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• W2541493485 abstract "Process equipment failures (PEFs) are recognized as one of the leading causes of process accidents. Failure modes and effect analysis (FMEA) as a risk assessment technique, has widely been used in a variety of process industries. The conventional form of FMEA uses three parameters of severity (S), occurrence (O), and detection (D) as risk factors to calculate a risk priority number (R.P.N) and rank the failure modes based on this number. But several shortcomings associated with the FMEA have limited its applicability. This study aims at the development of an extension of FMEA that could efficiently handle the vagueness and uncertainty exists in the experts’ judgments in process of failure modes ranking in conventional FMEA. In this paper we used the concept of the Z number to capture the inherent uncertainty exists in the experts’ judgments. In addition, we used Shannon entropy concept to deploy objective weights to adjust subjective weights assigned by experts. Furthermore, the fuzzy VIKOR technique applied to rank and prioritize the failure modes based on the minimum individual regret and the maxi group utility. A numerical example is presented to illustrate an application of the proposed method in a geothermal power plant (GPP). Results are also compared with the conventional FMEA. A sensitivity analysis was conducted to validate the obtained results. Findings indicate that the application of the proposed approach (subjective-objective ranking) in fuzzy environment can improve the applicability of the conventional FMEA method." @default.
• W2541493485 created "2016-11-04" @default.
• W2541493485 creator A5006178943 @default.
• W2541493485 creator A5049188959 @default.
• W2541493485 date "2017-02-01" @default.
• W2541493485 modified "2023-10-11" @default.
• W2541493485 title "An extended VIKOR method based on entropy measure for the failure modes risk assessment – A case study of the geothermal power plant (GPP)" @default.
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• W2541493485 doi "https://doi.org/10.1016/j.ssci.2016.10.006" @default.
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