OPTIMIZING MULTIRESPONSE PROBLEMS IN THE TAGUCHI METHOD BY FUZZY MULTIPLE ATTRIBUTE DECISION-MAKING

One of the conventional approaches used in off-line quality control is the Taguchi method. However, most previous Taguchi method application s have only dealt with a single-response problem and the multi-respons e problem has received only limited attention. The theoretical analysi s in this study reveals that Taguchi's quadratic loss function and the indifference curve in the TOPSIS (Technique for order preference by s imilarity 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 m ulti-response problems in the Taguchi method. Next, an effective proce dure is proposed by applying fuzzy set theory to multiple attribute de cision making (MADM). The procedure can reduce the uncertainty for det ermining a weight of each response and it is a universal approach whic h can simultaneously deal with continuous and discrete data. Finally, the effectiveness of the proposed procedure is verified with an exampl e of analysing a plasma enhanced chemical vapour deposition (PECVD) pr ocess experiment. (C) 1997 by John Wiley & Sons, Ltd.