Abstract

Using Taguchi method to achieve a robust experimental design in the study of product quality is an important issue. The Taguchi method is to seek the best factors/levels combination with lowest societal cost solution to achieve customers’ requirements. However, the Taguchi method can only be used to optimize the single-response problem; it cannot be used to optimize the multi-response problem. This paper submits an optimal procedure, N-D method (Artificial Neural Network and Data Envelopment Analysis), by using artificial neural networks (ANNs) and data envelopment analysis (DEA) to achieve the optimization of multi-response problem. Two case studies in Su and Tong (1997) and Tong and Su (1997) are resolved by the proposed N-D method. The result deriving from the proposed N-D method indicates that it offers an efficient and feasible solution in the multi-response problems.

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