Consensus and opinion evolution-based failure mode and effect analysis approach for reliability management in social network and uncertainty contexts

Abstract As a forward-looking reliability-management engineering technique, failure mode and effect analysis (FMEA) has been widely utilized to improve the reliability of products, processes, systems, and services. In practice, multiple responsible parties for FMEA implementation have different backgrounds, knowledge levels, and opinions. Integrating consensus into FMEA has some notable merits: the connections between FMEA participants can be strengthened, and a collective solution with a high degree of acceptability to the FMEA problem can be yielded. Meanwhile, the social network relationship among FMEA participants should be an essential element in FMEA because the participants’ opinions are subject to influence by each other and likely to evolve due to their social network interactions. Thus, this study first proposes a social network consensus model with minimum adjustment distance to assist FMEA participants in attaining a consensus, in which participants utilize a linguistic distribution assessment approach to represent their opinions. Second, an opinion evolution-based social network consensus model with minimum adjustment distance is further presented by considering the phenomenon of opinion evolution. Finally, some theoretical analyses, a case study, and a detailed comparative analysis are presented to verify the validity of the proposed FMEA approach.