|Optimizing multi-response problems in the Taguchi method by fuzzy multiple attribute decision making
National Chiao Tung University
Department of Industrial Engineering and Management
|Taguchi method;parameter design;multi-response problem;multiple attribute decision making;TOPSIS method
|One of the conventional approaches used in off-line quality control is the Taguchi method. However, most previous Taguchi method applications have only dealt with a single-response problem and the multi-response problem has received only limited attention. The theoretical analysis in this study reveals that Taguchi's quadratic loss function and the indifference curve in the TOPSIS (Technique for order preference by similarity to ideal solution) method have similar features, The Taguchi method deals with a one-dimensional problem and TOPSIS handles multi-dimensional problems. As a result, the relative closeness computed in TOPSIS can be used as a performance measurement index for optimizing multi-response problems in the Taguchi method. Next, an effective procedure is proposed by applying fuzzy set theory to multiple attribute decision making (MADM). The procedure can reduce the uncertainty for determining a weight of each response and it is a universal approach which can simultaneously deal with continuous and discrete data. Finally, the effectiveness of the proposed procedure is verified with an example of analysing a plasma enhanced chemical vapour deposition (PECVD) process experiment. (C) 1997 by John Wiley & Sons, Ltd.
|QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL
|Appears in Collections:
Files in This Item:
If it is a zip file, please download the file and unzip it, then open index.html in a browser to view the full text content.