FUZZY MULTIPLE CRITERIA GROUP DECISION-MAKING IN PERFORMANCE EVALUATION OF MANUFACTURING COMPANIES
Sara SALEHI
Sara.salehi@rdu.edu.trRauf Denktas Universit, Faculty of Architecture and Engineering, Department of Software Engineering, Northern Cyprus (Turkey)
Abstract
Today's market competition requires constant improvement of manufacturing companies. The primary key to sustainable improvement is evaluating the efficiency of manufacturing processes, which inevitably demands access to thorough and comprehensive information. However, due to the multiple numbers of effective factors that are varied in nature and value, it is impossible to identify certain factors that ensure the efficiency of a manufacturing procedure. As a solution, this paper proposes a novel approach that applies fuzzy TOPSIS. This approach provides the flexibility of evaluating multiple and varied factors of different weights in scrutinizing the efficiency of a manufacturer. The proposed approach has been applied to three different manufacturers (i.e., alternatives) in three steps. In the first step, with reference to the related literature and comments of manufacturing experts, the valuable factors (i.e., the criteria) have been selected to which experts specified linguistic terms. Linguistic terms were then converted to fuzzy numbers. Fuzzy TOPSIS was applied to analyze the efficiency performance of manufacturers. In the last step, to determine the impact of criteria weights on the decision-making process, sensitivity analysis was carried out. The findings confirm the implacability of the proposed approach to manufacturing performances in a consolidated manner. The approach can be employed by marketing managers, senior administrators, and other authorities in the manufacturing and business sectors.
Keywords:
Fuzzy theory, Fuzzy TOPSIS, Decision-making, Manufacturing CompanyReferences
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Authors
Sara SALEHISara.salehi@rdu.edu.tr
Rauf Denktas Universit, Faculty of Architecture and Engineering, Department of Software Engineering, Northern Cyprus Turkey
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