 The Mahalanobis-Taguchi system - two steps optimal algorithm for dynamic product design systemChing-Lien Huang International Journal of Manufacturing Technology and Management, 2012, vol. 26, issue 1/2/3/4, 104-113 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. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijmtma:v:26:y:2012:i:1/2/3/4:p:104-113 Access Statistics for this article More articles in International Journal of Manufacturing Technology and Management from Inderscience Enterprises Ltd |
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