Failure mode and effects analysis method based on Fermatean fuzzy weighted Muirhead mean operator

Failure mode and effects analysis (FMEA) is an important work in product reliability design. It can identify the weak links and key items in design through fault analysis, and provide basic information for evaluating and improving the reliability of system design. In view of the shortcomings of the existing FMEA method, such as the weak ability of experts to describe and process fuzzy information and the lack of consideration of the weight and correlation between risk factors. In this paper, by fusing Fermatean fuzzy sets (FFS) and Muirhead Mean (MM) operators, we propose Fermatean fuzzy weighted Muirhead mean (FFWMM) operator and develop a new FMEA method. Firstly, two new risk factors are proposed to overcome the shortcoming of insufficient consideration of the FMEA method. By introducing FFS, the ability of experts to express fuzzy information is enhanced. Using FFWMM operator to aggregate evaluation information can deal with the weight and correlation between influencing factors well. Finally, an example is given to illustrate the superiority of the proposed method. (c) 2023 Elsevier B.V. All rights reserved.

Automated summary

Failure mode and effects analysis (FMEA) is an important task in product reliability design as it helps identify weak areas and key components in the design. This paper introduces a new FMEA method that addresses the limitations of existing methods, such as the inability to handle fuzzy information and consider the weight and correlation of risk factors. By integrating Fermatean fuzzy sets (FFS) and Muirhead Mean (MM) operators, the proposed method enhances the expression of fuzzy information and effectively deals with the weight and correlation between influencing factors.