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

1
Proceedings of the National Conference on
Trends and Advances in Mechanical Engineering,
YMCA University of Science & Technology, Faridabad, Haryana, Oct 19-20, 2012
Application of Taguchi Method and Grey Relational Analysis in
Optimization of Machining Processes: a Review
Parveen Kamboj 1 , Sunil Kumar 2 ,and Kamal Jangra 3
JCDM College of Engieering, Sirsa, Haryana
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2 Yadavindra College of Engineering, Guru Kashi Campus, Talwandi Sabo, Bathinda, Punjab
3
YMCA Univrsity of Science and Technology, Faridabad, Haryana
E-mail: parveensama@india.com
Abstract
Optimization of process parameters is a key objective of manufacturers for generating components with high
productivity and low cost. Taguchi method is an effective tool for optimizing process parameters for single
performance characteristic only, while Grey relational analysis (GRA) can be combined with Taguchi method
for optimizing multiple-performance characteristics. This paper presents the application of Taguchi and GRA
technique in various machining processes including conventional and non conventional processes
Keywords: Taguchi method, Grey relational analysis, Parameters optimization
1. Introduction
The impetus for developing Modern Machining Processes (MMPs) is the research for finding the efficient and
better way of producing intricate geometry with high precision in high hardness and high strength materials like
cemented carbides, titanium alloys, stainless steels, other heat resisting super alloys etc. With the technological
and industrial growth, several non-conventional machining processes like ultrasonic machining (USM), electrical
discharge machining (EDM), wire electrical discharge machining (WEDM), laser beam machining (LBM), water
jet machining (WJM), electro-chemical machining (ECM) etc have been developed. These non-conventional
machining processes work on different principles. Depending upon the work material and objective, suitable
machining process can be selected. For example, EDM and WEDM are commonly used for machining of
electrical conductive materials only, while USM can machine insulating materials also.
There are several machining parameters available within a machine tool which needs to be optimized before
shaping any material into useful application. Out of these, few parameters may be highly significant i.e. they put
appreciable effect on machining characteristics by changing a small value, while other may be insignificant for
that particular process. In order to optimize the machining operation, numbers of experiments are required to
carry out for a particular material and machine tool before actual manufacturing. In recent years, Taguchi method
has been successfully applied various fields to optimize the system. Taguchi method is a powerful tool for the
design of good quality system. This method has been extensively used for optimization of single performance
measure. The main advantage of this method is that optimal values are very close to the target values. However,
the original Taguchi method has been designed to optimize the single performance characteristics. The grey
relational analysis (GRA) has proved to be very effective in optimizing the multi performance characteristics.
The objective of present paper is to present a review on application of Taguchi method and grey relational
analysis (GRA) in optimizing the machining processes.
2.Taguchi Method
The Taguchi method (Ross, 1996; Roy, 2001) is a systematic application of design and analysis of experiments
for the purpose of designing and improving product quality. Taguchi's approach to parameter design provides the
design engineer with a systematic and efficient method for determining near optimum design parameters for
performance and cost (Phadke, 1989; Taguchi 1986). The Taguchi method utilizes orthogonal arrays (OA) from
design of experiments theory to study a large number of variables with a small number of experiments. This
“OA” s is generalized Graeco-Latin squares. To design an experiment is to select the most suitable OA and to
assign the parameters and interactions of interest to the appropriate columns.
Taguchi method follows the following steps (Unal, 1991):
• Determine the quality characteristic to be optimized. Performance characteristics are characteristics
whose variations have a significant effect on performance of any component.
• Identify the noise factors and test conditions. These factors have adverse effect on the performance
measure and product quality. These are those which are uncontrollable.
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