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Article type: Research Article
Authors: Chen, Kuen-Suana; b; c | Yu, Chun-Mina; *
Affiliations: [a] Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung, Taiwan, R.O.C. | [b] Department of Business Administration, Chaoyang University of Technology, Taichung, Taiwan, R.O.C | [c] Institute of Innovation and Circular Economy, Asia University, Taichung, Taiwan, R.O.C
Correspondence: [*] Corresponding author. Chun-Min Yu, Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung 41170, Taiwan, R.O.C. E-mail: march@ncut.edu.tw.
Abstract: Many corporations purchase components from suppliers, which can reduce operating costs and enable firms to focus their resources on core advantages. Studies have indicated that process quality and manufacturing time performance are two crucial indicators for supplier selection. We used the process quality index and a manufacturing time performance index to create a dual dimensional fuzzy supplier selection model. First, the upper confidence limits of these two indices were derived, and a fuzzy membership function based on these limits was constructed. Based on the fuzzy test rules for process quality and manufacturing time performance, we divided the fuzzy supplier selection matrix into nine evaluation zones. Using the upper confidence limits of these two indices, we created evaluation coordinates and assigned weights based on the location of the coordinates. Then, the total of all the weights was employed to form a supplier selection index for which a higher value means a higher ranking. The use of confidence limits decreased the chance of misjudgment resulting from sampling errors while the fuzzy test rules increased the applicability of the model. Consequently, the proposed model can be used to select suppliers efficiently so as to form partnerships in which corporations and suppliers can grow together.
Keywords: Fuzzy supplier selection model, fuzzy membership function, manufacturing time performance, process quality, upper confidence limit
DOI: 10.3233/JIFS-202349
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11145-11158, 2021
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