Data envelopment analysis approaches for solving the multiresponse problem in the Taguchi method

This research proposes a procedure for solving the multiresponse problem in the Taguchi method utilizing two data envelopment analysis (DEA) approaches, including comparisons of efficiency between different systems (CEBDS) and bilateral comparisons. In this procedure, each experiment in Taguchi's orthogonal array (OA) is treated as a decision-making unit (DMU) with the multiresponses as the inputs and outputs for all DMUs. For each factor of OA, the DMUs are divided into groups, each at the same factor level. Then, DMU's efficiency is separately evaluated by the CEBDS approach and the bilateral comparisons approach for each factor. The level efficiency, or the average of the efficiencies obtained by the CEBDS and the bilateral comparisons approaches for that factor level, is then used to determine the optimal factor levels for multiresponses. Three case studies are provided for illustration; in all, the proposed procedure provides the largest total anticipated improvements. Hence, it should be considered the most effective among all approaches applied in the case studies, including principal component analysis, DEA-based ranking approach, and others. In addition, the proposed procedure is more effective and requires less computational effort when the DMU's efficiency is evaluated by the bilateral comparisons approach instead of the CEBDS approach. In conclusion, the proposed procedure will provide great assistance to practitioners for solving the multiresponse problems in manufacturing applications on the Taguchi method.