Paper Info
Title
An integrated fuzzy multi-criteria approach for the performance evaluation of multiple manufacturing plants
Abstract
The performance evaluation is regarded as a multiple criteria decision making (MCDM) problem and has a significant impact on the operations of the enterprise. This paper develops an integrated MCDM approach that combines the voting method and the fuzzy TOPSIS (technique for order preference by similarity to ideal solution) method to evaluate the performance of multiple manufacturing plants in a fuzzy environment. Fuzzy TOPSIS helps decision-makers carry out analysis and comparisons in ranking their preference of the alternatives with vague or imprecise data. Since the evaluation result is often greatly affected by the weights used in the evaluation process, the voting method is used in this study to determine the appropriate criteria weights. A case study demonstrating the applicability of the proposed model is presented. The case company is the world's largest manufacturer of power supplies. It has three primary manufacturing bases located in Wujiang, Dongguan, and Tianjin, China. The proposed approach is used to evaluate the performance of the company's five manufacturing plants in Wujiang, which produce switch power, telecom power, DC/DC converters, uninterruptible power systems (UPS) and AC/DC adapters.
Year
DOI
Venue
2010
10.1016/j.cie.2009.10.005
Computers & Industrial Engineering
Keywords
Field
DocType
evaluation process,evaluation result,performance evaluation,voting method,dc adapter,power supply,dc converter,integrated fuzzy multi-criteria approach,uninterruptible power system,multiple manufacturing plant,fuzzy topsis,telecom power,switch power,mcdm,decision maker
Multiple-criteria decision analysis,Ranking,Voting,Fuzzy logic,Ideal solution,Electric power system,Converters,Engineering,Fuzzy topsis,Reliability engineering,Operations management
Journal
Volume
Issue
ISSN
58
2
Computers & Industrial Engineering
Citations 
PageRank 
References 
19
1.10
13
Authors
2
Name
Order
Citations
PageRank
Vincent F. Yu142427.32
Kuo-Jen Hu2211.51