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Article type: Research Article
Authors: Wang, Weizhonga; b; * | Ma, Yilinc | Liu, Shulia; b; *
Affiliations: [a] School of Economics and Management, Anhui Normal University, Wuhu, Anhui, China | [b] Yangtze River Delta Development Research Institute, Anhui Normal University, Wuhu, Anhui, China | [c] School of Economics and Management, Anhui Normal University, Nanjing, Jiangsu, China
Correspondence: [*] Corresponding authors. Weizhong Wang, School of Economics and Management, Anhui Normal University, E-mail: [email protected]. Shuli Liu, School of Economics and Management, Anhui Normal University; Yangtze River Delta Development Research Institute, Anhui Normal University; E-mail: [email protected].
Abstract: Current risk prioritization approaches for FMEA models are insufficient to cope with risk analysis problem in which the self-confidence of expert’s judgment and the deviation among risk evaluation information are considered, simultaneously. Therefore, to remedy this limitation, this paper reports an extended risk prioritization approach by integrating the MULTIMOORA approach, Z-numbers and power weighted average (PWA) operator. Firstly, the Z-numbers with triangular fuzzy numbers are applied to reflect the self-confidence and uncertainty of expert’s judgment. Next, the PWA operator for Z-numbers (Z-PWA) with similarity measure is proposed to obtain the group risk evaluation matrix by considering the influence of the deviation among risk evaluation information. Then, an extended version of MULTIMOORA method with developed entropy method is presented to calculate risk priority ranking order of each failure. Finally, the equipment failures in a certain oil and gas plant is utilized to test the extended risk prioritization approach for FMEA model. After that, the sensitivity and comparison studies are led to illustrate the availability and reliability of the proposed risk prioritization approach for FMEA based risk analysis problem.
Keywords: Failure model and effect analysis, risk prioritization, Z-numbers, MULTIMOORA
DOI: 10.3233/JIFS-200678
Journal: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 2523-2537, 2021
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