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A new method to evaluate risk in failure mode and effects analysis under fuzzy information

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Abstract

Failure mode and effects analysis (FMEA) is a useful and effective tool to identify and mitigate project risk, which utilizes the risk priority number (RPN) to determine the risk priority order of failure modes. In many applications when multiple experts give their opinions about one failure mode, the risk evaluations can be vague and imprecise, which could arise conflicting evidence that is hard to manage. To address this issue, the information offered by experts should be analyzed under a model of fuzzy numbers and Dempster–Shafer (D–S) combination theory. Here, the traditional RPN is not sufficient for risk evaluation. A new RPN is proposed in this paper with two parts. The first part is a product of memberships whose average degrees are equal to one, and the second part results from applying the Dempster–Shafer theory with tools of evidential downscaling method and belief entropy function. The new RPN can be effective and convictive to handle conflicting evidence in FEMA.

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Acknowledgements

The work is partially supported by National Natural Science Foundation of China (Grant No. 61671384), Natural Science Basic Research Plan in Shaanxi Province of China (Program No. 2016JM6018), Aviation Science Foundation (Program No. 20165553036), and the Fund of SAST (Program No. SAST2016083).

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Authors and Affiliations

  1. School of Electronics and Information, Northwestern Polytechnical University, Xi’an, 710072, China

    Zhiming Huang, Wen Jiang & Yongchuan Tang

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  1. Zhiming Huang
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  2. Wen Jiang
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  3. Yongchuan Tang
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Correspondence to Wen Jiang.

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Zhiming Huang declares that he has no conflict of interest. Wen Jiang declares that she has no conflict of interest. Yongchuan Tang declares that he has no conflict of interest.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by V. Loia.

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Huang, Z., Jiang, W. & Tang, Y. A new method to evaluate risk in failure mode and effects analysis under fuzzy information. Soft Comput 22, 4779–4787 (2018). https://doi.org/10.1007/s00500-017-2664-x

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