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Super-Efficiency DEA Approach for Optimizing Multiple Quality Characteristics in Parameter Design

Super-Efficiency DEA Approach for Optimizing Multiple Quality Characteristics in Parameter Design

Abbas Al-Refaie
Copyright: © 2010 |Volume: 1 |Issue: 2 |Pages: 14
ISSN: 1947-3087|EISSN: 1947-3079|EISBN13: 9781609604257|DOI: 10.4018/jalr.2010040105
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MLA

Al-Refaie, Abbas. "Super-Efficiency DEA Approach for Optimizing Multiple Quality Characteristics in Parameter Design." IJALR vol.1, no.2 2010: pp.58-71. http://doi.org/10.4018/jalr.2010040105

APA

Al-Refaie, A. (2010). Super-Efficiency DEA Approach for Optimizing Multiple Quality Characteristics in Parameter Design. International Journal of Artificial Life Research (IJALR), 1(2), 58-71. http://doi.org/10.4018/jalr.2010040105

Chicago

Al-Refaie, Abbas. "Super-Efficiency DEA Approach for Optimizing Multiple Quality Characteristics in Parameter Design," International Journal of Artificial Life Research (IJALR) 1, no.2: 58-71. http://doi.org/10.4018/jalr.2010040105

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Abstract

This paper proposes an efficient approach for optimizing the multiple quality characteristics (QCHs) in manufacturing applications on the Taguchi method using the super efficiency technique in data envelopment analysis (DEA). Each experiment in Taguchi’s orthogonal array (OA) is treated as a decision making unit (DMU) with multiple QCHs set as inputs or outputs. DMU’s efficiency is measured then adopted as a performance measure to identify the combination of optimal factor levels. Three real case studies were employed for illustration in which the proposed approach provided the largest total anticipated improvements in multiple QCHs among other techniques such as principal component analysis (PCA) and DEA based ranking (DEAR) approach. Analysis of variance is finally employed to decide significant factor effects and to predict performance.

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