2009
DOI: 10.1080/00207540701777423
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Finding and optimising the key factors for the multiple-response manufacturing process

Abstract: With the advent of modern technology, manufacturing processes became so sophisticated that a single quality characteristic cannot reflect the true product quality. Thus, it is essential to perform the key factor analysis for the manufacturing process with multiple-input (factors) and multiple-output (responses). In this paper, an integrated approach of using the desirability function in conjunction with the Mahalanobis-Taguchi-Gram Schmit (MTGS) system is proposed in order to find and optimise the key factors … Show more

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Cited by 7 publications
(2 citation statements)
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References 12 publications
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“…Therefore, the increases in SN ratio before and after analysis can be analyzed to assess improvements in system functioning. Finally, validation group data were used for testing to confirm whether the reduced model exhibited sufficient classification and diagnostic capabilities [26][27][28][29][30].…”
Section: Mtsmentioning
confidence: 99%
“…Therefore, the increases in SN ratio before and after analysis can be analyzed to assess improvements in system functioning. Finally, validation group data were used for testing to confirm whether the reduced model exhibited sufficient classification and diagnostic capabilities [26][27][28][29][30].…”
Section: Mtsmentioning
confidence: 99%
“…Thus, logistic regression has been widely applied in social studies, bankruptcy prediction, market segmentation, customer behavior, and the establishment of classification models for personal loans. 17,18 Tam and Kiang 19 and Zhang 20 focused on bankruptcy and conducted classification prediction using classification methods such as logistic regression, neural networks, linear discriminant analysis, and decision trees for comparisons.…”
Section: Logistic Regressionmentioning
confidence: 99%