An evidence theory-based large group FMEA framework incorporating bounded confidence and its application in supercritical water gasification system

Supercritical water gasification (SCWG) is an advanced technology for sewage sludge treatment, which can effectively remove hazardous substances in it and realize the resource utilization of sludge. Given the harsh operating environment and complex operating process, it is particularly critical for SCWG system to adopt failure mode and effects analysis (FMEA) to ensure its reliability and security. In particular, the risk management process of SCWG system needs to include two considerations: the evaluation process requires the participation of a large number of team members (TMs) with different professional knowledge and operational skills, and the cross-correspondence between the factors within the system cannot be ignored in the analysis process. Thus, an FMEA framework is established to meet practical needs, which can model TMs' personality traits and reflect the interdependencies between factors. First, assessments in the form of probability linguistic term sets (PLTSs) are converted into mass functions due to the excellence of evidence theory in information aggregation. Second, a bounded confidence-based clustering method is developed to consider TMs' willingness to interact during clustering. Additionally, evidence conflicts are managed using a new discounting method that captures TMs' stubbornness. Besides, the cross-correspondence between factors is analyzed by an evidence theory-based DEMATEL method. Further considering TMs' bounded rationality, regret theory (RT) is used to distinguish and prioritize failure modes (FMs). Finally, a case study of an SCWG system is successfully solved by applying the proposed framework. The effectiveness and superiority are subsequently demonstrated by a series of analyses and discussions. (c) 2022 Elsevier B.V. All rights reserved.