An α-cut interval-based similarity aggregation method to evaluate fault tree events for system safety under fuzzy environment
Authors :- Mohit Kumar
Publication :- Engineering Reliability and Risk Assessment (Elsevier), Pages 185-200, 2023.
In real-world applications, it may be problematic to collect accurate and adequate quantitative failure data of system components to evaluate system reliability. This chapter presents a novel fuzzy set theory–based methodology to evaluate system failure probability by estimating the probabilities of basic events through qualitative failure data processing in the absence of quantitative failure data. An α-cut interval-based similarity aggregation method is employed to aggregate the opinions of different experts for failure possibilities of basic events. The presented approach applies α-cut interval-based arithmetic operations on fuzzy numbers. Employing α-cut interval-based arithmetic operations has significant advantage in fault tree analysis. Finally, the applicability of presented approach is demonstrated by considering a real-life safety system.