A scalable multi-objective maintenance optimization model for systems with multiple heterogenous components and a finite lifespan

Delivering after-sales maintenance services is a challenging task for original equipment manufacturers who must tailor their offers to customers’ needs. To accommodate this challenge, we propose a multi-objective optimization model to derive optimal maintenance policies for systems with a large number of heterogeneous components over a finite lifespan. Based on the practical assumption of a fixed time interval between two consecutive scheduled downs, we develop a decomposition approach that enables the fast computation of the optimal policy per component and the optimal time interval between two consecutive scheduled visits. We also analyze the structural properties of the optimal policies for both age-based and condition-based maintenance and prove that they have a non-static control-limit structure. Using a set of computational experiments, we first investigate the computational tractability of our model for systems with an increasing number of components. Then, we apply our model to a real case study to demonstrate how it can be used to derive optimal maintenance policies tailored to different customer needs