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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

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  • Certa, Antonella
  • Hopps, Fabrizio
  • Inghilleri, Roberta
  • La Fata, Concetta Manuela

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.

Suggested Citation

  • Certa, Antonella & Hopps, Fabrizio & Inghilleri, Roberta & La Fata, Concetta Manuela, 2017. "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," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 69-79.
    • Handle: RePEc:eee:reensy:v:159:y:2017:i:c:p:69-79
    DOI: 10.1016/j.ress.2016.10.018
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    References listed on IDEAS

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    8. Moath Alrifaey & Tang Sai Hong & Eris Elianddy Supeni & Azizan As’arry & Chun Kit Ang, 2019. "Identification and Prioritization of Risk Factors in an Electrical Generator Based on the Hybrid FMEA Framework," Energies, MDPI, vol. 12(4), pages 1-22, February.
    9. Zhang, Hengjie & Dong, Yucheng & Xiao, Jing & Chiclana, Francisco & Herrera-Viedma, Enrique, 2021. "Consensus and opinion evolution-based failure mode and effect analysis approach for reliability management in social network and uncertainty contexts," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    10. Carpitella, Silvia & Certa, Antonella & Izquierdo, Joaquín & La Fata, Concetta Manuela, 2018. "A combined multi-criteria approach to support FMECA analyses: A real-world case," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 394-402.
    11. Yifan Chen & Genbao Zhang & Yan Ran, 2019. "Risk Analysis of Coupling Fault Propagation Based on Meta-Action for Computerized Numerical Control (CNC) Machine Tool," Complexity, Hindawi, vol. 2019, pages 1-11, July.
    12. Chemweno, Peter & Pintelon, Liliane & Muchiri, Peter Nganga & Van Horenbeek, Adriaan, 2018. "Risk assessment methodologies in maintenance decision making: A review of dependability modelling approaches," Reliability Engineering and System Safety, Elsevier, vol. 173(C), pages 64-77.
    13. Salomon, Julian & Winnewisser, Niklas & Wei, Pengfei & Broggi, Matteo & Beer, Michael, 2021. "Efficient reliability analysis of complex systems in consideration of imprecision," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    14. Heng Zhang & Yaya Chen & Jingyu Cong & Junxiao Liu & Zhifu Zhang & Xirui Zhang, 2023. "Reliability Study of an Intelligent Profiling Progressive Automatic Glue Cutter Based on the Improved FMECA Method," Agriculture, MDPI, vol. 13(8), pages 1-17, July.
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