Powering stochastic reliability models by discrete event simulation

Markov reliability models are widely practiced tools for the analysis of repairable systems. Nevertheless, the assumptions of the Markov model may appear too restrictive to adequately model a real system and the explosion in the number of states as the size of the system increases may make it difficult to find a solution to the problem.

The power of modern computers and recent developments in discrete-event simulation (DES) software enable to diminish some of the drawbacks of stochastic models. In this paper we describe the insights we have gained based on using both Markov and DES models for simple systems. By contrasting the results of the two models we illuminate their advantages and disadvantages as well as we conclude that it is a good way of model validation.