Analysis of cascading probabilistic common cause failures

Abstract

AbstractCommon cause failures may contribute significantly to the reliability of a system and has attracted considerable research attentions. However, the existing models often assumed deterministic failures of components affected by the common cause (CC) and no cascading effects. This paper contributes by modeling cascading probabilistic common cause failures (CPCCFs), where a CC may cause multiple system components to fail with different probabilities and some components may fail in a domino chain manner. An explicit, analytical method is proposed for the reliability analysis of systems subject to CPCCFs, which may be triggered by external or internal CCs. The complex cascading effects are modeled using a directed acyclic graph structure. The proposed method has no limitation on the component time‐to‐failure distributions. Applications and advantages of the proposed method are illustrated through a detailed case study of a safety instrumented system for oil and gas transportation. Correctness of the proposed method is verified by Monte Carlo simulations. The time and space complexity of the method is also studied.