Optimal Redundancy Allocation in Multi-Indenture Systems Considering Human Error-Induced Common Cause Failures

This paper deals with a redundancy allocation optimization problem (RAOP) for multi-indenture systems under common cause failures (CCF). A beta-factor model for CCF is applied to predict the system reliability in multi-indenture systems. Human errors are considered a main source of CCFs, and it is assumed that the effects of CCFs depend on the hierarchical system structure, and CCFs exist in redundancy at the lowest level (component level). A beta-factor model is used to represent CCF effects, including human-error-related factors such as maintenance, installation, and operational errors. The proposed model compares the reliability effects of component-level and module-level redundancy under CCF. A genetic algorithm (GA) is used to determine the optimal redundant objects and redundant numbers that maximize system reliability under a design cost constraint. The sensitivity analysis is performed to investigate the effect of model parameters on the objective function and the optimal solutions. The effects of CCF on the system reliability between module-level redundancy and component-level redundancy are compared in numerical examples.