An improved reliability model for FMEA using probabilistic linguistic term sets and TODIM method
Jia Huang,
Hu-Chen Liu (),
Chun-Yan Duan () and
Ming-Shun Song
Additional contact information
Jia Huang: China Jiliang University
Hu-Chen Liu: Tongji University
Chun-Yan Duan: Shanghai University
Ming-Shun Song: China Jiliang University
Annals of Operations Research, 2022, vol. 312, issue 1, No 12, 235-258
Abstract:
Abstract Failure mode and effects analysis (FMEA) is known to be a proactive reliability analysis model broadly utilized to recognize and evaluate potential failure modes in various industries. The normal risk priority number (RPN) method, however, has suffers from a lot of criticisms, such as requirement of precise risk estimation, lack of scientific basis in computing RPN, and neglecting the weights of risk factors. Therefore, this paper devises a new FMEA model to evaluate and prioritize the risk of failure modes by integrating probabilistic linguistic term sets and TODIM (an acronym in Portuguese for interactive multi-criteria decision making) method. The probabilistic linguistic term sets are utilized to handle the intrinsic ambiguity existed in the risk assessments of FMEA team members, whilst an extended TODIM method is employed for determining the priority ranking of the individuated failure modes. Further, based on the technique for order of preference by similarity to ideal solution (TOPSIS), an objective weighting method is presented to derive the relative weights of risk factors. Finally, two illustrative examples are implemented and comparisons with other existing methods are performed to demonstrate the rationality and superiority of our proposed FMEA model.
Keywords: Reliability modeling; Failure mode and effects analysis (FMEA); Probabilistic linguistic term set; TODIM method; Risk assessment (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10479-019-03447-0
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