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Publicações
Yazdi, M. (2019), “Footprint of knowledge acquisition improvement in failure diagnosis analysis”, Quality and Reliability Engineering International, Vol. 35, pp. 405–422
Fault tree analysis (FTA) as an effective and efficient risk assessment tool arewidely used to analyze the reliability of a complex system. In this context, FTAcan properly improve the safety performance of the system by preventing anevent which may lead to occurrence of a catastrophic accident. However, tradi-tional FTA is still suffering from dynamic structure demonstration and impor-tantly epistemic uncertainty processing. In this study, a novel methodology isintroduced using Bayesian updating mechanism to deal with dynamic structureand 2-tuple fuzzy set named as intuitionistic fuzzy numbers are employed to copewith subjectivity of uncertainty processing. Accordingly, the most critical systemcomponents which affect the system reliability are recognized by using an appro-priate sensitivity analysis method. The proposed methodology is then applied ona real case study application (a brake fluid filling system) in order to examine theeffectiveness and feasibility of the approach. The results illustrated that the newmethodology can have enough benefits for diagnosing the systems' faults com-pared with listing approaches of safety and reliability analysis. In terms of empir-ical case study,“electromotor failure”was evaluated as the second most criticalbasic event in conventional-based approaches, whereas in the novel methodol-ogy“high pressure liquefied material”was recognized as the second one.
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