Using DEA's multi-choice method to reach multi-response optimization in Taguchi's problem

Taguchi method is a traditional approach for robust experimental design that seeks to obtain a best combination set of factors/levels with lowest societal cost solution to achieve customers' requirements. So far, the Taguchi method can only be used for a single response problem; it cannot be used to optimize a multi-response problem. In this paper, an optimal procedure based on data envelopment analysis (DEA) for multi-response robust design isproposed. With the proposed procedure, a set of multiple responses for each combination of factors/levels (CFL) (the each CFL is named decision-making unit (DMU)) is firstly transformed into a relative efficiency value by DEA technique to obtain its relative performance. Then according to the relative performance, the multi-choice from the relative efficiency value 100% can assist engineers' favorite choice, which is also the best, and then the optimal factor/level combination will be determined. Two case studies in Su are resolved by the proposed optimal procedure. Compared with Taguchi method and Su's method, the result deriving from the proposed optimal procedure indicates it offers a superior solution to the multi-response problems.