Reliability Assessment of Man-Machine Systems Subject to Probabilistic Common Cause Errors

Human factors play an important role in man-machine systems (MMSs) and human errors (HEs) have serious consequences on system reliability. Multiple HEs may be affected by a common cause (CC), which can be caused by external events such as inappropriate organizational circumstances, extreme environmental conditions or by internal failures within the MMSs, such as equipment failure. These errors are known as the common cause error (CCE) and can contribute significantly to system risk. The impact of CCE can be either deterministic or probabilistic, where the probabilistic CCE (PCCE) is defined as any condition or event that results in multiple HEs occurring with different probabilities. A system subject to PCCE is sometimes affected by multiple CCs. However, the current study only considers the effect of CC on component failures while neglecting the effect on HE. This paper proposes an explicit method and an implicit method based on the CREAM to analyze the reliability of MMSs subjected to internal and external PCCEs. The proposed methods take into account the different relationships among multiple CCs in a single model, and are applicable to systems in which multiple CCs affect different HEs with different dependencies. Both of the proposed methods are illustrated through detailed analyzes of an example system.