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Title: An integrated approach of fuzzy linguistic preference based AHP and fuzzy COPRAS for machine tool evaluation
Authors: Nguyen, Huu-Tho
Md Dawal, Siti Zawiah
Nukman, Yusoff
Aoyama, Hideki
Case, Keith
Keywords: Machine tool evaluation
Fuzzy preference relation
Fuzzy AHP
Fuzzy COPRAS
Decision making
Issue Date: 2015
Publisher: Public Library of Science
Citation: NGUYEN, H.-T. ... et al, 2015. An integrated approach of fuzzy linguistic preference based AHP and fuzzy COPRAS for machine tool evaluation. PLoS One, 10 (9), e0133599.
Abstract: Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment.
Description: This is an open access article distributed under the terms of the Creative Commons Attribution License, https://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Sponsor: This research is supported by High Impact Research MOHE Grant UM.C/625/1/HIR/MOHE/ENG/35 (D000035-16001) from the Ministry of Education Malaysia.
Version: Published
DOI: 10.1371/journal.pone.0133599
URI: https://dspace.lboro.ac.uk/2134/18634
Publisher Link: http://dx.doi.org/10.1371/journal.pone.0133599
ISSN: 1932-6203
Appears in Collections:Published Articles (Mechanical, Electrical and Manufacturing Engineering)

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