A procedure for ranking efficient units in data envelopment analysis
Management Science
The use of data envelopment analysis for technology selection
Computers and Industrial Engineering
A closer look at the use of data envelopment analysis for technology selection
Computers and Industrial Engineering
Quality Engineering Using Robust Design
Quality Engineering Using Robust Design
Data envelopment analysis approaches for solving the multiresponse problem in the taguchi method
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
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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.