Modeling and Analysis of a Scheduled Maintenance System: a DSPN Approach

This paper describes a way to manage the modeling and analysis of Scheduled Maintenance Systems (SMS) within an analytically tractable context. We chose a significant case study having a variety of interesting features like a heavily redundant architecture and a test and maintenance policy whose execution is made on-line without halting the system. We apply a methodology we previously developed based on the Deterministic Stochastic Petri Net (DSPN) approach where the underlying stochastic process is Markov regenerative (MRGP) solved in our setting with efficient analytical solution method. The model construction and its analysis have been carried out with the help of a tool for the modeling and the dependability evaluation of the Phased Mission Systems (PMS). We exercise our methodology with such case study, to check whether it can master real and complex SMS problems and compare its efficacy with traditional approaches (fault trees). At the same time the paper investigates the problem of the optimal tuning of a maintenance program, giving a useful decision support tool to evaluate the system performance since the early design stage.