Dependability analysis is a crucial tool in the control of risk that is a result of failures in modern complex industrial systems. This paper proposes a modelling approach that constructs dynamic models of fault-tolerant (FT) systems based on stochastic activity networks (SANs). This approach allows the systematic inclusion of diagnosis performance in the dependability analysis. This SAN model is used jointly with Monte Carlo simulation to assess the impact of the diagnosis performance on the availability of a FT system when various redundancy and maintenance policies are employed.
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