Condition-based joint maintenance optimization for a large-scale system with homogeneous units

A joint maintenance policy that simultaneously repairs multiple units is useful for large-scale systems where the setup cost to initiate the maintenance is generally higher than the repair costs. This study proposes a new method for scheduling maintenance activities in a large-scale system with homogeneous units that degrade over time. Specifically, we consider the maintenance type that renews all units at each maintenance activity, which is practically applicable for systems where the units need to be regularly maintained. To make the analysis computationally tractable, we discretize the health condition of each unit into a finite number of states. The proposed optimization formulation triggers the maintenance activity based on the fraction of units at each degradation state. Based on relevant asymptotic theories, we analytically obtain the optimal threshold in the fraction of units at each state that minimizes the long-run average maintenance cost. Our implementation results with a wide range of parameter settings show that the proposed maintenance strategy is more cost-effective than alternative strategies.