Modeling a dynamic design system using the mahalanobis taguchi system-two-step optimal algorithm

Abstract

This work presents a novel algorithm, the Mahalanobis Taguchi System- Two Step Optimal algorithm (MTS-TSO), which combines the Mahalanobis Taguchi System (MTS) and Two-Step Optimal (TSO) algorithm for parameter selection of product design, and parameter adjustment under the dynamic service industry environments. From the results of the confirm experiment, a service industry company is adopted to applies in the methodology, we find that the methodology of the MTS-TSO algorithm can easily solves pattern-recognition problems, and is computationally efficient for constructing a model of a system. The MTS-TSO algorithm is good at pattern-recognition and model construction of a dynamic service industry company system. © 2010 Springer-Verlag Berlin Heidelberg.