Modeling dependence in the inter-failure times. An analysis in Reliability models by Markovian Arrival Processes

The most common assumptions in reliability studies are that failures occur independently and with the same distribution. However, these two assumptions are unrealistic in practice since inter-failure times are usually correlated and not identically distributed. In this sense the Markov Arrival Process (MAP) is an active research field for managing these features. We study two versions of the MAP approach. The first one is a model which we developed in previous works. The second one is based on a non-stationary MAP of second order. We compare the results of both models with simulated data.