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Failure mode and effect analysis using regret theory and PROMETHEE under linguistic neutrosophic context
Institution:1. Faculty of Computers and Informatics, Zagazig University, Sharqiyah, Egypt;2. Deakin-SWU Joint Research Centre on Big Data, School of Information Technology, Deakin University, Burwood 3125, VIC, Australia;1. School of Management, Shanghai University, 99 Shangda Road, Shanghai 200444, PR China;2. Shanghai Pudong New Area Zhoupu Hospital, No. 135 Guanyue Road, Shanghai 201318, PR China;3. East Hospital Affiliated to Tongji University, No. 150 Jimo Road, Shanghai 200120, PR China;1. School of Business Administration, Southwestern University of Finance and Economics, Chengdu 611130, China;2. Department of Computer Science and Artificial Intelligence, University of Granada, Granada 18071, Spain;3. Business School, Sichuan University, Chengdu 610064, China;4. School of Economics, Sichuan University, Chengdu 610064, China;5. Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia
Abstract:Failure mode and effect analysis (FMEA), which aims to identify and assess potential failure modes in a system, has been widely utilized in diverse areas for improving and enhancing the performance of systems due to it is a powerful and useful risk and reliability assessment instrument. However, the conventional FMEA approach has been suffered several criticisms for it has some shortcomings, such as unable to handle ambiguous and uncertain information, neglect the relative weights of risk criteria, and without considering the psychological behaviors of decision-makers. To ameliorate these limitations, this paper aims at establishing a hybrid risk ranking model of FMEA via combing linguistic neutrosophic numbers, regret theory, and PROMETHEE (Preference ranking organization method for enrichment evaluation) approach. In the presented model, linguistic neutrosophic numbers are adopted to capture decision-makers’ evaluation regarding the failure modes on each risk criterion. A modified PROMETHEE approach based on regret theory is presented to obtain the risk priority of failure modes considering the psychological behaviors of decision-makers. Moreover, a maximizing deviation model and TOPSIS (Technique for order preference similar to ideal solution) are separately applied to derive the weights of risk criteria and decision-makers. Finally, a numerical example relating to the supercritical water gasification system is employed to implement the presented method, and the effectiveness and feasibility of the proposed model are validated by the results derived from a sensitivity and comparison analysis.
Keywords:Failure mode and effect analysis  Linguistic neutrosophic numbers  TOPSIS  Regret theory  PROMETHEE
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