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Robust DEA methodology via computer model for conceptual design under uncertainty

Robust DEA methodology via computer model for conceptual design under uncertainty This paper presents an integrated approach for an alternative exploration and selection of product development via computer aided engineering under uncertainty. For the proposed approach, a set of possible alternatives (decision making units, DMUs) are generated by designers during product development. The computer models are introduced to convert the design values of the controllable variables of DMUs into the multiple responses of interest; these are categorized into inputs and outputs. These inputs and outputs are randomized values under uncertain environments. Because of incompatible dimensions in terms of input and output values, they are further normalized prior to data envelopment analysis (DEA). Subsequently, the randomized and normalized inputs and outputs are used for DEA analysis. The first DMU ranking, chosen on the basis of the DEA analysis, is considered to be the best DMU of all available DMUs under the impact of uncertainty. Two examples: a bike frame design and an electronic circuit design are introduced to demonstrate the proposed approach. The computer models, where ANSY represents an example of the former and WEBENCH represents an example of the latter, are adopted as conversion processes during DEA analysis. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Intelligent Manufacturing Springer Journals

Robust DEA methodology via computer model for conceptual design under uncertainty

Journal of Intelligent Manufacturing , Volume 30 (3) – Mar 6, 2017

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References (36)

Publisher
Springer Journals
Copyright
Copyright © 2017 by Springer Science+Business Media New York
Subject
Business and Management; Production; Manufacturing, Machines, Tools, Processes; Control, Robotics, Mechatronics
ISSN
0956-5515
eISSN
1572-8145
DOI
10.1007/s10845-017-1310-x
Publisher site
See Article on Publisher Site

Abstract

This paper presents an integrated approach for an alternative exploration and selection of product development via computer aided engineering under uncertainty. For the proposed approach, a set of possible alternatives (decision making units, DMUs) are generated by designers during product development. The computer models are introduced to convert the design values of the controllable variables of DMUs into the multiple responses of interest; these are categorized into inputs and outputs. These inputs and outputs are randomized values under uncertain environments. Because of incompatible dimensions in terms of input and output values, they are further normalized prior to data envelopment analysis (DEA). Subsequently, the randomized and normalized inputs and outputs are used for DEA analysis. The first DMU ranking, chosen on the basis of the DEA analysis, is considered to be the best DMU of all available DMUs under the impact of uncertainty. Two examples: a bike frame design and an electronic circuit design are introduced to demonstrate the proposed approach. The computer models, where ANSY represents an example of the former and WEBENCH represents an example of the latter, are adopted as conversion processes during DEA analysis.

Journal

Journal of Intelligent ManufacturingSpringer Journals

Published: Mar 6, 2017

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