Abstract

Failure mode effects and criticality analysis (FMECA) is widely used, by developing a Risk Priority Number (RPN), to identify the failure modes and to prioritize them. But this has been extensively criticized due to several drawbacks in the literature. This issue can be solved partly by using Fuzzy FMECA (FFMECA) although Fuzzy logic itself has been criticized of having a direct bearing on subjectivity. This paper makes use of Dempster-Shafer Theory (DST) of evidence-a proper mathematical framework to deal with the epistemic uncertainty often affecting the input evaluations of risk parameters. DST based FMECA is capable of providing an appropriate, precise and fault-free, failure mode prioritization. Belief and Plausibility distributions are used to synthesize the obtainable information and to make them useful for the purpose. The results obtained from DST-FMECA is compared to the results drawn from the FFMECA applications (already conducted in the liquefied natural gas (LNG) storage facility) to validate FFMECA and vice versa. The comparative results presented in this paper establish the capabilities of both the approaches, especially in a complex system like the LNG storage and similar facilities where even a minor failure may lead to catastrophic effects.

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