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RESEARCH PRODUCT

A Dempster-Shafer Theory-based approach to the Failure Mode, Effects and Criticality Analysis (FMECA) under epistemic uncertainty: application to the propulsion system of a fishing vessel

Antonella CertaRoberta InghilleriFabrizio HoppsConcetta Manuela La Fata

subject

EngineeringEpistemic uncertainty021103 operations researchFailure modes prioritizationbusiness.industryProcess (engineering)0211 other engineering and technologiesDempster-Shafer Theory02 engineering and technologyInterval (mathematics)Industrial and Manufacturing EngineeringReliability engineeringIdentification (information)Propulsion systemFailure mode effects and criticality analysisDempster–Shafer theorySettore ING-IND/17 - Impianti Industriali Meccanici0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingUncertainty quantificationSafety Risk Reliability and QualitybusinessFailure mode and effects analysisReliability (statistics)FMECA

description

Abstract Failure Mode and Effects Analysis (FMEA) is a safety and reliability analysis tool widely used for the identification of system/process potential failures, their causes and consequences. When aimed at the failure modes prioritization, FMEA is named Failure Mode, Effects and Criticality Analysis (FMECA). In the latter case, failure modes are commonly prioritized by means of the Risk Priority Number (RPN) that has been widely criticized to have several shortcomings. Firstly, in the presence of multiple experts supplying different and uncertain judgments on risk parameters, RPN is not able to deal with such a kind of information. Therefore, the present paper proposes the Dempster-Shafer Theory (DST) of evidence as a proper mathematical framework to deal with the epistemic uncertainty often affecting the input evaluations on risk parameters. In particular, such evaluations are supposed to be elicited from experts in an interval or crisp form, and then opportunely propagated to obtain a multiple-values characterization of the RPN associated with each analyzed failure mode. In order to synthesize the available information and make them useful for failure mode's prioritization aims, Belief and Plausibility distributions are used. The methodology is finally applied to the propulsion system of a fishing vessel operating in Sicily.

https://doi.org/10.1016/j.ress.2016.10.018