Effects of redundancy management on reliability modeling

Two methods are investigated for incorporating the effects of fault detection and isolation (FDI) decision errors and redundancy management (RM) policy into reliability models for a simple single-component-dual-redundant system. These two methods are combinatorial analysis and Markov chain modeling. Reliability analysts have traditionally chosen the classical combinatorial approach. However, the authors show that the existence of time-ordered event sequences resulting from the interaction of FDI decision errors with the RM policy considerably complicates the construction of the combinatorial model. An error analysis illustrates that a simplified combinatorial model, which ignores these time-ordered event sequences, inaccurately predicts the system reliability. The Markov modeling technique is an excellent alternative to the combinatorial approach because it easily and accurately accounts for time-ordered event sequences such as those present in fault-tolerant systems