Uncertainty Management in Assessment of FMEA Expert Based on Negation Information and Belief Entropy

Lei Wu, Yongchuan Tang, Liuyuan Zhang, Yubo Huang

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

The failure mode and effects analysis (FMEA) is a commonly adopted approach in engineering failure analysis, wherein the risk priority number (RPN) is utilized to rank failure modes. However, assessments made by FMEA experts are full of uncertainty. To deal with this issue, we propose a new uncertainty management approach for the assessments given by experts based on negation information and belief entropy in the Dempster–Shafer evidence theory framework. First, the assessments of FMEA experts are modeled as basic probability assignments (BPA) in evidence theory. Next, the negation of BPA is calculated to extract more valuable information from a new perspective of uncertain information. Then, by utilizing the belief entropy, the degree of uncertainty of the negation information is measured to represent the uncertainty of different risk factors in the RPN. Finally, the new RPN value of each failure mode is calculated for the ranking of each FMEA item in risk analysis. The rationality and effectiveness of the proposed method is verified through its application in a risk analysis conducted for an aircraft turbine rotor blade.

Original languageEnglish
Article number800
JournalEntropy
Volume25
Issue number5
DOIs
StatePublished - May 2023

Keywords

  • belief entropy
  • Dempster–Shafer evidence theory
  • multi-source information fusion
  • negation evidence
  • uncertainty

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