Imperfect Preventive Maintenance Policy for Complex Systems Based on Bayesian Networks

The main challenge in maintenance planning lies in the realistic modeling of the maintenance policy. This paper is focused on the maintenance optimization of complex repairable systems using Bayesian networks. A new policy is developed for periodic imperfect preventive maintenance policy with minimal repair at failure; this policy allows us to take into consideration several types of preventive maintenance with different efficiency levels. The Bayesian networks are used for complex system modeling, allowing the evaluation of the model parameters. The Weibull parameters and the maintenance efficiency are evaluated thanks to the proposed methodology using Bayesian inference. The approach developed in this paper is applied on a real system, to determine the optimal maintenance plan for a turbo‐pump in oil industry.