LAUSR

Abstract Failure mode and effect analysis (FMEA) is a systematic and multidisciplinary team-based reliability analysis technology used in various industries, which can alleviate the failure risk of products, systems and services. The experts are usually drawn from different departments or areas. Thus, it is important to promote the consensus of experts to produce a collective solution with a high degree of acceptability for reliability assessment of FMEA. Meanwhile, there may be social influence relationships between experts, i.e., their opinions can interact and evolve. Hence, this study first integrates group consensus-reaching mechanism into the FMEA approach. Then, according to the uncertainty and similarity of expert assessments of each risk factor of FMEA, heterogeneous social networks among experts are constructed for opinion interaction, which exactly describes the professional expertise and influence of experts. Considering the important role of opinion dynamics and social network dissemination, dynamic heterogeneous social network consensus reaching model (DHSNCRM) with the minimum adjustment distance is further designed to help experts reach a consensus and obtain the consentient priority of failure modes by using a two-stage feedback process. Finally, a case study of reliability management of the intelligent minimally invasive medical equipment system is presented to verify the effectiveness of our proposed FMEA method.