Optimizing multi-response problem in the Taguchi method by DEA based ranking method

Looks at the Taguchi method, a traditional approach that seeks to obtain the best combination of factors with the lowest societal cost solution to achieve customer requirements, and also principal component analysis (PCA). States that the Taguchi method can only be used to optimize single response problems and not multi-response problems and that PCA, although it has been considered to solve multi-response problems, itself has shortcomings. Proposes a data envelopment analysis ranking (DEAR) approach as an effective means of optimizing the multi-response problem. Includes a series of steps from the proposed approach which are capable of decreasing uncertainty caused by engineering judgement in the Taguchi method and overcoming the shortcomings of PCA. Concludes that the DEAR approach is more powerful for practical applications.