Selecting Failure Countermeasures through Decision Network Analysis

We propose a framework for the selection of failure countermeasures and repair actions, based on Decision Networks (DN). We show, through specific examples, that standard probabilistic inference on DN can be used to compute system reliability, component importance measures, as well as to select the best (in terms of Maximum Expected Utility) set of failure countermeasures to activate. Finally, by exploiting the DN formalism, both modeling and analysis capabilities are improved with respect to standard combinatorial models, without resorting to the complexity of global state-space models.