期刊
IEEE TRANSACTIONS ON RELIABILITY
卷 72, 期 3, 页码 1107-1122出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TR.2022.3215110
关键词
Cloud model; decision-making trial and evaluation laboratory (DEMATEL); failure mode and effect analysis; interaction; Shapley-LINMAP
Failure mode and effect analysis (FMEA) is a powerful tool for reliability management that has been widely applied in various fields. However, the interaction among experts, risk factors, and failure modes in the FMEA framework is often neglected. Therefore, this study proposes an improved FMEA method that comprehensively considers the interaction between each part. The effectiveness and superiority of the method are verified through a case study of automatic transmission (AMT) in new energy vehicles, enriching the theoretical research of FMEA and improving the reliability of AMT risk assessment.
Failure mode and effect analysis (FMEA) is a powerful tool for reliability management that has been widely applied in a variety of areas. The interaction relationship exists in the whole process of FMEA risk assessment, and has an important impact on it. However, few scholars consider the interaction among experts, risk factors, and failure modes in theFMEAframework. Therefore, we propose an improved FMEA method, which comprehensively considers the interaction between each part. First, the Choquet integral is used to improve the incomplete part of the social trust network, then the importance of experts is determined. Second, the Shapley-LINMAP linear programming method based on cloud model is proposed to calculate the weight of risk factors. Finally, the improved decision-making trial and evaluation laboratory method based on cloud model is used to rank the failure modes. By applying the method proposed in this article to the case of automatic transmission (AMT) of new energy vehicles, the effectiveness and superiority can be verified fromthe comparison analysiswith other methods, which enriches the theoretical research of the FMEA method and improves the reliability of risk assessment of AMT.
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