A risk evaluation and prioritization method for FMEA with prospect theory and Choquet integral. (December 2018) - Wang, Weizhong; Liu, Xinwang; Qin, Yong; Fu, Yong
Highlights: A new risk assessment method in FMEA is proposed with prospect theory and fuzzy set. The Choquet integral is used to model interdependence among risk factors. A new fuzzy number ranking method is used to determine risk priority of failure mode. Comparisons with other FMEA methods is done to verify validity of the proposed FMEA. Abstract: Failure modes and effect analysis (FMEA) as one of the most effective risk analysis methods, has been widely adopted in various fields to improve the security and reliability of systems. The risk evaluation and prioritization of failure mode is an important issue in FMEA approach, which can be regarded as a MCDM (multi-criteria decision making) problem. Different researches indicate that the decision maker's psychological behavior and interaction relationships among risk factors have a major impact on this process. Nevertheless, such influence is neglected in the existing literature on FMEA approach. In this paper, a new approach considering decision maker's psychological behavior and interaction relationships among risk factors simultaneously is developed to solve the risk evaluation and prioritization in FMEA method. First, to consider the FMEA team member's psychological behavior in the risk evaluation in FMEA approach, the prospect theory is adopted to determine risk evaluation of risk factors. Second, with regard to the interaction relationships among risk factors, the fuzzy measure and Choquet integral are used to aggregate the prospect value of failure modes on each risk factors. After calculating prospect value of each failure mode, the entropy weighting method is employed to obtain the overall risk priority number (RPN) associated with each failure mode, and the relative preference relation is introduced for failure mode's prioritization. Finally, an illustrative case of aircraft landing system is selected to demonstrate the application and feasibility of the proposed hybrid FMEA method, and a comparison study is also performed to validate the effectiveness of the novel FMEA model.