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10-Step Methodology for Deploying Taguchi's Design of Experiment for Process Optimization Dr Koilakuntla Maddulety Assistant Professor in Operations Management National Institute of Industrial Engineering (NITIE), Mumbai international awards, some of the recent awards are: Bharat Jyoti Award (2012); Best Citizens of India Award (2012); Asia’s Best Professor Award(2011); Best Professor in Operations Management Award(2011) and Best Teacher in Operations Management Award(2011). He can be reached at koila@rediffmail.com, koila@nitie.edu or Contact +919969326007 DR KOILAKUNTLA MADDULETY About the author Dr Koilakuntla Maddulety has 21 years of industrial/teaching experience and published/presented 50 plus research papers /case-studies in Journals (International & National)/Conferences and Seminars. He is member of several research committees and academic boards in India. He is the recipient of several national and Design of Experiments (DOE) techniques enables designers to determine simultaneously the individual and interactive effects of many factors that could affect the output results in any design. DOE also provides a full insight of interaction between design elements; therefore, it helps turn any standard design into a robust one. Simply put, DOE helps to pin point the sensitive parts and sensitive areas in designs that cause problems in yield. Designers are then able to fix these problems and produce robust and higher yield designs prior to going into production. R.A. Fisher in England developed the classical methods for design of experiments in the early part of the 20 th century. They include a full variety of statistical design 1 NOVEMBER 2012
techniques based on Latin squares (balanced square arrangements required for unbiased statistical experimentation) and developed for agricultural industry. While rigorous, a major problem with applying Fisher’s method in manufacturing industry is the time and cost required to learn and use it. Further, Fisher’s methods are often cumbersome to implement in manufacturing industrial experimentation because of certain assumptions and procedural emphasis. The Taguchi’s Approach Dr. Genichi Taguchi of Japan developed a method for designing experiments to investigate how different parameters affect the mean and variance of a process performance characteristic that defines how well the process is functioning. The experimental design proposed by Taguchi involves using orthogonal arrays to organize the parameters affecting the process and the levels at which they should be varying. Instead of having to test all possible combinations like the factorial design, the Taguchi method tests pairs of combinations. This allows for the collection of the necessary data to determine which factors most affect product quality with a minimum amount of experimentation, thus saving time and resources. The Taguchi method is best used when there is an intermediate number of variables (3 to 50), few interactions between variables, and when only a few variables contribute significantly. Genichi Taguchi believed that quality should be designed into the products and not inspected into it. Inspection does not produce good products but only segregates them from bad products. He also propagated that quality is best achieved by minimizing the deviation from a target and the cost of quality should be measured as a function of the deviation from the standard Taguchi’s approach to the design of experiments utilizes the concept of robust design. Robust design refers to designing a product or a process in a way that it has minimal sensitivity to the external noise factors. It adds a new dimension to Fisher’s statistical experimental design by explicitly addressing the concerns faced by all process and product designers, namely • How to reduce economically the variation of a product’s function in the customer’s environment, and • How to ensure that the decisions found to be optimum during laboratory experiments will prove to be so in manufacturing and in customer environments? Taguchi’s methods lead to excellence in the selection and setting of product/process design parameters and their tolerances. In the past decade, engineers have applied these methods in over 500 automotive, electronics, information technology and process-industries worldwide. These applications have reduced cracks in castings, increased the life of drill bits, produced VLSI with fewer defects, speeded up the response time of UNIX V, and even guided 2 NOVEMBER 2012
Page 2 and 3: CONTENTS Editorial Director’s Mes
Page 4 and 5: Dinesh Kumar Likhi, Prof. Koilakunt
Page 8 and 9: human resource management systems d
Page 10 and 11: Operations Strategy Dr. Dinesh Likh
Page 12 and 13: People are assets whose value can b
Page 14 and 15: References [1]. Robert H. Hayes and
Page 16 and 17: environment including energy effici
Page 18 and 19: Dark Ages of Manufacturing Industry
Page 20 and 21: Also the policy makers do not bothe
Page 22 and 23: product to the government at a frac
Page 24 and 25: various public and private sector c
Page 26 and 27: Mr. J L Aggarwal: The steel industr
Page 28 and 29: Q) Sir, the term PMI is very common
Page 30 and 31: DEBATE- Is a Strong Manufacturing B
Page 32 and 33: Summer Internship Prashant Meshram
Page 34 and 35: Summer Internship Abhijeet Srivasta
Page 36 and 37: learnt by observing Toyota over the
Page 38 and 39: Crossword Across 1. Type of manufac
Page 40 and 41: Solution to Crossword Team Strive 3

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