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Failure Mode and Effects Analysis Based on Z-Numbers and the Graded Mean Integration Representation

Hanhan Zhang1, Zhihui Xu2, Hong Qian1, Xiaoyan Su1,*

1 School of Automation Engineering, Shanghai University of Electric Power, Shanghai, 200090, China
2 State Key Laboratory of Nuclear Power Safety Monitorig Technology and Equipment, Shenzhen, 518172, China

* Corresponding Author: Xiaoyan Su. Email:

(This article belongs to this Special Issue: Computer-Aided Structural Integrity and Safety Assessment)

Computer Modeling in Engineering & Sciences 2023, 134(2), 1005-1019.


Failure mode and effects analysis (FMEA) is a widely used safety assessment method in many fields. Z-number was previously applied in FMEA since it can take both possibility and reliability of information into consideration. However, the use of fuzzy weighted mean to integrate Z-valuations may have some drawbacks and is not suitable for some situations. In this paper, an improved method is proposed based on Z-numbers and the graded mean integration representation (GMIR) to deal with the uncertain information in FMEA. First, Z-numbers are constructed based on the evaluations of risk factors O, S, D for each failure mode by different experts. Second, weights of the three risk factors and experts are determined. Third, the integration representations of Z-numbers are obtained by a new method based on the GMIR method. Finally, risk priorities of the failure modes are derived considering the weights of experts and risk factors. Two examples and a case study are given to show the use of the proposed method and comparison with other methods. The results show that the proposed method is more reasonable, universal and simple in calculation.


Cite This Article

Zhang, H., Xu, Z., Qian, H., Su, X. (2023). Failure Mode and Effects Analysis Based on Z-Numbers and the Graded Mean Integration Representation. CMES-Computer Modeling in Engineering & Sciences, 134(2), 1005–1019.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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