The Mahalanobis-Taguchi system - two steps optimal algorithm for dynamic product design system

This work presents a novel algorithm, the Mahalanobis-Taguchi System (MTS), which offers the Mahalanobis-Taguchi System (MTS) method for product parameter selections and presents the two steps optimal algorithm (TSO) for a dynamic product design. The MTS algorithm is successful and effective for pattern recognitions from the literature reviews. Studies using a dynamic environment for data-mining in product designs are scarce. And, the TSO method can solve dynamic condition problems. Therefore, this study integrates the MTS and TSO algorithm to create the novel MTS-TSO algorithm that can be applied to construct a product designs model for dynamic environments. From the results of the experiment, we find that the methodology of the MTS algorithm can easily solves pattern-recognition problems, and is computationally efficient as well as the TSO algorithm is a simple and efficient procedure for constructing a model of a dynamic product designs system (DPDS).