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An improved failure mode and effects analysis method based on uncertainty measure in the evidence theory
Author(s) -
Wu Dongdong,
Tang Yongchuan
Publication year - 2020
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.2660
Subject(s) - ambiguity , failure mode and effects analysis , reliability (semiconductor) , dempster–shafer theory , ranking (information retrieval) , measure (data warehouse) , reliability engineering , computer science , process (computing) , discounting , risk analysis (engineering) , risk management , data mining , engineering , machine learning , economics , medicine , power (physics) , physics , management , finance , quantum mechanics , programming language , operating system
mode and effects analysis (FMEA) is an effective tool to assess the risk of a system or process under uncertain environment. However, how to handle the uncertainty in the subjective assessment is an open issue. In this paper, a novel method to deal with the uncertainty coming from subjective assessments of FMEA experts is proposed in the framework of Dempster–Shafer evidence theory. First, the uncertain degree of the assessment is measured by the ambiguity measure. Then, the uncertainty is transformed to the reliability of each FMEA expert and the relative importance of each risk factor. After that, the assessments from FMEA team will be fused with a discounting‐based combination rule to address the potential conflict. Moreover, to avoid the situation that different risk priorities of failure modes may have the same ranking based on classical risk priority number method, the gray relational projection method (GRPM) is adopted for ranking risk priorities of failure modes. Finally, an application of the improved FMEA model in sheet steel production process verifies the reliability and validity of the proposed method.