responsiveness and<br />

884


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

efficiency in each <strong>of</strong> these drivers allows a supply chain to “increase throughput while simultaneously reducing<br />

inventory and operating expense.”<br />

PRODUCTION<br />

INVENTORY LOCATION INFORMATION<br />

TRANSPORTATION<br />

Figure 1. Supply Chain Drivers<br />

Supply Chain Elements:<br />

Simplest form <strong>of</strong> supply chain is consisting <strong>of</strong> a company and the suppliers and customers <strong>of</strong> particular<br />

company. This is the basic elements that form a simple supply chain. Due to complexity <strong>of</strong> the business<br />

processes, the Supply chains were extended by adding three additional types <strong>of</strong> elements. First there is the<br />

supplier’s supplier at the beginning <strong>of</strong> an extended supply chain. Then there is the customer’s customer or final<br />

customer at the end <strong>of</strong> an extended supply chain. Finally there is a whole category <strong>of</strong> companies who are service<br />

providers to other companies in the supply chain. These are companies who supply services in logistics, finance,<br />

marketing, and information technology. In any given supply chain there is some combination <strong>of</strong> companies who<br />

perform different functions. There are companies that are producers, distributors or wholesalers, retailers, and<br />

companies or individuals who are the customers, the final consumers <strong>of</strong> a product. Supporting these companies<br />

there will be other companies that are service providers that provide a range <strong>of</strong> needed services.<br />

Simple Supply Chain Structure<br />

Supplier Company Customer<br />

Extended Supply Chain<br />

Suppliers<br />

Supplier<br />

Supplier Company Customer<br />

Final<br />

Customer<br />

Service Providers<br />

in areas Such as :<br />

• Logistics<br />

• Finance<br />

• Market Research<br />

• Product Design<br />

• Information <strong>Technology</strong><br />

Service<br />

Provider<br />

Figure 2. Supply Chain Structure<br />

Role <strong>of</strong> Supplier:<br />

Suppliers play important role in the quality management and it is the suppliers who can help a company to<br />

achieve excellence. Company should identify what are their internal and external suppliers What are their true<br />

needs and expectations How they communicate their needs and expectations to suppliers Do their suppliers<br />

have the capability to measure and meet these needs and expectations This helps the companies to improve their<br />

own quality by improving their supplier’s product and service quality which is possible only through the<br />

integrating <strong>of</strong> the suppliers in quality system. Supplier has to play following different role:<br />

• Improving transportation facilities<br />

• Proper stocking and transportation <strong>of</strong> materials Improve delivery performance and time based agreements<br />

• Fulfilling demand/requirements<br />

• Inventory Management<br />

• Funds Management<br />

• Efficient supply <strong>of</strong> materials<br />

• Reducing information fluctuations using IT tools<br />

• Proper communication<br />

• Continuous Monitoring<br />

• Market know-how’s<br />

Supplier Quality Assurance System:<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

In an effort to provide high quality, low cost products and services that meet and exceed customer’s<br />

expectations, integration <strong>of</strong> Quality Tools and Techniques is needed in supplier’s manufacturing process that will<br />

assist in reducing variation and waste in products and services by better controlling and standardizing processes.<br />

Quality Tools and Techniques:<br />

1. Lean Manufacturing:<br />

Lean Manufacturing is simply a group <strong>of</strong> Strategies for the identification and elimination <strong>of</strong> the Waste inside the<br />

Value Stream. Waste exists at all levels and in all activities which are to be Identified and Eliminated by<br />

involving all the employees and department compromising the organization.<br />

Types <strong>of</strong> Waste:<br />

Type Definition Characteristics Causes<br />

Waste<br />

Producing more than is<br />

needed, faster than<br />

needed or before<br />

needed.<br />

* Idle Operator waiting for Equipment.<br />

* Production Bottlenecks.<br />

* Production waiting for Operators.<br />

* Unplanned Equipment Downtime.<br />

* Inconsistent Work Methods.<br />

* Lack <strong>of</strong> Proper Equipment.<br />

* Long Setup Times.<br />

* Low Man/machine Effectiveness.<br />

* Poor Equipment Maintenance.<br />

* Production Bottle Necks.<br />

* Skills Monopolies.<br />

Transportation<br />

Waste<br />

Any material movement<br />

that does not directly<br />

support immediate<br />

production<br />

* Endless Product/Process Refinement.<br />

* Excessive Copies/Excessive<br />

Information<br />

* Process Bottlenecks.<br />

* Redundant Reviews and Approvals.<br />

* Unclear Customer Specifications.<br />

* Decision Making at Inappropriate<br />

Levels.<br />

* Inefficient Policies and Procedures.<br />

* Lack <strong>of</strong> Customer Input Concerning<br />

Requirements.<br />

* Poor Configuration Control.<br />

* Spurious Quality Standards.<br />

Inventory Waste<br />

Any supply in excess <strong>of</strong><br />

process requirements<br />

necessary to produce<br />

goods or services in a<br />

Just-in-Time Manner.<br />

* Additional Material Handling<br />

Resources.<br />

* Extensive Rework <strong>of</strong> Finished Goods.<br />

* Extra Space on Receiving material.<br />

* Long Lead Times for Design Changes.<br />

* Storage Congestion Forcing LIFO<br />

(Last In First out).<br />

* Inaccurate Forecasting Systems.<br />

* Incapable Processes.<br />

* Incapable Suppliers.<br />

* Local Optimization.<br />

* Long Change Over Times.<br />

* Poor Inventory Planning and tracking.<br />

* Unbalanced Production Processes.<br />

Motion Waste<br />

Any movement <strong>of</strong><br />

people which does not<br />

contribute added value<br />

to the product or<br />

service.<br />

* Excess Moving Equipment.<br />

* Excessive Reaching or Bending.<br />

* Unnecessarily Complicated procedures<br />

* Excessive Tool gathering.<br />

* Widely Dispersed Materials/Tools.<br />

* Ineffective Equipment, Office and<br />

Plant Layout.<br />

* Lack <strong>of</strong> Visual Controls.<br />

* Poor Process Documentation.<br />

* Poor Work Place Organization.<br />

Defect Waste<br />

Repair or rework <strong>of</strong> a<br />

product or service to<br />

fulfill customer<br />

requirements as well as<br />

scrap waste resulting<br />

from materials deemed<br />

to be un-repairable or<br />

un-reworkable.<br />

Complex Material Flows.<br />

Excess Finished Goods Inventory.<br />

Excessive Floor Space/Tools/Equipment<br />

Excessive Manpower to Inspect<br />

/Rework/repair.<br />

High Customer Complaints/returns.<br />

High Scrap Rates.<br />

Poor Production Schedule Performance<br />

Questionable Quality.<br />

Reactive Organization.<br />

* Excessive Variation.<br />

* High Inventory Levels.<br />

* Inadequate Tools/Equipment.<br />

* Incapable/Incompatible processes.<br />

* Insufficient Training.<br />

* Poor Layouts/Unnecessary Handling.<br />

2. Quality at the Source<br />

A quality philosophy that places the responsibility for meeting customer specifications and standards at the point<br />

<strong>of</strong> manufacture. To do this carry out the source inspection for purchased components, Operators self-inspect their<br />

work as well as inspecting (and/or rejecting) the work <strong>of</strong> previous operators, Poka -Yoke designed<br />

manufacturing devices, processes and products.<br />

3. Poka -Yoke<br />

A design approach to quality that places the responsibility for preventing defects within the design <strong>of</strong> the product<br />

and/or production process. This done by design and process/fixture approach. Within the product design<br />

specifications replace those specs which require defect prone processes/components with those that require non-<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

defect prone processes/components. Within manufacturing replace those processes/fixtures which are defect<br />

prone with those that are not. Poka-yoke Characteristics includes-<br />

* Goals and reasons for installation are clear<br />

* Effective against recurrence – never malfunctions<br />

* Stops flow without making, sending, or missing non-conforming material<br />

* Costs little or no money<br />

* Made with shop floor wisdom and ingenuity<br />

* Simple, durable, and easy to maintain<br />

* Can be widely used in other processes<br />

* Does not impair operability<br />

* Operator fully trained<br />

4. 5S (Workplace Organization)<br />

A methodology for organizing, clearing, developing, and sustaining a productive work environment.<br />

WHY 5S<br />

* Eliminate wastes that result from uncontrolled processes<br />

* Gain control on equipment, material, and inventory<br />

* Apply control techniques to eliminate erosion <strong>of</strong> improvements<br />

* Standardize improvements for maintenance<br />

* Improve delivery consistency<br />

* Improve quality<br />

* Improve safety<br />

* Improve reliability<br />

Sort –Items which are not used in work area should be removed and items frequently used should be properly<br />

identified and stored out <strong>of</strong> sight.<br />

Set In Order – Organize the work area. All production items and their storage locations should be clearly<br />

identified. Accessibility should be prioritized with reference to use. Cleaning materials/utensils must be stored in<br />

the work area. The sharing <strong>of</strong> cleaning materials/utensils between work areas should be discouraged.<br />

Shine - It is essential that enough attention be paid to the neatness <strong>of</strong> work stations so that the workers will be<br />

able to take pride in ownership.<br />

Standardize – Establish written standards for order and cleanliness.<br />

Sustain – Maintain the standards through training, empowerment, commitment and discipline<br />

5. Cellular Manufacturing<br />

A manufacturing approach in which equipment and workstations are arranged in a bounded area to facilitate<br />

small-lot, continuous-flow production. The fundamental <strong>of</strong> cellular manufacturing includes-<br />

* Material Flow – Cells are arranged in relation to each other so that material movement is minimized.<br />

* Capital proximity – Expensive machines which cannot be easily relocated to cells should be located between<br />

the cells that use them (Point-<strong>of</strong>-Use).<br />

* Assembly line – The layout <strong>of</strong> machines within each cell should resemble a small assembly line.<br />

* Mobility – Quick positional adjustments should be used to arrange/rearrange the machines within a cell.<br />

* Layout proximity – Sequential processes need to be placed side by side.<br />

* Unified Management Structure – the productive resources need to answer to the same voice.<br />

The implementation <strong>of</strong> cellular manufacturing includes-<br />

* Better use <strong>of</strong> human resources<br />

* Easier to automate<br />

* Easier to control<br />

* Multifunctional workers<br />

* Reduced material handling and transit time<br />

* Reduced setup time<br />

* Reduced work-in-process inventory<br />

6. Standardized Work<br />

The process <strong>of</strong> documenting and standardizing tasks throughout the value stream which includes process<br />

instructions and standard operating procedures. The benefits includes-<br />

* Increase in the Effectiveness <strong>of</strong> Cross-training.<br />

* Increased sustainability <strong>of</strong> product and procedural improvements.<br />

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* Less downtime due to absenteeism.<br />

* More Consistent production Schedules.<br />

* Reduced training costs.<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Process instruction contents part number and description, drawing revision, next use list, process instruction<br />

revision, process bill <strong>of</strong> material, tool/fixture list, miscellaneous specifications (Equipment settings, time<br />

requirements, etc.),<br />

Task instructions are the instructions that should be complete and adequate to enable a qualified equipment<br />

operator to perform the process. The liberal use <strong>of</strong> visual aids is highly desirable.<br />

7. Kaizen<br />

A philosophy <strong>of</strong> continual improvement, emphasizing employee participation, in which every process is<br />

continuously evaluated and improved in terms <strong>of</strong> time, resources, quality, and other aspects relevant to the<br />

process. Kaizen is <strong>of</strong>ten confused with Kaizen Events. They are not the same. Kaizen events are artificial group<br />

setups to address single subjects/areas. They are usually one time only affairs. Kaizen is intended to be<br />

incorporated as a normal day by day approach to the improvement <strong>of</strong> the entire value stream. There are two<br />

types <strong>of</strong> Kaizen<br />

* Flow kaizen – value stream improvement.<br />

* Point Kaizen – elimination <strong>of</strong> waste. Finally and most important <strong>of</strong> all, it must be made clear that everyone will<br />

be participating.<br />

Quality Kaizen Tools<br />

* Process Mapping<br />

* Cause & Effect Diagram<br />

* Gage R&R<br />

* Process Capability Studies<br />

* Graphical Analysis Methods<br />

– Pareto Analysis<br />

– Histogram<br />

– Scatter Diagram<br />

– Correlation Analysis<br />

– Check Sheet<br />

* Statistical Methods<br />

– Correlation and Regression<br />

– Design <strong>of</strong> Experiments (DOE)<br />

* Rolled Throughput Yield (RTY)<br />

* Failure Mode and Effect Analysis (FMEA)<br />

* Error Pro<strong>of</strong>ing<br />

* Control Plans<br />

8. Kanban<br />

Kanban is Japanese for “card” – Pull Scheduling combined with traveling instructions conveyed by simple visual<br />

devices in the form <strong>of</strong> cards, balls, carts, containers, etc. and can be applied to both material flow in the factory,<br />

information or project flow in the <strong>of</strong>fice, and material flow between suppliers and customers. Following are the<br />

benefits:<br />

* Reduced Inventories<br />

* Predictable flow <strong>of</strong> Materials<br />

* Simplified Scheduling<br />

* Visual Pull System at the Point <strong>of</strong> Production<br />

* Improved Productivity<br />

Conclusion:<br />

Supplier is the important element in the supply chain. Supplier quality is seen as a first step towards making<br />

supply chain more efficient. Companies understand the criticality <strong>of</strong> supplier quality management and<br />

considering them as their strategic business partners are making huge investments in this area. Suppliers are<br />

expected to have a high level commitment to quality which will be possible only through the integration <strong>of</strong><br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

different quality tools and techniques. If these tools and techniques are implemented and integrated properly in<br />

process, which gives confidence to supplier regarding the quality <strong>of</strong> their products and services.<br />

References:<br />

Altekar RV., <strong>20</strong>05, “Supply chain management: concepts and cases”, New Delhi: Prentice Hall <strong>of</strong> India.<br />

Chandra C, Kumar S., <strong>20</strong>00, “Supply chain management in theory and practice: a passing fad or a fundamental<br />

change” Ind. Manag. Data Syst., Vol.100, No. 3, pp. 100 - 113.<br />

Cooper M. C., L. M. Ellram., <strong>19</strong>93, “Characteristics <strong>of</strong> Supply Chain Management and the Implications for<br />

Purchasing and Logistics Strategy”, International Journal <strong>of</strong> Logistics Management, Vol.4, No.2, pp. 13-24.<br />

Ganeshan, R., and Harrison, P.T., <strong>19</strong>95, “An Introduction to Supply Chain management”, Pennsylvania State<br />

<strong>University</strong>.<br />

Gunasekaran, A., Patel, C., and McGaughey, R., C., <strong>20</strong>03, “A framework for supply chain performance<br />

measurement”, International Journal <strong>of</strong> Production Economics, 87, 333–347.<br />

Jauhar, S., Tillasi , P., Choudhary, R., <strong>20</strong>12, “Integrating Lean Six Sigma and Supply Chain Practices for<br />

Improving the Supply Chain Performance”, Undergraduate Academic Research Journal (UARJ), Vol.01, No. 01,<br />

ISSN : 2278 – 1129<br />

Juran, J. M., Gryna F. M., <strong>19</strong>88, “Quality Control Handbook”, 4th Edition McGraw Hill.<br />

Laraia, Anthony, Moody, Patricia, Hall, Robert, <strong>19</strong>99, “The Kaizen Blitz”, John Wiley & Sons.<br />

Lim, R.Y.G., Baines, T., Tjahjono, B., Chandraprakaikul, W., <strong>20</strong>06, “Integrated strategic supply chain<br />

positioning for SMEs: an empirical study”, The International Journal <strong>of</strong> Logistics Management, Vol.17, No. 2,<br />

pp. 260-276.<br />

Power, D., <strong>20</strong>05, “Supply chain management integration and implementation: a literature review”, Supply Chain<br />

Management: An International Journal, Vol. 10, No.4, pp. 252–263<br />

S. Thomas Foster Jr., <strong>20</strong>07, “Towards an understanding <strong>of</strong> supply chain management”, Journal <strong>of</strong> operations<br />

Management, Vol.6.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

CRITICAL ISSUES FOR INDIAN SMALL AND MEDIUM ENTERPRISES<br />

FOR ADOPTING KNOWLEDGE MANAGEMENT<br />

A. Anand 1* , M. D. Singh 2 , R. Kant 3<br />

1 Research Scholar, Department <strong>of</strong> Mechanical Engineering, M. N. N. I.T, Allahabad, (INDIA)<br />

2 Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, M.N. N. I. T, Allahabad, (INDIA)<br />

3 Assistant Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, S.V.N.N.I.T, Surat, (INDIA)<br />

email: apurva<strong>20</strong>50@yahoo.co.in<br />

Abstract<br />

The aim <strong>of</strong> this paper is to understand critical issues regarding Knowledge management (KM) in context <strong>of</strong> Indian<br />

small and medium enterprises (SMEs) sector as it is one <strong>of</strong> the fastest growing sectors <strong>of</strong> Indian economy. So it is<br />

very important for SMEs to know what their knowledge assets are, and how to manage and make best use <strong>of</strong> these<br />

assets to get maximum return. It has been observed that all over the world, SMEs are considered as a major source<br />

for economic growth. The management <strong>of</strong> knowledge is considered as an important and necessary factor for the<br />

competitive growth <strong>of</strong> an organization. The worldwide economy has been shifted from production-based economy to<br />

a knowledge-based economy. The traditional sources <strong>of</strong> competitive advantages in any organization are no longer<br />

seemed to be sufficient in the era <strong>of</strong> global-business competition. At present business environment organizations<br />

have to look at their strategies to remain competitive for their survival and growth. Knowledge drives strategy and<br />

strategy drive KM in an organization.<br />

Key word: Knowledge management, km strategy, competitive organizations, Small to medium-sized enterprises.<br />

1. Introduction<br />

The management <strong>of</strong> knowledge is considered as an important and necessary factor for the competitive growth. In the<br />

present complex and global business environment, KM is a tool which can provide a solution for every problem<br />

faced by the SMEs. There are various concepts, conflicting definitions and overlapping views among the researchers<br />

and practitioners on KM, but the central theme is still the same for all <strong>of</strong> them i.e. managing the knowledge and<br />

encouraging people to share the same to create the value adding products and services [1-6]. The international<br />

scenario is changing rapidly towards quality, responsiveness, diversity and customization <strong>of</strong> products and services<br />

[7]. KM is encouraging individuals to communicate their knowledge by creating environments and systems for<br />

capturing, organizing, and sharing knowledge throughout the organizations [8]. It comprises the practices and<br />

technologies which facilitate the efficient creation and exchange <strong>of</strong> knowledge on an organization-wide level in order<br />

to enhance the quality <strong>of</strong> decision making [9]. KM can be helpful in almost all the areas <strong>of</strong> the SMEs starting from<br />

the effort <strong>of</strong> R&D, products and process development, purchase and store, manufacturing and quality control.<br />

Various activities like sound planning, attention to the customers, savvy marketing, quality checks etc., can be<br />

supported by KM to enhance the competitiveness. KM can provide a competitive edge for the Indian SMEs to<br />

sustain the pressure <strong>of</strong> globalization. SMEs has simple systems and procedures, which allows flexibility, immediate<br />

feedback, short decision-cycle, better understanding and quicker response to customer needs than larger<br />

organizations. In spite <strong>of</strong> these supporting characteristics <strong>of</strong> SMEs, they are on tremendous pressure to sustain their<br />

competitiveness in domestic as well as global markets. For continuous improvement and change; SMEs have to<br />

define their strategy themselves with the best in the industry to adopt KM.<br />

2. Choosing the right Strategy<br />

Strategy specifies the potential products and markets, long-term objectives, and policies for achieving the objectives.<br />

Organizations must continuously review their manufacturing strategies to identify the aspects <strong>of</strong> market priority,<br />

product structure, manufacturing configuration, and investment [10-11].Improvement programs should match<br />

operational goals and objectives [12-14].Strategic issue helps us in defining the organization goals and objectives<br />

which will in result help in successful implementation <strong>of</strong> KM. It involves the deployment <strong>of</strong> an organization’s<br />

capability and resources to achieve KM goals. In the present scenario, due to the rapid changes in technology and<br />

also due to changes in the behaviors <strong>of</strong> competitors, consumers, suppliers etc, the KM implementation is the only<br />

way to manage changes in organization. It provides structure and context for developing knowledge, a sustainable<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

and renewable source <strong>of</strong> competitive advantage [15]. Liebowitz, have suggested that there are so many strategies for<br />

successful implementation <strong>of</strong> KM but a suitable strategy will be selected as per the situation and context <strong>of</strong> the<br />

organization [16]. The role <strong>of</strong> strategic planning is very important to achieve the goals <strong>of</strong> KM for the survival <strong>of</strong> the<br />

organization in the global market. Here are some strategic issues which are put together to be thought over before<br />

deciding the path for the successful adoption <strong>of</strong> KM (See Figure 1).<br />

Figure1.Path for the successful adoption <strong>of</strong> KM<br />

2.1 Competitive priorities<br />

Competitive priorities represent a holistic set <strong>of</strong> tasks, which should be performed by the manufacturing function in<br />

order to support the business strategy [17]. Competitiveness <strong>of</strong> a company is mostly dependent on its ability to<br />

perform well in dimensions such as cost, quality, delivery, dependability and speed, innovation and flexibility to<br />

adapt itself to variations in demand [18]. While alignment <strong>of</strong> the SMEs with strategic priorities is core to<br />

competitiveness. Therefore, competitive priorities will have to be chosen very carefully because it will set the path<br />

for the implementation <strong>of</strong> KM practices <strong>of</strong> the organization. Competitive priorities are to be decided by the top<br />

management depending on the need and objective. Some <strong>of</strong> the widely accepted priorities are shown in figure 2.<br />

When the competitive priorities are once set then choosing a KM strategy will be truthful to meet the organizational<br />

need <strong>of</strong> the SMEs.<br />

Figure 2. Competitive priorities<br />

2.2 Basis <strong>of</strong> planning the KM strategies<br />

Some foundation is required before planning for KM strategies in SMEs. Nunes have observed that by adequately<br />

capturing, storing, sharing and disseminating knowledge, SMEs could achieve greater innovation and productivity<br />

[<strong>19</strong>]. The foundation is to be chosen by SMEs in such a way that it should keep in pace with competition and<br />

challenge. Planning <strong>of</strong> KM strategy may be based on priorities as shown in figure 3.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 3. Basis <strong>of</strong> planning the KM strategies<br />

2.3 Priority <strong>of</strong> strategies for implementing KM<br />

When competitive priorities and basis <strong>of</strong> KM planning strategies are once set then the need for right priority <strong>of</strong> the<br />

strategy for implementing KM will allow SMEs to create value by effectively utilizing those who create new<br />

knowledge and share knowledge within the organization. The key challenge is to identify how the priorities will help<br />

the SMEs in knowledge creation. Some priorities <strong>of</strong> strategies which can be best for SMEs are shown in figure 4.<br />

Figure 4. Priority <strong>of</strong> strategies for implementing KM<br />

2.4 Knowledge critical to the success <strong>of</strong> the organization<br />

Knowledge is extensively accepted as a base for creating core competencies and competitive advantages <strong>of</strong> the<br />

organizations. It is defined as the whole set <strong>of</strong> insights, experiences, and procedures which are considered correct and<br />

true, and which therefore guide the thoughts, behaviours, and communication <strong>of</strong> people [<strong>20</strong>]. KM is the systematic,<br />

explicit, and deliberate building, renewal, and application <strong>of</strong> knowledge to maximize an organization’s knowledge<br />

related effectiveness and returns <strong>of</strong> its knowledge assets [21]. Identification <strong>of</strong> critical knowledge in different areas<br />

<strong>of</strong> the organization is very essential criteria for organizations to compete in the market [22]. Some <strong>of</strong> the critical<br />

knowledge which may be best for SMEs are shown in figure 5.<br />

Figure 5. Knowledge critical to the success <strong>of</strong> the organization<br />

2.5 Organization need <strong>of</strong> KM<br />

For continuous improvement and changes SMEs have to identify their organizational need <strong>of</strong> KM. Based on the<br />

priorities, organizations can adopt KM. Effective implementation <strong>of</strong> KM will definitely lead to performance<br />

improvement. Some <strong>of</strong> the organization need <strong>of</strong> KM <strong>of</strong> SMEs is (See figure 6).<br />

Figure 6. Organization need <strong>of</strong> KM<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2.6 Using KM in different areas <strong>of</strong> your organization<br />

Innovation, firm’s knowledge accumulation and the development <strong>of</strong> internal technical capabilities help SMEs in<br />

achieving a better competitive position in the international and national market [23]. There should be a link between<br />

above explained strategic issues and priority <strong>of</strong> using KM in different area <strong>of</strong> the organization to get its fullest<br />

potential. Some <strong>of</strong> the critical areas where KM may be best to apply in SMEs are shown in figure 7.<br />

Figure 7. Using KM in different areas <strong>of</strong> your organization<br />

2.7 Justification <strong>of</strong> investments for KM<br />

It must be realized that KM can only directly impact knowledge processing, which in turn can only impact business<br />

processes, which ultimately impacts business outcomes [24]. It is now a well known fact that there are extensive<br />

documented pro<strong>of</strong>s that the promotion <strong>of</strong> KM does indeed enhance a company’s financial performance in terms <strong>of</strong><br />

any one or more measures shown below (see figure 8).<br />

Figure 8. Justification <strong>of</strong> investments for KM<br />

3. Conclusion<br />

KM is a philosophy that affects the entire organization, processes, culture, people technology, systems, structure,<br />

roles, size, and external forces. All the points which are discussed above are to be taken into account in adopting KM<br />

successfully. KM will force the Indian SMEs to rethink how they can restructure themselves and can achieve the<br />

benefits <strong>of</strong> KM which include improved competency, efficiency, decision making, learning, innovation, and increase<br />

in revenues. The SMEs who want to grow fast must adopt KM related activities in a comprehensive and balanced<br />

way covering all aspects <strong>of</strong> their intangible assets, rather than as eclectic discrete activities. Right now Indian SMEs<br />

is not following any comprehensive framework on KM. The present paper has tried to identify strategic issues for<br />

successful KM adoption in Indian SMEs .On the basis <strong>of</strong> the identified priorities, further study need to be carried out<br />

to develop a comprehensive framework on KM for Indian SMEs considering all aspects <strong>of</strong> organizational<br />

performance and approach.<br />

4. References<br />

[1] M. Alavi, and D. Leidner, “Knowledge management systems: Emerging views and practices from the field,”<br />

Proc. <strong>of</strong> the 32nd Hawaii International IEEE Conf. on System <strong>Science</strong>s,<strong>19</strong>99.<br />

[2] G.D. Bhatt, “Knowledge management in organizations: Examining the interaction between technologies,<br />

techniques, and people,” Journal <strong>of</strong> Knowledge Management, vol.5, no.1, pp. 68-75, <strong>20</strong>01.<br />

[3] D.N. Chorafas, “Expert systems at the banker's reach,” International Journal <strong>of</strong> Bank Marketing, vol. 5, no.4, pp.<br />

72-81, <strong>19</strong>87.<br />

[4] T.H. Davenport, “Coming soon: The CKO,” Information Week, September 5, <strong>19</strong>94.<br />

[5] Y. Malhotra, “Deciphering the knowledge management type,” Journal <strong>of</strong> Quality and Participation, vol. 21, no.<br />

4, pp.58-60, <strong>19</strong>98.<br />

[6] A. Mayo, “Memory bankers,” People Management, vol. 4, no.2, pp.34-38, <strong>19</strong>98.<br />

[7] K. M. Wiig, “Knowledge management: An introduction and perspective,” Journal <strong>of</strong> Knowledge Management,<br />

vol.1, no.1, pp. 6-14, <strong>19</strong>97.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[8] M.N. Martinez, “The collective power <strong>of</strong> employee knowledge,” HR Magazine, vol. 43, no. 2, pp.88-94, <strong>19</strong>98.<br />

[9] Delphi, Delphi Consulting Group: Delphi On Knowledge Management, Research and Perspectives on Today’s<br />

Knowledge Landscape, Boston, MA (USA), <strong>19</strong>97.<br />

[10] Errin, E, “Technological intelligence and competitive strategies: an application study with fuzzy logic”, Journal<br />

<strong>of</strong> Intelligent Manufacturing, Vol. 15 No. 4, pp. 417-29, <strong>20</strong>03.<br />

[11] Silveira, G.J.C, “Market priorities, manufacturing configuration, and business performance: an empirical<br />

analysis <strong>of</strong> the order-winners framework”, Journal <strong>of</strong> Operations Management, Vol. 23 No. 6, pp. 662-7), <strong>20</strong>05.<br />

[12] Muda, M.S. and Hendry, L, “The SHEN model for MTO SMEs: a performance improvement tool”,<br />

International Journal <strong>of</strong> Operations & Production Management, Vol. 23 No. 5, pp. 470-86,<strong>20</strong>05.<br />

[13] Sum, C.C, “A taxonomy <strong>of</strong> operations strategies <strong>of</strong> high performing small and medium enterprises in<br />

Singapore”, International Journal <strong>of</strong> Operations & Production Management, Vol. 24 No. 3, pp. 321-45, <strong>20</strong>04.<br />

[14] Raymond, L. and St-Pierre, J.“Antecedents and performance outcomes <strong>of</strong> advanced manufacturing s ystems<br />

sophistication in SMEs”, International Journal <strong>of</strong> Operations & Production Management, Vol. 25 No. 6, pp. 514-33.<br />

<strong>20</strong>05.<br />

[15] Akhter, S.H, Strategic planning, hyper-competition, and knowledge management, Business Horizons, pp.<strong>19</strong>-24,<br />

<strong>20</strong>03.<br />

[16] Liebowitz, j, Key ingredients to the success <strong>of</strong> an organization’s knowledge management strategy, Knowledge<br />

and Process Management, Vol.6 No.1, pp.37-40,<strong>19</strong>99.<br />

[17] Kim, J.S. and Arnold, P. “Operationalising manufacturing strategy: an exploratory study <strong>of</strong> constructs and<br />

linkage”,International Journal <strong>of</strong> Operations & Production Management, Vol. 16 No. 12, pp. 45-73, <strong>19</strong>96.<br />

[18] Carpinetti, L.C.R., Gerolamo, M.C. and Dorta, M. “A conceptual framework for deployment <strong>of</strong> strategy-related<br />

continuous improvements”, The TQM Magazine, Vol. 12 No. 5, pp. 340-9, <strong>20</strong>06.<br />

[<strong>19</strong>] Nunes, M.B., Annansingh, F., Eaglestone, B. and Wakefield.R. “Knowledge management issues in knowledgeintensive<br />

SMEs”, Journal <strong>of</strong> Documentation, Vol. 62 No. 1, pp. 109-<strong>19</strong>, <strong>20</strong>06.<br />

[<strong>20</strong>] Van der Spek, R. and Spijkervet, A. Knowledge management: dealing intelligently with knowledge. In<br />

Liebowitz, W. (Ed.), Knowledge Management and Its Integrative Elements, CRC Press, Boca Raton, FL, <strong>19</strong>97.<br />

[21] Liebowitz, J., Beckman, T. Knowledge Organizations: What Every Manager Should Know. St Lucie Press,<br />

Boca Raton, F, <strong>19</strong>98.<br />

[22] Singh, M. D., Narain, R. and Kant, R. Critical factors for successful implementation <strong>of</strong> knowledge management:<br />

An interpretive structural modeling approach. In the proc. <strong>of</strong> International conf. on Innovation and Knowledge<br />

Management <strong>of</strong> Social and Economic Issues: International Perspective, New Delhi, India, <strong>20</strong>07.<br />

[23] Vargas, D.M. and Rangel, R.G.T. “Development <strong>of</strong> internal resources and capabilities as sources <strong>of</strong><br />

differentiation <strong>of</strong> SME under increased global competition: a field study in Mexico”, Technological Forecasting and<br />

Social Change, Vol. 74 No. 1, pp. 90-9,(<strong>20</strong>07).<br />

[24] McElroy, M. W. The New Knowledge Management: Complexity, Learning, and Sustainable Innovation,<br />

Butterworth-Heinemannn Press , <strong>20</strong>03.<br />

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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

JIT SUPPLY CHAIN MANAGEMENT: AN INTRODUCTION<br />

O P Mishra 1 *, Vikas Kumar 1 , Dixit Garg 2<br />

1 Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad 121006, India<br />

2 Department <strong>of</strong> Mechanical Engineering, National Institute <strong>of</strong> <strong>Technology</strong>, Kurkshetra ,India<br />

e-mail: opmishra.m@rediffmail.com<br />

Abstract<br />

The JIT supply chain for any firm is an effective and efficient management tool. The planning, control, and coordination<br />

<strong>of</strong> all activities in the supply chain to move sufficient material supplies from the source (e.g., overseas or<br />

local central distributors) to the final customers on real time. The activities must be performed when needed at the<br />

right time, not earlier or later in the supply chain. The paper deals with the benefits <strong>of</strong> the JIT supply chain and risk<br />

associated with. The paper is all about the basic concept behind JIT and is supplemented with a case study <strong>of</strong> supply<br />

chain failure due to break down <strong>of</strong> a leading car manufacturing company. It is understood that though benefits <strong>of</strong> JIT<br />

supply chain are obvious, but its implementation in firm is not like a plug in and use.<br />

Key words: JIT supply chain, Management tools, risk, supply chain Failure.<br />

1. Introduction<br />

A 'supply chain’ is the system <strong>of</strong> organizations, people, technology, activities, information and resources involved in<br />

moving a product or service from supplier to customer. Some times goods enter the supply chain at any point where<br />

residual value is recyclable. Supply chains link activities transform natural resources, raw materials and components<br />

into a finished product that is delivered to the end customer (Kim, <strong>20</strong>03). In sophisticated supply chain systems, used<br />

products may re- chains. Sell One- Make One’ (SOMO) is the philosophy <strong>of</strong> Nissan and Toyota, which stress on lean<br />

production. Similar is the philosophy <strong>of</strong> General Motors and such like other automobiles companies.. The JIT supply<br />

chain for any firm as effective and efficient management, planning, control, and co-ordination <strong>of</strong> all activities in the<br />

supply chain to move sufficient material supplies from the source (e.g., overseas or local central distributors to the<br />

final customers (Yasin et.al. <strong>20</strong>01). In short, we define JIT supply chain as value added in performing activities <strong>of</strong><br />

moving materials supplies from the right source to the point <strong>of</strong> consumption or use, at the right time, and at reduced<br />

cost in order to enhance the quality <strong>of</strong> the service given by the product. A JIT supply chain is a strategy that produces<br />

just what and how much is needed, when it is needed, and where it is needed (Banerjee, <strong>20</strong>07).<br />

2. Literature review<br />

Steele (<strong>20</strong>00) expresses just in time supply chain management is the management <strong>of</strong> the flow <strong>of</strong> material starting<br />

from procurement, production processes, ware housing and distribution on real time. He has linked the various firms<br />

together in a chain for delivering customer value. Banerjee (<strong>20</strong>07) expresses on pr<strong>of</strong>itability through JIT process in<br />

the supply chain. The conceptual model that integrates links between three sets <strong>of</strong> variables, i.e. JIT driven processes<br />

in the supply chain, improvement in production processes and financial performance indicators. Kumar V (<strong>20</strong>04)<br />

propose a framework that includes qualitative factors concerning TQM, material flow decisions, supply chain<br />

uncertainty and manufacturing practices to ascertain JIT supply chain working. Zimmer (<strong>20</strong>02) has discussed about<br />

Coordinating producer and supplier is one <strong>of</strong> the main issues <strong>of</strong> supply chain management and to make it more<br />

responsive the activities are to be done in JIT environment. Ohno, (<strong>20</strong>11) deals with a supply chain system where the<br />

production or manufacturing facility operates under a just-in-time (JIT) environment, and the facility consists <strong>of</strong> raw<br />

material suppliers, manufacturers, and retailers where inventory <strong>of</strong> raw materials, work-in-process, and finished<br />

goods are involved, respectively. Cost reduction, waste elimination, low inventories, flexible manufacturing,<br />

efficient transportation, quick delivery etc are some <strong>of</strong> the important aspect <strong>of</strong> the JIT supply chain found in various<br />

literatures (Primrose <strong>19</strong>91, Kim <strong>20</strong>03, Yasin et.al.<strong>20</strong>01, Zimmer <strong>20</strong>02,)<br />

2.1 Attributes <strong>of</strong> the JIT supply chain management<br />

The following section covers the three basic attributes related to the JIT supply chain management. The first<br />

attributes is taken as JIT production. JIT production consists <strong>of</strong> thee separate divisions. The first is the material<br />

system within the JIT which flows through out the chain and which is visible. The second branch <strong>of</strong> JIT production is<br />

production planning prerequisites.TQM, and Kaizen effects are two most important prerequisite <strong>of</strong> JIT production It<br />

is also found that without JIT production just in time supply chain even cannot be thought up. The second attribute is<br />

taken as product delivery and logistics which will be explained in subsequent paragraph. The third attribute is<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

purchasing and communication (Steele, <strong>20</strong>00). Intensive literature reviews shows that JIT concept though is not new<br />

but its applicability is still mysterious. Zimmer (<strong>20</strong>02) claims supply chain as integration <strong>of</strong> the raw material<br />

suppliers, manufacturers, and retailers where inventory <strong>of</strong> raw materials, work-in-process, and finished goods are<br />

involved, respectively. Here it can be thought up that supply <strong>of</strong> raw material is a procurement process, manufacturing<br />

as production processes and retailers and delivery as logistics process. The processes are exercises in the JIT<br />

environment which is based on any kind <strong>of</strong> waste elimination. For better understanding we have collected important<br />

JIT attributes found in the literatures which are listed below in table -1 and a brief discussion is given on the<br />

subsequent paragraph (Garg, Deshmukh , & Kaul , <strong>19</strong>97, <strong>19</strong>99).<br />

Table 1. Attributes <strong>of</strong> JIT supply chain management<br />

S.N. Purchasing and communication Production attributes<br />

Logistics and delivery attributes<br />

attributes<br />

1 Vendor selection 5S Quick response<br />

2 Supplier evaluation Setup Reduction Pull distribution<br />

3 Suppliers training Standard Work Cross docking<br />

4 Long term contract Group technology Small shipment size<br />

5 Mutual trust Takt Time Short delivery time to customer<br />

6 Suppliers participation Waste eliminations 3 rd party logistics<br />

7 Short lead time Visual Controls Reliable Transportation<br />

8 Reduce paper work Pull Production Scheduling Quality packing<br />

9 Cost competitive Cross-Trained Workforce Ware housing<br />

10 Frequent supplies Kaizen Events<br />

2.1.1 Purchasing and communication attributes is concerns with purchase <strong>of</strong> material following the JIT concept, like<br />

proper vendor selection, supplier’s evaluation, suppliers training and their participation in product design. The JIT<br />

procurement is a long term contract between suppliers and manufacturers for the supply <strong>of</strong> the material in shortest<br />

possible time without failure to maintain the mutual trust. The training and support to the suppliers are extended by<br />

the firm to meet the required standard (Kim, <strong>20</strong>03)<br />

Vendor selection: to supply the raw material and other services firms seek the good and responsive vendors who can<br />

meet the supply requirement adhering the JIT concept<br />

Supplier evaluation: before giving the supply order to a vendor his capacity, history, timeliness and technological<br />

supports are evaluated<br />

Supplier training: once the supplier or vendor is selected the firm gives the technological support in terms <strong>of</strong><br />

training, how to maintain the quality and standard <strong>of</strong> the firm.<br />

Long term contract: the supply order to a firm should be for considerable long time so that cost effectiveness and<br />

benefits <strong>of</strong> JIT may be taken by both suppliers and manufacturers.<br />

Mutual trust: the firm and supplier must have faith in each other and should share the informative material readily.<br />

Supplier’s participations: supplier <strong>of</strong> the firm must actively participate in technological development with the firm<br />

for the improvement <strong>of</strong> raw material supply and in product design development.<br />

Short lead time: the supply <strong>of</strong> the material should be at the shortest possible time to avoid the ideal condition.<br />

Reduced paper work: the firm uses the electronic data sharing and e- biding which reduces the paper work greatly.<br />

Cost competitive: the supplied material should be cost effective and lowest for the particular quality exiting in<br />

market.<br />

Frequent supply: the supply <strong>of</strong> the material in JIT system is exactly as per requirement <strong>of</strong> the production process on<br />

daily basis, as carrying the minimum inventory even tending to zero to meet JIT supply chain. This requires frequent<br />

shipping <strong>of</strong> raw material in small lot.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2.1.2. Production attributes in JIT environment is producing the material as and when required keeping Minimum<br />

inventory always by reducing the set up time (tools), following the standard working procedures, using group<br />

technology and other attributes mentioned in table no 1. The continuous improvement in the processes is the main<br />

theme <strong>of</strong> the JIT production (Farahani et.al <strong>20</strong>08).<br />

5S: was developed in Japan. It can be defined as workplace organization method that uses a list <strong>of</strong> five Japanese<br />

words: seiri, seiton, seiso, seiketsu, and shitsuke. Translated into English, they all start with the letter "S". The list<br />

describes how to organize a work space for efficiency and effectiveness by identifying and storing the items used,<br />

maintaining the area and items, and sustaining the new order.<br />

Set up reduction: the tool changing time is very critical as till that time production remains stand still and the<br />

working force, inventory and other associated cost add no value in process. So to meet JIT requirement reduced tool<br />

set up time is most urgent requirement.<br />

Standard work: The Toyota Production System organizes all jobs around human motion and creates an efficient<br />

production sequence without any "Muda." Work organized in such a way is called standardized work. It consists <strong>of</strong><br />

three elements: Takt-Time, Working Sequence, and Standard In-Process Stock.<br />

Takt-Time" is the time which should be taken to produce a component on one vehicle. This timing mechanism is<br />

based on the monthly production schedule. The takt time allows us to produce many parts <strong>of</strong> many different types for<br />

use in vehicles on the production schedule and to supply those parts to each process on the assembly line at the<br />

proper time. This keeps production on schedule and permits flexible response to change in sales.<br />

Waste elimination: Non-value added activities to be eliminated. Muda is translated as waste. There are seven types <strong>of</strong><br />

muda: (Overproduction, waiting, conveyance, processing, inventory, motion and correction) which are to be<br />

eliminated in the supply chain process.<br />

Visual control: Go and see the problem. It is the belief that practical experience is valued over theoretical knowledge.<br />

Visualization is very important to understand the real problem.<br />

Pull production system: It refers to the manufacturing and conveyance <strong>of</strong> only “what is needed, when it is needed,<br />

and in the amount needed.” It is based upon order to build.<br />

Cross trained working force: in today’s scenario workers are to be trained for multi tasking to meet the flexibility <strong>of</strong><br />

the manufacturing process.<br />

Kaizen events: Kaizen means continuous improvement. Kaizen events can be as short as four hours or as long as<br />

five days depending on the improvement opportunity that is being addressed.<br />

2.1.3. Logistics and delivery attributes are to positioning <strong>of</strong> warehouses and distribution <strong>of</strong> the finished goods. The<br />

finished goods are positioned (warehoused) at the convenient place so that JIT delivery may be possible (Wang W.et.<br />

al., <strong>20</strong>04). Quick delivery, 3 rd party logistics, reliable transportation and small shipment <strong>of</strong> the material are the main<br />

attributes <strong>of</strong> the JIT logistics (Steele, <strong>20</strong>00).<br />

Quick response: JIT supply chain is based on the quick responses to the customers as well as to the manufacturers in<br />

terms <strong>of</strong> getting the right material at the shortest possible time.<br />

Pull distribution: An inventory system in which a minimal amount <strong>of</strong> stock is kept on hand and inventory items are<br />

replaced as they are pulled from the warehouse to fill specific orders. A pull distribution system works best with<br />

product that is readily available or has a minimal manufacturing lead time.<br />

Cross docking: is a practice in logistics <strong>of</strong> unloading materials from an incoming semi-trailer truck or railroad car<br />

and loading these materials directly into outbound trucks, trailers, or rail cars, with little or no storage in between.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

This may be done to change type <strong>of</strong> conveyance, to sort material intended for different destinations, or to combine<br />

material from different origins into transport vehicles (or containers) with the same, or similar destination.<br />

Small shipment size: goods transported should be in small lots and supply should be as per demand.<br />

Short delivery time to customer: the demand raised by the customer is to be supplied with the right quantity as soon<br />

as possible.<br />

3 rd party logistics: A third-party logistics provider (abbreviated 3PL, or sometimes TPL) is a firm that provides<br />

service to its customers <strong>of</strong> outsourced (or "third party") logistics services for part, or all <strong>of</strong> their supply chain<br />

management functions. Third party logistics providers typically specialize in integrated operation, warehousing and<br />

transportation services that can be scaled and customized to customers' needs based on market conditions and the<br />

demands and delivery service requirements for their products and materials.<br />

Reliable transportation: Quick, efficient and cost competitive transportation is one <strong>of</strong> the most important means to<br />

meet JIT distribution and logistics.<br />

Quality packing: the packaging <strong>of</strong> the goods should be standard to avoid the damage in transit.<br />

Ware housing: positioning <strong>of</strong> storage site for the shipped material or before shipping and after goods out from the<br />

firm is very strategically issue in the supply chain<br />

3. Discussion <strong>of</strong> key factor associated with JIT supply chain (gang, <strong>19</strong>94)<br />

Implementation <strong>of</strong> JIT is not a process <strong>of</strong> one day. It takes a long journey to be dissolved as a culture <strong>of</strong> doing the<br />

thing in right way. The concept application to the Supply chain becomes more critical as it covers all activities <strong>of</strong> the<br />

firm related to the supply chain. The following factors can be laid down in success <strong>of</strong> the Just in time supply chain.<br />

• Sustained senior management support.<br />

• Thorough examination <strong>of</strong> company operations to ascertains the applicability <strong>of</strong> JIT - e.g. formulation <strong>of</strong> a<br />

business plan based on clearly stated aims, objectives and strategies; analysis <strong>of</strong> why JIT is needed;<br />

• Strong and committed JIT leader/coordinator;<br />

• Employee involvement from the outset, including understanding the JIT philosophy, skills acquisition and<br />

training;<br />

• Demonstrable benefits <strong>of</strong> JIT, which have reinforced management and employee Commitment;<br />

• Regular staff meetings, good communication;<br />

• company-wide implementation <strong>of</strong> JIT-i.e. extended beyond merely the manufacturing phase to supply and<br />

delivery;<br />

• Readiness to seek external assistance e.g. consultants to solve problems and to maintain program<br />

• Pre-existence <strong>of</strong> a quality program;<br />

• Engineers dedicated to achieving result;<br />

• Implementation <strong>of</strong> JIT in conjunction with other techniques;<br />

• Need to question and where necessary to move beyond traditional methods,<br />

• Identification <strong>of</strong> the level <strong>of</strong> customer service to be achieved.<br />

Conviction that the program will succeed and persistence in overcoming problems enroute;<br />

4. Supply chain management and its key problems<br />

Researcher has reported some problems which deter the efficiency <strong>of</strong> only SCM like fore casting errors, bullwhip<br />

effect which causes the chaos in the market and low commitment towards delivery and satisfaction <strong>of</strong> the customers.<br />

Also manufacturer bears cost <strong>of</strong> surplus inventory, ideal work force and other non value added activities. To<br />

overcome some <strong>of</strong> the basic problem <strong>of</strong> only supply chain implementation <strong>of</strong> Just in time purchasing, production and<br />

logistics are the recent thought which not only enhances the supply chain activities efficiently it also changes the<br />

attitudes <strong>of</strong> the working to bring obvious positive change in business performance <strong>of</strong> the firm (Farhani et.al,<strong>20</strong>08).<br />

JIT supply chain basically works on the JIT production concept. Just in time supply chain can not be thought without<br />

JIT production process. (Steele, <strong>20</strong>00)<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5. Benefits <strong>of</strong> JIT supply chain Management<br />

The closer approach to JIT situation, the more responsive a firm feels to its customers and the less capital have been<br />

tied up in raw materials and finished goods inventory. The less the firm spend to store and carry inventory, the less<br />

obsolescence have to be written <strong>of</strong>f, and the better optimization <strong>of</strong> firms transportation and logistics operations.<br />

Ultimately, this all translates into saving <strong>of</strong> huge company real money. The JIT system is aimed at improving pr<strong>of</strong>its,<br />

and return on investment through cost reductions, inventory reductions, and quality improvements (Farahani<br />

et.al.<strong>20</strong>08). These benefits explain the wide acceptance <strong>of</strong> JIT in industry. The following are some benefits <strong>of</strong> a JIT<br />

system stated by researchers ((Dangayach,et.al <strong>20</strong>03, Farahani et.al <strong>20</strong>08, Garg , Deshmukh , & Kaul , <strong>19</strong>97, <strong>19</strong>99,<br />

Kumar V ,<strong>20</strong>04)<br />

• Reduce space requirements.<br />

• Reduce inventory investment in purchased parts, raw materials, work in process and finished goods.<br />

• Reduce manufacturing lead times.<br />

• Increase the productivity <strong>of</strong> direct labor employees,<br />

• Indirect support employees and clerical staff.<br />

• Increase equipment utilization.<br />

• Reduce paperwork and require only simple planning systems.<br />

• Set valid priorities for production scheduling.<br />

• Encourage participation by the work force.<br />

• Increase product quality.<br />

• Close supplier/customer relations<br />

Total cost is reduced due to the above mentioned benefits <strong>of</strong> JIT while managing the supply chain <strong>of</strong> the firm.<br />

6. Failure <strong>of</strong> JIT supply chain: A Case study<br />

Indian automobile industries and JIT supply chain (source: The Times <strong>of</strong> India may 8, <strong>20</strong>11 edition.)<br />

The automotive industry in India is one <strong>of</strong> the largest in the world and one <strong>of</strong> the fastest growing globally. India's<br />

passenger car and commercial vehicle manufacturing industry is the sixth largest in the world, with an annual<br />

production <strong>of</strong> more than 3.9 million units in <strong>20</strong>11. According to recent reports, India overtook Brazil and became the<br />

sixth largest passenger vehicle producer in the world (beating such old and new auto makers as Belgium, United<br />

Kingdom, Italy, Canada, Mexico, Russia, Spain, France, Brazil), growing 16 to 18 per cent to sell around three<br />

million units in the course <strong>of</strong> <strong>20</strong>11-12. In <strong>20</strong>09, India emerged as Asia's fourth largest exporter <strong>of</strong> passenger cars,<br />

behind Japan, South Korea, and Thailand. India is home to 40 million passenger vehicles. More than 3.7 million<br />

automotive vehicles were produced in India in <strong>20</strong>10 (an increase <strong>of</strong> 33.9%), making the country the second (after<br />

China) fastest growing automobile market in the world. According to the Society <strong>of</strong> Indian Automobile<br />

Manufacturers, annual vehicle sales are projected to increase to 5 million by <strong>20</strong>15 and more than 9 million by <strong>20</strong><strong>20</strong>.<br />

By <strong>20</strong>50, the country is expected to top the world in car volumes with approximately 611 million vehicles on the<br />

nation's roads.<br />

Supply chain strategies <strong>of</strong> XY Company<br />

The supply chain process at XY starts from the costumer and ends with the customer. XY uses built-to-order system<br />

to give their customers what they want. Customer makes their request through the dealers. The information is then<br />

communicated to plant. The information is captured in a central data base. Bill allocation is done to determine cost <strong>of</strong><br />

manufacturing and deciding where the car will be manufactured. This is informed by the nature <strong>of</strong> the product, the<br />

lead time and the cost involved. All parts are supplied on built-to-stock basis on the model life <strong>of</strong> the car and just in<br />

time are followed sincerely. Generally vendors are local to whom company XY imparts technical support and<br />

training to make aware <strong>of</strong> JIT programme <strong>of</strong> the firm. Company out source 90% automotive parts from its sister<br />

concern firms. The firm also takes the aids <strong>of</strong> foreign aids to import the important parts <strong>of</strong> the automotive.<br />

Supply chain break down<br />

XY firm faced months <strong>of</strong> supply woes and a slump in market share and sales as a lockout at the key car factory for<br />

50 days due to labour unrest battered volumes and pr<strong>of</strong>it. The shutdown <strong>of</strong> the factory, suffered a daily cost <strong>of</strong> $15<br />

million in lost production, hampering the carmaker's performance in India's key October sales. This was the second<br />

consecutive break down <strong>of</strong> the plant in two years. XY’s share <strong>of</strong> the passenger car market fell 8 percentage points to<br />

40 percent by the time the strikes ended. That had recovered to 44 percent in the April-June period <strong>of</strong> this year, but a<br />

similar slide looms. XY’s closure was especially painful because it was the only plant that makes the company's<br />

hugely popular model <strong>of</strong> a car, which already had a waiting list <strong>of</strong> two months and in April was India's most popular<br />

899


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

car, outselling even oldest cheapest model, XY also denied importing cars or shifting production elsewhere to meet<br />

the shortfall in production at the plant, which accounts for just over a third <strong>of</strong> the company's total vehicle output.<br />

The company supply chain was JIT based in which commitment <strong>of</strong> the work force was exemplary since long. In due<br />

course <strong>of</strong> the time company failed to maintain the harmony among the workers and managerial staff. In order to<br />

capture the demand <strong>of</strong> the market and cutting the production cost the company continued its day to day production<br />

on Just in time Pattern. This led the working pressure mounting on the workers and managerial staff. The poor<br />

coordination between managerial and working staff become open when a mass violence <strong>of</strong> discipline erupted causing<br />

even death <strong>of</strong> senior managerial staff and then shutting <strong>of</strong> the plant for indefinite time leaving the suppliers and<br />

customers <strong>of</strong> the firm in dilemma <strong>of</strong> the supply. The plant outsources 90% parts from its vendors who regularly<br />

followed JIT delivery system to ascertain that firm’s production which does not get delayed due to supply. So<br />

supplier always keeps the buffer stock with them to meet the sudden demand <strong>of</strong> the raw materials. In case <strong>of</strong> shut<br />

down the capital trapped in stock was blocked leaving the supplier into dark. It is understood that reducing the cost<br />

and waste continuously is not very simple task. Supplier suffered the loss for the shut down period which may not<br />

recoverable while he maintained the JIT concept accordance to the firm. We recommend the following few points<br />

which may be the cause <strong>of</strong> the supply break down.<br />

• Lack <strong>of</strong> Strong and committed JIT leader/coordinator;<br />

• Lack <strong>of</strong> Regular staff meetings, good communication<br />

• Reluctance <strong>of</strong> Readiness to seek external assistance - e.g. consultants to solve problems and to maintain<br />

program<br />

• Government neutral policy and let the situation go beyond the control.<br />

• Lack <strong>of</strong> cultural attitudes<br />

7. Conclusion<br />

Just in time supply chain is an integration <strong>of</strong> the procurement, production and delivery process in JIT environment,<br />

where waste elimination, cost reduction, quality production and delivery are the committed task. The literature and<br />

this study show that benefits <strong>of</strong> JIT supply chain are obvious, but Just in time concept implementation in firm is not<br />

like a plug in and use type. The building <strong>of</strong> the concept in a firm takes time and it is a long journey done by<br />

committed staff <strong>of</strong> the firm. The risk associated in implementation <strong>of</strong> JIT is also very high. We can not say a firm a<br />

JIT follower firm till the Just in Time concept is not applied through out the firm’s activities. The ultimate goal <strong>of</strong><br />

any firm is to synchronize demand through the supply chain by generating precise, timely orders at each tier. This<br />

practice occurs on a limited basis, but there are obstacles yet to overcome, such as better inventory control;<br />

accurately reporting production and scrap; and accurate bill-<strong>of</strong>-material usage data.<br />

References<br />

Banerjee Ajviit, Kim Seung-Lae, Burton Jonathan,<strong>20</strong>07. Supply chain coordination through effective multi-stage<br />

inventory linkages in a JIT environment. Int. J. Production Economics 108 (<strong>20</strong>07) 271–280<br />

Business news <strong>20</strong>11, Auto companies relook at just-in-time mantra, The times <strong>of</strong> India may 8, <strong>20</strong>11 edition.<br />

Garg D., Deshmukh S.G, & Kaul O.N., <strong>19</strong>98. “Price Quantity Discount in JIT Purchasing Environment: Parametric<br />

Analysis Using Spreadsheet”. Industrial Engineering Journal, Vol. 27, pp. 9-13.<br />

G.S. Dangayach, S.G. Deshmukh <strong>20</strong>03, Evidence <strong>of</strong> manufacturing strategies in Indian industry: a survey Int. J.<br />

Production Economics 83 (<strong>20</strong>03) 279-298<br />

Gang Duk Su, <strong>19</strong>94. How a Leading Heavy Industries Co., Ltd in Korea Implements JIT Philosophy to,its<br />

Operations, Computers ind. Engn8 Vol. 27, Nos 1--4, pp. 5-9, <strong>19</strong>94 Elsevier <strong>Science</strong> Ltd. Printed in Great Britain<br />

Farahani I R.Z.,. Elahipanah M, <strong>20</strong>08. A genetic algorithm to optimize the total cost and service level for just-in-time<br />

distribution in a supply chain. International. Journal <strong>of</strong>. Production Economics 111, 229–243<br />

Kim Seung-Lae, <strong>20</strong>03. A JIT lot-splitting model for supply chain management: Enhancing buyer–supplier linkage,<br />

Int. J. Production Economics 86 (<strong>20</strong>03) 1–10<br />

Kumar Vikas et.al.<strong>20</strong>04. JIT practices in Indian Context: a survey report. Journal <strong>of</strong> scientific research, volume 63,pp<br />

655-662.<br />

Ohno, Iwase M., K, <strong>20</strong>11. The performance evaluation <strong>of</strong> a multi-stage: JIT production system with stochastic<br />

demand and production capacities. European Journal <strong>of</strong> Operational Research 214, 216–222<br />

Primrose Peter L.<strong>19</strong>91. Evaluating the introduction <strong>of</strong> JIT. International Journal <strong>of</strong> Production Economics, 27, 9-22<br />

Steele L Andrew, <strong>20</strong>00. Cost drivers and other management issues in the JIT supply Chain Environment. Production<br />

andinventory management journal second quarter @ APIC<br />

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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Yasin M.M., Wafa M. & Small M.H. [<strong>20</strong>01], “Just-in-Time Implementation in the Public Sector: An Empirical<br />

Examination.” International Journal <strong>of</strong> Operations & Production Management, Vol.21, pp. 1<strong>19</strong>5-1<strong>20</strong>4.<br />

Wang Wei, Richard Y.K. Fung, Chai Yueting, <strong>20</strong>04. Approach <strong>of</strong> just-in-time distribution requirements planning for<br />

supply chain management. International Journal <strong>of</strong> Production Economics 91, 101–107.<br />

Zimmer K., <strong>20</strong>02. Supply chain coordination with uncertain just-in-time delivery. International journal <strong>of</strong> Production<br />

Economics 77 –15.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

INTENSITY OF CRITICAL FACTORS FOR IMPLEMENTING AMT–<br />

AN ANP APPROACH<br />

Sanjeev Goyal and Sandeep Grover<br />

Department <strong>of</strong> Mechanical Engineering, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad<br />

E-mail: goyal.sanjeev@hotmail.com<br />

Abstract<br />

To attain flexibility and shorter lead times, industries are attaining Advanced Manufacturing Technologies<br />

(AMT). These technologies although provide many benefits but involve large cost and complex implementation<br />

process. Organisations are unaware <strong>of</strong> the strategies to implement AMT. It would be beneficial for the<br />

organisations to know the intensity <strong>of</strong> critical factors affecting the AMT implementation process. In the present<br />

work, an endeavour has been made to find the intensity <strong>of</strong> critical factors affecting the AMT using Analytical<br />

Network Process (ANP). ANP allows interdependencies and feedback within and between clusters <strong>of</strong> factors.<br />

ANP is the generalized form <strong>of</strong> AHP. A group <strong>of</strong> experts were consulted to establish interrelations and to<br />

provide weightage for pairwise comparison. Outcome <strong>of</strong> the ANP is weighted comparison <strong>of</strong> the factors.<br />

Keywords: AMT, Implementation Process, Critical factors, Analytical Network Process (ANP)<br />

1. Introduction<br />

With the quest <strong>of</strong> globalization, changing daily prices, increasing labour cost, increasingly sophisticated<br />

customer, a record number <strong>of</strong> companies are looking for advanced manufacturing systems so that they can<br />

become flexible, adaptive, responsive and innovative. Extensive literature available on AMT reveals the various<br />

facets <strong>of</strong> AMT covered by various authors and researchers across the globe.<br />

Advanced manufacturing technology can be defined according its application and use. According to McDermott<br />

and Stock (<strong>19</strong>99), it is an automated production system <strong>of</strong> people, machines and tools for the planning and<br />

control <strong>of</strong> the production process, including the procurement <strong>of</strong> raw materials, parts, components and the<br />

shipment and service <strong>of</strong> finished products. In the same way, Small and Yasin (<strong>19</strong>97) described it as a group <strong>of</strong><br />

computer-based technologies, including Computer-Aided Design (CAD), robotics, Flexible Manufacturing<br />

Systems (FMS), Automated Materials Handling Systems (AMHS), Computer Numerically Controlled (CNC)<br />

machine.<br />

St-Pierre et al. (<strong>20</strong>04) feel that the pressure <strong>of</strong> quality, cost and delivery are the main hurdles for any company to<br />

remain competitive in today’s scenario. Pagell et al. (<strong>20</strong>00) & Dangayach & Deshmukh (<strong>20</strong>04) find that<br />

advanced manufacturing technologies are looked as a tool for gaining competitive advantage for manufacturing<br />

industries. Advanced manufacturing technology provides the manufacturing company a competitive advantage at<br />

every level <strong>of</strong> the operation, if used in proper way. The benefits <strong>of</strong> advanced manufacturing technologies have<br />

been realised and classified into tangible and intangible [Kaplan (<strong>19</strong>86); Choobineh (<strong>19</strong>86)].The tangible<br />

benefits are reduced inventory, more return on equity, less cost per unit and intangible benefits are flexibility,<br />

competitive advantage, enhanced quality and improved delivery. Dangayach & Deshmukh (<strong>20</strong>04) conducted a<br />

survey on 1<strong>20</strong> companies and found that even, advanced manufacturing technologies are being touched by<br />

progressive firms in developing countries.<br />

Thomas et al. (<strong>20</strong>07) conducted a survey on 300 SME’s and classified them into three categories like large scale<br />

companies, which have already adopted AMS, medium sized companies, which have not adopted the AMS, but<br />

already realized its potential for competitive advantage, but don’t know how to implement it and at the last,<br />

small scale industries which are reluctant to go for advanced manufacturing systems seeing its high cost and<br />

complexity.<br />

The author, during literature survey has not come across any work related to find the intensity <strong>of</strong> critical factors<br />

pertaining to AMT implementation. In the present work, it is proposed to find the intensity <strong>of</strong> critical factors<br />

affecting the AMT implementation process.<br />

2. Identification <strong>of</strong> critical factors for AMT Implementation<br />

The critical factors <strong>of</strong> AMT implementation have been taken from Goyal & Grover (<strong>20</strong>11) and are listed in<br />

Table 1 below:<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 1: Critical Factor for AMT Implementation<br />

Critical Factors<br />

Description<br />

1. Strategic Planning Strategic planning mainly involves the assessment <strong>of</strong> the capabilities <strong>of</strong> the<br />

organisation to meet the requirements <strong>of</strong> the AMT<br />

(i) Person Responsible Person responsible is the leader, who take all the initiatives for successful<br />

implementation <strong>of</strong> AMT<br />

(ii) Financial Risk The possibility that shareholders will lose money when they invest in AMT<br />

(iii) Level <strong>of</strong> <strong>Technology</strong> How much advanced technology is needed to achieve organisations’ goals<br />

Investment<br />

(iv) Government Policies The policies made by the government affecting the implementation <strong>of</strong> AMT<br />

2. Concept Development Investing feasibility and selecting the best AMT alternative<br />

(i) End User The targeted customer<br />

(ii) Supplier Support Relationship between supplier and buyer<br />

(iii) Location<br />

(iv) Feasibility Analysis<br />

Raw materials, customers and competitors depend upon this<br />

Evaluation <strong>of</strong> strengths and weaknesses <strong>of</strong> the AMT<br />

3. Infrastructure Physical and organisational structure needed for operation <strong>of</strong> AMT<br />

(i) Size Size <strong>of</strong> the firm i.e. whether large or small size<br />

(ii) Financial Position<br />

Financial capability to invest<br />

(iii) <strong>Technology</strong> Competent Availability <strong>of</strong> the technology competent workers<br />

Workers<br />

(iv) Computerized Linking together previously separated activities by using computer<br />

Integration<br />

4. Performance<br />

A process towards measuring the predetermined goals<br />

Measurement<br />

(i) Flexibility Ability to quickly respond to the market changes<br />

(ii) Quality<br />

Fit for purpose<br />

(iii) Delivery Time Time between order placed and goods to deliver at the customer end<br />

(iv) Cost<br />

It should remain competitive<br />

5. Human Resource Practice Value enhancement <strong>of</strong> the workers<br />

(i) Employees’<br />

Psychological feature that arouses an employee to give his/her best<br />

Motivation<br />

(ii) Management Support Support <strong>of</strong> the management for AMT implementation<br />

(iii) Recruitment<br />

Recruitment <strong>of</strong> the right work force to handle AMT<br />

(iv) Employees’ Training Training to the employees for handling AMT<br />

6. Post Implement<br />

Required to make future strategies<br />

Evaluation<br />

(i) Customers’ Feedback will help to improve the AMT outcome<br />

(ii) Production Rate A factor to judge the benefits <strong>of</strong> installing AMT<br />

(iii) Competition<br />

How implementing AMT will improve the position among the competitors<br />

(iv) Quality <strong>of</strong> the Product How AMT implementation has improved the quality <strong>of</strong> the product<br />

3 . Analytical Network Process (ANP)<br />

ANP is a general form <strong>of</strong> AHP. AHP was first proposed by Saaty (<strong>19</strong>80a & <strong>19</strong>80b). The AHP is a widely used<br />

MADM based on the representation <strong>of</strong> a decision making problem by a hierarchical structure where elements are<br />

independent and unidirectionally linked. By considering both qualitative and quantitative aspects <strong>of</strong> a decision<br />

and through a pairwise comparison, it allows to set priorities among the elements and make the best decision.<br />

Decision problems are not always structured in a hierarchal way i.e. they may have interrelations among the<br />

elements at the same level. To overcome this difficulty, ANP was introduced by Saaty in <strong>19</strong>96. ANP<br />

simultaneously takes into account both feedback and dependence. ANP generalizes the AHP by allowing<br />

networks with or without hierarchal structure. ANP makes the best decision by allowing feedback within<br />

elements <strong>of</strong> a cluster (inner dependence) or between clusters (outer dependence). ANP methodology is explained<br />

in Saaty’s book (Saaty, <strong>20</strong>05). A brief description is given here because <strong>of</strong> space limitation. The ANP comprises<br />

<strong>of</strong> the following major steps:<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Step 1: Model construction through networks<br />

Decision problem should be structured into networks by using appropriate methods or through brainstorming.<br />

Step 2: Pairwise comparison and priority vectors<br />

Decision makers are asked to compare clusters through a series <strong>of</strong> questions for inner and outer dependence to<br />

achieve the goal. The relative importance values are determined on the scale <strong>of</strong> 1-9. Where a score <strong>of</strong> 1<br />

represents the equal importance among the elements and a score <strong>of</strong> 9 represents the extreme importance <strong>of</strong> one<br />

element over the other (Meade & Sarkis , <strong>19</strong>99). A reciprocal value is assigned to the inverse comparison i.e.<br />

b ij =1/b ji . Local priority vectors are derived similar to AHP. This step is done to derive the eigenvectors and to<br />

form a supermatrix.<br />

Step 3: Supermatrix formation<br />

The outcome <strong>of</strong> step 2 is unweighted supermatrix. Supermatrix is actually a partitioned matrix. Its columns<br />

represent priorities derived from the pairwise comparison <strong>of</strong> the elements. As unweighted supermatrix may not<br />

be column stochastic, so as to obtain one, multiply each block with cluster priority obtained in the step 2. This<br />

stochastic matrix is known as weighted supermatrix. To obtain a convergence on the importance <strong>of</strong> weights, the<br />

supermatrix is raised to large powers and the resulted matrix is known as limit matrix. Priorities can be directly<br />

obtained from the limit matrix.<br />

4 . Intensity <strong>of</strong> AMT Implementation Critical Factors- an ANP Approach<br />

To find the intensity <strong>of</strong> critical factors ANP approach has been applied through Superdecision s<strong>of</strong>tware 2.0.8. As<br />

shown in Table 1, there are six clusters having four factors. A questionnaire has been prepared to rate each factor<br />

<strong>of</strong> cluster with respect to the other factors. Experts were asked to give rating <strong>of</strong> the pairwise comparison <strong>of</strong> the<br />

factors on 1-9 scale. On this basis, Superdecision s<strong>of</strong>tware generated Unweighted, Weighted Supermatrix and<br />

Limit matrix. Priorities <strong>of</strong> the factors can be directly taken from the Limit matrix. The priorities <strong>of</strong> the factors are<br />

shown in Table 2. The top five factors are Management Support, Quality, Computerized Interaction, Level <strong>of</strong><br />

technology Investment and Financial Risk.<br />

Table 2: Intensity <strong>of</strong> Critical Factors based upon ANP<br />

Critical Factors <strong>of</strong> AMT Implementation Normalized Limiting Intensity<br />

(i) Person Responsible 0.49 0.04 7<br />

(ii) Financial Risk 0.271 0.04 5<br />

(iii) Level <strong>of</strong> <strong>Technology</strong> Investment 0.273 0.04 4<br />

(iv) Government Policies 0.137 0.02 12<br />

(v) End User 0.17 0.03 10<br />

(vi) Supplier Support 0.08 0.01 24<br />

(vii) Location 0.138 0.01 17<br />

(viii) Feasibility Analysis 0.068 0.01 22<br />

(ix) Size 0.114 0.01 18<br />

(x) Financial Position 0.189 0.02 14<br />

(xi) <strong>Technology</strong> Competent Workers 0.046 0.01 <strong>19</strong><br />

(xii) Computerized Integration 0.286 0.05 3<br />

(xiii) Flexibility 0.041 0.01 <strong>20</strong><br />

(xiv) Quality 0.297 0.05 2<br />

(xv) Delivery Time 0.229 0.01 15<br />

(xvi) Cost 0.103 0.01 21<br />

(xvii) Employees’ Motivation 0.387 0.02 11<br />

(xviii) Management Support 0.34 0.06 1<br />

(xix) Recruitment 0.<strong>19</strong>3 0.01 16<br />

(xx) Employees’ Training 0.087 0.01 23<br />

(xxi) Customers’ Feedback 0.183 0.04 6<br />

(xxii) Production Rate 0.173 0.04 8<br />

(xxiii) Competition 0.162 0.03 9<br />

(xxiv) Quality <strong>of</strong> the Product 0.134 0.02 13<br />

904


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5. Findings <strong>of</strong> the Research Paper<br />

The paper endeavours to find the intensity <strong>of</strong> critical factors affecting implementation <strong>of</strong> AMT through<br />

systematic approach. The critical factors help an organization to assess their capability against AMT<br />

implementation. Also these factors help the organisation to implement the AMT in systematic way.<br />

The proposed structural approach based on ANP for the evaluation <strong>of</strong> intensity <strong>of</strong> critical factors affecting<br />

implementation <strong>of</strong> AMT has the following features:<br />

1. It permits modelling <strong>of</strong> dependence among factors.<br />

2. Application <strong>of</strong> ANP makes it convenient for visual analysis and computer processing.<br />

3. The intensity <strong>of</strong> critical factors affecting the implementation <strong>of</strong> AMT is indicated by numerical values<br />

4. The method permits to consider different factors in alternative environment.<br />

5. Systematic methodology for conversion <strong>of</strong> qualitative factors to quantitative values and mathematical<br />

modelling gives an edge to the proposed technique over conventional methods.<br />

References<br />

[1] Choobineh, F., & Suri, R. (<strong>19</strong>86). Justification <strong>of</strong> Flexible Manufacturing Systems. Norcross, GA :<br />

Institute <strong>of</strong> Industrial Engineers.<br />

[2] Dangayach, G. S., & Deshmukh , S. G. (<strong>20</strong>04). Advanced Manufacturing Technologies: Evidences<br />

from Indian Automobile Companies. International Journal <strong>of</strong> Manufacturing <strong>Technology</strong> and<br />

Management, 6(5), 426-433.<br />

[3] Goyal, S., & Grover, S. (<strong>20</strong>11). Evaluating Implementation Model <strong>of</strong> AMT- a Graph Theoretic<br />

Approach. Journal <strong>of</strong> Marketing and Operations Management Research, 1(2), 115-142.<br />

[4] Kaplan, R. S. (<strong>19</strong>86, April). Must CIM be Justified by Faith Alone. Harvard Business Review, pp. 87-<br />

95.<br />

[5] McDermott, C., & Stock, G. (<strong>19</strong>99). Organisational Culture and Advanced Manufacturing<br />

Implementation. Journal <strong>of</strong> Operation Management, 17(5), 521-533.<br />

[6] Meade, L. M., & Sarkis , J. (<strong>19</strong>99). Analyzing Organizational Project Alternatives for Agile<br />

Manufacturing Processes-Analytical Network Approach. International Journal <strong>of</strong> Production Research,<br />

37(2), 241-261.<br />

[7] Pagell, M., Hanfield, R. D., & Barber, A. E. (<strong>20</strong>00). Effects <strong>of</strong> Operational Employee Skills on<br />

Advanced Manufacturing <strong>Technology</strong> Performance. Production and Operations Management, 9(3),<br />

222-238.<br />

[8] Saaty, T. L. (<strong>19</strong>80a). The Analytic Hierarchy Process-Planning, Priority Setting, Resource. New York:<br />

Mc-Graw Hill.<br />

[9] Saaty, T. L. (<strong>19</strong>80b). The Analytic Hierarchy Process. New York: Mc-Graw Hill.<br />

[10] Saaty, T. L. (<strong>19</strong>96). Decision Making with Dependence and Feedback: The Analytic Network Process.<br />

Pittsburgh: RWS Publications.<br />

[11] Saaty, T. L. (<strong>20</strong>05). Theory and Applications <strong>of</strong> the Analytic Network Process. Pittsburgh: RWS<br />

Publications.<br />

[12] Small, M. H., & Yasin, M. M. (<strong>19</strong>97). Advanced Manufacturing <strong>Technology</strong>: Implementation Policy<br />

and Performance. Journal <strong>of</strong> Operation Management, 15(4), 349-370.<br />

[13] St-Pierre, J., & Raymond, L. (<strong>20</strong>04). Short-term Effects <strong>of</strong> Benchmarking on the Manufacturing<br />

Practices and Performance <strong>of</strong> SMEs. International Journal <strong>of</strong> Productivity and Performance<br />

Management, 53(8), 681-699.<br />

[14] Thomas , A. J., Braton, R., & John, E. G. (<strong>20</strong>07). Advanced Manufacturing <strong>Technology</strong><br />

Implementation, A Review <strong>of</strong> Benefits and a Model for Change. International Journal <strong>of</strong> Productivity<br />

and Performance Management, 57(2), 156-176.<br />

905


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

A VIEW OF QUEUE ANALYSIS WITH CUSTOMER BEHAVIOUR,<br />

BALKING AND RENEGING<br />

Neetu Gupta*, Reena Garg<br />

Assistant Pr<strong>of</strong>essor, Department <strong>of</strong> Humanities and Applied <strong>Science</strong>s, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and<br />

<strong>Technology</strong>, Faridabad, 121006, India<br />

e-mail:neetuymca@yahoo.co.in<br />

Abstract<br />

This paper presents an analysis for an queueing system with customer behaviour, balking and reneging. Arriving<br />

customers balk with a probability and renege (leave the queue after entering) according to some distribution.<br />

Balking means that customers do not enter in the system, when queue is too long. Reneging means that a customer<br />

enter in the system, wait for some time and leave the system without getting service. Notations and performance <strong>of</strong><br />

queueing model are also given. At the end <strong>of</strong> paper benefits and limitations <strong>of</strong> queueing theory is also given.<br />

Keywords: Balking and Reneging, Queueing system.<br />

I. Introduction<br />

Queueing theory was developed to provide models to predict the behavior <strong>of</strong> systems that attempt to<br />

provide service for randomly arising demands; not unnaturally, then, the earliest problems studied where those<br />

<strong>of</strong> telephone traffic congestion. The pioneer investigator was the Danish mathematician A. K. Erlang [13], who,<br />

in <strong>19</strong>09, published “The Theory <strong>of</strong> Probabilities and Telephone Conversations”. In later works he observed<br />

that a telephone system was generally characterized by either (1) Poisson input, exponential holding (service)<br />

times, and multiple channels (servers), or (2) Poisson input, constant holding times, and a single channel.<br />

Erlang was also responsible for the notion <strong>of</strong> stationary equilibrium, for the introduction <strong>of</strong> so-called<br />

balance-<strong>of</strong>-state equations, and for the first consideration <strong>of</strong> the optimization <strong>of</strong> a queueing system. Work <strong>of</strong><br />

A. K. Erlang is described by Bbocmeyer [9].<br />

Work on the application <strong>of</strong> the theory to telephony continued after Erlang. In <strong>19</strong>27, E. C. Molina published<br />

his paper “Application <strong>of</strong> the Theory <strong>of</strong> Probability to Telephone Trunking Problems”, which was followed<br />

one year later by Thornton Fry’s published a paper “Probability and Its Engineering Uses”, which expanded<br />

much <strong>of</strong> Erlang’s earlier work. In the early <strong>19</strong>30s, Felix Pollaczek [28] did some further pioneering work<br />

on Poisson input, arbitrary output, and single- and multiple-channel problems. Additional work was done at<br />

that time in Russia by Kolmogorov [26] and Khintchine [25], in France by Crommelin [12], and in Sweden<br />

by Palm [27]. The work in queueing theory picked up momentum rather slowly in its early days, but<br />

accelerated in <strong>19</strong>50s, and there has been a great deal <strong>of</strong> work in the area since then. Work on queueing<br />

process was also done by Homma [<strong>20</strong>] and Kendall [23].<br />

There are many valuable applications <strong>of</strong> the theory, most <strong>of</strong> which have been well documented in the<br />

literature <strong>of</strong> probability, operations research, management science, and industrial engineering. Some examples<br />

are traffic flow (vehicles, aircraft, people, communications), scheduling (patients in hospitals, jobs on machines,<br />

programs on a computer), and facility design (banks, post <strong>of</strong>fices, amusement parks, fast-food restaurants).<br />

2. Characteristics <strong>of</strong> queueing processes<br />

In most cases, six basic characteristics <strong>of</strong> queueing processes provide an adequate description <strong>of</strong> a queueing<br />

system: (1) arrival pattern <strong>of</strong> customers, (2) service pattern <strong>of</strong> servers, (3) queue discipline, (4) system<br />

capacity, (5) number <strong>of</strong> service channels, and (6) number <strong>of</strong> service stages.<br />

3. Notations <strong>of</strong> queueing models<br />

As a shorthand for describing queueing processes, a notation has evolved, due for the most part to Kendall<br />

[23] (<strong>19</strong>53), which is now rather standard throughout the queueing literature. A queueing process is described<br />

by a series <strong>of</strong> symbols and slashes such as A/B/X/Y/Z, where A indicates in some way the interarrival- time<br />

distribution, B the service pattern as described by the probability distribution for service time, X the number<br />

906


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

<strong>of</strong> parallel service channels, Y the restriction on system capacity, and Z the queue discipline. For A and B the<br />

following abbreviations are very common:<br />

• M (Markov): this denotes the exponential distribution. The name M stems from the fact that the exponential<br />

distribution is the only continuous distribution with the markov property, i.e. it is memoryless.<br />

• D ( Deterministic): all values from a deterministic “distribution” are constant, i.e. have the same value.<br />

• E k ( Erlang-k) : Erlangian Distribution with k phases k = 1,2, …….. This distribution is popular for<br />

modeling telephone call arrivals at a central <strong>of</strong>fice.<br />

• H k ( Hyper-k): Hyperexponential Distribution with k phases.<br />

• G( General): General Distribution.<br />

4. Performance <strong>of</strong> queueing models<br />

Up to now the concentration has been on the physical description <strong>of</strong> the queueing processes. Generally<br />

there are three types <strong>of</strong> system responses <strong>of</strong> interest. These are: (1) some measure <strong>of</strong> the waiting time that<br />

a typical customer might be forced to endure; (2) an indication <strong>of</strong> the manner in which customers may<br />

accumulate; (3) a measure <strong>of</strong> the idle time <strong>of</strong> the servers. Since most queueing systems have stochastic<br />

elements, these measures are <strong>of</strong>ten random variables and their probability distributions, or at the very least<br />

their expected values, are desired. There are two types <strong>of</strong> customer waiting times, the time a customer<br />

spends in the queue and the total time a customer spends in the system (queue plus service). Depending on<br />

the system being studied, one may be <strong>of</strong> more interest than the other. For example, if we are studying an<br />

amusement park, it is the time waiting in the queue that makes the customer unhappy. On the other hand, if<br />

we are dealing with machines that require repair, then it is the total down time (queue wait plus repair<br />

time) that we wish to keep as small as possible. Correspondingly, there are two customer accumulation<br />

measures as well: the number <strong>of</strong> customers in the queue and the total number <strong>of</strong> customers in the system.<br />

The former would be <strong>of</strong> interest if we desire to determine a design for waiting space (say the number <strong>of</strong><br />

seats to have for customers waiting in a hair- styling salon), while the latter may be <strong>of</strong> interest for knowing<br />

how many <strong>of</strong> our machines may be unavailable for use. Idle- service measures can include the percentage <strong>of</strong><br />

time any particular server may be idle, or the time the entire system is devoid <strong>of</strong> customers. The task <strong>of</strong><br />

the queueing analyst is generally one <strong>of</strong> the two things. He or she is either to determine the values <strong>of</strong><br />

appropriate measures <strong>of</strong> effectiveness for a given process, or to design an “optimal” (according to some<br />

criterion) system. To do the former, one must relate waiting delays, queue lengths, and such to the given<br />

properties <strong>of</strong> the input stream and the service procedures. On the other hand, for the design <strong>of</strong> a system the<br />

analyst might want to balance customer waiting time against the idle time <strong>of</strong> servers according to some<br />

inherent cost structure. If the costs <strong>of</strong> waiting and idle service can be obtained directly, they can be used to<br />

determine the optimum number <strong>of</strong> channels to maintain and the service rates at which to operate these<br />

channels. Also, to design the waiting facility it is necessary to have information regarding the possible size<br />

<strong>of</strong> the queue to plan for waiting room. There may also be a space cost which should be considered along<br />

with customer- waiting and idle- server costs to obtain the optimal system design. In any case, the analyst<br />

will strive to solve this problem by analytical means; however, if these fail, he or she must resort to<br />

simulation. Ultimately, the issue generally comes down to a trade- <strong>of</strong>f <strong>of</strong> better customer service versus the<br />

expense <strong>of</strong> providing more service capability, that is, determining the increase in investment <strong>of</strong> service for a<br />

corresponding decrease in customer delay.<br />

5. Queues with impatience<br />

The intent <strong>of</strong> this part is to discuss the effects <strong>of</strong> customer impatience upon the development <strong>of</strong> waiting lines <strong>of</strong> the<br />

M/M/c type. These customers may be easily extended to other Markovian model in a reasonably straight-forward<br />

fashion and will not be explicitly pursued.<br />

Customers are said to be impatient if they tend to join the queue only when a short waiting is expected and tend to<br />

remain in line if the wait has been sufficiently small. The impatience that results from an excessive wait is just as<br />

important in the total queueing process as the arrivals and departures. When this impatience becomes sufficiently<br />

strong and customers leave before being served, the manager <strong>of</strong> enterprise involved must take action to reduce the<br />

congestion to levels that customers can tolerate. The models subsequently developed find practical application in this<br />

attempt <strong>of</strong> management to provide adequate service for its customers with tolerable waiting. Queueing with<br />

impatient customers are studied by [4,8,10] and with multiple heterogeneous servers by [5,6]. M/M/1 queue with<br />

impatient customers <strong>of</strong> higher priority is studied by Choi B. D. [11].<br />

907


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Impatience generally takes three forms. The first is balking, the reluctance <strong>of</strong> a customer to join a queue upon arrival;<br />

the second reneging, the reluctance to remain in line after joining and waiting; and the third jockeying between lines<br />

when each <strong>of</strong> number <strong>of</strong> parallel lines has its own queue.<br />

In real life, many queueing situations arise in which there may be a tendency for customers to be discouraged by a<br />

long queue. As a result, the customers either decide not to join the queue (i.e. balk) or depart after joining the queue<br />

without getting service due to impatience (i.e. renege). Balking and reneging are not only common phenomena in<br />

queues arising in daily activities, but also in various machine repair models. Many practical queueing systems<br />

especially those with balking and reneging have been widely applied to many real-life problems, such as the<br />

situations involving impatient telephone switchboard customers, the hospital emergency rooms handling critical<br />

patients, and the inventory systems with storage <strong>of</strong> perishable goods.<br />

.Queueing systems with balking, reneging or both have been studied by many researchers. Haight [<strong>19</strong>] first<br />

considered an M/M/1 queue with balking. An M/M/1 queue with customers reneging was also proposed by Haight.<br />

The combined effects <strong>of</strong> balking and reneging in an M/M/1/N queue have been investigated by Ancker and Gafarian<br />

[2], [3]. Abou-EI-Ata and Hariri [1] considered the multiple servers queueing system M/M/c/N with balking and<br />

reneging.<br />

In dealing with problems <strong>of</strong> queueing, several writers (Kolmogorovv, (<strong>19</strong>32); Erlang ; Kendall, (<strong>19</strong>51, <strong>19</strong>53);<br />

Lindley, (<strong>19</strong>52); Takacs, (<strong>19</strong>55)) have discussed the situation where queue stability is obtained by assuming that the<br />

demand for service does not overload the service mechanism. Thus λ, the average number <strong>of</strong> arrivals per unit time, is<br />

assumed to be less than µ, the average number <strong>of</strong> departures per unit time, so that their ratio, ρ, is less than unity.<br />

Kawata, (<strong>19</strong>55), on the other hand, has shown that queue stability can also be obtained by assuming that, although<br />

arrivals occur more frequently than departures, some arrivals choose not to join the queue. In theory this case can be<br />

included in the original one, simply by supposing. λ to be computed only from the values provided by those who<br />

actually join the queue. However, if the decision to join or not depends on some random variables, it is sensible to<br />

inquire into the relationship between these variables and those which characterize the queue, such as queue length<br />

and waiting time.<br />

The factors which influence the decision <strong>of</strong> a person to join a queue or not may be considered under two general<br />

headings: (a) those relating to the importance <strong>of</strong> being served, and (b) those relating to the obstacle which the queue<br />

presents, namely the waiting time which he must experience.<br />

Reneging in single server queues with general service time distribution has been studied by Daley, Rao, Cohen,<br />

Stanford and Baccelietal. Subsequently Kendall and Reuter, [24], treated this problem quite rigorously, and Haight,<br />

[<strong>19</strong>], has applied it to many particular distributions, under the name "Queueing with Balking". In the year <strong>20</strong>08 and<br />

<strong>20</strong>09 we also published two papers on balking and reneging [15,17], One is performance analysis <strong>of</strong> M/M/c/N<br />

queueing model with balking and reneging and second is performance analysis <strong>of</strong> M/M/1/N queueing model with<br />

balking and reneging. In these papers by using the Markov process method, we first develop the equations <strong>of</strong> the<br />

steady state probabilities. Next, we give some performance measures <strong>of</strong> the system. Finally, we present some<br />

numerical examples to demonstrate how the various parameters <strong>of</strong> the model influence the behavior <strong>of</strong> the system.<br />

Preemptive queue are basic models in queueing theory and have been studied by many researchers [7, 14, 21, 22, 29,<br />

30]. In the year <strong>20</strong>09 we also published two papers on priorities [16,18], One is performance analysis <strong>of</strong> M/M/1/k<br />

queueing model with non-preemptive priority and second is performance analysis <strong>of</strong> M/M/1/k queueing model with<br />

preemptive priority. In these papers by using the Markov process method, we first develop the equations <strong>of</strong> the<br />

steady state probabilities. Next, we give some performance measures <strong>of</strong> the system. Finally, we present some<br />

numerical examples to demonstrate how the various parameters <strong>of</strong> the model influence the behavior <strong>of</strong> the system.<br />

6. Benefits and limitations <strong>of</strong> queueing theory<br />

Queueing theory has been used for many real life applications to a great advantage. It is so because many problems<br />

<strong>of</strong> business and industry can be assumed/simulated to be arrival-departure or queueing problems. Queueing theory<br />

techniques can be applied to problems such as:<br />

a) Planning, scheduling and sequencing <strong>of</strong> parts and components to assembly lines in a mass production<br />

system.<br />

b) Scheduling <strong>of</strong> workstations and machines performing different operations in mass production.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

c) Scheduling and dispatch <strong>of</strong> war material <strong>of</strong> special nature based on operational needs.<br />

d) Scheduling <strong>of</strong> service facilities in a repair and maintenance workshop.<br />

e) Scheduling <strong>of</strong> overhaul <strong>of</strong> used engines and other assemblies <strong>of</strong> aircrafts, missile systems, transport fleet<br />

etc.<br />

f) Scheduling <strong>of</strong> limited transport fleet to a large number <strong>of</strong> users.<br />

g) Scheduling <strong>of</strong> landing and take <strong>of</strong>f from airports with heavy duty <strong>of</strong> air traffic and air facilities.<br />

h) Decision <strong>of</strong> replacement <strong>of</strong> plant, machinery, special maintenance tools and other equipment base on<br />

different criteria.<br />

Special benefits which this technique enjoys in solving problems such as above are<br />

1) Queueing theory attempts to solve problems based on a scientific understanding <strong>of</strong> the problems<br />

and solving them in optimal manner so that facilities are fully utilized and waiting time is reduced<br />

to minimum possible.<br />

2) Waiting time (or queueing) theory models can recommend arrival <strong>of</strong> customers to be serviced,<br />

setting up <strong>of</strong> workstations, requirement <strong>of</strong> manpower etc. based on probability theory.<br />

Limitations <strong>of</strong> Queueing Theory<br />

Though queueing theory provides us a scientific method <strong>of</strong> understanding the queues and solving such problems, the<br />

theory has certain limitations which must be understood while using the technique, some <strong>of</strong> these are:<br />

a) Mathematical distribution, which are assume while solving queueing theory problems , are only a close<br />

approximation <strong>of</strong> the behaviour <strong>of</strong> customers, time between their arrival and service time required by each<br />

customer.<br />

b) Most <strong>of</strong> real life queuing problems are complex situation and very difficult to use the queueing theory<br />

technique, even then uncertainty will remain.<br />

c) Many situations in industry and service are multi-channel queueing problems. When a customer has been<br />

attended to and the service provided, it may still have to get some other service from another service and<br />

may have to fall in queue once again. Here the departure <strong>of</strong> one channel queue becomes the arrival <strong>of</strong> other<br />

queue. In such situations, the problem becomes still more difficult to analyse.<br />

d) Queueing model may not be ideal method to solve certain very difficult and complex problems and one may<br />

have to resort to other techniques like Monte-Carlo simulation method.<br />

References<br />

[1] Abou El-Ata M. O., Hariri A. M. A., “The M/M/C/N queue with balking and reneging” Computers and<br />

Operations Research <strong>19</strong>, pp. 713-716, <strong>19</strong>92.<br />

[2] Ancker Jr. C. J., Gafarian A. V., “Some queueing problems with balking and reneging”, I. Operations Research<br />

11, pp. 88-100, <strong>19</strong>63.<br />

[3] Ancker Jr. C. J., Gafarian A. V., “Some queueing problems with balking and reneging”, II. Operations Research<br />

11, pp. 928-937, <strong>19</strong>63.<br />

[4] Ancker Jr. C. J., Gafarian A. V., "Queueing with Impatient Customers who Leave at Random", J. Indust. Eng. 13,<br />

pp. 86-87, <strong>19</strong>62.<br />

[5] Ancker Jr. C. J., Gafarian A. V., "Queueing with Reneging and Multiple Hetero-geneous servers”, Naval Res.<br />

Log. Quart. 10, pp. 137-139, <strong>19</strong>63.<br />

[6]. Ancker Jr. C. J., Gafarian A. V., "Queuing with Reneging and Multiple Heterogeneous Servers", SP-372,<br />

System Development Corporation, pp. 16-18, <strong>19</strong>61.<br />

[7] Avi-Itzhak B., Naor P., “Some queueing problems with the service station subject to breakdown”, Oper. Res., 11,<br />

pp. 303-3<strong>20</strong>, <strong>19</strong>63.<br />

[8] Barrer D.Y., “Queuing with impatient customers and ordered service”, Oper. Res. 5, pp. 650-656, <strong>19</strong>57.<br />

[9] Bbocmeyer E., Halstrom H. L., Jensen A., “The Life and Works <strong>of</strong> A. K. Erlang”, Copenhagen Telephone<br />

Company, <strong>19</strong>48.<br />

[10] Boots N.K., Tijms H., “A multiserver queueing system with impatient customers”,Management Sci. 45, pp. 444-<br />

448, <strong>19</strong>99.<br />

[11] Choi B.D., Kim B., Chung J., “M/M/1 queue with impatient customers <strong>of</strong> higher priority”, Queueing Systems<br />

38, pp. 49-66. <strong>20</strong>01.<br />

[12] Crommelin C. D., “Delay Probability Formulae When the Holding Times Are Constant”, P. O. Elec. Eng. J. 25,<br />

pp. 41-50, <strong>19</strong>32.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

[13] Erlang A. K., “The Theory <strong>of</strong> Probabilities and Telephone Conservations”, Nyt Tidsskrift Mat. B <strong>20</strong>, pp.<br />

33-39, <strong>19</strong>09.<br />

[14] Gaver D. P., Junior, “A waiting line with interrupted service, including priorities”, J. Roy. Stat. Soc., B 24, pp.<br />

73-90, <strong>19</strong>62.<br />

[15] Gupta N., Mishra G.D., Choubey A., “Performance analysis <strong>of</strong> an queueing model M/M/c/N with balking and<br />

reneging”, International Journal <strong>of</strong> Computer Mathematical <strong>Science</strong>s and Applications, Vol 2, No. 4, pp. 335-339,<br />

October-December <strong>20</strong>08.<br />

[16] Gupta N., Mishra G.D., Choubey A., “Performance analysis <strong>of</strong> An M/M/1/K Queue with Non-Preemptive<br />

Priority”, International Journal <strong>of</strong> Mathematical <strong>Science</strong>s and Engineering Applications, Vol 3, No. 2, pp. <strong>19</strong>1-<strong>19</strong>7,<br />

<strong>20</strong>09.<br />

[17] Gupta N., Mishra G.D., Choubey A., “Performance analysis <strong>of</strong> queueing model M/M/I/N with balking and<br />

reneging”, International Journal <strong>of</strong> Pure Applied Mathematical <strong>Science</strong>s, Vol. LXX, No. 1-2, pp. 59-65, September<br />

<strong>20</strong>09.<br />

[18]Gupta N., Mishra G.D., Choubey A., “Performance Analysis <strong>of</strong> An M/M/1/K Queue with Preemptive Priority”,<br />

International journal <strong>of</strong> Business Research, Vol. July, pp. 50-57, <strong>20</strong>09.<br />

[<strong>19</strong>] Haight F. A., “Queueing with balking”, Biometrika 44, pp. 360-369, <strong>19</strong>57.<br />

[<strong>20</strong>] Homma T., "On a Certain Queuing Process", Rept. Statist. Application Research, Union Japanese Scientists<br />

and Engrs. 4, No. 1, <strong>19</strong>55.<br />

[21] Jaiswal N. K.,”Priority Queues”, New York, Academic Press, <strong>19</strong>68.<br />

[22] Keilson J., “Queues subject to service interruption”, Ann. Math. Statist., 33, pp. 1314-1322, <strong>19</strong>62.<br />

[23] Kendall D. G., “Stochastic Processes Occuring in the Theory <strong>of</strong> Queues and Their Analysis by the Method <strong>of</strong><br />

Imbedded Markov Chains”, Ann. Math. Statist. 24, pp. 338-354,<strong>19</strong>53.<br />

[24] Kendall D. G., Reuter G. E. H., “The calculation <strong>of</strong> the ergodic projection for Markov chains and processes<br />

with a countable infinity <strong>of</strong> states”, Acta Mathematica, 97, pp. 103—144, <strong>19</strong>57.<br />

[25] Khintchine A.Y., “Mathematisches ϋber die Erwortung vor einemöffenthchen Schalter”, Mat. Sb. 39, pp. 73-84,<br />

<strong>19</strong>32.<br />

[26] Kolmogorov A. N., “Sur le problem d’attente”, Mat. Sb. 8, pp.101-106, <strong>19</strong>32.<br />

[27] Palm C., “Analysis <strong>of</strong> the Erlang Traffic Formulae for Busy Signal Arrangements”, Ericsson Tech. 6, pp. 39-58,<br />

<strong>19</strong>38.<br />

[28] Pollaczek F., “Lösung eines Geometrischen Wahrsceinlichkeits-problems”, Math. Z. 35, pp. 230-278, <strong>19</strong>32.<br />

[29] Takine T., Hasegawa T., “The workload in the MAP/G/l queue with state dependent services: Its application to<br />

a queue with preemptive resume priority'”, Comm. Statist. Stochastic Models, 10, pp. 183-221, <strong>19</strong>94.<br />

[30] Welch P. D., “On preemptive resume priority queues”, Ann. Math. Statist., 35, pp. 600-612, <strong>19</strong>64.<br />

910


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

IMPROVING THE ORGANISATION THROUGH 5S<br />

METHODOLOGY<br />

Ravinder Kumar Panchal<br />

M.Tech, Manufacturing & Automation, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad<br />

Mobile No: +91-9315133048, e-mail: ravi<strong>19</strong>8<strong>19</strong>88@yahoo.co.in<br />

Abstract<br />

This paper focused on the methodology adopted in 5S and implementation <strong>of</strong> the same in a company. It can be<br />

observed that introducing the 5S rules bring the great changes in the company, for example: process improvement<br />

by costs’ reduction, increasing <strong>of</strong> effectiveness and efficiency in the processes, maintenance and improvement <strong>of</strong> the<br />

machines’ efficiency, safety increasing and reduction <strong>of</strong> the industry pollution, proceedings according to decisions.<br />

The 5S methodology permits to analyse the processes running on the workplace. The 5S is the methodology <strong>of</strong><br />

creation and maintaining well organized, clean, high effective and high quality workplace. Own research clearly<br />

showed, that very essential is training <strong>of</strong> workers about the 5S rules. Essential thing is to divide activities on some<br />

main steps and to maintain the continuous improvement. The 5S method begins each programme <strong>of</strong> improvement in<br />

a company and can be used in all companies. Its result is the effective organization <strong>of</strong> the workplace. This paper<br />

shows the effect <strong>of</strong> implementation <strong>of</strong> the 5S rules in the production process.<br />

Key words: The 5S methodology, Quality management, TPM<br />

Introduction<br />

Total Productive Maintenance (TPM) [1] is a productive maintenance system requiring the participation <strong>of</strong> all<br />

departments in order to obtain maximum equipment efficiency in an organization, which involves all human<br />

resources. It is defined as the integrity <strong>of</strong> effective maintenance and autonomous maintenance activities conducted<br />

by all personnel as in small group activities<br />

In the frames <strong>of</strong> implementation <strong>of</strong> the Total Productive Maintenance on the operating level more and more popular<br />

becomes the idea <strong>of</strong> so called 5S.<br />

The 5S method begins each programme <strong>of</strong> improvement. It is the tool for helping the analysis <strong>of</strong> processes running<br />

on the workplace. The 5S is the methodology <strong>of</strong> creation and maintaining well organized, clean, high effective and<br />

high quality workplace. Its result is the effective organization <strong>of</strong> the workplace, reduction <strong>of</strong> work’s environment,<br />

elimination <strong>of</strong> losses connected with failures and breaks, improvement <strong>of</strong> the quality and safety <strong>of</strong> work [2]<br />

It has been targeted to set this as a guide for the directors <strong>of</strong> the company and the researches working in this field.<br />

The philosophy <strong>of</strong> the 5S has its roots in Japan. Name 5S is the acronym <strong>of</strong> five Japanese words <strong>of</strong> the following<br />

meanings:<br />

The 5S Methodology<br />

S means [3]<br />

Seiri (sorting, organization <strong>of</strong> the workplace, elimination <strong>of</strong> unnecessary materials). Refers to the practice <strong>of</strong> sorting<br />

through all the tools, materials, etc., in the work area and keeping only essential items. Everything else is stored or<br />

discarded. This leads to fewer hazards and less clutter to interfere with productive work.<br />

Seiton (set in order, place for everything).Focuses on the need for the workplace in order. Tools, equipment, and<br />

materials must be systematically arranged for the easiest and the most efficient access. There must be a place for<br />

everything, and everything must be in its place.<br />

Seiso (shine, cleaning, removing <strong>of</strong> wastes, dust etc.). Indicates the need to keep the workplace clean as well as neat.<br />

Cleaning in Japanese companies is a daily activity. At the end <strong>of</strong> each shift, the work area is cleaned up and<br />

everything is restored to its place.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Seiketsu (standardize, constant place for things, constant rules <strong>of</strong> organization, storage and keeping cleanness).<br />

Allows for control and consistency. Basic housekeeping standards apply everywhere in the facility. Everyone knows<br />

exactly what his or her responsibilities are. Housekeeping duties are part <strong>of</strong> regular work routines.<br />

Shitsuke (sustain, automatic realization <strong>of</strong> above-mentioned rules). Refers to maintaining standards and keeping the<br />

facility in safe and efficient order day after day, year after year.<br />

Implementing the 5S rules should begin from trainings <strong>of</strong> productive workers in the range <strong>of</strong> the 5S’s elements and<br />

advantages from their usage. It is important that all participants <strong>of</strong> trainings will understand the need <strong>of</strong> using the 5S<br />

rules on the own workplace and will agree on the changes. During trainings it is essential to train the usage <strong>of</strong> all<br />

rules on the clear example, so that every participant can understand the methodology <strong>of</strong> realization <strong>of</strong> the 5S’s<br />

elements. Very important fact is that these rules do not refer only to the productive positions, but also refer to the<br />

warehouse, <strong>of</strong>fice positions and others .<br />

Table-1 Meaning <strong>of</strong> 5S<br />

5S Definitions<br />

Japanese term English Equivalent Meaning in Japanese Context<br />

Seiri Sort Throwaway all rubbish and unrelated materials in the workplace<br />

Seiton Orderliness/Set in order Set everything in proper place for quick retrieval and storage<br />

Seiso Cleanliness/Shine Clean the workplace; everyone should be a janitor<br />

Seiketsu Standardization Standardize the way <strong>of</strong> maintaining cleanliness<br />

Practice 'Five S' daily - make it a way <strong>of</strong> life; this also means<br />

Shitsuke<br />

Discipline/Sustain 'commitment'<br />

1 S – Sorting<br />

Through the suitable sorting it can be identified the materials, tools, equipment and necessary information for<br />

realization the tasks. Sorting eliminates the waste material (raw materials and materials), nonconforming products,<br />

and damaged tools. It helps to maintain the clean workplace and improves the efficiency <strong>of</strong> searching and receiving<br />

things, shortens the time <strong>of</strong> running the operation.<br />

The 1S rule’s proceedings [4]:<br />

A) On the first stage one should answer to so-called Control Questions:<br />

Are unnecessary things causing the mess in the workplace<br />

Are unnecessary remainders <strong>of</strong> materials thrown anywhere in the workplace<br />

Do tools or remainders <strong>of</strong> materials to production lie on the floor (in the workplace)<br />

Are all necessary things sorted, classified, described and possess the own place<br />

Are all measuring tools properly classified and kept<br />

On the basis <strong>of</strong> the answer to the above questions it is possible the estimation <strong>of</strong> the workplace in terms <strong>of</strong> the 1S<br />

rule so littering the workplace. If on any question answer is yes, it should execute sorting <strong>of</strong> things, which are in the<br />

workplace.<br />

B) On the second stage one should execute the review <strong>of</strong> all things which are in the workplace and group them<br />

according to the definite system. According to carried out sorting it should execute the elimination from the<br />

workplace the things, which were found “unnecessary”.<br />

C) To permanent usage the 1S rule is so-called the Programme <strong>of</strong> the Red Label. It means giving the red label to<br />

things, which operator will recognize as useless within his workplace. This label will make possible not only the<br />

elimination <strong>of</strong> the given thing, but through its own formula will make possible the liquidation <strong>of</strong> the reasons <strong>of</strong><br />

appearing on the workplace this given thing.<br />

2 S – Set in order<br />

Especially important is visualization <strong>of</strong> the workplace (e.g. painting the floor helps to identify the places <strong>of</strong> storage<br />

<strong>of</strong> each material or transport ways, drawing out the shapes <strong>of</strong> tools makes possible the quick putting aside them on<br />

the constant places, coloured labels permit to identify the material, spare parts or documents etc.).<br />

912


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Implementing the 2S rule [5]:<br />

It should execute the segregation <strong>of</strong> things and mark the places <strong>of</strong> their storing. Used things should always be<br />

divided on these, which should be:<br />

- In close access (1st degree sphere),<br />

- Accessible (2nd degree sphere),<br />

- In the range <strong>of</strong> hand (3rd degree sphere).<br />

To the estimation <strong>of</strong> the workplace in terms <strong>of</strong> the 2S rule that is setting in order things serve the following Control<br />

Questions:<br />

- Is position (location) <strong>of</strong> the main passages and places <strong>of</strong> storing clearly marked<br />

- Are tools segregated on these to regular uses and on specialist tools<br />

- Are all transport palettes stored on the proper heights<br />

- Is anything kept in the area <strong>of</strong> devices against the fire<br />

- Has the floor any irregularity, cracks or causes other difficulties for the operator’s movement<br />

Things used occasionally and seldom should be on the workplace but outside the direct using sphere. Their distance<br />

and location from the place <strong>of</strong> work should depend on the frequency <strong>of</strong> using these materials or tools. Places <strong>of</strong><br />

storage should be marked in the manner making possible their quick identification. It can be used coloured lines,<br />

signs or tool boards. Once defined places and methods <strong>of</strong> storage should be invariable.<br />

3 S – Shine<br />

Regular cleaning permits to identify and to eliminate sources <strong>of</strong> disorder and to maintain the clean workplaces.<br />

During cleaning it is checked the cleanness <strong>of</strong> machine, workplace and floor, tightness <strong>of</strong> equipment, cleanness <strong>of</strong><br />

lines, pipes, sources <strong>of</strong> light, current data, legibility and comprehensibility <strong>of</strong> delivered information etc.<br />

Indispensable is also taking care <strong>of</strong> and maintenance the personal tidiness <strong>of</strong> the operator.<br />

Implementing the 3S rule [6]:<br />

The first step <strong>of</strong> realization the 3S rule is renovation the workplace. It is assumed that “the first cleaning” forces the<br />

exact checking <strong>of</strong> usage two <strong>of</strong> the previous rules. The usage <strong>of</strong> the 3S rule relies on everyday keeping in faultless<br />

cleanness the workplace. It is executed by the operator <strong>of</strong> the given workplace. To the estimation <strong>of</strong> the workplace in<br />

terms <strong>of</strong> the 3S rule, that is cleaning the workplace, serve the following Control Questions:<br />

- Are the oil’s stains, dust or remains <strong>of</strong> metal found around the position, machine, on the floor<br />

- Is machine clean<br />

- Are lines, pipes etc. clean, will they demand repairing<br />

- Are pipe outlets <strong>of</strong> oils not clogged by some dirt<br />

- Are sources <strong>of</strong> light clean<br />

4 S – Standardize<br />

Worked out and implemented standards in the form <strong>of</strong> procedures and instructions permit to keep the order on the<br />

workplaces. Standards should be very communicative, clear and easy to understand. Regarding this during<br />

preparation and improving, it should be involved all participants <strong>of</strong> the process on the given workplace, it means<br />

direct workers. The group knows the best specificity <strong>of</strong> its own activities, and process <strong>of</strong> elaboration and after that,<br />

usage gives them possibility <strong>of</strong> understanding the essence and each aspect <strong>of</strong> the operation. In the aim <strong>of</strong> assuring all<br />

the easy access, obligatory standards should be found in constant and visible places.<br />

It is assumed that standards should not be implemented only in the typical operational processes e.g. production,<br />

movement maintenance, storing, but also in the administrative processes, for example: book-keeping, customer<br />

service, human resources management, or secretariat service [7].<br />

5 S – Sustain<br />

Implementing the idea <strong>of</strong> the 5S will demand from workers the compact self-discipline connected with<br />

implementing and obeying the rules <strong>of</strong> regularity in cleaning and sorting. It leads to increasing the consciousness <strong>of</strong><br />

staff, and decreasing the number <strong>of</strong> non-conforming products and processes, improvements in the internal<br />

communication, and through this to improvement in the human relations.<br />

It is also important to understand the need <strong>of</strong> executing the routine inspections <strong>of</strong> usage the 5S rule. This inspection<br />

is executed by helping <strong>of</strong> so-called Check List and created on its basis the radar graph <strong>of</strong> the 5S, which serves to<br />

913


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

estimation <strong>of</strong> the workplace. The inspection <strong>of</strong> realization <strong>of</strong> the 5S rule is executed once a month by chosen team<br />

implementing the 5S rule – the control team [2].<br />

Case study<br />

The 5S methodology relies on the creation and keeping well organized, clean, high effective and high quality<br />

workplace. Study has been carried out in the selected Fastening industry. During the study it was executed the<br />

selection <strong>of</strong> process parameter/procedure in the chosen production process, on each workplace. The 5S methodology<br />

was introduced to workers and control questions have been asked. Each rule has been implemented and in<br />

consequence the great changes have appeared as reflected in figure 1 to 8:<br />

Questions asked from workers<br />

• What is 5S<br />

• Where can we implement it<br />

• It’s a regular practice or not<br />

• Whether it is an only a housekeeping<br />

• Who should do it<br />

• When should do it<br />

Changes that take place after 5S Implementation<br />

1 S:<br />

• things were sorted on necessary and unnecessary,<br />

• unnecessary things were removed,<br />

• workplaces were released from the disturbing things,<br />

2 S:<br />

• all things to quick usage were properly arranged,<br />

• the time <strong>of</strong> preparing the workplace was shortened,<br />

3 S:<br />

• machines are maintained in cleanness,<br />

• conditions <strong>of</strong> work are tidy and safe,<br />

4 S:<br />

• all obligatory rules in the company are obeyed (procedures, instructions, regulations, orders),<br />

5 S:<br />

• self-control,<br />

• cooperation in team solving the problems,<br />

• proceedings is in accordance with decisions.<br />

• In the aim <strong>of</strong> execution the inspection <strong>of</strong> the 5S rules’ activity it is used so-called Check List once a term.<br />

BEFORE<br />

AFTER<br />

Figure 1.Heap <strong>of</strong> items which is not sort (1S) Figure 2.Useful material found during 1S.<br />

914


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 3.Files lying in disorder.<br />

Figure 4.After Systematic arrangement (2S).<br />

Figure 5.Gangway not proper cleaned.<br />

Figure 6.After proper marking & Painting (3S).<br />

Figure 7.Not standard <strong>of</strong> flow in pipes.<br />

Figure 8.Now all pipes are standardized (4S).<br />

Conclusions<br />

The advantages from implementing the 5S rules<br />

1 S:<br />

• Process improvement by costs’ reduction,<br />

• Stock decreasing.<br />

• Better usage <strong>of</strong> the working area.<br />

• Prevention <strong>of</strong> losing tools.<br />

2 S:<br />

• Process improvement (increasing <strong>of</strong> effectiveness and efficiency).<br />

• Shortening <strong>of</strong> the time <strong>of</strong> seeking necessary things.<br />

• Safety improvement.<br />

3 S:<br />

• Increasing <strong>of</strong> machines efficiency.<br />

• Maintenance the cleanness <strong>of</strong> devices.<br />

915


• Maintenance and improvement <strong>of</strong> the machines efficiency.<br />

• Maintenance the clean workplace, easy to check.<br />

• Quick informing about damages (potential sources <strong>of</strong> damages).<br />

• Improvement <strong>of</strong> the work environment.<br />

• Elimination <strong>of</strong> the accidents’ reasons.<br />

4 S:<br />

• Safety increasing and reduction <strong>of</strong> the industry pollution.<br />

• Working out the procedures defining the course <strong>of</strong> processes.<br />

5 S<br />

• Increasing <strong>of</strong> the awareness and morale.<br />

• Decreasing <strong>of</strong> mistakes quantity resulting from the inattention.<br />

• Proceedings according to decisions.<br />

• Improvement <strong>of</strong> the internal communication processes.<br />

• Improvement <strong>of</strong> the inter human relations.<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

References<br />

[1] J. Susaka, Hotoji, Implementation <strong>of</strong> TPM by basic 5S activity 21/1(<strong>20</strong>11)<br />

[2] M. Urbaniak, Quality management – theory and practice, Difin, Warsaw, <strong>20</strong>09.<br />

[3] Yoshio Egami,TPM an Integrated Approaching – Implementing Total Productive Maintenance through<br />

Japanese 5S Japan, <strong>20</strong>10.<br />

[5] J. Peterson, R. Smith, The 5S Pocket Guide, Quality Resources, New York, <strong>20</strong>01.<br />

[6] H.J. Harrington, Business Process Improvement: The Breakthrough Strategy for Total Quality, Productivity,<br />

and Competitiveness, McGraw-Hill Inc., New York, <strong>20</strong>00.<br />

[7]M. Dudek-Burlikowska, Quality research methods as a factor <strong>of</strong> improvement <strong>of</strong> preproduction sphere, Journal <strong>of</strong><br />

Achievements in Materials and Manufacturing Engineering 18 (<strong>20</strong>06) 435-438.<br />

916


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

APPLYING SIX SIGMA METHODOLOGY IN A BRICK KILN<br />

INDUSTRY THEREBY REDUCING DEFECT LEVEL<br />

Akhil Khajuria 1 , Kapil Singh 1 , Khalid Sheikh 1 and Navdeep Malhotra 2<br />

1 Student, M.Tech (M&A) SME, Shri Mata Vaishno Devi <strong>University</strong>, (J&K), India<br />

2 Pr<strong>of</strong>essor (Mech Engg.) <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Sec-6, Faridabad, Haryana,India<br />

e-mail: akhil.khajuria@yahoo.com<br />

Abstract:<br />

The fundamentals <strong>of</strong> brick manufacturing have not changed over time. However, technological advancements have<br />

made contemporary brick plants substantially more efficient and have improved the overall quality <strong>of</strong> the products.<br />

A more complete knowledge <strong>of</strong> raw materials and their properties, better control <strong>of</strong> firing, improved kiln designs and<br />

more advanced mechanization have all contributed to advancing the brick industry.. Since the repetitive production<br />

<strong>of</strong> bricks meeting standards is very demanding in the industry, the implementation <strong>of</strong> cyclic control on the brick kiln<br />

set-up has naturally become an important objective for researchers. In this paper, a similar kind <strong>of</strong> work has been<br />

presented with the objective <strong>of</strong> reducing the no. <strong>of</strong> defects that were caused due to various reasons in a Brick Kiln set<br />

up.The purpose <strong>of</strong> this research is to study quality related problems while producing building product and to<br />

improve the quality <strong>of</strong> the product using Six Sigma methodologies in a Brick Kiln Industry. This research paper aims<br />

at using a case study approach to show how Six Sigma methodologies can be used in order to improve the quality <strong>of</strong><br />

Bricks in a Kiln. The variables which were affecting the production quality were sorted out and consistently the<br />

defect level was reduced by using DMAIC principle <strong>of</strong> six sigma implementation on the manufacturing set up after<br />

formulating the problem.<br />

Keywords: De-Hacking, forming, firing, CTQ (characteristics Critical to Quality), DMAIC, Schimdt and<br />

Launsby formula.<br />

1.0 Introduction<br />

In today's competitive world, an organization's success is based on its ability to produce the products and services<br />

faster, superior and cheaper than their competitors. Global competition and demand from the customer for high<br />

quality andlow cost product is forcing the organizations to search for the means to improve their products and<br />

processes. Six Sigma is a well-known concept for improving quality and productivity.Six Sigma is a structured and<br />

disciplined process, focused on delivering perfect product or services to the customer consistently [1]. In statistical<br />

terms, Six Sigma means 3.4 defects per million opportunities (DPMO). It is a methodology that emphasizes Define,<br />

Measure, Analyze, Improve & Control (DMAIC) approach to problem solving [2].The aim <strong>of</strong> Six Sigma<br />

methodology is to integrate all operations throughout the processes to make them produce their desired results. It can<br />

be implemented in various processes related to manufacturing and services including health care, information<br />

technology, distribution operations, warehouse and inventory management, supply chainmanagement and<br />

manufacturing.This work aims at improving the quality <strong>of</strong> a product in ABC Brick Kiln industry using Six Sigma<br />

DMAIC methodology.<br />

1.1 Statement <strong>of</strong> the Problem<br />

ABC Brick iln industry analyses a quality complaint in its product from customer. The company was required to<br />

improve the quality <strong>of</strong> the product for its customer satisfaction.<br />

1.2 Purpose <strong>of</strong> the Work<br />

The purpose <strong>of</strong> the work is to study quality related problems in therm<strong>of</strong>ormed plastic products and improve quality<br />

<strong>of</strong> the product using Six Sigma DMAIC Methodology.<br />

1.3 Objectives <strong>of</strong> the Work<br />

1. To study and determine quality problems in the Industry.<br />

2 To identify commonly used Six Sigma tools and techniques.<br />

3 To solve the quality related problem and increase quality <strong>of</strong> the product using Six Sigma DMAIC methodology.<br />

917


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

1.4 Assumptions <strong>of</strong> the Work<br />

1. The data provided by the industry are precise.<br />

2. The data collection process adopted by the industry is reliable.<br />

2.0 case study<br />

Although the basic principles <strong>of</strong> manufacturing are fairly uniform, individual manufacturing plants tailor their<br />

production to fit their particular raw materials and operation. Essentially, brick are produced by mixing ground clay<br />

with water, forming the clay into the desired shape, and drying and firing. In developed countries, all molding is<br />

performed by brick-making machines. However in India half <strong>of</strong> the Brick kilns still use the conventional method <strong>of</strong><br />

molding. Even in this brick kiln manual method (using cope and drag) is used for molding bricks.<br />

Figure 2. Systematic Representation <strong>of</strong> Brick Manufacturing Process<br />

Table 1 proposes the specifications <strong>of</strong> the process.<br />

Material Used<br />

Operating Temperature<br />

Production Rate/hr<br />

Manufacturing time<br />

Fuel Materials Used<br />

Table 1. Process Specifications<br />

Brick Cakes from the mixture <strong>of</strong> Clay, Soil and Water<br />

<strong>20</strong>4 o C(final drying)<br />

3<strong>20</strong>0-3500 Units per hour<br />

10hrs (with a break <strong>of</strong> 1 hr)<br />

Coal + Coaltar + Wood<br />

2.0 Application <strong>of</strong> six sigma DMAIC methodology<br />

3.1 Define phase<br />

In this stage, with the help <strong>of</strong> supplies, input, process and output various stages in the rings process were identified.<br />

The results <strong>of</strong> the Define stage are as follows:<br />

1. Customer – Workers who are involved in the process <strong>of</strong> De-Hacking.<br />

2. Team – Project Team involves all those who are involved in the process <strong>of</strong> Preparation, Forming,<br />

Drying, Hacking and finally firing.<br />

3. Process Boundaries – All Process Steps from putting the raw materials till the final Bricks are obtained<br />

All set-ups have preventive maintenance schedules in addition to random breakdowns.All work is inspected before<br />

moving to the next operation in order to eliminate additional rework steps.Setups are required at each step in the<br />

process whenever the previous and current product types differ.<br />

918


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3.2 Measure phase<br />

In this stage, the characteristics <strong>of</strong> the product or process to be measured are selected and the performance standards<br />

for those outputs are defined, and then a “CTQ (characteristics Critical to Quality) Flowdown” is performed to<br />

understand the relationship between the inputs and outputs.<br />

Figure 2. Manufacturing Cycle<br />

The diagram above shows how the primary CTQ manufacturing cycle is a function <strong>of</strong> parameters which are under<br />

control, such as machining times, setup and down times and crane availability. Other factors, such as product mix<br />

and holiday schedules are also be taken into account. The basic aim <strong>of</strong> this stage is to focus on improvement effort<br />

by gathering information on the current situation. This information include what is the current sigma level and how<br />

much can be expected to improve and how much time will be required to do so.<br />

3.2.1 Current Sigma Level<br />

For this purpose data for the production <strong>of</strong> bricks was taken every day. Product yield was determined and number <strong>of</strong><br />

defects in total to establish defect yield and sigma value. Fig. 3 Production v/s Defects below shows the number <strong>of</strong><br />

bricks produced & number <strong>of</strong> defective bricks produced for the consecutive five days.<br />

3.2.2 Calculations<br />

Defects/unit (DPU) = 0.<strong>19</strong>12<br />

Figure 3. Production v/s Defects<br />

Defects per million opportunities (DPMO) [3]<br />

9<strong>19</strong>


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

= × 1,000,000<br />

= × 1,000,000<br />

= <strong>19</strong>1253.6443<br />

So, DPMO is <strong>19</strong>1253.<br />

3.2.3 Schimdt and Launsby formula [4]<br />

This formula is a basic formula for calculating the sigma level. It just needs the variable i.e. Defects per million<br />

opportunities i.e. DPMO.<br />

Sigma<br />

= 0.8406 + Sqrt (29.37-2.221×ln(DPMO))<br />

= 2.3767<br />

3.3 Analyze Phase<br />

Once all the measurements have been done it is the time to critically analyze the process, and to determine the key<br />

variables and also to determine the next step for the purpose <strong>of</strong> improvement.<br />

With the help <strong>of</strong> workers and engineers there and studies have determined the following factors that influence the<br />

product quality:-<br />

• Proportion in which the various raw materials are mixed viz clay, soil, water<br />

• Method <strong>of</strong> Drying and the time required for drying also plays a vital role<br />

• Rough Handling <strong>of</strong> the Raw Bricks can also produce defects<br />

• Brick kiln Design<br />

• Method <strong>of</strong> Firing<br />

• Proper placements <strong>of</strong> Raw Bricks in the firing chamber during Hacking<br />

• Most <strong>of</strong> the bricks break during packing and transportation i.e packing and transportation losses<br />

Although the above factors were the key variables that effect the sigma value but it was practically impossible for us<br />

to measure the %age effect that each factor has on the production quality. So it was decided to prepare charts and<br />

analysis report on the no. <strong>of</strong> defects that are produced at each <strong>of</strong> the six stages mentioned before .Results are shown<br />

in the following table.<br />

Table 2. Average defects and their effect<br />

Stage Average no. <strong>of</strong> defects on variation (per 1000) %age effect <strong>of</strong> each variable<br />

Mining & Storage 0 0<br />

Preparation 4 2.14<br />

Forming the Brick 36 <strong>19</strong>.25<br />

Drying 71 37.96<br />

Firing & Cooling 47 25.14<br />

De-hacking 29 15.51<br />

Total 187 100<br />

This shows that the no. <strong>of</strong> Defects in drying stage is maximum followed by firing and cooling, forming, de-hacking<br />

and Preparation. We have almost zero defects in mining stage. So our improvements will be based on this analysis.<br />

9<strong>20</strong>


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

3.4 Improve Phase<br />

After the analysis and brainstorming in the previous step, now comes the Improvement stage. For this purpose a visit<br />

was taken up in another brick kiln located in the vicinity. Then the processes used in the kilns were compared. On the<br />

basis <strong>of</strong> this comparison, knowledge and understanding some improvements were proposed. Then these<br />

improvements were consulted with various expertise and the kiln owners. Here is the list <strong>of</strong> all the improvements that<br />

were made:-<br />

3.4.1 Improvement List- 1<br />

a) Improve Brick Drying Before Firing:-Extended drying time reduces fuel requirements, even drying<br />

throughout brick stacks reduces defective firing <strong>of</strong> bricks.<br />

b) Improve Air Circulation For Drying Purpose:-This can be done by using high speed fans. This will improve<br />

the quality <strong>of</strong> raw brick.<br />

c) Improve Air Flow Control In The Kiln:-Controlling the kiln opening size allows better control <strong>of</strong> air flow<br />

speed and direction to improve combustion.<br />

d) Stack Fuel Around Bricks To Facilitate Preheating:-Solid fuel is mixed with the bricks throughout the kiln,<br />

either as sawdust mixed into the brick mass or as fuel channels in different levels <strong>of</strong> the kiln. By doing this,<br />

a combustion zone can be generated in the kiln that gradually moves upwards, using the residual heat in the<br />

lower, already burnt bricks for preheating <strong>of</strong> combustion air. The residual heat in the flue gasses is used for<br />

drying and preheating <strong>of</strong> the higher levels <strong>of</strong> crude bricks.<br />

e) Switch To Propane Or Natural Gas Fuel:-If available and competitively priced, these fuels have<br />

significantly less emissions and can increase production quality and speed.<br />

f) Proper Placement Of Raw Bricks In The Furnace:-The setting pattern <strong>of</strong> the bricks has considerable<br />

influence on the defect level. The bricks should not be placed face to face or face to back instead they<br />

should be placed with some spacing in between. This will increase the brick area that is open to fire.<br />

3.4.2 Improvement List- 2:-<br />

This is a list <strong>of</strong> those improvements which the kiln owners have considered infeasible and denied to apply due to<br />

financial constraints and lack <strong>of</strong> time. Here they are in brief:-<br />

a) New and Improved Kiln Design instead <strong>of</strong> using conventional kilns<br />

b) Stopping air leakages help in better control <strong>of</strong> air flow and also improve combustion<br />

c) Use <strong>of</strong> Robotic Arms in case <strong>of</strong> loading and unloading the bricks in Hacking and De- hacking processes<br />

reduces the manual effort and time. It can also reduce the defects that are caused in these stages.<br />

d) Transportation Losses if reduced will also contribute in reducing the total no. <strong>of</strong> defects.<br />

e) Use <strong>of</strong> Automatic Brick Molding Machine instead <strong>of</strong> using conventional manual molding methods using<br />

Drag and Cope will reduce the time taken considerably. Use <strong>of</strong> this machine can reduce all the defects that<br />

were produced in the Forming Stage.<br />

f) Improve the method <strong>of</strong> Firing will not only reduce the pollution caused by the kiln but also help in<br />

controlled Firing thereby reducing the defects.<br />

g) The proportion with which the raw materials specially water and clay are mixed.<br />

With the help <strong>of</strong> the Brick kiln Owner we finally these improvements were applied. The Defect level has came down.<br />

Reading was taken <strong>of</strong> the three furnace chambers.<br />

3.4.1 Calculations<br />

Defects/unit (DPU) = = 0.01099<br />

S.No. No. <strong>of</strong> Defects Total no. <strong>of</strong> parts produced<br />

1 37 3<strong>20</strong>0<br />

2 35 3100<br />

3 39 3800<br />

Total 111 10100<br />

Defects per million opportunities (DPMO) [3]<br />

921


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

= ×1,000,000 = × 1,000,000 = 10990<br />

So, DPMO is 10990.<br />

3.4.2 Schimdt and Launsby formula [4]<br />

Sigma = 0.8406 + Sqrt (29.37-2.221×ln(DPMO))<br />

Capability= Sigma/3<br />

So, Sigma = 3.7908.<br />

This clearly shows that defect level has come down and sigma level has improved. It is now 3.79. Finally the success<br />

was achieved in reducing the defect level to such an extent. We could have achieved even more but that required<br />

changes in the whole processes, using high quality machines, automatic machines for clamping and packaging<br />

purpose. All these steps will decrease the manual effort and decrease the time taken thus improving the efficiency <strong>of</strong><br />

the process.<br />

3.5 Control phase<br />

The final step in this DMAIC project was to ensure that the proposed improvements should be applied in the<br />

manufacturing process <strong>of</strong> bricks. Further stress should be paid on other improvements as well particularly in the<br />

method <strong>of</strong> Firing. There is a need to understand that new methods can further be improved. Also we should<br />

summarize our key learning’s and involve every worker in suggesting improvements. We should also develop a<br />

Monitoring System. Whenever, the inputs were determined to be out <strong>of</strong> bounds, immediate attention should be given<br />

to correct the situation and bring the process back under control.<br />

4.0 Conclusion<br />

So finally the success was achieved in reducing the defect level and thereby improving the sigma value in. The final<br />

sigma value <strong>of</strong> 3.79 is achieved. However if industries want to retain or improve this sigma value, necessary control<br />

measures have to be taken and proper checks have to be imposed. Quality culture must be developed amongst<br />

employees and proper training must be given to them. A good decision for project generation not only provides<br />

pr<strong>of</strong>its but also increases customer satisfaction. This study aims to investigate the effect <strong>of</strong> applying six sigma tools<br />

in a Brick Kiln industry trying to decrease the scrap rate. This study has two advantages. First is to choose the best<br />

tools that fit that type <strong>of</strong> industry. Second is to encourage similar companions to apply the same methodology.<br />

5.0 References<br />

1. Linderman, K., Schroeder, R., Zaheer, S., Choo, A., (<strong>20</strong>03). “Six Sigma: A goal-theoretic perspective”,<br />

Journal <strong>of</strong> Operations Management, Vol. 21, No. 2, Mar., pp. <strong>19</strong>3-<strong>20</strong>3.<br />

2. Pande, P., Neuman, R., Cavanaugh, R., (<strong>20</strong>00). “The Six Sigma Way: How GE, Motorola, and Other Top<br />

Companies are Honing Their Performance”, McGraw-Hill, New York.<br />

3. Breyfogle, F. W. (<strong>20</strong>03), “Implementing Six Sigma: Smarter Solutions Using Statistical Methods”, Wiley.<br />

4. Schmidt , S.R., and Launsby, R.G., Understanding Industrial Designed Experiments, 4 th ed., Air Academy<br />

Press, Colorado.<br />

922


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

ROLE OF OPERATIONS RESEARCH APPLICATIONS IN FINANCIAL<br />

MARKETS- A LITERATURE REVIEW<br />

Ashok Kumar¹, Jyotsana Chawla², Neha Goyal³<br />

1 (Student) Department <strong>of</strong> Management Studies, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & Tech., Faridabad, HR<br />

2 (Asst. Pr<strong>of</strong>.) Department <strong>of</strong> Management Studies, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & Tech., Faridabad, HR<br />

e-mail: ashok.ymca111@gmail.com<br />

Abstract<br />

This paper reviews the application <strong>of</strong> OR to financial markets. After considering reasons for the attractiveness <strong>of</strong><br />

general finance problems to OR researchers. The main types <strong>of</strong> financial market problem amenable to OR are<br />

identified, and some <strong>of</strong> the many problems solved using OR are documented. While mathematical programming<br />

is the most widely applied technique, and other simulation methods are increasingly widely used. OR now plays<br />

an important role in the operation <strong>of</strong> financial markets and this importance is likely to increase, creating the<br />

opportunity for OR (and operations researchers) to play an even greater role.<br />

Keywords: - operation research technique, finance, financial market problem<br />

Research Methodology<br />

Operations Research, OR, has been applied to problems in finance for at least the last half century. There is an<br />

even larger number <strong>of</strong> papers on the application <strong>of</strong> OR techniques to finance in the finance, mathematics,<br />

engineering and other literatures, so that, in total, there are several thousand papers which apply OR techniques<br />

to finance in academic journals. This paper considers the application <strong>of</strong> OR techniques to financial markets. This<br />

covers decisions concerning trading by decision makers in financial markets (e.g. the debt, equity and foreign<br />

exchange markets and the corresponding derivatives markets), and represents a more recent and still growing<br />

area for the application <strong>of</strong> OR techniques to finance. This paper does not consider the more traditional<br />

applications <strong>of</strong> OR to the management <strong>of</strong> the firm’s finances: working capital management (which can be<br />

subdivided into the management <strong>of</strong> cash, receivables and liabilities), capital investment (including the appraisal<br />

and implementation <strong>of</strong> sets <strong>of</strong> large interdependent investments), multinational taxation, and financial planning<br />

models (such as those developed for banks); which have been reviewed by Ashford, Berry and Dyson (<strong>19</strong>88).<br />

Models for forecasting movements in financial markets and bankruptcy prediction are not considered, as they are<br />

deemed to be outside the scope <strong>of</strong> this paper. After considering some <strong>of</strong> the reasons for the attractiveness <strong>of</strong><br />

finance problems for the application <strong>of</strong> OR techniques, this paper identifies the main types <strong>of</strong> problem that are<br />

amenable to OR analysis, and documents some <strong>of</strong> the many problems in financial markets which have been<br />

addressed using OR techniques.<br />

1. How the Finance Problems arises<br />

An important distinguishing feature <strong>of</strong> problems in financial markets is that they are generally separable and well<br />

defined. The objective is usually to maximise pr<strong>of</strong>it or minimise risk, and the relevant variables are amenable to<br />

quantification, almost always in monetary terms. In finance problems, the relationships between the variables are<br />

usually well defined, so that, for example, the way in which an increase in the proportion <strong>of</strong> a portfolio invested<br />

in a particular asset affects the mean and variance <strong>of</strong> the portfolio is clear. Thus the resulting OR model is a good<br />

representation <strong>of</strong> reality, particularly as the role <strong>of</strong> non-quantitative factors is <strong>of</strong>ten small. Finance problems also<br />

have the advantage that any solution produced by the analysis can probably be implemented, while in other areas<br />

there may be unspecified restrictions concerned with human behaviour and preferences that prevent the<br />

implementation <strong>of</strong> some solutions. Furthermore, finance practitioners are accustomed to the quantitative analysis<br />

<strong>of</strong> problems. The investigator is likely to find that much <strong>of</strong> the requisite historical data has already been collected<br />

and is available from company records or recorded market transactions, and that large amounts <strong>of</strong> real time data<br />

are available on prices (traded and quoted) in financial markets which can readily be used in OR models. In<br />

addition, non-quantitative factors are generally absent from formulations <strong>of</strong> finance problems. The availability <strong>of</strong><br />

real time data means that solutions can <strong>of</strong>ten be implemented very quickly (e.g. a few seconds) and, as trading in<br />

financial markets <strong>of</strong>ten involves very large sums <strong>of</strong> money, even a very small improvement in the quality <strong>of</strong> the<br />

solution (under 0.5%) is beneficial. Furthermore, such problems tend to recur, possibly many times per day,<br />

spreading the costs <strong>of</strong> developing an OR solution over a large number <strong>of</strong> transactions. This scale and repetition<br />

makes the development <strong>of</strong> an OR model more attractive than for small or one-<strong>of</strong>f decisions. Thus, because<br />

finance applications (especially applications to financial markets) are largely numerical problems with welldefined<br />

boundaries and objectives, clear relationships between the variables, large benefits from very small<br />

improvements in the quality <strong>of</strong> decision making and excellent data, they are well suited to OR analysis. This<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

paper analyses the application <strong>of</strong> OR techniques to financial markets in more detail by considering some <strong>of</strong> the<br />

major types <strong>of</strong> problem in financial markets, and the OR techniques that have been used to analyse them.<br />

2. Portfolio Theory<br />

A seminal application <strong>of</strong> OR techniques to finance was by Harry Markowitz (<strong>19</strong>52, <strong>19</strong>87) when he specified<br />

portfolio theory as a quadratic programming problem (for a survey <strong>of</strong> this theory, see Board, Sutcliffe and<br />

Ziemba, <strong>19</strong>99). Participants in financial markets usually wish to construct diversified portfolios because this has<br />

the substantial advantage <strong>of</strong> reducing risk, while leaving expected returns unchanged. The objective function for<br />

the portfolio problem is generally specified as minimising risk for a given level <strong>of</strong> expected return, or<br />

maximising expected return for a given level <strong>of</strong> risk. While returns produce a linear objective function, risk is<br />

modelled using the variance, leading to an objective function with quadratic variance and covariance terms. The<br />

Markowitz model also includes non-negativity constraints on the decision variables to rule out short selling <strong>of</strong><br />

the asset concerned. As well as specifying the portfolio problem within a mean-variance framework, Markowitz<br />

also developed solution algorithms for more general quadratic programming problems. This provides an example<br />

<strong>of</strong> the interaction between OR techniques and finance, with the former sometimes being tailored to meet the<br />

needs <strong>of</strong> the latter. Subsequently the idea <strong>of</strong> using the variance to model risk has been extensively used in<br />

finance, and hence in applications <strong>of</strong> OR to finance. Although the most obvious application <strong>of</strong> portfolio theory is<br />

to the choice <strong>of</strong> equity portfolios, and empirical papers (e.g. Board and Sutcliffe, <strong>19</strong>94; and Perold, <strong>19</strong>84) have<br />

used quadratic programming to compute efficient equity portfolios, the technique can be applied to a much wider<br />

range <strong>of</strong> problems. Konno and Kobayashi (<strong>19</strong>97) proposed using quadratic programming to form portfolios <strong>of</strong><br />

both equities and bonds. Other authors have been concerned with managing bond portfolios to maximize their<br />

expected value, and have used stochastic linear programming to allow for interest rate risk (e.g. Bradley and<br />

Crane, <strong>19</strong>72). Golub et al. (<strong>19</strong>95), Zenios (<strong>19</strong>91, <strong>19</strong>93b) and Zenios et al (<strong>19</strong>98) employed stochastic<br />

programming to select a portfolio <strong>of</strong> fixed interest securities (Mortgage Backed Securities, MBS2) that<br />

maximised the expected utility <strong>of</strong> terminal wealth, after using Monte Carlo simulation to generate the various<br />

scenarios, while Ben- Dov, Hayre and Pica (<strong>19</strong>92, used stochastic programming to form portfolios <strong>of</strong> MBS and<br />

other assets for clients that were expected to outperform some pre-specified target return. Pension funds hold<br />

portfolios <strong>of</strong> both assets and liabilities, making investments in shares, bonds, and other financial assets; to fund<br />

their obligations to existing and future pensioners. The problem <strong>of</strong> selecting an investment policy for a pension<br />

fund can be analysed using asset-liability management models that allow for the non-zero correlations between<br />

the values <strong>of</strong> the assets and liabilities (e.g. rapid inflation increases the value <strong>of</strong> both equities and the liabilities <strong>of</strong><br />

a pension scheme based on final salaries) which, if positive, reduce risk. While these problems may be<br />

formulated using quadratic programming, they have usually been solved in other ways (see Ziemba and Mulvey,<br />

<strong>19</strong>98). Mulvey (<strong>19</strong>94) assumed that the objective was to maximise the expected value <strong>of</strong> a non-linear utility <strong>of</strong><br />

wealth function, and specified the problem as a nonlinear network problem, with the simulation <strong>of</strong> future pension<br />

fund liabilities. Similar asset liability problems are also faced by insurance companies, for example Cariño et al<br />

(<strong>19</strong>94, <strong>19</strong>98a, <strong>19</strong>98b) formulated this problem for a Japanese insurance company. Their model maximises the<br />

expected market value <strong>of</strong> the company, with risk measured as the underachievement <strong>of</strong> the specified goals. The<br />

aim was to minimise the expected cost, subject to a chance constraint that the probability <strong>of</strong> the cost <strong>of</strong> the<br />

chosen hedging strategy does not exceed the cost <strong>of</strong> using the forward market alone. Clewlow, Hodges and<br />

Pascoa (<strong>19</strong>98) show how linear, goal and dynamic programming can be used to hedge options in the presence <strong>of</strong><br />

transactions costs. In some applications <strong>of</strong> portfolio theory, the decision variables must be integer. Some authors<br />

have argued that formulation and solving quadratic programming portfolio problems is too onerous, and<br />

proposed simplified solution techniques. Sharpe (<strong>19</strong>63) proposed a single index model which simplifies the<br />

variance-covariance matrix required by the Markowitz model by assuming that assets are related to each other<br />

only through their correlation with a single common factor. This simplification removes the need for large<br />

numbers <strong>of</strong> covariance terms in the objective function, enabling the use <strong>of</strong> special purpose quadratic<br />

programming algorithms. When each asset represents only a small proportion <strong>of</strong> the portfolio, Sharpe (<strong>19</strong>67)<br />

shows that his single index model can be treated as having a linear objective function. In essence, well<br />

diversified portfolios have only systematic risk, and this is measured by asset betas, which then gives a linear<br />

objective function. In <strong>19</strong>71, Sharpe suggested using a piecewise linear approximation to the quadratic objective<br />

function, enabling the application <strong>of</strong> linear programming to solve portfolio problems. Another proposal is to<br />

minimize the mean absolute deviation (MAD), which can be solved using linear programming, rather than<br />

quadratic programming. Konno and Yamazaki (<strong>19</strong>91 and <strong>19</strong>97) applied MAD to forming portfolios <strong>of</strong> Japanese<br />

equities and also equities and bonds. Worzel, Vassiadou- Zeniou and Zenios (<strong>19</strong>94) suggested using both<br />

simulation and linear programming for tracking fixed-interest indices. First, the holding period returns for the<br />

securities in the index are simulated; then linear programming, with risk measured by the MAD, is used to select<br />

a portfolio which maximises the expected return, subject to the risk <strong>of</strong> underperforming the index not exceeding<br />

some specified upper bound. This bound is then minimised by iteratively solving the linear programming<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

problem. Seix and Akhoury (<strong>19</strong>86) proposed using linear programming to devise a portfolio to track a bond<br />

index by maximising the value <strong>of</strong> the portfolio, while matching the duration, quality, sectors, and coupons <strong>of</strong> the<br />

bond index. Another approach to removing the need to solve a quadratic programming problem is to specify the<br />

problem as choosing between ranges <strong>of</strong> pre-specified equity portfolios using data envelopment analysis (DEA)<br />

(Premachandra, Powell and Shi, <strong>19</strong>98). In portfolio immunization the aim is to construct a portfolio <strong>of</strong> interest<br />

rate dependent securities whose value is the same as some target asset (usually another interest rate dependent<br />

asset). By matching the duration <strong>of</strong> the portfolio with that <strong>of</strong> the target asset, the portfolio is immunized against<br />

small parallel shifts in the yield curve. Fong and Vasicek (<strong>19</strong>83) proposed a measure <strong>of</strong> the risk from general<br />

interest rate movements (e.g. non-parallel shifts in the yield curve) and proposed devising a bond portfolio to<br />

minimise this, subject to achieving a specified duration, by linear programming. They also suggest that the<br />

investor could compute an efficient frontier <strong>of</strong> portfolios that minimise the standard deviation <strong>of</strong> the return on the<br />

immunized portfolio for a given level <strong>of</strong> expected return, again using linear programming. Using higher<br />

moments <strong>of</strong> a generalised duration measure, Kornbluth and Salkin (<strong>19</strong>87) show it is possible to immunise<br />

against changes in the shape <strong>of</strong> the yield curve, as well as parallel shifts, using linear fractional goal<br />

programming. Nawalkha and Chambers (<strong>19</strong>96) used a modified duration measure to quantify the risk <strong>of</strong> an<br />

immunized portfolio, and minimised this using linear programming. Alexander and Resnick (<strong>19</strong>85) who<br />

incorporated default risk also specified immunization as a linear goal programming problem. What all these<br />

immunization studies have in common is that the chosen risk measure does not involve squares or cross products<br />

<strong>of</strong> the decision variables, so that linear programming, not quadratic programming, is the solution technique.<br />

Portfolio theory (and quadratic programming) has also been applied to problems that do not directly involve<br />

traded financial assets.<br />

3. The Valuation <strong>of</strong> Financial Instruments<br />

It is very important when trading in financial markets to have a good model for valuing the asset being traded,<br />

and OR techniques have made a substantial contribution in this area.<br />

Although European style call and put options can be valued using the Black-Scholes model, which provides a<br />

good closed form solution, OR techniques have made a substantial contribution to the pricing <strong>of</strong> more complex<br />

derivatives. In <strong>19</strong>77, Boyle proposed the use <strong>of</strong> Monte Carlo simulation as an alternative to the binomial model<br />

for pricing options for which a closed form solution is not readily available. Monte Carlo simulation has the<br />

advantage over the binomial model that its convergence rate is independent <strong>of</strong> the number <strong>of</strong> state variables (e.g.<br />

the number <strong>of</strong> underlying asset prices and interest rates), while that <strong>of</strong> the binomial model is exponential in the<br />

number <strong>of</strong> state variables. Monte Carlo simulation is used to generate paths for the price <strong>of</strong> the underlying asset<br />

until maturity. The cash flows from the option for each path, weighted by their risk neutral probabilities, can then<br />

be discounted back to the present using the risk free rate, allowing the average present value across all the<br />

sample paths to be computed to give the current price <strong>of</strong> the option (Boyle, Broadie and Glasserman, <strong>19</strong>97). A<br />

range <strong>of</strong> variance reduction methods have been used in the Monte Carlo pricing <strong>of</strong> options (e.g. control variates,<br />

antithetic variates, stratified sampling, Latin hypercube sampling, importance sampling, moment matching and<br />

conditional Monte Carlo). In addition, quasi-Monte Carlo methods have been applied to finance problems to<br />

speed up the simulation (Joy, Boyle and Tan, <strong>19</strong>96). As well as generating option prices, Monte Carlo simulation<br />

can be used to compute the various sensitivities - “the Greeks” - including the hedge ratio, which are essential<br />

for many trading strategies (Broadie and Glasserman, <strong>19</strong>96). There are no closed form solutions for American<br />

style options, and until recently it was thought that Monte Carlo simulation could not be used to price such<br />

options. This is a major problem, as the majority <strong>of</strong> options are American style. However, progress is being<br />

made in developing Monte Carlo simulation techniques for pricing American style options (Broadie and<br />

Glasserman, <strong>19</strong>97; Grant, Vora and Weeks, <strong>19</strong>97). Options have also been priced using finite difference<br />

approximations, and Dempster and Hutton (<strong>19</strong>96) and Dempster, Hutton and Richards (<strong>19</strong>98) have proposed the<br />

use <strong>of</strong> linear programming to solve the finite difference approximations to the price <strong>of</strong> American style put<br />

options. In addition, American style options can be priced using dynamic programming, Dixit and Pindyck<br />

(<strong>19</strong>94). If a closed form pricing equation cannot be derived for an option or other derivative; provided a price<br />

history is available, a neural network can be trained to produce prices using a specified set <strong>of</strong> inputs, which can<br />

then be used for out-<strong>of</strong>-sample pricing (Hutchinson, Lo and Poggio, <strong>19</strong>94). This approach was able to<br />

outperform the Black-Scholes formula when pricing options on S&P500 futures, and has considerable potential<br />

for generating prices for “hard to price” derivatives that are already traded on competitive markets. Empirical<br />

research has found that, although the Black-Scholes pricing model provides accurate prices for at-the-money<br />

options, there are some unexpected patterns in options prices, such as the “volatility smile”12. Modelling this<br />

effect, and given a contemporaneous set <strong>of</strong> prices for European style put and call options on the same underlying<br />

asset, Rubinstein (<strong>19</strong>94) has shown how the implied risk neutral probability distribution can be computed using<br />

quadratic programming. This procedure selects a set <strong>of</strong> risk neutral probabilities that minimise the sum <strong>of</strong> the<br />

squared difference between themselves and the risk neutral probabilities generated by some prior guess. These<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

probabilities can be used to infer a recombining binomial tree that is consistent with the observed options prices,<br />

which is then used in hedging or valuing European style options on the underlying asset over the period until<br />

maturity in a way that allows for the presence <strong>of</strong> the “smile”. Jackwerth and Rubinstein (<strong>19</strong>96) generalised this<br />

approach using nonlinear programming to minimise four other objective functions. Municipal authorities in the<br />

USA who wish to borrow money by issuing bonds usually invite bids from underwriting syndicates. These bids<br />

must specify a schedule <strong>of</strong> bond coupons (i.e. interest payments), subject to various restrictions imposed by the<br />

municipality, and by the need for the underwriting syndicate to market the bonds to the public. The winning bid<br />

is generally that with the lowest net interest cost to the municipality. The underwriting syndicate typically have<br />

only 15 to 30 minutes to prepare a bid, and so a computerized solution procedure is needed. This decision was<br />

formulated as a linear programming problem by Percus and Quinto (<strong>19</strong>56) and Cohen and Hammer (<strong>19</strong>65,<br />

<strong>19</strong>66), while Weingartner (<strong>19</strong>72) respecified it as a dynamic programming problem. If the municipality places an<br />

upper bound on the number <strong>of</strong> different coupon rates, it becomes an integer programming problem that can also<br />

be solved as a zero-one dynamic programming problem (Weingartner, <strong>19</strong>72; Friemer, Rao and Weingartner,<br />

<strong>19</strong>72). Nauss and Keeler (<strong>19</strong>81) added the constraint that the coupon rates be set to integers times a specified<br />

multiplier, and proposed an integer programming formulation. The municipality can specify the true interest cost<br />

(which is the internal rate <strong>of</strong> return (IRR) on the bond), rather than the net interest cost, as the selection criterion<br />

to be used. The use <strong>of</strong> the IRR as the objective to be minimised makes the problem non-linear. Bierwag, <strong>19</strong>76,<br />

proposed a linear programming algorithm for solving this problem. Nauss, <strong>19</strong>86, added some additional<br />

restrictions which make the problem integer, and suggested an approximate solution using integer linear<br />

programming. Mortgage backed securities (MBS) are created by the securitisation <strong>of</strong> a pool <strong>of</strong> mortgages. For<br />

any specific mortgage, the borrower has the right to repay the loan early - the prepayment option, or may default<br />

on the payments <strong>of</strong> capital and interest. These risks feed through to the owners <strong>of</strong> MBS, in addition to the risks<br />

<strong>of</strong> fluctuations in the rate <strong>of</strong> interest payable on flexible rate mortgages (Zipkin, <strong>19</strong>93). Thus MBS are hybrid<br />

securities, as they are variable interest rate securities with an early exercise option. Monte Carlo simulation can<br />

be used to generate interest rate paths for future years. Forecasts <strong>of</strong> the mortgage prepayment rates then permit<br />

the computation <strong>of</strong> the cash flows from each interest rate path, and these sequences <strong>of</strong> cash flows are used to<br />

value the MBS (Zenios, <strong>19</strong>93a; Ben-Dov, Hayre and Pica, <strong>19</strong>92; Boyle, <strong>19</strong>89). This procedure, which can be<br />

used to identify mispriced MBS in real time, is computationally demanding and parallel (and massively parallel)<br />

and distributed processing have been used in the solution <strong>of</strong> the problem. Simulation has also been used to price<br />

collateralised mortgage obligations or CMOs13 (Paskov, <strong>19</strong>97). Other hybrid securities, such as callable and<br />

potable bonds and convertible bonds face similar valuation problems to MBSs and require similarly intensive<br />

solution methods. There is an active secondary market in loan portfolios which may carry a significant default<br />

risk. Del Angel el al (<strong>19</strong>98) used a Markov chain analysis with 14 loan performance states and Monte Carlo<br />

simulation to generate the probability distribution <strong>of</strong> the present value <strong>of</strong> loan portfolios.<br />

4. Imperfections in Financial Markets<br />

As well as accurately pricing financial securities, traders are interested in finding imperfections in financial<br />

markets which can be exploited to make pr<strong>of</strong>its (Keim and Ziemba, <strong>19</strong>99; Ziemba, <strong>19</strong>94). One aspect <strong>of</strong> this is<br />

the search for weak form inefficiency (i.e. that an asset’s past prices can be used as the basis <strong>of</strong> a pr<strong>of</strong>itable<br />

trading rule). Among the early attempts to find such exploitable regularities in stock prices were Dryden’s (<strong>19</strong>68,<br />

<strong>19</strong>69) use <strong>of</strong> Markov chains. A fundamental feature <strong>of</strong> financial markets is the existence <strong>of</strong> no-arbitrage<br />

relationships between prices and small price discrepancies can be exploited by arbitrage trades to give large<br />

riskless pr<strong>of</strong>its. Network models have been used to find arbitrage opportunities between sets <strong>of</strong> currencies. This<br />

problem can be specified as a maximal flow network, where the aim is to maximise the flow <strong>of</strong> funds out <strong>of</strong> the<br />

network, or as a shortest path network. While some network formulations are linear and could be formulated and<br />

solved as linear programming models, interpretation <strong>of</strong> the problem as a network enables the use <strong>of</strong><br />

computationally faster algorithms. Chandy and Kharabe (<strong>19</strong>86) developed a model for identifying under-priced<br />

bonds. They suggested solving a linear programming model to form a bond portfolio with maximum yield. This<br />

solution then gives the break even yield, which is the minimum bond yield necessary for inclusion in the<br />

portfolio. Hodges and Schaefer (<strong>19</strong>77) devised a linear programming model which minimises the cost <strong>of</strong> a given<br />

pattern <strong>of</strong> cash flows, enabling underpriced bonds to be traded. There has been a growing interest in using<br />

artificial intelligence based techniques (expert systems, neural networks, genetic algorithms, fuzzy logic and<br />

inductive learning) to develop trading strategies for financial markets. Such approaches have the advantage<br />

14that they can pick up non-linear dynamics, and require little prior specification <strong>of</strong> the relationships involved.<br />

Firer, Sandler and Ward, <strong>19</strong>92, simulated the returns from a stock market timing strategy for a range <strong>of</strong> levels <strong>of</strong><br />

forecasting skill, so quantifying the likely benefits from various levels <strong>of</strong> forecasting ability. Taylor (<strong>19</strong>89) used<br />

Monte Carlo simulation to generate a long time series <strong>of</strong> data for use in back-testing the performance <strong>of</strong> trading<br />

rules for a variety <strong>of</strong> financial assets.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5. Funding Decisions<br />

OR techniques have also been used to help firms to determine the most appropriate method by which to raise<br />

capital from the financial markets to finance their activities. Brick, Mellon, Surkis and Mohl (<strong>19</strong>83) put forward<br />

a chance constrained linear programming model to compute the values <strong>of</strong> the debt-equity ratio each period that<br />

maximize the value <strong>of</strong> the firm. Other studies have specified the choice between various types <strong>of</strong> funding as a<br />

linear goal programming problem. Ness (<strong>19</strong>72) used linear programming to find the least cost financing decision<br />

for an investment project by a multi-national company. Kornbluth and Vinso (<strong>19</strong>82) modelled the financing<br />

decision <strong>of</strong> a multi-national corporation as involving two goals - minimizing the overall cost <strong>of</strong> capital and<br />

achieving target debt/equity ratios in each country. A different approach to the debt problem is to assume that the<br />

firm has found its desired debt equity ratio, and is purely concerned with raising the requisite debt as cheaply as<br />

possible. In this case, debt can be treated like any other input to the productive process, and inventory models<br />

used to determine the optimal “reorder” times and quantities (Bierman, <strong>19</strong>66; Litzenberger and Rutenberg,<br />

<strong>19</strong>72). An additional aspect <strong>of</strong> the problem is that, bonds’ maturity must be chosen by the borrower to reflect the<br />

different current interest rates payable on alternative maturities, the uncertain costs <strong>of</strong> future borrowing and the<br />

marketability <strong>of</strong> alternative maturities. Crane, Knoop and Pettigrew (<strong>19</strong>77) formulated this as a linear<br />

programming problem to minimise costs, which they solved for three different interest rate scenarios. Firms,<br />

governmental organizations and others may choose to issue callable bonds in which the issuer has the option to<br />

repay the bond at a time <strong>of</strong> their choosing before the maturity date <strong>of</strong> the bond. The issuer must choose various<br />

parameters <strong>of</strong> the callable bond, and Consiglio and Zenios (<strong>19</strong>97a, <strong>19</strong>97b) have used nonlinear programming to<br />

design such securities in a way that is most beneficial to the issuer, while Holmer, Yang and Zenios (<strong>19</strong>98) used<br />

a simulated annealing algorithm. Firms which have issued callable debt must decide when to call (repay) the<br />

existing debt and refinance it with a new issue, presumably at a lower cost - the bond scheduling problem. This<br />

is a dynamic programming problem and has been modelled as such by Weingartner (<strong>19</strong>67). Baker and Van Der<br />

Weide extended this model to cover a multi-subsidiary company with debt requirements for each subsidiary.<br />

Dempster and Ireland developed a model which applies a range <strong>of</strong> OR techniques in a complementary fashion to<br />

the bond scheduling problem. The model begins by using stochastic linear programming to devise a multi-period<br />

plan for both issuing and calling bonds. The plan is refined using heuristics, possibly leading to multiple plans,<br />

and the probability distributions <strong>of</strong> these revised plans are derived using simulation. Finally, an expert system is<br />

used to help in deciding between alternative plans. An important question when appraising investment projects is<br />

determining the appropriate cost <strong>of</strong> capital, i.e. the price which must be paid in the financial markets to finance<br />

the project. Boquist and Moore proposed the use <strong>of</strong> linear goal programming to estimate the cost <strong>of</strong> capital for<br />

divisions by incorporating corporate prior beliefs concerning betas. Certificates <strong>of</strong> deposit (CDs) are issued by<br />

banks and indicate that a specified sum has been deposited at the issuing depository institution. As such, CDs<br />

represent a source <strong>of</strong> funding for banks. Russell and Hickle developed a simulation model to predict the impact<br />

<strong>of</strong> various interest rate scenarios on the cost <strong>of</strong> this funding source. Finally, the problem facing borrowers <strong>of</strong><br />

choosing between alternative mortgage contracts (e.g. fixed rate, variable rate and adjustable rate mortgages) has<br />

been modelled using decision trees.<br />

6. Strategic Problems<br />

In recent years, some <strong>of</strong> the decisions facing traders and market makers in financial markets have been analysed<br />

using game theory. These models typically involve one or more market makers, and traders who may be<br />

informed or uninformed, and discretionary or non-discretionary. Traders in stock markets seek to trade at the<br />

most attractive prices and large trades are <strong>of</strong>ten broken up into a sequence <strong>of</strong> smaller trades in an effort to<br />

minimise the price impact. This can be viewed as a strategic problem with the aim <strong>of</strong> devising a strategy for<br />

trading the block <strong>of</strong> shares. The initial trades influence the price <strong>of</strong> subsequent trades, and so executing the large<br />

trade at the lowest cost is a dynamic problem. Applied game theory to the situation where a company has two<br />

major shareholders, and a large number <strong>of</strong> very small shareholders. This can be modelled as an oceanic game, in<br />

which the two large players behave strategically while the many small shareholders (the ocean) do not. This<br />

approach can be used to derive the highest price a large shareholder will pay in the market for corporate control.<br />

7. Regulatory and Legal Problems<br />

Financial regulators have become increasingly concerned about financial markets with their very large and rapid<br />

international financial flows. OR techniques have proved useful in regulating the capital reserves held by banks<br />

and other financial institutions to cover their risk exposure. OR techniques have also been used to ensure<br />

compliance with various legal requirements by designing appropriate strategies and to solve other legal problems<br />

relating to financial markets. A key regulatory issue is determining the capital required by financial institutions<br />

to underpin their activities in financial markets. An increasingly popular approach to this problem is to quantify<br />

the value at risk (VAR). If the specified period and probability are 1 day and 1% respectively, then the VAR is<br />

927


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

the largest loss that will occur due to market risk 99% <strong>of</strong> the time. Thus, VAR involves quantification <strong>of</strong> the<br />

lower tail <strong>of</strong> the probability distribution <strong>of</strong> outcomes from the firm’s portfolio. Monte Carlo simulation can<br />

either make distributional assumptions, or use the distribution <strong>of</strong> historical realizations, i.e. bootstrapping.<br />

Usually there is no default, while occasionally there is a substantial or total default. Traders are required to put<br />

up margin when they trade options, and there are complicated rules for determining the total margin required on<br />

a portfolio <strong>of</strong> options and shares. Traders wish to minimise their margin payments, and Rudd and Schroeder<br />

have developed a linear programming model in which the problem was modelled as a transportation problem for<br />

determining the minimum required margin. Sharda (<strong>19</strong>87) proposed a linear programming formulation to<br />

establish the maximum loss that investors could have sustained from trading in a company’s shares. This figure<br />

can then be used by the company’s lawyers when fighting a lawsuit claiming damages from a misleading<br />

statement by the company. In August <strong>19</strong>82 the Kuwait Stock Market collapsed leaving $94 billion <strong>of</strong> debt to be<br />

resolved. This led to the problem <strong>of</strong> devising a fair method for distributing the assets seized from insolvent<br />

brokers among the other brokers and private investors. This problem was solved using linear programming,<br />

which reduced the total unresolved debt to $<strong>20</strong> billion, saving an estimated $10.34 billion in lawyer’s fees (Taha,<br />

<strong>19</strong>91, Elimam, Girgis and Kotob, <strong>19</strong>96, <strong>19</strong>97).<br />

8. Economic Understanding<br />

In addition to its traditional role <strong>of</strong> improving the quality <strong>of</strong> decision making, OR can also help in trying to<br />

understand the economic forces shaping the finance sector. Financial innovation may occur when there is an<br />

exogenous change in the constraints or in the costs <strong>of</strong> meeting existing constraints. Using a linear programming<br />

model <strong>of</strong> a bank, Ben-Horim and Silber employed annual data to compute movements in the shadow prices <strong>of</strong><br />

the various constraints. They suggested that a rise in the shadow price <strong>of</strong> the deposits constraint led to the<br />

financial innovation <strong>of</strong> negotiable CDs. Arbitrage Pricing Theory (APT), which can be viewed as a<br />

generalization <strong>of</strong> the Capital Asset Pricing Model (CAPM), seeks to identify the factors which affect asset<br />

returns. Most tests <strong>of</strong> the APT use factor analysis, and have difficulty in determining the number and definition<br />

<strong>of</strong> the factors that influence asset returns. To overcome these problems Ahmadi just suggested using a neural<br />

network to test the APT. This also has the advantage that the results are distribution free.<br />

9. Conclusions<br />

Mathematical programming is the OR technique that has been most widely applied in financial markets. Most<br />

types <strong>of</strong> mathematical programming have been employed - linear, quadratic, nonlinear, integer, goal, chance<br />

constrained, stochastic, and fractional, DEA and dynamic. Mathematical programming has been used to solve a<br />

considerable range <strong>of</strong> problems in financial markets - forming portfolios <strong>of</strong> equities, bonds, loans and currencies,<br />

generalized hedging, immunization, equity and bond index tracking, estimating the implied risk neutral<br />

probabilities for options, devising a schedule <strong>of</strong> coupons for municipal bond bids, identifying under-priced<br />

bonds, setting the firm’s debt-equity ratio, deciding when to refinance outstanding bonds, estimating the<br />

divisional cost <strong>of</strong> capital, determining the required minimum option margin, structuring MBS and CMO<br />

securitisations, creating a trading strategy to execute a block trade, designing leveraged leases, computing the<br />

maximum loss sustained by shareholders, spotting insolvent banks, sorting out the failure <strong>of</strong> a stock exchange<br />

and understanding the forces leading to financial innovations. Monte Carlo simulation is also widely used in<br />

financial markets - mainly to value exotic options and securities with embedded options, and to estimate the<br />

VAR for various financial institutions.<br />

Simulation has also been useful in testing trading rules, and for examining the risks <strong>of</strong> a position in securities. In<br />

some cases the use <strong>of</strong> OR techniques has influenced the way financial markets function since they permit traders<br />

to make better decisions in less time. For example, exotic options would trade with much wider bid-ask spreads,<br />

if they traded at all, in the absence <strong>of</strong> the accurate prices computed using Monte Carlo simulation.<br />

Other OR techniques are less used in financial markets. Arbitrage and multi-period portfolio problems have been<br />

formulated as network models, while market efficiency has been tested using neural networks. Game theory has<br />

been applied to battles for corporate control, decision trees to analyse mortgage choice, inventory models to set<br />

the size and timing <strong>of</strong> corporate bond issues, and Markov chains to valuing loan portfolios and testing market<br />

efficiency. One important OR technique has found little application in financial markets - queuing theory. The<br />

main areas <strong>of</strong> financial markets in which OR techniques have been applied are portfolio problems and pricing<br />

complex financial instruments accurately. OR techniques can also be used by financial regulators and financial<br />

institutions in setting capital adequacy standards. Some other application areas also exist - devising feasible<br />

solutions that meet a complicated set <strong>of</strong> the legal requirements, making funding decisions, spotting imperfections<br />

and arbitrage opportunities in financial markets and solving strategic problems.<br />

928


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The relationship between finance and OR is bidirectional. Not only have various OR techniques been applied to<br />

finance problems, but finance theories have created a need to develop and improve OR solution techniques, and<br />

at least two Nobel Prize winners in finance have made contributions to OR. Markowitz was honoured in <strong>19</strong>89 by<br />

ORSA/TIMS for his work on sparse matrices and inventing the computer simulation language SIMSCRIPT;<br />

while both he and Sharpe have produced computer algorithms for solving portfolio problems. This paper<br />

indicates that OR techniques play an important role in financial markets and, with the recent dramatic<br />

improvements in the real time availability <strong>of</strong> data and in computer speed, this role will increase. This will create<br />

the opportunity for OR techniques to play an even greater role in financial markets.<br />

References<br />

Ashford, R.W., Berry, R.H. and Dyson, R.G. (<strong>19</strong>88) Operational Research and Financial Management,<br />

European Journal <strong>of</strong> Operations Research, vol. 36, no. 2, pp. 143-152.<br />

Ben-Dov, Y., Hayre, L. and Pica, V. (<strong>19</strong>92) Mortgage Valuation Models at Prudential Securities, Interfaces, vol.<br />

22, no. 1, January-February, pp. 55-71.<br />

Ben-Horim, M. and Silber, W.L. (<strong>19</strong>77) Financial Innovation: A Linear Programming Approach, Journal <strong>of</strong><br />

Banking and Finance, vol. 1, no. 3, November, pp. 277-296.<br />

Sharpe, W.F. (<strong>19</strong>63) A Simplified Model for Portfolio Analysis, Management <strong>Science</strong>, vol. 9, no. 1, January, pp.<br />

277-293.<br />

Sharpe, W.F. (<strong>19</strong>67) A Linear Programming Algorithm for Mutual Fund Portfolio Selection, Management<br />

<strong>Science</strong>, vol. 13, no. 7, March, pp. 499-510.<br />

Sharpe, W.F. (<strong>19</strong>71) A Linear Programming Approximation for the General Portfolio Analysis Problem, Journal<br />

<strong>of</strong> Financial and Quantitative Analysis, vol. 6, no. 5, December, pp. 1263-1275.<br />

Worzel, K.J., Vassiadou-Zeniou, C. and Zenios, S.A. (<strong>19</strong>94) Integrated Simulation and Optimization Models for<br />

Tracking Indices <strong>of</strong> Fixed Income Securities, Management <strong>Science</strong>, vol. 42, no. 2, March-April, pp. 223-233.<br />

Weingartner, H.M. (<strong>19</strong>67) Optimal Timing <strong>of</strong> Bond Refunding, Management <strong>Science</strong>, vol. 13, no. 7, March, pp.<br />

511-524.<br />

Weingartner, H.M. (<strong>19</strong>72) Municipal Bond Coupon Schedules With Limitations on the Number <strong>of</strong> Coupons,<br />

Management <strong>Science</strong>, vol. <strong>19</strong>, no. 4, December, pp. 369-378.<br />

Wong, K. and Selvi, Y. (<strong>19</strong>98) Neural Network Applications in Finance: A Review and Analysis <strong>of</strong> Literature<br />

(<strong>19</strong>90-<strong>19</strong>96), Information and Management, vol. 34, no. 3, pp. 129-139.<br />

Vassiadou-Zeniou, C. and Zenios, S.A. (<strong>19</strong>96) Robust Optimization Models for Managing Callable Bond<br />

Portfolios, European Journal <strong>of</strong> Operational Research, vol. 91, pp. 264- 273.<br />

Yawitz, J.B., Hempel, G.H. and Marshall, W.J. (<strong>19</strong>76) A Risk-Return Approach to the Selection <strong>of</strong> Optimal<br />

Government Bond Portfolios, Financial Management, vol. 5, no. 3, Autumn,<br />

pp. 36-45.<br />

Zenios, S.A. (<strong>19</strong>91) Massively Parallel Computations for Financial Planning Under Uncertainty. In Very Large<br />

Scale Computation in the 21st Century, edited by Jill P. Mesirov, Society for Industrial and Applied<br />

Mathematics, Philadelphia, pp. 273-294.<br />

Zenios, S.A. (<strong>19</strong>93a) Parallel Monte Carlo Simulation <strong>of</strong> Mortgage Backed Securities. In Financial<br />

Optimization, edited by S.A. Zenios, Cambridge <strong>University</strong> Press., pp. 325- 343.<br />

Zenios, S.A. (<strong>19</strong>93b) A Model for Portfolio Management with Mortgage Backed Securities, Annals <strong>of</strong><br />

Operations Research, vol. 43, no. 1-4, pp. 337-356.<br />

Zenios, S.A., Holmer, M.R., McKendall, R. and Vassiadou-Zeniou, C. (<strong>19</strong>98) Dynamic Models for Fixed<br />

Income Portfolio Management Under Uncertainty, Journal <strong>of</strong> Economic Dynamics and Control, vol. 22. no. 10,<br />

September, pp. 1517-1541.<br />

Zenios, S.A. and Kang, P. (<strong>19</strong>93) Mean Absolute Deviation Portfolio Optimization for Mortgage Backed<br />

Securities, Annals <strong>of</strong> Operations Research, vol. 45, nos. 1-4, December, pp. 433- 450.<br />

Ziemba, W.T. (<strong>19</strong>94), World Wide Security Market Regularities, European Journal <strong>of</strong> Operational Research,<br />

vol. 74, no. 2, <strong>19</strong>8-229.<br />

Ziemba, W.T. and Mulvey, J.M. eds. (<strong>19</strong>98) Worldwide Asset and Liability Modelling, Cambridge <strong>University</strong><br />

Press.<br />

Taha, H.A. (<strong>19</strong>91) Operations Research Analysis <strong>of</strong> a Stock Market Problem, Computers and 30 Operations<br />

Research, vol. 18, no. 7, pp. 597-602.<br />

Taylor, S.J. (<strong>19</strong>89) Simulating Financial Prices, Journal <strong>of</strong> the Operational Research Society, vol. 40, no. 6,<br />

June, pp. 567-569.<br />

Trippi, R.R. and Turban, E. (editors) (<strong>19</strong>93) Neural Networks in Finance and Investing: Using Artificial<br />

Intelligence to Improve Real World Performance, Probus Publishing Co, Chicago.<br />

Zipkin, P. (<strong>19</strong>93) Mortgages and Markov Chains: A Simplified Evaluation Model, Management<strong>Science</strong>, vol. 39,<br />

no. 6, June, pp. 683-691.<br />

929


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

QUEST FOR ENVIRONMENTAL PROTECTION BY INTEGRATED<br />

GREEN MANUFACTURING SYSTEM<br />

Sandeep Handa 1 , Tilak Raj 2 , Sandeep Grover 2<br />

1 Research Scholar, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Sector-6, Mathura Road, Faridabad – 121<br />

006.<br />

2 Pr<strong>of</strong>essor, <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Sector-6, Mathura Road, Faridabad – 121 006.<br />

E-mail: handasandeep @yahoo.com<br />

Abstract<br />

In recent years there has been an appalling rate <strong>of</strong> depletion <strong>of</strong> natural resources due to an ever-increasing<br />

number <strong>of</strong> goods manufactured to satisfy human needs. There is intense pressure from government regulatory<br />

acts and consumers on the manufactures to become environmentally friendly. Green Manufacturing has emerged<br />

as a key approach for industries seeking to become environmentally friendly. This study reviewed various<br />

literatures to explore the interrelationships between environmental issues and manufacturing strategies. This<br />

paper identifies various issues involved in enhancing eco-efficiency <strong>of</strong> a manufacturing system<br />

Introduction<br />

The increase in consumption and production <strong>of</strong> goods using non-replenish able resources and environmentally<br />

detrimental manufacturing practices over the past few years has increased the scale <strong>of</strong> negative human impact on<br />

earth. Manufacturing industry provides mankind with goods to fulfill his various needs but at the same time it<br />

generates serious problems <strong>of</strong> the resources depletion and environmental degradation. Henriques and Sadorsky<br />

(<strong>19</strong>99) highlighted that manufacturers today are being subjected to intense scrutiny to mitigate environmental<br />

damage by diverse stakeholder groups like end-consumers, industrial customers, suppliers, financial institutions<br />

and government regulators The manufacturing activity needs to be carried in such a manner that is<br />

environmentally benign, energy conscious and economically viable<br />

As per Melnyk and Smith(<strong>19</strong>96) manufacturing managers have to adopt Green Manufacturing strategies to limit<br />

the adverse impact <strong>of</strong> their operations and products on the natural environment. They defined green<br />

manufacturing as a system that integrates product and process design issues with issues <strong>of</strong> manufacturing<br />

planning and control in such a manner as to identify, quantify, assess, and manage the flow <strong>of</strong> environmental<br />

waste with the goal <strong>of</strong> reducing and ultimately minimizing environmental impact while also trying to maximize<br />

resource efficiency. Green manufacturing encourages the utilization <strong>of</strong> resources which have relatively lower<br />

environmental impacts then the existing ones. It focuses on elimination or minimizesing waste in the form <strong>of</strong><br />

energy, emission, hazardous chemical and solid waste. Green manufacturing includes source reduction, recycling<br />

and green product design. Cairncross et. al (<strong>19</strong>92)emphasizes the importance <strong>of</strong> having a corporate<br />

environmental policy. These environmental policies and strategies must reflect sound environmental goals.<br />

These environmental goals and targets should be both clear and measurable. The formation <strong>of</strong> an environmental<br />

policy is usually one <strong>of</strong> the first, if not the first, steps in developing an environment management system. It<br />

establishes an overall sense <strong>of</strong> direction and sets the guidelines for environmental actions by the organization in<br />

place.<br />

Facets <strong>of</strong> a Green Manufacturing System<br />

2.1 Process Design<br />

Green process design is a process for assessing and evaluating the environmental, occupational health and<br />

resource consequences <strong>of</strong> a product through all phases <strong>of</strong> its life, i.e. extracting and processing raw materials,<br />

production, transportation and distribution, use, remanufacturing, recycling and final disposal Alting L(<strong>19</strong>93)<br />

Green process design is an optimization problem by maximizing the added value and minimizing the resource<br />

consumption and waste dispersion activities at different stages <strong>of</strong> manufacturing. Life cycle analysis (LCA)<br />

involves a detailed study <strong>of</strong> the different environmental parameters at different stages <strong>of</strong> the product<br />

There are various variants <strong>of</strong> LCA which are used by different designers. Cradle-to–gate approach is partial<br />

assessment method which only takes into account the environmental impact <strong>of</strong> manufacturing within the factory<br />

gate. Cradle–to–Cradle is a biometric approach to the design <strong>of</strong> system which analysis environmental impact<br />

right from inception to final disposal <strong>of</strong> product. Due to the rising cost <strong>of</strong> energy Life Cycle Energy Analysis<br />

approach based on total life cycle energy consumption <strong>of</strong> a product is also being favored by manufactures.<br />

930


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2.2 Product Design<br />

Researchers have analyzed different facets <strong>of</strong> manufacturing a product and developed techniques for formulating<br />

the design <strong>of</strong> the product from an environmental perspective. Dornfeld, D., Lee, D. E.(<strong>20</strong>07) highlighted Designlevel<br />

changes provide the greatest flexibility and therefore the greatest opportunities for energy savings thus help<br />

in green manufacturing. These techniques are referred as the design for environment (DFE) as per Fiksel J<br />

(<strong>19</strong>96). DFE can be broken down into many stages which deal with different aspects resources consumption due<br />

to product design. Hesselbash (<strong>19</strong>98) highlights use <strong>of</strong> design for energy conservation approach to reduce the<br />

energy consumption. To mitigate the problems waste management Henshaw J. W. (<strong>19</strong>94) advocates the use <strong>of</strong><br />

designing for minimizing the discharge <strong>of</strong> hazardous byproducts approach. Design for recycling approach is<br />

favored by Issacs J A (<strong>19</strong>96) for reducing the consumption <strong>of</strong> scant natural resources by encouraging the use <strong>of</strong><br />

recycled material.<br />

2.3 Lean and Green Manufacturing practices<br />

Many leading companies have implemented Lean Manufacturing Programs which yield increased efficiency,<br />

reduced costs, improved customer response time, and more. Others have adopted “Green” Programs resulting in<br />

reduced energy consumption, waste generation, and hazardous materials usage. Gary G. Bergmiller, et. al.<br />

(<strong>20</strong>09) highlights that models for both Lean and Green manufacturing include management systems, waste<br />

identification, and implementation <strong>of</strong> waste reducing techniques (WRT) to achieve desired business results.<br />

Studying known Lean companies, it is confirmed that strength <strong>of</strong> management system correlates with WRT<br />

implementation which correlates with business results for both Lean and Green Programs. Ge<strong>of</strong>f Miller et.<br />

al.(<strong>20</strong>10) recommended that integrated lean tools and sustainability concepts aid in the elimination <strong>of</strong> waste have<br />

helped the company meet ever increasing customer demands while preserving valuable resources for future<br />

generations.<br />

2.4. Green Supply Chain Management<br />

As per Handfield R (<strong>20</strong>05) Green supply chain management(GSCM) is designed to incorporate environmental<br />

considerations into decision making at each stage <strong>of</strong> an organization’s materials management and logistics<br />

functions until post-consumer disposal . Vachon S (<strong>20</strong>07) highlights the tangle linkages between green supply<br />

chain practices such as environmental collaboration with suppliers, environmental monitoring upon suppliers,<br />

environmental collaboration with customers, environmental monitoring by customers and the selection <strong>of</strong><br />

environmental technologies . GSCM impact on relationship conditions existing between a customer and its<br />

suppliers were highlighted by Simpson D (<strong>20</strong>07).<br />

2.5 Consumers pull for greener products and Environmental Marketing<br />

Green manufacturing is imperative, not just due to tightening regulations or cost benefits, but also because<br />

consumers are demanding it. Not only are consumers becoming increasingly aware and conversant with green,<br />

they are also adopting Green habits and buying Green products. The continuing expansion <strong>of</strong> green<br />

consciousness around the world presents a huge opportunity for smart companies. Consumers greatly value the<br />

direct benefits that Green products <strong>of</strong>fer, such as – superior freshness and taste, the promise <strong>of</strong> safety and health,<br />

and savings on energy costs. They are willing to pay higher prices for Green products that have better quality<br />

perception.<br />

Companies efforts at designing, promoting, pricing and distributing products that do not harm the environment<br />

constitutes environmental marketing .As per Fuller (<strong>19</strong>99) companies reorient customers choices towards<br />

choices which are environmentally compatible, reorient the marketing mix to include such choices, reorganize<br />

the company delivery system to enable them to meet challenges. Newman and Hanna (<strong>19</strong>96) highlighted that<br />

companies that proactively incorporate environmental goals into their business practices and strategic plans<br />

enjoy a competitive advantage .Ryan<strong>20</strong>04 recommends manufactures to follow an eco-efficiency strategy with<br />

the aim <strong>of</strong> reducing costs and environmental impact. Nash et al(<strong>19</strong>97) highlights that by following “beyond<br />

leadership compliance “marketing strategy the companies gain the first mover advantage in their field. Reinhardt<br />

(<strong>19</strong>99) highlights the need for companies to go for eco-branding so as to create a credible green band around<br />

their products. As per Orsato (<strong>20</strong>06) a manufactures products acquire a price premium if fallows environmental<br />

marketing.strategry.<br />

931


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2.7 Eco-innovation<br />

Chen <strong>20</strong>08 highlights proportionally relationship between manufacturing practices and green innovation .Green<br />

innovation in production requires manufacturers to take actions for planning and managing the work regarding<br />

the minimization <strong>of</strong> environmental impacts related to the innovation function. Green innovation as a way <strong>of</strong><br />

innovation is mainly focused on improving the efficiency <strong>of</strong> resources usage and protecting the environment.<br />

Eco-innovation and its environmental benefits go beyond the conventional organizational boundaries.. Dechant<br />

and Altman (<strong>19</strong>94) identified the best practices <strong>of</strong> firms that were successful at managing environmental issues<br />

and identified common practices. The authors emphasize that in order to manage change better, it is necessary to<br />

conduct assessments <strong>of</strong> environmental projects, manage human resources; ensure that employees share the<br />

common vision and are empowered to act on it. They suggest that adequate training will also be needed for<br />

employees to avoid costly environmental mistakes and to increase environmental awareness.<br />

Green Manufacturing and Management in Electronics Industry –a case study<br />

The issues pertaining to Green Manufacturing activities can be best illustrated with the help <strong>of</strong> a practical case<br />

study <strong>of</strong> the <strong>of</strong> computer manufacture which may be taken as a representative electronic industry. The issues<br />

encompass the entire gamut <strong>of</strong> green initiatives. The company has to deal with various environmental issues <strong>of</strong><br />

products. Each electronic item manufactured is a TOXIC Trap. Workers working in chip making facilities are<br />

likely to be exposed to toxic chemicals that may lead to cancer, miscarriage, birth defects etc. Many<br />

manufacturing sites <strong>of</strong> chips generate hazardous wastes and contaminate ground water. EOL PCs contribute to<br />

the mounting “electronics” waste containing phosphor, barium, Chromium, Beryllium etc. The company needs<br />

to use DFE technique for designing green products. Design <strong>of</strong> products is made to be a function <strong>of</strong> the<br />

parameters such as resource consumption <strong>of</strong> raw material, electricity etc. Reduction/elimination <strong>of</strong> hazardous<br />

substances (Cd, Pb, PBBE etc), Recyclability etc are also taken into account. Purchasing is made in a manner<br />

which leads to compliance <strong>of</strong> environment laws and supplier audits are made on a regular basis. The company<br />

focuses on areas like Energy Consumption, Water Consumption, Waste Reduction, and Emission Reduction to<br />

reduce environmental impact. It under takes GSCM initiatives for complaining with environmental aspects in<br />

transportation and optimization <strong>of</strong> logistics End <strong>of</strong> Life Product Disposal <strong>of</strong> E-Waste, Recycling, Repair, Reuse,<br />

Remanufacture, Incineration, Land-fill reduction etc are focal areas for the company as per its green<br />

manufacturing strategies.<br />

Conclusion<br />

The paper highlights various issues which influence the achievement <strong>of</strong> an environmentally efficient<br />

manufacturing. Green manufacturing being a new paradigm in manufacturing requires changes in the processes,<br />

products and practices Green manufacturing covers all phases <strong>of</strong> product’s life cycle from design, production<br />

and distribution phases to the use <strong>of</strong> products by the end users and its disposal at the end <strong>of</strong> product’s life cycle.<br />

Green process design is an optimization problem by maximizing the added value and minimizing the resource<br />

consumption and waste dispersion activities at different stages <strong>of</strong> manufacturing. With the use different design<br />

for environment principles the problems <strong>of</strong> environmental impact are addressed at the design stage and products<br />

are designed to be environmentally benign. Model for both Lean and Green manufacturing management systems<br />

highlights waste identification, and implementation <strong>of</strong> waste reducing techniques to achieve desired business<br />

results. Environmental considerations must be taken into account in decision making at every stage <strong>of</strong> an<br />

organization’s materials management and logistics functions. Manufactures that incorporate environmental goals<br />

into their business marketing practices and strategic plans have a competitive advantage. Innovations <strong>of</strong> green<br />

methods coupled with consumers pull for green products are necessitating a move towards green manufacturing.<br />

The paper highlight successful implementation <strong>of</strong> Green manufacturing requires going beyond small standalone<br />

initiatives, and adopting an integrated approach for achieving better eco-efficiency<br />

References<br />

1) Henriques, I., Sadorsky, P., <strong>19</strong>99. The relationship between environmental commitment and managerial<br />

perceptions <strong>of</strong> stakeholder importance. Academy <strong>of</strong> Management Journal 42(1), 87–99.<br />

2) Melnyk S A and Smith R T., <strong>19</strong>96, “Green Manufacturing” ,SME Publication<br />

3) Cairncross, F., (<strong>19</strong>92), “How Europe’s companies reposition to recycle.” Harvard Business Review, pp. 34-<br />

45.<br />

4) Alting L, Jùrgensen J. The life cycle concept as a basis for sustainable industrial production. Annals <strong>of</strong> the<br />

CIRP <strong>19</strong>93;42(1):163±7.<br />

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Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

5) Fiksel J. Design for environment: creating eco-efficient products and processes. McGraw-Hill, <strong>19</strong>96.<br />

6) Henshaw JM. Design for recycling: new paradigm or just the latest `design-for-X'fad International Journal<br />

<strong>of</strong> Materials and Product <strong>Technology</strong> <strong>19</strong>94;9:125±38.<br />

7) Hesselbach J, KuÈ hn M. Disassembly assessment and planning for electronic consumer appliances. In:<br />

Proceedings <strong>of</strong> the First International Working Seminar on Reuse, Eindhoven, The Netherlands, 11±13<br />

Nov.<strong>19</strong>96, <strong>19</strong>96. p. 136±69.<br />

8) Isaacs JA, Gupta SM, Messac A. A decision tool to assess the impact <strong>of</strong> automobile design on disposal<br />

strategies. Proceedings <strong>of</strong> the Environmentally Conscious Manufacturing and Design Conference,<br />

Cleveland,OH, 23±25 July <strong>19</strong>96, <strong>19</strong>96. p. <strong>20</strong>7±14.<br />

9) Gary G. Bergmiller, “Parallel Models for Lean and Green Operations” Proceedings <strong>of</strong> the <strong>20</strong>09 Industrial<br />

Engineering Research Conference<br />

10) Ge<strong>of</strong>f Miller, Janice Pawloski, Charles Standridge, “A case study <strong>of</strong> lean, sustainable manufacturing”,<br />

Journal <strong>of</strong> Industrial Engineering and Management, <strong>20</strong>10, Vol: 3 Issue: 1 Pages/record No. 11-32<br />

11) Handfield R, Sroufe R, Walton S” Integrating environmental management and supply chain strategies.”<br />

Business Strategy and the Environment <strong>20</strong>05;14(1):1–<strong>19</strong>.<br />

12) S. Vachon, “Green supply chain practices and the selection <strong>of</strong> environmental technologies,” International<br />

Journal <strong>of</strong> Production Research, <strong>20</strong>07.<br />

13) D. Simpson, D. Power, and D. Samson, “Greening the automotive supply chain: a relationship<br />

perspective,” International Journal <strong>of</strong> Operations and Production Management, <strong>20</strong>07.<br />

14) Fuller D.A.(<strong>19</strong>99) “Sustainable Marketing :Managerial ecological issues”Thousand Oaks CA : Sage<br />

Publications<br />

15) Ryan C “Eco-efficiency and Industrial ecology “Journal <strong>of</strong> Industrial Ecology <strong>20</strong>05 pp 4-9<br />

16) Reinhardt F. l.. Environmental product Differsation :Implication for Corporate Strategy California<br />

Management Review <strong>19</strong>98 pp 43-73<br />

17) Orsato R (<strong>20</strong>06) Completive Environmental strategy When Does it pay to be green California Management<br />

Review pp123- 43<br />

18) Dechant, K. and Altman, B., (<strong>19</strong>94), “Environmental leadership; from compliance to competitive<br />

advantage.” Academy <strong>of</strong> Management Executive, Vol. 8, No.3, pp.1-14.<br />

933


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

A REVIEW ON JIT IMPLEMENTATION ASPECTS IN SERVICE<br />

SECTOR<br />

Sandeep Phogat 1 , Dr. A. K. Gupta 2<br />

1 Research Scholar, Department <strong>of</strong> Mechanical Engineering, DCRUST Murthal, Sonepat, Haryana.<br />

2 Associate Pr<strong>of</strong>essor, Department <strong>of</strong> Mechanical Engineering, DCRUST Murthal, Sonepat, Haryana.<br />

E-mail: sandeepphogat1@gmail.com<br />

Abstract<br />

Just in-time (JIT) the formalized process <strong>of</strong> waste reduction, has achieved a strong foothold in the manufacturing<br />

sector. The service sector, however, has not been as quick to recognize the benefits <strong>of</strong> JIT. Services are much like<br />

manufacturing in that both employ processes that add value to the basic inputs used to create the end product.<br />

JIT focuses on the process, not the product. It can, therefore, be applied to any process within manufacturing or<br />

service operations. Cost, quality, patient satisfaction etc. are some important issues facing service sector.<br />

Service sector are searching continuously for innovative ways to contain costs without sacrificing quality and<br />

meet the customer needs. This paper provides a review for applying JIT processes in the service sector, with the<br />

goal <strong>of</strong> investigating how JIT principles can be implemented in services.<br />

Keywords – Just-in-Time (JIT), kanban, quality, cost, service sector.<br />

1.0 INTRODUCTION<br />

Why Just-In-Time manufacturing when there are dozens <strong>of</strong> other manufacturing philosophies from which a<br />

company may choose Just-In-Time (JIT) manufacturing distances itself from the competition because no large<br />

capital outlays are required. Other methods promote complexity, large overheads, automation, and other "state<strong>of</strong>-the-art"<br />

technologies, while JIT advocates simplifying and streamlining the existing manufacturing process.<br />

Since World War II, traditional American companies have developed a way <strong>of</strong> doing business that entails top<br />

management planning, re-planning, and more planning. Although some planning is good, it ultimately adds no<br />

value to the end product. Customers want quality products at competitive prices - they couldn't care less how<br />

much planning was required to get that product to them. By implementing JIT, much <strong>of</strong> the planning disappears<br />

and a large portion <strong>of</strong> the remaining planning is entrusted to the shop floor personnel.<br />

The JIT process has been primarily applied to the manufacturing industry. Its obvious and measurable<br />

applications for manufacturing make it relatively easy to employ in a manufacturing environment. A more<br />

elusive area for application <strong>of</strong> JIT is the service industry. Yet, the US economy is experiencing a rapidly growing<br />

service base. It is estimated that the percentage <strong>of</strong> personal consumption expenditures for services is near 50<br />

percent. Increased growth and competition in the services industry will mandate that businesses work toward<br />

some applications <strong>of</strong> JIT principles. When JIT is used in the context <strong>of</strong> services, the focus is <strong>of</strong>ten on the time to<br />

deliver the service. Examples <strong>of</strong> fast delivery are Domino's Pizza, Federal Express and Express Mail, fast-food<br />

restaurants, and emergency services through 911 (Stevenson, <strong>19</strong>99). Service environments with repetitive<br />

operations, with high volumes, and with tangible items such as mail, checks or bills are expected to benefit more<br />

from application <strong>of</strong> JIT principles (Krajewski and Ritzman,<strong>19</strong>99).Services are much like manufacturing, in that<br />

both employ processes that add value to the basic inputs used to create the final product. JIT focuses on the<br />

process, not the product. It can therefore, be applied to any group <strong>of</strong> processes, whether manufacturing or<br />

service. The philosophy behind JIT is to continuously seek ways to make processes more efficient. The ultimate<br />

goal <strong>of</strong> JIT is to produce a good or a service without waste. This goal is approached by testing each step in a<br />

process to determine if it adds value to the product or to the service. If the step does not add value, then, it is<br />

examined closely to determine possible alternatives. In this way, each process gradually and continually<br />

improves. Thus, one <strong>of</strong> the key requirements <strong>of</strong> JIT is the constant and continual testing <strong>of</strong> processes, whether<br />

they are in manufacturing or in services. The purpose <strong>of</strong> this paper is to provide a framework for the integration<br />

and application <strong>of</strong> JIT principles in the service sector.<br />

1.1 JIT in Manufacturing<br />

Owing to its relatively small geographical area, Japan was forced to find ways to efficiently use its scarce<br />

resources. The Japanese have turned these disadvantages into advantages by successfully developing and<br />

implementing JIT production systems. They view the manufacturing process as a network <strong>of</strong> linked work centers<br />

934


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

where the optimal arrangement enables each worker to finish his or her task and deliver it to the next worker<br />

exactly when it is needed. The ultimate goal is to completely eliminate all waiting time so that inventory<br />

investment can be minimized, production lead times can be shortened, demand changes can be quickly<br />

addressed, and quality problems can be uncovered, and solved. JIT can be seen as a new way <strong>of</strong> thinking,<br />

planning, and performing with respect to manufacturing. JIT is simplicity, efficiency, and minimum waste<br />

(Hernandez, <strong>19</strong>89). The basic principle <strong>of</strong> JIT is to eliminate all forms <strong>of</strong> waste, defined as anything that does not<br />

add value to the product (Burnham, <strong>19</strong>87). The first step is to identify activities that are waste-producing. The<br />

major areas for different forms <strong>of</strong> waste that may be present in many departments are (Hernandez, <strong>19</strong>89;<br />

Stonebraker and Leong, <strong>19</strong>94):<br />

1. Waste in the production line.<br />

2. Waste in the materials department.<br />

3. Waste involving suppliers.<br />

4. Waste in design engineering.<br />

5. Waste from waiting.<br />

6. Waste from transportation.<br />

7. Waste from defective parts.<br />

JIT also emphasizes simplifying the manufacturing process in order to quickly detect problems and force<br />

immediate solutions (Fitzsimmons and Fitzsimmons, <strong>19</strong>94; Hernandez, <strong>19</strong>89). Several researchers recognize JIT<br />

as a system-wide approach to manufacturing which focuses on the timely delivery <strong>of</strong> quality products sought by<br />

the customer and the elimination <strong>of</strong> waste (Burnham, <strong>19</strong>87; Byard, <strong>19</strong>87; Chase et al.<strong>19</strong>98; Hernandez, <strong>19</strong>89;<br />

Krajewski and Ritzman, <strong>19</strong>99; Lee, <strong>19</strong>90; Schniederjans, <strong>19</strong>93). The implementation <strong>of</strong> a JIT system yields<br />

minimum inventories by having each part delivered when it is needed, where it is needed, and in the quantity<br />

needed to produce the product. A JIT system enables companies to operate efficiently with the least amount <strong>of</strong><br />

resources, and thus, improves quality, reduces inventory levels, and provides maximum motivation to solve<br />

problems as soon as they occur (Hernandez, <strong>19</strong>89; Krajewski and Ritzman, <strong>19</strong>99; Lee, <strong>19</strong>90; Schniederjans,<br />

<strong>19</strong>93). In summary, the objective <strong>of</strong> JIT can be simply stated as “produce the right item, at the right time, in the<br />

right quantities”. By achieving this objective, companies work toward the elimination <strong>of</strong> waste in their<br />

manufacturing processes and realize the following benefits (Chase et al., <strong>19</strong>98; Hernandez, <strong>19</strong>89):<br />

1. Lower raw material, work-in-process, and finished goods inventories.<br />

2. Higher levels <strong>of</strong> product quality.<br />

3. Increased flexibility and ability to meet customer demands.<br />

4. Lower overall manufacturing costs.<br />

5. Increased employee involvement.<br />

JIT principles, if successfully applied in the service sector, should yield similar benefits to those found in<br />

manufacturing. JIT has been applied successfully to job shops, which typically produce a wide variety <strong>of</strong> custom<br />

products in varying amounts (Billesbach and Schniederjans, <strong>19</strong>89). If the principles <strong>of</strong> JIT can be utilized<br />

successfully in these diverse environments, it seems reasonable to conclude that these principles can be applied<br />

to non-manufacturing activities that are repetitive in nature (Krajewski and Ritzman, <strong>19</strong>99).<br />

2.0 Examples <strong>of</strong> JIT applications in the Service Sector:<br />

Ronald G. Conant [<strong>19</strong>88] implemented JIT successfully in a mail order operation and increased the productivity<br />

and lead time by reducing the processing time up to large extent. Thomas J. Billesbach [<strong>19</strong>89] applied JIT<br />

successfully in administration and finds finally organizations that adopts the JIT philosophy in the administrative<br />

area continually increase productivity year after year. Ricardo Hitec [<strong>19</strong>94] utilized analytically JIT process on<br />

Air craft catering and improves the quality <strong>of</strong> the service <strong>of</strong>fered to the customers. Leslie K. Duclos et al. [<strong>19</strong>95]<br />

maintains that although service industries would benefited from research concerning the implementation <strong>of</strong> JIT<br />

techniques. Ajay Das et al. [<strong>19</strong>97] summarized JIT practices derive the benefit <strong>of</strong> more frequent deliveries and<br />

lower on hand Inventory level as compared to non – JIT global sourcing firms.<br />

Brian Wood [<strong>19</strong>99] discussed perceptions <strong>of</strong> building maintenance and care. Contrasts the “received wisdom” <strong>of</strong><br />

planned preventive maintenance with the concept <strong>of</strong> “Just-in-time maintenance”. Identifies possible locations <strong>of</strong><br />

“intelligence” in people and buildings. Also examines the relationship between technology and users, particularly<br />

regarding user satisfaction. Considered the penetration <strong>of</strong> the maintenance/care market by non-traditional players<br />

935


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

and describes features <strong>of</strong> “Call-centered maintenance”. Identifies the opportunity within the Private Finance<br />

Initiative for total building care services.<br />

Cem Canel et al. [<strong>20</strong>00] provided JIT focuses on the process, not the product. It can, therefore, be applied to any<br />

process within manufacturing or service operations. They provided a framework for applying JIT to processes in<br />

the service sector, with the goal <strong>of</strong> investigating how JIT principles can be implemented in services. Low Sui<br />

Pheng et al. [<strong>20</strong>01] promoted the JIT philosophy for managing precast concrete components and examines the<br />

readiness <strong>of</strong> precasters in Singapore to adopt the JIT Philosophy in producing and delivering precast concrete<br />

components to contractor clients.<br />

Journal <strong>of</strong> Operations Management Editorial [<strong>20</strong>02] told about the evidence that a well designed service system<br />

is a representation <strong>of</strong> the Quality <strong>of</strong> Life in many societies and also encouraged manuscripts on services.<br />

Christine M. Wright et al. [<strong>20</strong>02] specified clearly a lack <strong>of</strong> investigation <strong>of</strong> operations problem that are<br />

important to Service Organizations and gives the empirical results to overcome from these problems.<br />

Vikas Kumar et al. [<strong>20</strong>04] supported the notion that JIT has the potential to increase the operational efficiency,<br />

quality and organizational effectiveness <strong>of</strong> Indian Industries, to gain the benefit <strong>of</strong> JIT, Indian Industries must be<br />

willing to modify their procedures and operations. W. K. Wong et al. [<strong>20</strong>06] demonstrated that the genetically<br />

optimized JIT schedules simultaneously improve the internal satisfaction <strong>of</strong> downstream operation departments<br />

and reduce production cost in fabric cutting process in Apparel Manufacturing. Marc H. Meyer et al. [<strong>20</strong>07]<br />

provided results <strong>of</strong> a case study that examined the application <strong>of</strong> platform design to improve the integration <strong>of</strong><br />

Patient care Services across the continuum <strong>of</strong> care.<br />

Daniel I. Prajogo [<strong>20</strong>08] studied the relationships between selected operations strategies and the associated<br />

operations activities. Specifically, for service firms targeting specific competitive priorities, it examines the<br />

extent to which there are significant differences in the relationships between these priorities and the operations<br />

activities among high- versus low-performing firms. They showed that high-performing firms have stronger<br />

relationships between their operations strategies and operations activities than low-performing firms. The results<br />

also reveal how different operations strategies need to be deployed into different operations activities.<br />

Vikas Kumar [<strong>20</strong>10] suggested that the product quality is very important for long-term survival <strong>of</strong> a company.<br />

Therefore, the question <strong>of</strong> how much quality is enough seems relevant. During the late <strong>19</strong>70s and early <strong>19</strong>80s,<br />

the common answer <strong>of</strong> this question in western countries was to accept a small but allowable amount <strong>of</strong> poor<br />

quality in outgoing manufactured goods. The Japanese during same time chose a different course <strong>of</strong> action called<br />

“Just-in-Time (JIT) Based Quality Management”. Under this approach, product perfection is goal and poor<br />

quality <strong>of</strong> any kind is not acceptable.<br />

Low Sui Pheng et al. [<strong>20</strong>11] studied that the current case management system <strong>of</strong> the provider, as structured, was<br />

not fulfilling its potential for achieving medical quality, operational cost, or patient satisfaction. A number <strong>of</strong><br />

areas where improvements could be made were identified, and an integrated case management approach based<br />

on modular platform design was recommended as a key approach to realize such improvements. This study<br />

involves only one major provider and therefore the direct application <strong>of</strong> an integrated case management approach<br />

based on platform design to other providers would have to be further researched. However, the proposed<br />

integrated, cross-continuum model <strong>of</strong> case management appears to be a novel way to both improve care and<br />

achieve financial cost efficiencies.<br />

Mattias Elg et al. [<strong>20</strong>12] did the analytical study to develop a model for patient co-creation and learning based on<br />

diaries for use in health care service development in Sweden Health Service Industry. The study suggested a<br />

model for co-creation and learning in health-care service development through three learning methods. First, the<br />

model may be used as a means for generating and collecting patient ideas; second, a single patient’s story can be<br />

illustrated and can serve as incentive for health-care service development and creation <strong>of</strong> patient-centered care;<br />

finally, a larger number <strong>of</strong> diaries can be analyzed and combined with patient surveys to provide a deeper<br />

understanding <strong>of</strong> how the patient experiences health care services.<br />

3.0 Differences between Services and Manufacturing:<br />

Any discussion <strong>of</strong> service systems must look at how they differ from manufacturing systems. A review <strong>of</strong><br />

the specific characteristics <strong>of</strong> services and the implications for operations managers follows (Rosen, <strong>19</strong>90).<br />

1. Inseparability <strong>of</strong> production and consumption<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2. Intangibility:<br />

3. Perishability.<br />

4. Heterogeneity.<br />

It is readily apparent from the above discussion that there are many potential differences between<br />

manufacturing and service operations. Until recently, services have been sheltered from competition and<br />

have had little incentive to drive out efficiency. Shielded by regulation and confronted by few foreign<br />

competitors, service companies have allowed their white-collar payrolls to become bloated, their<br />

investments in information technology to outstrip the paybacks, and their productivity to stagnate.<br />

Deregulation and foreign direct investment are introducing new players that are challenging the practices<br />

and philosophies <strong>of</strong> individual companies, whole industries, indeed the entire US service sector. Service<br />

companies should not make the same mistakes as their manufacturing counterparts did: cutting costs at the<br />

expense <strong>of</strong> securing enduring competitive strength. Overzealous cost-cutting may make the companies<br />

more efficient over the short run but unable to motivate, respond to customers, or provide quality services<br />

over the long run.<br />

4.0 JIT issues in Service Industries:<br />

Service system design is similar to that <strong>of</strong> manufacturing, which indicates that service industries could<br />

benefit from the application <strong>of</strong> materials requirements planning (MRP) and other inventory control<br />

techniques in the same way as have manufacturing operations (Khumawala et al., <strong>19</strong>86; Wasco et al.,<br />

<strong>19</strong>91). The majority <strong>of</strong> JIT research and case studies focus on the manufacturing sector and the technical<br />

elements <strong>of</strong> JIT, and thus, generally exclude the service sector. Manufacturing and service organizations<br />

both produce a product, whether that product is a good or a service. The JIT concepts and techniques are<br />

equally applicable to both manufacturing and service operations because they are process rather than<br />

product oriented.<br />

The main themes <strong>of</strong> JIT consist <strong>of</strong>:<br />

1. Total visibility;<br />

2. Synchronization and balance;<br />

3. Respect for people;<br />

4. Flexibility;<br />

5. Continuous improvement;<br />

6. Responsibility for the environment;<br />

7. Simplicity; and<br />

8. Holistic approach<br />

Areas <strong>of</strong> greatest potential for improving performance in Service Sector:<br />

1. Training <strong>of</strong> employees<br />

2. <strong>Technology</strong><br />

3. Layout<br />

4. Quality<br />

5. Standardization<br />

6. Delivery<br />

5.0 Conclusions and Future Directions:<br />

The basic philosophy behind JIT in manufacturing and service operations represents a uniquely organized<br />

set <strong>of</strong> activities which can be utilized to produce low cost and high quality products and services. The<br />

discussion presented in this paper highlights the importance <strong>of</strong> the service sector to developed and<br />

developing economies. Global competition is forcing companies to improve the quality <strong>of</strong> their products<br />

and their customer service while reducing the cost <strong>of</strong> their operations. This is a critical requirement for<br />

maintaining competitiveness. It is postulated that the implementation <strong>of</strong> JIT concepts in the service sector<br />

will facilitate the achievement <strong>of</strong> benefits long realized by the manufacturing sector. A comparison <strong>of</strong><br />

manufacturing and service operations was conducted in an attempt to show the transferability and<br />

applicability <strong>of</strong> these concepts to the service sector. The activities that would most likely show the greatest<br />

potential for the improvement <strong>of</strong> services through the use <strong>of</strong> JIT concepts were analyzed and discussed. The<br />

philosophy <strong>of</strong> JIT can bring impressive advances in productivity and quality to the increasingly servicedominated<br />

economies <strong>of</strong> the future.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

6.0 References<br />

1. Just in Time Manufacturing: Introduction and Major Components, Alejandro A. Lorefice New<br />

York – April <strong>19</strong>98, Servicioy Tecnologia S.A.<br />

2. “Are push and pull systems really so different” M.C. Bonney, Zongmao Zhang, M.A. Head,<br />

C.C. Tien, R.J. Barson, Int. J. Production Economics 59 (<strong>19</strong>99) 53-64.<br />

3. Mehra, S., Inman, R.A., <strong>19</strong>92. Determining the critical elements <strong>of</strong> Just-in-Time implementation.<br />

Decision <strong>Science</strong>s 23 (1), 160–174.<br />

4. Sakakibara, S., Flynn, B.B., Schroeder, R.G., <strong>19</strong>93. A framework and measurement instrument for<br />

Just-in-Time manufacturing. Production and Operations Management 2 (3), 177–<strong>19</strong>4.<br />

5. V.D. Wakchaure, Dr. M.A. Venkatesh & Dr. S.P. Kallurkar, <strong>20</strong>06, “Review <strong>of</strong> JIT Practices in<br />

Indian Manufacturing Industries”, IEEE International Conference on Management <strong>of</strong> Innovation<br />

and <strong>Technology</strong>, pp: 1099-1103.<br />

6. Rosemary R. Fullerton & Cheryl S. McWatters, <strong>20</strong>01, “The production performance benefits from<br />

JIT implementation”, Journal <strong>of</strong> Operations Management <strong>19</strong> (<strong>20</strong>01), pp: 81-96.<br />

7. Mattias Elg, Jon Engström, Lars Witell, Bozena Poksinska, (<strong>20</strong>12), “Co-creation and learning in<br />

health-care service development", Journal <strong>of</strong> Service Management, Vol. 23 Iss: 3 pp. 328 – 343.<br />

8. Low Sui Pheng, Faisal Manzoor Arain, Jolene Wong Yan Fang, "Applying just-in-time principles<br />

in the delivery and management <strong>of</strong> airport terminal buildings", Built Environment Project and<br />

Asset Management, Vol. 1 Iss: 1 pp. 104 -121.<br />

9. Vikas Kumar (<strong>20</strong>10), “JIT Based Quality Management: Concepts and Implications in Indian<br />

Context”, International Journal <strong>of</strong> Engineering <strong>Science</strong> and <strong>Technology</strong>, Vol. 2 Iss: 1 pp. 40-50.<br />

10. Daniel I. Prajogo, Christopher M. McDermott, (<strong>20</strong>08),"The relationships between operations<br />

strategies and operations activities in service context", International Journal <strong>of</strong> Service Industry<br />

Management, Vol. <strong>19</strong> Iss: 4 pp. 506 – 5<strong>20</strong>.<br />

11. Marc H. Meyer, Eliot Jekowsky, Frederick G. Crane, (<strong>20</strong>07),"Applying platform design to<br />

improve the integration <strong>of</strong> patient services across the continuum <strong>of</strong> care", Managing Service<br />

Quality, Vol. 17 Iss: 1 pp. 23 – 40.<br />

12. W.K. Wong, C.K. Kwong, P.Y. Mok and W.H. Ip (<strong>20</strong>06), “ Genetic optimization <strong>of</strong> JIT operation<br />

schedules for fabric – cutting process in apparel manufacture”, Journal <strong>of</strong> Intelligent<br />

Manufacturing, Vol. 17 Iss: 1 pp 341-354.<br />

13. Vikas Kumar, Dixit Garg and N P Mehta (<strong>20</strong>04), “JIT practices in Indian context: A survey”,<br />

Journal <strong>of</strong> scientific & Industrial Research, Vol. 63 pp 655-662.<br />

14. Christine M. Wright and George Mechling (<strong>20</strong>02), “The importance <strong>of</strong> operations management<br />

problems in Service Organizations”, The International Journal <strong>of</strong> Management <strong>Science</strong>, Vol. 30 pp<br />

77-87.<br />

15. Editorial (<strong>20</strong>02), “New issues and opportunities in Service Design Research”, Vol. <strong>20</strong> pp 117-1<strong>20</strong>.<br />

16. Low Sui Pheng, Choong Joo Chuan, (<strong>20</strong>01),"A study <strong>of</strong> the readiness <strong>of</strong> precasters for just-in-time<br />

Construction", Work Study, Vol. 50 Iss: 4 pp. 131 – 140.<br />

17. Cem Canel, Drew Rosen and Elizabeth A. Anderson (<strong>20</strong>00), “JIT is not just for Manufacturing: A<br />

Service Perspective”, Industrial Management & Data Systems, Vol. 100 Iss: 2 pp 51-60.<br />

18. Brian Wood, (<strong>19</strong>99),"Intelligent building care", Facilities, Vol. 17 Iss: 5 pp. 189 – <strong>19</strong>4.<br />

<strong>19</strong>. Ajay Das, Robert B. Handfield, (<strong>19</strong>97),"Just-in-time and logistics in global sourcing: an empirical<br />

study", International Journal <strong>of</strong> Physical<br />

<strong>20</strong>. Distribution & Logistics Management, Vol. 27 Iss: 3 pp. 244 – 259.<br />

21. Leslie K. Duclos, Samia M. Sih and Rhonda R. Lummus (<strong>19</strong>95), “JIT in Services: A review <strong>of</strong><br />

current practices and future directions for research”, Vol. 6 Iss: 5 pp 36-52.<br />

22. Ricardo Hitec, (<strong>19</strong>94),"Management <strong>of</strong> a catering facility", Assembly Automation, Vol. 14 Iss: 1<br />

pp. 28 – 29.<br />

23. Thomas J. Billesbach and Marc J. Schniederjans (<strong>19</strong>89), “Applicability <strong>of</strong> JIT Techniques in<br />

Administration”, Production and Inventory Management Journal, Third Quarter pp 40-45.<br />

24. Ronald G. Conant (<strong>19</strong>88), “JIT in a Mail Order Operation Reduces Processing Time From Four<br />

Days to Four Hours”, Just-in-Time Update, Industrial Engineering pp 34-37.<br />

25. Stevenson, W.J. (<strong>19</strong>99), Production and Operations Management, Irwin/McGraw-Hill, New York,<br />

NY.<br />

26. Krajewski, L.J. and Ritzman, L.P. (<strong>19</strong>99), Operations Management Strategy and Analysis,<br />

Addison Wesley, Reading, MA.<br />

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

27. Burnham, J.M. (<strong>19</strong>87), ``Some conclusions about JIT manufacturing'', Production and Inventory<br />

Management, Vol. 28 No. 3, 3rdquarter, pp. 7-11.<br />

28. Hernandez, A. (<strong>19</strong>89), Just In Time Manufacturing, Prentice-Hall, Englewood Cliffs, NJ.<br />

29. Stonebraker, P.W. and Leong, G.K. (<strong>19</strong>94), Operations Strategy, Focusing Competitive<br />

Excellence, Allyn and Bacon, Needham Heights, MA.<br />

30. Fitzsimmons, J.A. and Sullivan, R.S. (<strong>19</strong>82), Service Operations Management, McGraw-Hill, New<br />

York, NY.<br />

31. Fitzsimmons, J.A. and Fitzsimmons, M.J. (<strong>19</strong>94), Service Management for Competitive<br />

Advantage, McGraw Hill, New York, NY.<br />

32. Krajewski, L.J. and Ritzman, L.P. (<strong>19</strong>99), Operations Management Strategy and Analysis,<br />

Addison Wesley, Reading, MA.<br />

33. Byard, J.B. (<strong>19</strong>87), ``Why using just-in-time is getting back to basics for American industry'',<br />

Industrial Engineering, Vol. <strong>19</strong> No. 8, pp. 43-4.<br />

34. Carmen, J.M. and Langeard, E. (<strong>19</strong>80), ``Growth strategies for service firms'', Strategic<br />

Management Journal, No. 1, January-March, pp. 7-22.<br />

35. Chase, R.B. and Tansik, D.A. (<strong>19</strong>83), ``The customer contact model for organizational design'',<br />

Management <strong>Science</strong>, Vol. 29 No 9, pp. 1037-50.<br />

36. Chase, R.B., Aquilano, N.J. and Jacobs F.R. (<strong>19</strong>98),Production and Operations Management,<br />

Irwin/McGraw Hill, New York, NY.<br />

37. Chase, R.B. and Stewart, D.M. (<strong>19</strong>93), ``Make your service failsafe'', COMER Working Paper 93-<br />

018R.<br />

38. Khumawala, B.M., Hixon, C. and Law, J.S. (<strong>19</strong>86), ``MRP II in the service industries'', Production<br />

and Inventory Management journal, 3rd Quarter, pp. 57-63.<br />

39. Wasco, C.W., Stonehocker, R.E. and Feldman, L.H. (<strong>19</strong>91), ``Success with JIT and MRP II in a<br />

service organization'', Production and Inventory Management Journal, 4th Quarter, pp. 15-21.<br />

40. Rosen, D.L. (<strong>19</strong>90), The Measurement and Modeling <strong>of</strong> Quality in Service Organizations,<br />

unpublished PhD Dissertation, <strong>University</strong> <strong>of</strong> South Carolina.<br />

939


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

GENETIC ALGORITHMS: A PROBLEM SOLVING APPROACH<br />

Jyoti*, Neetu Gupta<br />

Asst. Pr<strong>of</strong> -H.A.S Department, <strong>YMCA</strong> Univ. <strong>of</strong> Sci. & Tech, Faridabad<br />

Abstract<br />

Genetic Algorithms (GAs) are adaptive heuristic search algorithm premised on the evolutionary ideas <strong>of</strong> natural<br />

selection and genetic. The basic concept <strong>of</strong> GAs is designed to simulate processes in natural system necessary for<br />

evolution, specifically those that follow the principles first laid down by Charles Darwin <strong>of</strong> survival <strong>of</strong> the fittest. As<br />

such they represent an intelligent exploitation <strong>of</strong> a random search within a defined search space to solve a problem.<br />

First pioneered by John Holland in the 60s, Genetic Algorithms has been widely studied, experimented and applied<br />

in many fields in engineering worlds. Not only does GAs provide an alternative method to solving problem, it<br />

consistently outperforms other traditional methods in most <strong>of</strong> the problems link. Many <strong>of</strong> the real world problems<br />

involved finding optimal parameters, which might prove difficult for traditional methods but ideal for GAs.<br />

However, because <strong>of</strong> its outstanding performance in optimization, GAs has been wrongly regarded as a function<br />

optimizer. In fact, there are many ways to view genetic algorithms. In this paper we aim at providing an insight into<br />

the field <strong>of</strong> genetic algorithms and its areas <strong>of</strong> application<br />

Keywords: Genetic Algorithms, Optimization, Application <strong>of</strong> GAs.<br />

Introduction<br />

Genetic algorithm is a randomized search methodology having its roots in the natural selection process. Initially the<br />

neighborhood search operators (crossover and mutation) are applied to the preliminary set <strong>of</strong> solutions to acquire<br />

generation <strong>of</strong> new solutions. Solutions are chosen randomly from the existing set <strong>of</strong> solutions where the selection<br />

probability and the solution’s objective function value are proportional to each other and eventually the aforesaid<br />

operators are applied on the chosen solutions. Genetic algorithms have aided in the successful implementation <strong>of</strong><br />

solutions for a wide variety <strong>of</strong> combinatorial problems.<br />

History<br />

Computer simulations <strong>of</strong> evolution started as early as in <strong>19</strong>54 with the work <strong>of</strong> Nils Aall Barricelli. His <strong>19</strong>54<br />

publication was not widely noticed. Starting in <strong>19</strong>57, the Australian quantitative geneticist Alex Fraser published a<br />

series <strong>of</strong> papers on simulation <strong>of</strong> artificial selection <strong>of</strong> organisms with multiple loci controlling a measurable trait.<br />

From these beginnings, computer simulation <strong>of</strong> evolution by biologists became more common in the early <strong>19</strong>60s,<br />

and the methods were described in books by Fraser and Burnell (<strong>19</strong>70) and Crosby (<strong>19</strong>73). Fraser's simulations<br />

included all <strong>of</strong> the essential elements <strong>of</strong> modern genetic algorithms. In addition, Hans-Joachim Bremermann<br />

published a series <strong>of</strong> papers in the <strong>19</strong>60s that also adopted a population <strong>of</strong> solution to optimization problems,<br />

undergoing recombination, mutation, and selection. Bremermann's research also included the elements <strong>of</strong> modern<br />

genetic algorithms. Other noteworthy early pioneers include Richard Friedberg, George Friedman, and Michael<br />

Conrad. Many early papers are reprinted by Fogel (<strong>19</strong>98).<br />

Although Barricelli, in work he reported in <strong>19</strong>63, had simulated the evolution <strong>of</strong> ability to play a simple game,<br />

artificial evolution became a widely recognized optimization method as a result <strong>of</strong> the work <strong>of</strong> Ingo Rechenberg and<br />

Hans-Paul Schwefel in the <strong>19</strong>60s and early <strong>19</strong>70s – Rechenberg's group was able to solve complex engineering<br />

problems through evolution strategies. Another approach was the evolutionary programming technique <strong>of</strong> Lawrence<br />

J. Fogel, which was proposed for generating artificial intelligence. Evolutionary programming originally used finite<br />

state machines for predicting environments, and used variation and selection to optimize the predictive logics.<br />

Genetic algorithms in particular became popular through the work <strong>of</strong> John Holland in the early <strong>19</strong>70s, and<br />

particularly his book Adaptation in Natural and Artificial Systems (<strong>19</strong>75).Research in GAs remained largely<br />

theoretical until the mid-<strong>19</strong>80s, when The First International Conference on Genetic Algorithms was held in<br />

Pittsburgh, Pennsylvania.[5]<br />

940


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

What is Genetic Algorithm<br />

In a genetic algorithm, a population <strong>of</strong> strings (called chromosomes or the genotype <strong>of</strong> the genome), which encode<br />

candidate solutions (called individuals, creatures, or phenotypes) to an optimization problem, is evolved toward<br />

better solutions. Traditionally, solutions are represented in binary as strings <strong>of</strong> 0s and 1s, but other encodings are<br />

also possible. The evolution usually starts from a population <strong>of</strong> randomly generated individuals and happens in<br />

generations. In each generation, the fitness <strong>of</strong> every individual in the population is evaluated; multiple individuals<br />

are stochastically selected from the current population based on their fitness, and modified and possibly randomly<br />

mutated to form a new population. The new population is then used in the next iteration <strong>of</strong> the algorithm.<br />

Commonly, the algorithm terminates when either a maximum number <strong>of</strong> generations has been produced, or a<br />

satisfactory fitness level has been reached for the population. [5].<br />

Basically a genetic algorithm requires:<br />

1. a genetic representation <strong>of</strong> the solution domain,<br />

2. a fitness function to evaluate the solution domain.<br />

A standard representation <strong>of</strong> the solution is as an array <strong>of</strong> bits. Arrays <strong>of</strong> other types and structures can be used in<br />

essentially the same way. The main property that makes these genetic representations convenient is that their parts<br />

are easily aligned due to their fixed size, which facilitates simple crossover operations. Variable length<br />

representations may also be used, but crossover implementation is more complex in this case. Tree-like<br />

representations are explored in genetic programming and graph-form representations are explored in evolutionary<br />

programming; a mix <strong>of</strong> both linear chromosomes and trees is explored in gene expression programming.<br />

The fitness function is defined over the genetic representation and measures the quality <strong>of</strong> the represented solution.<br />

The fitness function is always problem dependent.<br />

Once the genetic representation and the fitness function are defined, a GA proceeds to initialize a population <strong>of</strong><br />

solutions (usually randomly) and then (usually) to improve it through repetitive application <strong>of</strong> the mutation,<br />

crossover, inversion and selection operators. Uniform Crossover<br />

In the crossover operation, two new children are formed by exchanging the genetic information between two parent<br />

chromosomes. Multipoint crossover defines crossover points as places between loci where an individual can be split.<br />

Uniform crossover generalizes this scheme to make every locus a potential crossover point. [4] .A crossover mask,<br />

the same length as the individual structure is created at random and the parity <strong>of</strong> the bits in the mask indicate which<br />

parent will supply the <strong>of</strong>fspring with which bits. This method is identical to discrete recombination. Consider the<br />

following two individuals with 11 binary variables each:<br />

Individual 1 0 1 1 1 0 0 1 1 0 1 0<br />

Individual 2 1 0 1 0 1 1 0 0 1 0 1<br />

For each variable the parent who contributes its variable to the <strong>of</strong>fspring is chosen randomly with equal probability.<br />

Here, the <strong>of</strong>fspring 1 is produced by taking the bit from parent 1 if the corresponding mask bit is 1 or the bit from<br />

parent 2 if the corresponding mask bit is 0. Offspring 2 is created using the inverse <strong>of</strong> the mask, usually.<br />

Sample 1 0 1 1 0 0 0 1 1 0 1 0<br />

Sample 2 1 0 0 1 1 1 0 0 1 0 1<br />

After crossover the new individuals are created:<br />

<strong>of</strong>fspring 1 1 1 1 0 1 1 1 1 1 1 1<br />

<strong>of</strong>fspring 2 0 0 1 1 0 0 0 0 0 0 0<br />

Uniform crossover has been claimed to reduce the bias associated with the length <strong>of</strong> the binary representation used<br />

and the particular coding for a given parameter set. This helps to overcome the bias in single-point crossover<br />

towards short substrings without requiring precise understanding <strong>of</strong> the significance <strong>of</strong> the individual bits in the<br />

941


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

individual’s representation. How uniform crossover may be parameterized by applying a probability to the swapping<br />

<strong>of</strong> bits was demonstrated by William M. Spears et al.[2]<br />

This extra parameter can be used to control the amount <strong>of</strong> disruption during recombination without introducing a<br />

bias towards the length <strong>of</strong> the representation used. The chromosome cloning takes place when a pair <strong>of</strong><br />

chromosomes does not crossover, thus creating <strong>of</strong>f springs that are exact copies <strong>of</strong> each parent.<br />

The ultimate step in each generation is the mutation <strong>of</strong> individuals through the alteration <strong>of</strong> parts <strong>of</strong> their genes.<br />

Mutation alters a minute portion <strong>of</strong> a chromosome and thus institutes variability into the population <strong>of</strong> the<br />

subsequent generation. Mutation, a rarity in nature, denotes the alteration in the gene and assists us in avoiding loss<br />

<strong>of</strong> genetic diversity. Its chief intent is to ensure that the search algorithm is not bound on a local optimum. [1]<br />

The Complete Process<br />

Initialization<br />

Initially many individual solutions are randomly generated to form an initial population. The population size<br />

depends on the nature <strong>of</strong> the problem, but typically contains several hundreds or thousands <strong>of</strong> possible solutions<br />

Selection<br />

During each successive generation, a proportion <strong>of</strong> the existing population is selected to breed a new generation.<br />

Individual solutions are selected through a fitness-based process, where fitter solutions (as measured by a fitness<br />

function) are typically more likely to be selected. Certain selection methods rate the fitness <strong>of</strong> each solution and<br />

preferentially select the best solutions.<br />

Reproduction<br />

The next step is to generate a second generation population <strong>of</strong> solutions from those selected ones through genetic<br />

operators: crossover (also called recombination), and/or mutation.<br />

For each new solution to be produced, a pair <strong>of</strong> "parent" solutions is selected for breeding from the pool selected<br />

previously. By producing a "child" solution using the above methods <strong>of</strong> crossover and mutation, a new solution is<br />

created which typically shares many <strong>of</strong> the characteristics <strong>of</strong> its "parents". New parents are selected for each new<br />

child, and the process continues until a new population <strong>of</strong> solutions <strong>of</strong> appropriate size is generated. These processes<br />

ultimately result in the next generation population <strong>of</strong> chromosomes that is different from the initial generation.<br />

Generally the average fitness will have increased by this procedure for the population, since only the best organisms<br />

from the first generation are selected<br />

This generational process is repeated until a termination condition has been reached. Common terminating<br />

conditions are:<br />

‣ A solution is found that satisfies minimum criteria<br />

‣ Fixed number <strong>of</strong> generations reached<br />

‣ Allocated budget (computation time/money) reached<br />

‣ The highest ranking solution's fitness is reaching or has reached a plateau such that successive iterations no<br />

longer produce better results<br />

‣ Manual inspection<br />

Genetic algorithm procedure (main steps)<br />

Choose the initial population <strong>of</strong> individuals<br />

Evaluate the fitness <strong>of</strong> each individual in that population<br />

Repeat on this generation until termination (time limit, sufficient fitness achieved, etc.):<br />

942


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

‣ Select the best-fit individuals for reproduction<br />

‣ Breed new individuals through crossover and mutation operations to give birth to <strong>of</strong>fspring<br />

‣ Evaluate the individual fitness <strong>of</strong> new individuals<br />

‣ Replace least-fit population with new individuals<br />

Applications <strong>of</strong> Genetic Algorithms<br />

GAs have been used for problem-solving and for modelling. GAs are applied to many scientific, engineering<br />

problems, in business and entertainment, including:<br />

Optimization: GAs have been used in a wide variety <strong>of</strong> optimisation tasks, including numerical optimisation, and<br />

combinatorial optimisation problems such as traveling salesman problem (TSP), circuit design , job shop scheduling<br />

and video & sound quality optimisation.<br />

Automatic Programming: GAs have been used to evolve computer programs for specific tasks, and to design other<br />

computational structures, for example, cellular automata and sorting networks.<br />

Machine and robot learning: GAs have been used for many machine- learning applications, including<br />

classification and prediction, and protein structure prediction. GAs have also been used to design neural networks, to<br />

evolve rules for learning classifier systems or symbolic production systems, and to design and control robots.<br />

Economic models: GAs have been used to model processes <strong>of</strong> innovation, the development <strong>of</strong> bidding strategies,<br />

and the emergence <strong>of</strong> economic markets.<br />

Immune system models: GAs have been used to model various aspects <strong>of</strong> the natural immune system, including<br />

somatic mutation during an individual's lifetime and the discovery <strong>of</strong> multi-gene families during evolutionary time.<br />

Ecological models: GAs have been used to model ecological phenomena such as biological arms races, hostparasite<br />

co-evolutions, symbiosis and resource flow in ecologies.<br />

Population genetics models: GAs have been used to study questions in population genetics, such as "under what<br />

conditions will a gene for recombination be evolutionarily viable"<br />

Interactions between evolution and learning: GAs have been used to study how individual learning and species<br />

evolution affect one another.<br />

Models <strong>of</strong> social systems: GAs have been used to study evolutionary aspects <strong>of</strong> social systems, such as the<br />

evolution <strong>of</strong> cooperation, the evolution <strong>of</strong> communication, and trail-following behavior in ants.[7]<br />

Criticisms<br />

There are several criticisms <strong>of</strong> the use <strong>of</strong> a genetic algorithm compared to alternative optimization algorithms:<br />

Repeated fitness function evaluation for complex problems are <strong>of</strong>ten the most prohibitive and limiting segment <strong>of</strong><br />

artificial evolutionary algorithms. Finding the optimal solution to complex high dimensional, multimodal problems<br />

<strong>of</strong>ten requires very expensive fitness function evaluations. In real world problems such as structural optimization<br />

problems, one single function evaluation may require several hours to several days <strong>of</strong> complete simulation. Typical<br />

optimization methods can not deal with such types <strong>of</strong> problem<br />

Genetic algorithms do not scale well with complexity. That is, where the number <strong>of</strong> elements which are exposed to<br />

mutation is large there is <strong>of</strong>ten an exponential increase in search space size. This makes it extremely difficult to use<br />

the technique on problems such as designing an engine, a house or plane. In order to make such problems tractable<br />

to evolutionary search, they must be broken down into the simplest representation possible.<br />

The "better" solution is only in comparison to other solutions. As a result, the stop criterion is not clear in every<br />

problem.<br />

943


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

In many problems, GAs may have a tendency to converge towards local optima or even arbitrary points rather than<br />

the global optimum <strong>of</strong> the problem. This means that it does not "know how" to sacrifice short-term fitness to gain<br />

longer-term fitness<br />

Several methods have been proposed to remedy this by increasing genetic diversity somehow and preventing early<br />

convergence, either by increasing the probability <strong>of</strong> mutation when the solution quality drops (called triggered<br />

hypermutation), or by occasionally introducing entirely new, randomly generated elements into the gene pool (called<br />

random immigrants). Again, evolution strategies and evolutionary programming can be implemented with a socalled<br />

"comma strategy" in which parents are not maintained and new parents are selected only from <strong>of</strong>fspring. This<br />

can be more effective on dynamic problems.<br />

Alternative and complementary algorithms include evolution strategies, evolutionary programming, simulated<br />

annealing, Gaussian adaptation, hill climbing, and swarm intelligence (e.g.: ant colony optimization, particle swarm<br />

optimization) and methods based on integer linear programming. [3]<br />

Conclusion<br />

Genetic Algorithms has been widely studied, experimented and applied in many fields in engineering worlds. Not<br />

only does GAs provide an alternative method to solving problem, it consistently outperforms other traditional<br />

methods in most <strong>of</strong> the problems link. Many <strong>of</strong> the real world problems involved finding optimal parameters, which<br />

might prove difficult for traditional methods but ideal for GAs. New algorithms are being explored and applied as a<br />

focused approach for problem solving nowadays.<br />

References:<br />

[1] S. Narmadha, V Selladurai, G. Sathish “Multi product inventory optimization uniform crossover genetic<br />

algorithm” (IJCSIS, Vol:7, No.1, <strong>20</strong>10)<br />

[2] William M.Spears and K.A.De Jong, “On the Virtues <strong>of</strong> Uniform Crossover,”4 th International conference on<br />

Genetic Algorithms ,La Jolla, California, July <strong>19</strong>91<br />

[3] S. Narmadha, V Selladurai, G. Sathish, “Efficient Inventory Optimization <strong>of</strong> Multi Product Multi Suppliers with<br />

lead time using PSO” International Journal <strong>of</strong> Computer <strong>Science</strong> and information Security, Vol 7,No.1,<strong>20</strong>10.<br />

[4] Syswerdr, Gilbert,” Uniform crossover in genetic algorithm, Proc. 3 rd International conference on genetic<br />

algorithms, Morgan Kaufmenn publishing, p.61-69, June 01, <strong>19</strong>89<br />

[5]D.Beasley ,D.R.Bull and R.R.Martin,<br />

“An overview <strong>of</strong> genetic algorithms:Part1,Fundamentals,<br />

<strong>University</strong> Computing,15(2):58-69,<strong>19</strong>93<br />

[6] L.Davis, “Genetic Algorithms and simulated annealing”, Morgan Kaufman Publishers. Los Altos, <strong>19</strong>87. [5],<br />

[7] D.Beasley,D.R.Bull and R.R.Martin, “An overview <strong>of</strong> genetic algorithms:Part 2,Research Topics” 15(2):58-69,<br />

<strong>19</strong>93<br />

944


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

A Systematic Review <strong>of</strong> Literature on Benchmarking<br />

Bhupender Singh 1 , Dr.Sandeep Grover 2 , Dr.Vikram Singh 3<br />

Asst.Pr<strong>of</strong>essor 1 , Department <strong>of</strong> Mechanical Engg., <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad (Hr.)<br />

Pr<strong>of</strong>essor 2 , Department <strong>of</strong> Mechanical Engg., <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad (Hr.)<br />

Associate Pr<strong>of</strong>essor 3 , Department <strong>of</strong> Mechanical Engg., <strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> and <strong>Technology</strong>, Faridabad<br />

(Hr.)<br />

Abstract<br />

In today's competitive environment &changing economy has forced organizations to consider and implement a<br />

variety <strong>of</strong> innovative management philosophies and techniques. One technique is benchmarking which has been<br />

attracting considerable attention for its effectiveness. Benchmarking is a very versatile tool that can be applied in a<br />

variety <strong>of</strong> ways to meet a range <strong>of</strong> requirements for improvement. Xerox and Kodak were the main organization who<br />

describe this technique briefly. Furthermore world class companies like IBM, Ford Motor Company and<br />

Weyerhaeuser etc.uses this technique regularly The Xerox benchmarking methodology was a ten-step process &<br />

Kodak uses a six-step benchmarking process. A large number <strong>of</strong> publications by various authors reflect the interest<br />

in this technique. In the past, many reviews <strong>of</strong> literature on benchmarking have been done by many authors. In this<br />

paper, the authors had reviewed the benchmarking literature in a way that would help researchers, to take a closer<br />

look at the growth, & applicability <strong>of</strong> this technique. There are more than 300 articles on the benchmarking topic<br />

were published in the last 12 years, as revealed in this literature review. Considering the number <strong>of</strong> publications it<br />

can be said that the benchmarking technique have a steady growth.<br />

Keywords: Benchmarking, classification, technique, effectiveness.<br />

Introduction:<br />

Benchmarking is first and foremost tool for improvement achieved through comparison with other organizations<br />

which have recognized as the best within specified area. The philosophy <strong>of</strong> benchmarking is that one should be able<br />

to recognize one’s short comings and acknowledge that someone is doing a better job and implementing it in one's<br />

own business for organizational improvements. Benchmarking gives the firm an external focus and forces the<br />

organization to look at what its competitors are doing. For some companies and organizations, benchmarking is<br />

synonymous with survival. It provides them with a way to assess their business performance. Strategic policies<br />

supported by benchmarking enables any organization to focus the change in institutional policies on areas where it<br />

yields the best return. Academicians and researchers involved in strategic management have devoted increasing<br />

attention in the recent decade to the influence <strong>of</strong> benchmarking processes on process improvement, quality<br />

assurance, performance evaluation, and performance enhancement. Benchmarking as a total quality management<br />

tool has been widely adopted by manufacturing and service industries, and other industries around the world,<br />

It is essential that present attempt is different from the earlier reviews. This paper is providing a review <strong>of</strong> literature<br />

on benchmarking, covers the following objectives:<br />

1. Arranging the publications in an orderly manner for quick search<br />

2. Classification <strong>of</strong> literature<br />

3. Survey the outcome <strong>of</strong> publications and identifying gaps<br />

Considering the growth <strong>of</strong> publications, few attempts have been made in past to review the literature <strong>of</strong><br />

benchmarking. This paper gives a comparison among the earlier reviews on benchmarking and the outcome in each<br />

case and Further classified them. The growth and categorization <strong>of</strong> publications are presented in a graphical form.<br />

The paper gives scope for more work in future.<br />

Literature on Benchmarking:<br />

Yasin (<strong>20</strong>02) In this paper, author summarizes that despite the increasing scope <strong>of</strong> benchmarking activities and<br />

increasing the number <strong>of</strong> organizations utilizing benchmarking, the field <strong>of</strong> benchmarking remains to a large extent<br />

without a unifying theory to guide its advancement.<br />

945


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Rakesh Jain and Om Prakash Yadav (<strong>20</strong>06) This paper discuses, how benchmarking can be an effective means<br />

for the food processing industry to help identify improvement opportunities and implement change process to<br />

improve business effectiveness. They discuss a benchmarking study <strong>of</strong> two food-processing companies has been<br />

carried out to identify a number <strong>of</strong> improvement opportunities for both the companies.<br />

Baltacioglu et al (<strong>20</strong>07) developed a new framework for the service supply chain, which is built on the existing<br />

knowledge derived with an application in the healthcare industry The efforts to propose conceptual models to<br />

pinpoint service supply chains and measure service supply chain processes for the case <strong>of</strong> management consulting<br />

have provided useful insights to the study <strong>of</strong> SSCPM. These works however provide only a conceptualized service<br />

supply chain framework and performance measurement for a specific service sector.<br />

Li-Yueh Lee and Ya-Hui Kao et al (<strong>20</strong>09) In this paper the Customer relationship management(CRM) dimensions<br />

are verify through Data Envelopment Analysis (DEA), and identify the benchmarking group and efficiency level<br />

among tourist hotels. The data were obtained from the opinions department managers <strong>of</strong> different tourist hotels. The<br />

results indicated the efficiency <strong>of</strong> hotels towards CRM for International Tourism.<br />

Alfred Radauer and Lothar Walter et al (<strong>20</strong>10) In this paper, the relevant findings <strong>of</strong> the benchmarking study<br />

have been amended with an additional literature review and with an outline <strong>of</strong> the tool <strong>of</strong> semantic patent analysis. It<br />

is found that the competence <strong>of</strong> the operating staff, easy identification/visibility and timely delivery are among the<br />

most significant quality aspects from the point <strong>of</strong> view <strong>of</strong> the SMEs, while the geographical proximity <strong>of</strong> the SMEs<br />

to the service premises is a factor <strong>of</strong> less importance.<br />

Kull and Narasimhan et al (<strong>20</strong>10) The paper give the benchmarking in Quality Management (QM) has emerged<br />

as a management paradigm for enhancing organizational effectiveness and competitiveness. Several empirical<br />

studies suggest that firms achieve higher levels <strong>of</strong> pr<strong>of</strong>itability and organizational performance through successful<br />

implementation <strong>of</strong> practices associated with quality management<br />

Giannakis (<strong>20</strong>11) In this paper, the view capacity <strong>of</strong> benchmarking as a key to understanding the service, by<br />

considering the process <strong>of</strong> providing a service as the transfer <strong>of</strong> capacity for the purposes <strong>of</strong> providing value to the<br />

customer<br />

The above literature on benchmarking gives the different outcomes related to papers applied in different area like<br />

Manufacturing Industries, Service sectors etc. There are different techniques are used on benchmarking in different<br />

areas for getting in top position in the relevant area. For finding the model <strong>of</strong> benchmarking a lot <strong>of</strong> literature<br />

review is required in the different areas where benchmarking is applied. Now the outcome from some more papers<br />

related to the literature on benchmarking are shown in the table no.1 which gives the aim <strong>of</strong> earlier review in the<br />

field <strong>of</strong> Benchmarking. After this, all the papers <strong>of</strong> different -2 field <strong>of</strong> benchmarking are classified in different<br />

categories, where these are coded on timely basis and find the outcome from these papers. After finding outcome,<br />

the gap is find out from the categories. This gap will help us for better understanding <strong>of</strong> literature on benchmarking<br />

into different areas. This paper firstly, provide a comparison between the earlier reviews on benchmarking and<br />

highlights the results in each case.. The categorization <strong>of</strong> publications are presented in a graphical form with timely<br />

interval. There is a table below which shows the outcomes from the earlier literature reviews on benchmarking.<br />

946


Title <strong>of</strong> paper<br />

Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 1.Outcome <strong>of</strong> Earlier Literature Views:<br />

Outcome<br />

“Overcoming benchmarking reluctance: a<br />

literature review” John Williams, Cheryl Brown<br />

and Anita Springer (<strong>20</strong>12)<br />

“Evolving benchmarking practices: a review for<br />

research perspectives’’Paul Hong, Soon W.<br />

Hong, James Jungbae Roh and Kihyun Park<br />

(<strong>20</strong>12)<br />

“A Literature Review On Benchmarking”.<br />

B.Md. Deros, M. Zeinalnezhad, Mohd. N.<br />

Ab.Rahman and T. Pourrostam (<strong>20</strong>11)<br />

“International benchmarking <strong>of</strong> healthcare<br />

quality :A review <strong>of</strong> the literature” Dr Ellen<br />

Nolte (<strong>20</strong>10)<br />

“Benchmarking the benchmarking models” G.<br />

Anand & Rambabu Kodali (<strong>20</strong>08)<br />

This paper concludes that organizational leadership best<br />

practices have been found to counter each <strong>of</strong> the four major<br />

benchmarking reluctance concerns: soundness <strong>of</strong> benchmarking<br />

theory /practices; lack <strong>of</strong> resources for benchmarking; inertia<br />

impeding pursuit <strong>of</strong> new practices; and specific impacts <strong>of</strong><br />

implementing new practices. The study is a qualitative analysis<br />

<strong>of</strong> 32 peer-reviewed sources from January <strong>20</strong>05-July <strong>20</strong>10.<br />

Content analysis is used to identify reasons for benchmarking<br />

reluctance and ways to overcome reluctance.<br />

This paper examines the benchmarking literature and presents a<br />

framework that suggests evolving patterns <strong>of</strong> firms<br />

benchmarking practices. The paper examines the studies<br />

published in Benchmarking Management, SCM, and <strong>Technology</strong><br />

Management journals from <strong>20</strong>01 to <strong>20</strong>10. ln this paper, five<br />

research dimensions for benchmarking are discussed in terms <strong>of</strong><br />

the strategy-based benchmarking; operational effectivenessbased<br />

benchmarking; technical efficiency-based benchmarking<br />

and micro-macro integrative benchmarking. For sustainable<br />

competitive advantage, benchmarking goes beyond the<br />

operational level and moves into a wide range <strong>of</strong> value chain,<br />

strategic, operational, and project levels<br />

In this paper the authors have attempted to conduct a more<br />

comprehensive review with respect to bench marking technique.<br />

Authors had reviewed the benchmarking literature in a way that<br />

would help researchers, academicians and practitioners to take a<br />

closer look at the growth, development and applicability <strong>of</strong> this<br />

technique. They found a total about 450 articles on the<br />

benchmarking topic were published in the last 10 years and find<br />

out the gaps between the literature<br />

In this study, author has focused on three quality domains i.e.<br />

effectiveness <strong>of</strong> care, patient safety and patient experience.<br />

Indeed, access to care is considered an important domain <strong>of</strong><br />

quality in several frameworks, He developed a framework for<br />

describing, analyzing and improving health system performance<br />

Effectiveness and affordable tools that can be used nationally to<br />

provide timely on system performance to undertake periodic<br />

assessments <strong>of</strong> health systems performance in the WHO.<br />

This paper aims to make the fundamental classification scheme<br />

<strong>of</strong> benchmarking and there by the unique benchmarking models<br />

that are developed for each type <strong>of</strong> benchmarking. Further it<br />

aims to propose a universal benchmarking model, which can be<br />

applied for all types <strong>of</strong> benchmarking. There is about 71 steps in<br />

which around 13 steps have been addressed by many researchers.<br />

The remaining unique steps were considered to be the best<br />

practices in benchmarking.<br />

The earlier outcome states that there is lot <strong>of</strong> work is done on Literature review <strong>of</strong> benchmarking that will be<br />

classified in different category for better study <strong>of</strong> benchmarking Technique.<br />

947


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

The classification proposed in this paper includes a simultaneous parallel categorization that gives the growth <strong>of</strong><br />

literature during various time period:<br />

1. Benchmarking: Research Papers<br />

2. Benchmarking: Case Studies<br />

3. Benchmarking: General Viewpoints<br />

4. Benchmarking: Literature Reviews<br />

One Pareto diagram <strong>of</strong> the number <strong>of</strong> publications in different categories is given in Figure 1.<br />

All the publications in the categories, have been coded based on the chronological appearance <strong>of</strong> the article, for the<br />

convenience <strong>of</strong> the readers. The first code in the form a number from 1 to 4, refers to the categories 1 to 4 illustrated<br />

above. Coding has been done from <strong>20</strong>00 onwards i.e. 3 years group for every category. Publications after <strong>20</strong>00 have<br />

been categorized on a time interval <strong>of</strong> three years.<br />

250<br />

<strong>20</strong>0<br />

150<br />

100<br />

50<br />

0<br />

Category 1 Category 2 Category 3 Category 4<br />

Figure 1. Pareto diagram showing the number <strong>of</strong> publications with publications category.<br />

The time periods are represented as “a”, “ b”, “c” and “d” from <strong>20</strong>00 to <strong>20</strong>12 into four groups i. e. shown in table 2<br />

briefly.<br />

Table 2. The coding pattern for classification based on time <strong>of</strong> publication<br />

Time Period <strong>20</strong>00-03 <strong>20</strong>03-06 <strong>20</strong>06-09 <strong>20</strong>09-12<br />

Category a b c d<br />

1 1a 1b 1c 1d<br />

2 2a 2b 2c 2d<br />

3 3a 3b 3c 3d<br />

4 4a 4b 4c 4d<br />

As an example the paper “ Benchmarking environmental performance : five leading steel mills in India” by M.<br />

Rahul Amin & Sharmistha Banerjee <strong>20</strong>10 is coded under 1- d . This means the publication was made during <strong>20</strong>09<br />

to <strong>20</strong>12 (I.e. <strong>20</strong>10) and it deals with category 1, “which is benchmarking research papers”. Similarly as belongs to<br />

948


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

4-a. that means the publication is under range <strong>of</strong> year <strong>20</strong>00-<strong>20</strong>03 and in the category <strong>of</strong> “Benchmarking: literature<br />

reviews”<br />

Similarly, all the publications, based on this coding pattern, are identified in Table 3, by their serial number as given<br />

into the bibliographical list. In this review mainly 317 publications in total are analyzed for the purpose <strong>of</strong> providing<br />

insights the growth and development <strong>of</strong> benchmarking concept. These publications are included specific papers in<br />

the journals and conferences. Books written on benchmarking are omitted from the review. In this review there is<br />

total <strong>20</strong>3 papers <strong>of</strong> Benchmarking research paper, 52 <strong>of</strong> case studies,42 Benchmarking view points and <strong>20</strong> literature<br />

review papers are included.<br />

Table 3. Category 1. Benchmarking: Research papers<br />

1-a Cassell and Nadin and Gray, Chin and Pun and Lau, Cock and French,Chung, Fawcett and Cooper,<br />

Fernandez and McCarthy and Rakotobe-Joel, Fong and Shen and Cheng, Forker and Mendez, Fowler<br />

and Campbell, Fuller and Vassie, Johnston and Fitzgerald and Markou and Brignall, Kristensen and Juhi<br />

and Eskildsen,Kumar and Chandra, Landeghem and Persoons, Lau and lee, Loosemore and Hisin, Lied,<br />

Lee and Chuah, McNamee and O‟Reilly and McFerran, McAdam, Patovi, Prado, Reenen, Robson and<br />

Prabhu, Sarkis, Seen and Shen and Cheng, Talluri and Sarkis, Thermistocleous and Ulusoy, G. and Ikiz,<br />

Lambert, D. M., & Pohlen, T. L., Frohlich, M. T., & Westbrook , R., Berry, Bennet, R. Dattakumar&<br />

Brown,Zeithaml, Parasuraman, & Berry, M. sin, Battaglia, J. Jr and Musar, R. Fuller, Johnson, B. and<br />

Chamers, M.J. , Sarkis, J , Simpson, M. and Kondouli, D, Zairi, M. and Whymark, J. Al-Mashari and<br />

Zairi, Alstete, Andriopoulos and Gotsi, Ball and Bowerman and Hawksworth, Brah and Ong and Rao,<br />

Class and Xu, Comm and Mathaisel, Dacko, Davies and Kochhar, Favret, Fuller, Hart and Tzokas,<br />

Henderson and Evans, Hinton and Francis and Holloway, Higgins and Oluwoye and Lenard, Horton, Ho<br />

and Chan and Wong, Jarrar and Zairi, Jackson and Parks and Harrison and Stebbings, Longbottom,<br />

Mathews Mmed Zairi,Mohamed Yousse,llram et al, Kathawala & Abdou, Besterfield-Michna & Besterfield-<br />

Sacre, Tsourveloudis and Valavanis, Cunningham et al., Lowe, Ridgway and Atkinson, Sultan and<br />

Simpson, Yasin, Tolosi<br />

1b. Anderson and McAdam, Balzan and acchino, Bartley and Gomibuchi and Mann, Beringer and Kovacic,<br />

Bilalis and Alvizos and Tsironis and Wassenhove, Bowen and Moesen, Braadbaart, Butler and Bassiouni<br />

and El-Adly and Widjaja, Camgoz-Akdog, Carcangiu and Barba and Fanni and Mognaschi and<br />

Montisci, Chen and Sok, Dawkins and Feeny, Dharmapala and Saber, Enoma and Allen, Enshassi and<br />

Mohamed and Mayer and Abed, Hurreeram, Jaques and Provey, Hunter and Lumbers and Raats, Joo and<br />

Stoeberi and Kwon, Kovacic, Lam and Chan, Low, Manning and Baines and Chadd, McLeod and Childs<br />

and Heaford, Missigham and Moreno, Mostafa, Officer, Panagiotou, Papaioannou, Poll, Rajaniemi,<br />

Rigby and Bilodeau, Robson and Mitchell, Salem, Saunders and Mann and Smith, Stewart and<br />

Waroonkun, Soltani and Lai, Tiku and Azatian first and Pecht<br />

1c. Southard and Parente, Sweet and Rogers and Heritage and Turner Wong, Percin Cuthbertson and<br />

Piotrowicz, Das and Paul and Swierczek, Debnath and Shankar, Beringer and Wright and Malone, and<br />

Gourdin and Hartley, Huq and Abbo, Jain and Yadav and rathore, Jones and Kaluarachchi, Korosec<br />

Huiskonen, Peng Wong and Yew Bhat and Rajashekhar, Bohlke and Robinson, Burke and Ryan, Chau,<br />

Hollman, Fawcett<br />

1d. Wallin and Allred and Magnam, Fawcett and Allred and Magnan and Ogden, Gil and Berebguer and<br />

Ruiz, Goncharuk Gurumurthy and Kodali, Gonzalez and Quesada and Silc, Kwon and Stoeberi Lyne and<br />

Hill, Madritsch, Matook and Lasch and Tamaschke, M<strong>of</strong>fett and Gillespie and McAdam, Newell,<br />

Neubauer, Niemi ,Price and Clark, Pitt and Tucker, Punniyamoorthy and Murali, Rawabdeh, Rutowski,<br />

Sakr, Sawyer and Giannakis , Arlbjørn, Mei-Chi, Hao-Chen and Wei-Kang, Mahour Mellat, Stephanie<br />

G. Adams, Kull and Narasimhan, Alfred Radauer ,Lothar Walter. Perdomo-Ortiz, Bindu Gupta, Afdiman<br />

Anuar & Rosnah Mohd, Narasimhan, Afdiman anuar & Rosan M.Yusuf<br />

Table 4.Category 2.Benchmarking: Case Studies<br />

2a. Browell, C.M. and Tse and Ling and Fung, Diebacker, Mann and Voss, Moeller and Breinlinger and Elser,<br />

Moreland and Jawaid and Dhillon, Schmid and Conen, Sommerville and Robertson, Zairi and Whymark,<br />

Zairi and Whymark. Holt and Graves, Ralston and Wright and Kumar, Santos and Powell,<br />

Hargreaves and Christou, Houghton, Lee<br />

949


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

2b. Basnet and Corner and Wisner and Tan, Boks and Stevels, McNamee and O‟Reilly and Shiels and<br />

McFerran, Mirza and Green and Luyombya, Schvaneveldt. Axelsson and Steen, Bauer and Tanner and<br />

Neely, Coleman and Ingram, Hess and Francis, Jr, Maiga and Jakobs, Marr, Tavana, Austin, Friesner and<br />

Neufelder and Raisor and Khayum, Matykiewicz and Ashton<br />

2c. Gonzalez and Quesada and Urrutia and Gavidia, Jokioinen and Suomala, Manzini and Lazzarotti. Chim,<br />

Choy and Chow and Lee and Chan, Jafari and Akhavan and Fesharaki and Fathian.<br />

2d. Ahren and Parida, Balague and saarti.Carpinetti and Oiko.Funk, George and Rangaraj.Marwa and<br />

Zairi,McAdam and Hazlett and Gillespie, Miguel, Mistry, Si and Takala and Liu, Shahalizadeh and<br />

Amirjamshidi, Zambri and Visser<br />

Table 5.Category 3. Benchmarking: General Viewpoints<br />

3a. Palaneeswaran and Kumaraswamy, Prabhu and Appleby and Yarrow and Mitchell. Adebanjo, Barkley,<br />

Davies, Hughes, Jackson, Miciak and Desmarais<br />

3b. Ahokas and Kaivo-Oja, Alexander, Alshawi and Irani and Baldwin, Boulter, Comunale and Sexton,<br />

Flitman, Franceschini and Galetto and Pignatelli and Varetto, Magd and Curry, Matthews, Matthews and<br />

Lave<br />

3c. Batiz-Lazo, Chalasani and Sounderpandian, Mathaisel and Cathcart and Comm, Rohlfer, Simatupang and<br />

Sridharan, Ungan, Yasin and Wafa and Small.<br />

3d. Graham, Houston, Price, Wait and Nolte, Wynn-Williams , Huggins and Izushi(<strong>20</strong>08), Raymond,<br />

Wauters& Kenny and Meaton, Lusty<br />

Table 6.Category 4. Benchmarking: Literature Reviews<br />

4a. Al-Mashari and Zairi. Cagliano and Blackmon and Voss, Shi and Benet, Yasin & Khurrum S. Bhutta,<br />

Faizul Huq, Dattakumar and Jagadeesh<br />

4b. Tamimi and Rajan and Sebastianelli, Anderson and McAdam., Dattakumar and Jagadeesh<br />

4c. Paul Hong, Soon W. Hong, James Jungbae Roh, Kihyun Park<br />

4d. Baba Md. Deros, Masoomeh Zeinalnezhad, Mohd. Nizam & Ab.Rahman ,Towhid & Pourrostam, John<br />

Williams, Cheryl Brown, Anita Springer<br />

For showing the chronological appearance <strong>of</strong> all publications, a graph has presented in Figure 2. In this figure it can<br />

be seen that during <strong>20</strong>00 until <strong>20</strong>12 ,the most papers has published in the years <strong>of</strong> <strong>20</strong>00 and <strong>20</strong>03(95<br />

publications),whereas there is just minimum papers in recent years for literature review.<br />

Separately. There has been a decline, as seen in the chronological listing <strong>of</strong> publications number in the line graph in<br />

figure. For example it can be seen in this Figure that under the category <strong>of</strong> “Benchmarking: general reviews”, the<br />

number <strong>of</strong> publications increased from minimum in <strong>20</strong>03 to 10 in the next period. However, from <strong>20</strong>03 onwards<br />

there appears to be a drop in the number <strong>of</strong> publication.<br />

950


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

100<br />

80<br />

60<br />

40<br />

<strong>20</strong><br />

<strong>20</strong>00-03<br />

<strong>20</strong>03-06<br />

<strong>20</strong>06-09<br />

<strong>20</strong>09-12<br />

0<br />

1 2 3 4<br />

Figure 2. Graph showing Chronological Order <strong>of</strong> all Publications<br />

Conclusion:<br />

There is lot <strong>of</strong> literature on benchmarking in the last 12 years, as revealed in this literature review. Considering the<br />

publications it can be said that the benchmarking technique has seen a steady growth and appears to be heading<br />

towards maturity level. A scrutiny <strong>of</strong> the publications show that benchmarking along with many interesting and<br />

diversified applications, have been covered in sufficient detail. These publications can serve a great deal towards<br />

quality improvement. Thus academicians, researchers have a good number <strong>of</strong> sources in the form <strong>of</strong> more than 300<br />

articles, to study, discuss and debate over many aspects <strong>of</strong> benchmarking.<br />

The present review <strong>of</strong> literature on benchmarking, carried out as a part <strong>of</strong> on-going research, certain issues which<br />

have not been satisfactorily addressed or not been addressed at all. These issues can be regarded as inadequacies and<br />

they <strong>of</strong>fer scope for further research and exploration.<br />

1. In the first Category, during period <strong>of</strong> “a” (<strong>20</strong>00-<strong>20</strong>03) there is huge number <strong>of</strong> publications which is research<br />

papers which states that lot <strong>of</strong> work is done in the particular time and also in the remainining review periods .<br />

2.In the second category(case study), most <strong>of</strong> the work is done during first and second period that needs more work<br />

in relevant field requires now a time.There will be requirement for study <strong>of</strong> various case studies <strong>of</strong> several field that<br />

gives better results for improvement.<br />

3.In the third category, mainly work is done during “b” <strong>20</strong>03 to <strong>20</strong>06 and remains period needs more effort in the<br />

particular field <strong>of</strong> general view points.<br />

4.In the fourth category, very less work is done in the review field and during current years more work is needed in<br />

literature field .The more work in benchmarking gives better results in an Industry and organization.<br />

After Reviewing <strong>of</strong> all these papers we can say that the benchmarking applied in all the field, where for service<br />

quality it is applied on Health sectors,IT,Networking,Hotel Industries,Transports,Tourism,Banking,Food Sevices,<br />

Education,Manufacturing Industries and Public Sectors etc. These all types <strong>of</strong> Industries are using benchmarking as<br />

applying different tools such as Servqual, Servperf, Qualitometro etc. in which Six Sigma ,TQM, analytical Process<br />

and different Multiple decision techniques etc. are used. These tools improves the efficiency and growth <strong>of</strong> the<br />

above sectors. The findings <strong>of</strong> literature review may assist leaders to anticipate potential benchmarking barriers<br />

during the past several years, through extensive efforts, leading firms have come to realize that there is a better way<br />

to focus benchmarking activities for their improvement.<br />

References:<br />

Afdiman anuar & Rosan M.Yusuf (<strong>20</strong>11), Manufacturing best practices in Malaysian small and medium enterprises.<br />

Benchmarking: An International Journal, 18(3), 324-341.<br />

Baba Md. Deros, Masoomeh Zeinalnezhad, Mohd. Nizam Ab.Rahman and Towhid Pourrostam, A literature review<br />

on Benchmarking, Seminar 3 - AMReG 09, 29 July <strong>20</strong>09, Kajang, Selangor, Malaysia<br />

Bindu Gupta (<strong>20</strong>11) A comparative study <strong>of</strong> organizational strategy and culture across industry. Benchmarking: An<br />

International Journal ,18(4), 510-528.<br />

Boxwell, R.J. Jr (<strong>19</strong>94), Benchmarking for Competitive Advantage, McGraw-Hill, New York, NY<br />

951


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Dattakumar, R. & Jagadeesh, R. <strong>20</strong>03. A review <strong>of</strong> literature on benchmarking. Benchmarking: An International<br />

Journal 10(3).<br />

Lambert, D. M., & Pohlen, T. L. (<strong>20</strong>01). Supply chain metrics. The International Journal <strong>of</strong> Logistics Management,<br />

12(1), 1–<strong>19</strong>.<br />

Mohamad, R.M, & V.R Ghezavati (<strong>20</strong>10).An optimization model <strong>of</strong> benchmarking, Benchmarking: An<br />

International Journal,17(6), 876-888.<br />

Shi, N. & Bennett, D. <strong>20</strong>01. Benchmarking for information systems management using issues framework studies:<br />

content and methodology. Benchmarking: An International Journal 8 (5).<br />

Yasin, M M. <strong>20</strong>02. The theory and practice <strong>of</strong> benchmarking: then and now. Benchmarking: An International<br />

Journal 9(3).<br />

952


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

SYSTEMATIC MODEL DEVELOPMENT TO ANALYZE SERVICE QUALITY IN<br />

SUPPLY CHAIN FOR A MANUFACTURING ORGANIZATION<br />

Tarun Kumar Gupta 1 , Vikram Singh 2<br />

1 Mechanical Engineering Department, NGF College <strong>of</strong> Engineering and <strong>Technology</strong>, Palwal, Haryana, India<br />

2 Mechanical Engineering Department, <strong>YMCA</strong>UST Faridabad, Haryana, India<br />

e-mail: tarungupta<strong>19</strong>76@yahoo.com<br />

Abstract<br />

In today cut throat competition, individual firm cannot compete as an independent entity rather they have to<br />

work as an integral part <strong>of</strong> supply chain links. Today most <strong>of</strong> the organizations are seeking for close association<br />

in their upstream and downstream for maximizing their supply chain efficiency, their pr<strong>of</strong>it, reduce the lead time.<br />

The key to sustainable competitive advantage, in this competitive era, lies in delivering high quality service and<br />

that will result high customer satisfaction and ultimately customer delight.<br />

Keywords: Service quality in supply chain (SQSC), Distributor service quality (DSQ), Retailer service quality<br />

(RSQ), Customer service quality (CSQ).<br />

Introduction and literature review<br />

Today, in the time <strong>of</strong> tough competition, every organization changing its focus from pr<strong>of</strong>it maximization to<br />

maximizing the pr<strong>of</strong>it through increase customer satisfaction (Seth et al, <strong>20</strong>05). Every organization wants to<br />

increase the customer base to reduce the marketing expenses. During the last three decades the scenario <strong>of</strong><br />

business has considerably changed and organizations are putting more emphasis on quality <strong>of</strong> service. Quality is<br />

a concept, a philosophy and in true sense <strong>of</strong> realization can be observed when the service delivered results in<br />

utmost satisfaction. In this competitive fast developing world economy, there is radical pressure on the<br />

organizations to find new ways to improve the services and satisfy the customers, as these are the key to success.<br />

It is very easy to calculate the loss due to poor sale but very tough to calculate the loss due to poor service<br />

(Gupta and Singh, <strong>20</strong>12). The literature <strong>of</strong> service quality is very enriched by definitions, models and<br />

measurements supported by a number <strong>of</strong> empirical studies from a variety <strong>of</strong> services. Though there is no<br />

universal accepted definition, but many authors & researchers (Lewis & Booms <strong>19</strong>83, Gronroos <strong>19</strong>84,<br />

Parasuraman et al <strong>19</strong>85, Zeithaml et al <strong>19</strong>88, Christopher <strong>19</strong>92, Asubonteng et al <strong>19</strong>96,) gives the definition<br />

according to their ideas and work but in the current scenario & related to service quality in supply chain Gupta<br />

& Singh (<strong>20</strong>12) define the Service quality in supply chain as how well an organization meets or exceeds the<br />

customer expectations in unidirectional or bidirectional for each element <strong>of</strong> a supply chain i.e. supplier,<br />

manufacturer, distributor, retailer and customer or end consumer. The gap model developed by Parasuraman et al<br />

(<strong>19</strong>85) was considered as most accepted model and many research and models are based on that.<br />

Supplier service quality<br />

During the last decade the purchasing environment has became one <strong>of</strong> the most crucial elements in establishing<br />

the value added contents for the products and services and hence has become the vital determinant to ensure the<br />

pr<strong>of</strong>itability and survival <strong>of</strong> business organization in the dynamic international market (Mohanty and Deshmukh,<br />

<strong>19</strong>93). A supplier becomes part <strong>of</strong> a weak managed supply chain and “it will have a lasting effect on the<br />

competitiveness <strong>of</strong> the entire supply chain” (Choi and Hartely, <strong>19</strong>96). An extensive study performed by Rossler<br />

and Hirsz (<strong>19</strong>95) found that closer interaction with internal customers improved internal customers perceptions<br />

<strong>of</strong> purchasing responsiveness, but technical knowledge was even more important. Purchasing arguably is a<br />

critical link to adding value in the supply chain because it has both internal and external customer and acts crossorganizationally<br />

as manager <strong>of</strong> external suppliers (Giumnipero and Vogt, <strong>19</strong>97). Rota et al (<strong>20</strong>02) developed a<br />

simulation based planning model, which can help the supplier manager to determine what parameters affect the<br />

company performance. Seth et al (<strong>20</strong>06) discussed a tool called SSQSC to measure the supplier service quality in<br />

supply chain.<br />

953


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure -1 Classification <strong>of</strong> service quality literature<br />

Organization service quality<br />

Within the last few years researcher and practitioners have increasingly focused their attention on customer<br />

service and how to improve the quality <strong>of</strong> external service, encounters between the contact employee and<br />

external customer. Bitner et al., <strong>19</strong>90 was interested in the physical surrounding that improve service<br />

encounters, while Parasuraman et al. (<strong>19</strong>85, <strong>19</strong>88, <strong>19</strong>91) focused on minimization <strong>of</strong> organization gaps that<br />

effect customer satisfaction. When service quality levels are high, benefits are found to include greater<br />

pr<strong>of</strong>itability, cost saving and increased market share (Thompron et al., <strong>19</strong>85). Davis (<strong>19</strong>92) asserted that sound<br />

service quality strategy results in cost saving and financial gain over the long term.<br />

The importance <strong>of</strong> the internal environment and an employee role in delivering product and service quality to<br />

external customers, however in a relatively new idea Heskett et al. (<strong>19</strong>94) asserted importance <strong>of</strong> internal service<br />

quality to overall customer satisfaction by examining what they termed the “service – pr<strong>of</strong>it chain”. Based on<br />

extensive care studies, they suggested that pr<strong>of</strong>it and growth resulted from customer loyalty, which is an<br />

outcome <strong>of</strong> customer satisfaction service encounters play a vital role in external customer satisfaction and thus to<br />

the firm’s overall success. Negal and Cilliers (<strong>19</strong>90) defined the internal customer as anyone who receives<br />

product or services by others in the organization. For measuring service quality in the manufacturing side<br />

researchers preferred to explored quality management practices and their implications.<br />

Distributor service quality<br />

Rapid global changes in the environments <strong>of</strong> industrial markets make distributor commitment more important to<br />

suppliers and in some ways more difficult to achieve (Goodman and Dion, <strong>20</strong>01). Ma and Deng (<strong>20</strong>02) also<br />

advocated that the distribution part plays a crucial role in the management <strong>of</strong> a supply chain, so particularly<br />

separated it from general supply chain and defined it as distribution chain.<br />

Erengue et al. (<strong>19</strong>99) advocated for integrated production/distribution planning for effective supply chain<br />

functioning. Numerous researchers advocated for manufacturer distributor partnership and alliances. Li and Lee<br />

(<strong>19</strong>94) find that in competition between two equal firms, the one furnishing better service enjoys a larger<br />

market share and a price premium. A higher-quality service is thus presumed to lead to greater sales revenue.<br />

Consumers expect the whole package, which include distribution service (availability <strong>of</strong> stock, reliable delivery),<br />

Kumar and Sharma (<strong>19</strong>92).<br />

Retailer service quality<br />

Technical service quality is an important contributor to product quality and value perceptions. Sales person’s<br />

knowledge has a significant effect on perception <strong>of</strong> product quality and the value attached to a specific product.<br />

Sweeney et al (<strong>19</strong>97) discussed that service quality at the point <strong>of</strong> purchase influences consumer’s perceptions <strong>of</strong><br />

value and willingness to buy. A good service first time and every time built up the confidence <strong>of</strong> customer in the<br />

firm specially retailer firm.<br />

954


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Customer service quality<br />

In the supply chain everyone in the downstream is the customer <strong>of</strong> upstream. Haywood – Farmer (<strong>19</strong>88)<br />

discussed that customer is the ultimate judge and he judges the quality by comparing expectations and<br />

perceptions <strong>of</strong> any organization.<br />

The organization <strong>of</strong> paper is as follows: first is introduction and literature survey which further proceed to<br />

service quality in supply chain. Then service quality for different elements <strong>of</strong> supply chain will be discussed.<br />

After that model development and discussion will be their followed by conclusion.<br />

Framework<br />

It is evident from the literature that much work on service quality is in the area <strong>of</strong> services and models, but the<br />

applicability <strong>of</strong> service quality concepts in supply chain management as a whole seems to be inadequate. Thus<br />

there seems to be a gap in the modeling and measurement in supply chain management. This has motivated to<br />

propose the model described in the next section.<br />

Model development & Discussion<br />

For measurement <strong>of</strong> service quality in supply chain in manufacturing industries a model is proposed along with<br />

the detail <strong>of</strong> different types <strong>of</strong> gaps in forward and backward direction. This conceptual model is based on the<br />

gap model used by different researchers ((Leminen, <strong>20</strong>01; Guo, <strong>20</strong>02; Seth et al, <strong>20</strong>06) for different purposes. The<br />

gaps shown in the proposed model are divided in to two categories:<br />

Forward Gap: This gap is in the direction <strong>of</strong> material flow i.e. from supplier to organization, from organization<br />

to distributor, from distributor to retailer and from retailer to customer.<br />

Reverse Gap: This gap is in the direction <strong>of</strong> feed back or in the opposite <strong>of</strong> direction <strong>of</strong> material flow i.e. from<br />

customer to retailer, from retailer to distributor, from distributor to organization and from organization to<br />

supplier.<br />

The proposed model i.e. fig -2 attempts to analyze the various service quality gaps in the supply chain. The<br />

different types <strong>of</strong> bidirectional gap are:<br />

1) Inter-organizational (between supplier and industry);<br />

2) Intra-organizational (between industry and distributor);<br />

3) Intra-organizational (between distributor and retailer); and<br />

4) Inter-organizational (between retailer and customer).<br />

The detail <strong>of</strong> these gaps is discussed in table 1. This model also indicates that if customer has any problem with<br />

service or if customer is not satisfied it affect the whole supply chain.<br />

It is visualized that a typical supply chain is always influenced by a variety <strong>of</strong> external environmental factors<br />

which may play an important role in global economy (Seth et al, <strong>20</strong>06). The implications <strong>of</strong> these factors on<br />

supply chain are as follows:<br />

Competitions: an industry may have a number <strong>of</strong> suppliers. There may be a competition for <strong>Technology</strong>, Lead<br />

time, Market Share, Price, quality <strong>of</strong> service etc. for facing this tough competition the supply chain must be<br />

review and re-oriented though Chinese, Taiwanese and Korean products affect many customer in Indian market.<br />

Political Environment: Tax policies, Expansion policy, Resource allotment policy etc are the political affairs<br />

which affect the supply chain. Many times government gives the relaxation in taxes etc. for development <strong>of</strong> a<br />

particular region. It affect the plant location, warehouse, transportation cost etc.<br />

Technical: Better feature and performance at fewer prices attract the customer and increase the market share.<br />

Those who are having less market share <strong>of</strong>fer fewer price in same segment. In case <strong>of</strong> cars, for a particular<br />

segment, who gives more features and service at less price attract the customer more and enjoy the largest share<br />

<strong>of</strong> market.<br />

Price Fluctuation: Many times price fluctuation <strong>of</strong> the product force the customer to find some alternate. The<br />

price fluctuation may be due to Fuel price variation in Global market, USD rate variation, Availability <strong>of</strong> SPMs,<br />

Raw Material, Machining Price, Derivative etc.<br />

955


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Figure 2. Proposed service quality model for supply chain<br />

Poor Quality <strong>of</strong> Service: Lack <strong>of</strong> trust in goods and services from supply chain, reduced wages <strong>of</strong> employees,<br />

increase employees turnover are some cause for poor quality <strong>of</strong> services. Due to poor quality organization may<br />

lose market share & pr<strong>of</strong>it.<br />

Demographic: Generally most <strong>of</strong> the products or services are designed as per the customer characteristics &<br />

requirements. Age, sex, income <strong>of</strong> family etc. affect the product/ services utmost.<br />

Uncertainty: When product does not deliver on time, it loses the faith <strong>of</strong> customer in organization. This<br />

uncertainty may be due to non availability <strong>of</strong> transport, road conditions, Traffic jam etc.<br />

Labor union: More interference <strong>of</strong> labor union in day-to-day work may results more strike or less production<br />

per day which may looses confidence <strong>of</strong> supply chain in organization. The reason for interference may be more<br />

salary requirement due to high inflation, working hour, safety features etc.<br />

Socio-cultural: Caste, religion, family, locality etc. affect the future <strong>of</strong> some supply chains as some products or<br />

services like Jewellery items, Food chain etc may not be acceptable for a particular religion/area, e.g. McDonald<br />

prepared veg. burger first time in India<br />

Economic: Many times Pr<strong>of</strong>itability, less sale price, GDP, WTO implication etc. affects the entire supply chain<br />

operation. Many times outsourcing may favor economic conditions.<br />

Finance problem: During the death <strong>of</strong> technology/ product/ service organization looses the market share which<br />

result in increased inventory and reduces pr<strong>of</strong>it. It is better to change or adopt the new technology/ product or<br />

service during the death time.<br />

956


Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

Table 1. Gap amongst Supply Chain Echelons<br />

Sr. No. Gap Type Between<br />

1 Gap 1F Forward Supplier and Organization<br />

2 Gap 1R Reverse Organization and Supplier<br />

3 Gap2F Forward Organization and Distributor<br />

4 Gap 2R Reverse Distributor and Organization<br />

5 Gap 3F Forward Distributor and Retailer<br />

6 Gap 3R Reverse Retailer and Distributor<br />

7 Gap 4F Forward Retailer and Customer<br />

8 Gap 4R Reverse Customer and Retailer<br />

Conclusion<br />

The model proposed is an attempt to measure the service quality in supply chain considers the unidirectional and<br />

bidirectional gaps, their interdependence and may be interrelationship. This paper also indicates that dissatisfy<br />

customers affect whole supply chain. This paper may be considered as an attempt to enlighten the specific gaps<br />

in SQSC and will help researchers and practitioners to find the gap in their supply chain and to increase the<br />

efficiency <strong>of</strong> their supply chain though there is a need for empirical validation <strong>of</strong> the model and need for further<br />

study to check whether these gaps vary with functional responsibilities or products <strong>of</strong> different industries.<br />

References<br />

Asubonteng, P., McCleary, K.J. and Swan, J.E. (<strong>19</strong>96), “SERVQUAL revisited: a critical review <strong>of</strong> service<br />

quality”, The Journal <strong>of</strong> Services Marketing, Vol. 10, No. 6, pp. 62-81.<br />

Bitner, M.J., Booms, B.H. and Tetreault, M.S., (<strong>19</strong>90), “the service encounter: diagnosing favorable and<br />

unfavorable incidents:. Journal <strong>of</strong> marketing, Vol 54, No. 1, pp 71-84<br />

Christopher, M. (<strong>19</strong>92), “Logistics and supply chain management”, Pitman publishing, London.<br />

Davis, T.R.V., “Satisfying internal customers: The link to external customer satisfaction”, planning review,<br />

vol.<strong>20</strong> no.1, (<strong>19</strong>92), pp.34-37.<br />

Ghobadian, Abby (<strong>19</strong>93), “Service quality: concepts & models”, International Journal <strong>of</strong> Quality & Reliability<br />

Management, Vol. 11, No. 9, <strong>19</strong>94, pp. 43-66.<br />

Grönroos, C. (<strong>19</strong>84), “A service quality model and its marketing implications”, European Journal <strong>of</strong> Marketing,<br />

Vol. 18 No. 4, pp. 36-44.<br />

Gupta, Tarun K., & Singh, Vikram (<strong>20</strong>12) “Service Quality in Supply Chain: A Review” International Journal <strong>of</strong><br />

Engineering & <strong>Technology</strong>, Vol. 2, No. 8, pp. 1395-1404.<br />

Mohanty,R.P., and Deshmukh, S.G., Use <strong>of</strong> analytic hierarchical process for evaluating sources <strong>of</strong> supply,<br />

international journal <strong>of</strong> physical distribution and logistics management, vol.23, No.3, (<strong>19</strong>93), pp.26-38.<br />

Negal, P. and Cillier, W, “Customer satisfaction: A comprehensive approach”, International Journal <strong>of</strong> Physical<br />

Distribution and Logistics Management, Vol.<strong>20</strong>, No.6, (<strong>19</strong>90), pp2-46.<br />

Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (<strong>19</strong>85), “A conceptual model <strong>of</strong> service quality and its<br />

implications for future research”, Journal <strong>of</strong> Marketing, Vol. 49 No. 3, pp. 41-50.<br />

Seth, Nitin, Deshmukh, S.G. and Vrat, Prem (<strong>20</strong>06), “A frame work for measurement <strong>of</strong> quality <strong>of</strong> service in<br />

supply chains”, Supply Chain Management: An International Journal, Vol. 11 No. 1, pp 82-94.<br />

Seth, N., Deshmukh, S.G. and Vrat, P. (<strong>20</strong>06), “SSQSC: a tool to measure supplier service quality in supply<br />

chain”, Production Planning & Control, Vol. 17, No. 5, pp 448-63.<br />

Sweeney, J.C., Soutar, G.N. and Johnson, L.W. (<strong>19</strong>97), “Retail service quality and perceived value”, Journal <strong>of</strong><br />

Consumer Services, Vol. 4 No. 1, pp. 39-48.<br />

Zeithaml, V.A., Berry, L.L. and Parasuraman, A. (<strong>19</strong>88), “Communication and control processes in the delivery<br />

<strong>of</strong> service quality”, Journal <strong>of</strong> Marketing, Vol. 52 No. 2, pp. 35-48.<br />

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