Failure Mode, Effects, and Criticality Analysis (FMECA) is a proactive reliability and risk management technique extensively used in practice to ensure high system performance by prioritising failure modes. Owing to the limitations of traditional FMECA, multi-criteria decision-making methods have been employed over the past two decades to enhance its effectiveness. To consider the vagueness and uncertainty of the FMECA evaluation process, an interval-based extension of the Elimination et Choice Translating Reality (ELECTRE) TRI method is proposed in the present paper for the classification of failure modes into risk categories. Therefore, ratings of failure modes against risk parameters are provided in an interval form by a panel of FMECA experts and then properly synthesised to provide a group consensus and improve the accuracy of the results. The relative importance of the risk parameters is also considered. The method is validated using a numerical example relating to the propulsion system of a fishing vessel.

Improved FMECA for effective risk management decision making by failure modes classification under uncertainty

Giallanza A.
Secondo
;
Micale R.
Penultimo
;
2022-01-01

Abstract

Failure Mode, Effects, and Criticality Analysis (FMECA) is a proactive reliability and risk management technique extensively used in practice to ensure high system performance by prioritising failure modes. Owing to the limitations of traditional FMECA, multi-criteria decision-making methods have been employed over the past two decades to enhance its effectiveness. To consider the vagueness and uncertainty of the FMECA evaluation process, an interval-based extension of the Elimination et Choice Translating Reality (ELECTRE) TRI method is proposed in the present paper for the classification of failure modes into risk categories. Therefore, ratings of failure modes against risk parameters are provided in an interval form by a panel of FMECA experts and then properly synthesised to provide a group consensus and improve the accuracy of the results. The relative importance of the risk parameters is also considered. The method is validated using a numerical example relating to the propulsion system of a fishing vessel.
2022
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3224656
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