Fuzzy Reliability Assessment of Systems With Multiple-Dependent Competing Degradation Processes

• Published in: IEEE transactions on fuzzy systems Vol. 23; no. 5; pp. 1428 - 1438
• Main Authors: Yan-Hui Lin, Yan-Fu Li, Zio, Enrico
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); Institute of Electrical and Electronics Engineers
• Subjects: Biological system modeling; Computer simulation; Degradation; Electric power; Engineering Sciences; epistemic uncertainty; Equations; finite-volume (FV) method; Fuzzy; Fuzzy logic; fuzzy reliability; Fuzzy set theory; Fuzzy systems; Markov analysis; Mathematical model; Mathematical models; Mechanical properties; Multiple dependent competing degradation processes; Nuclear power plants; piecewise-deterministic Markov process (PDMP); Reliability; Transaction processing; Uncertainty; Valves; Epistemic uncertainty; piecewise-deterministic Markov process (PDMP); finite-volume (FV) method; fuzzy set theory; multiple-dependent competing degradation processes; fuzzy reliability
• ISSN: 1063-6706; 1941-0034
• DOI: 10.1109/TFUZZ.2014.2362145

Components are often subject to multiple competing degradation processes. For multicomponent systems, the degradation dependence within one component or/and among components need to be considered. Physics-based models and multistate models are often used for component degradation processes, particularly when statistical data are limited. In this paper, we treat dependence between degradation processes within a piecewise-deterministic Markov process (PDMP) modeling framework. Epistemic (subjective) uncertainty can arise due to the incomplete or imprecise knowledge about the degradation processes and the governing parameters, to take this into account, we describe the parameters of the PDMP model as fuzzy numbers. Then, we extend the finite-volume method to quantify the (fuzzy) reliability of the system. The proposed method is tested on one subsystem of the residual heat removal system of a nuclear power plant, and a comparison is offered with a Monte Carlo simulation solution the results show that our method can be most efficient.