After-sales services during an asset’s lifetime: collaborative planning of system upgrades

We consider a continuous-time stochastic model that aims to find an optimal upgrade policy for a single system in an asset with a fixed overhaul planning. In a novel model, we include the key critical factors that may drive an asset owner to upgrade a system: increasing functionality requirements due to evolving technology, age-dependent maintenance costs, a predetermined overhaul plan, and a finite lifetime of the asset. We characterize the structure of the optimal upgrade policy through analytical results, and use these to establish an efficient solution approach based on dynamic programming. We also consider the effects of the input parameters on the optimal total costs, both analytically as well as numerically.