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

Authors: Ching-Lien Huang

Addresses: Department of Industrial Management, Lunghwa University of Science and Technology, No. 300, Sec. 1, Wanshou Rd., Guishan, Taoyuan County 33306, Taiwan

Abstract: 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).

Keywords: data mining; Mahalanobis Taguchi system; MTS; two steps optimal algorithm; TSO; adaptive resonance theory neural networks; ARTN; dynamic product design; pattern recognition; Taguchi methods.

DOI: 10.1504/IJMTM.2012.051433

International Journal of Manufacturing Technology and Management, 2012 Vol.26 No.1/2/3/4, pp.104 - 113

Published online: 26 Nov 2014 *

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