A novel failure mode and effect analysis method with spherical fuzzy entropy and spherical fuzzy weight correlation coefficient

As a proactive reliability analysis technique, the purpose of failure mode and effect analysis (FMEA) is the detection of all failures and their effects within a system, and the determination of the causes of these failures. However, the traditional FMEA method shows some important drawbacks regarding failure mode evaluations, risk factor weights and risk priority ranking, etc. This paper aims to develop a novel FMEA to improve the performance of FMEA by using spherical fuzzy sets (SFSs) and spherical fuzzy weight correlation coefficient (SF-WCC). The method mainly includes three stages. The SFS is applied to capture risk evaluation information because it comprehensively considers the information expression in different scenarios in the first stage. A spherical fuzzy projection model is introduced to calculate the expert weights objectively for reducing the information difference caused by experience, psychology and other cognitive factors of experts in the second stage. Meanwhile, the spherical fuzzy entropy is defined to determine the incomplete weights of risk factors by constructing an optimization model in the second stage. The SF-WCC is proposed to prioritize the failure modes to avoid the prioritization controversy of failure modes by using different distance formulas in the third stage. In the experiment, a practical example is presented to illustrate the applicability and effectiveness of the proposed method, and results show that the proposed approach offers a reliable tool for practical FMEA problems. The conclusion is that the proposed method is applicable to multiple actual scenarios as a reliable risk assessment technology.

Automated summary

This paper presents a new method to improve the performance of the traditional failure mode and effect analysis (FMEA) by using spherical fuzzy sets (SFSs) and spherical fuzzy weight correlation coefficient (SF-WCC). The method includes three stages: capturing risk evaluation information using SFS, determining expert weights objectively using a spherical fuzzy projection model, and prioritizing failure modes using SF-WCC. The experiment demonstrates the applicability and effectiveness of the proposed method, indicating it as a reliable risk assessment technology for practical FMEA problems.