PROJECT TITLE :

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

ABSTRACT:

Parts are usually subject to multiple competing degradation processes. For multicomponent systems, the degradation dependence inside one component or/and among parts would like to be thought of. Physics-based mostly models and multistate models are often used for part degradation processes, notably when statistical data are restricted. During this paper, we treat dependence between degradation processes among a piecewise-deterministic Markov process (PDMP) modeling framework. Epistemic (subjective) uncertainty can arise due to the incomplete or imprecise knowledge regarding the degradation processes and also the governing parameters, to require this under consideration, 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 technique is tested on one subsystem of the residual heat removal system of a nuclear power plant, and a comparison is obtainable with a Monte Carlo simulation solution the results show that our technique will be best.