Dynamic repair priority rule based on remaining useful life predictions

In this paper, we propose a novel repair priority rule for spare parts in a repair station with limited repair capacity to minimize total inventory cost per time unit. Inventory cost is composed of holding costs and backorder costs. The proposed rule uses Remaining Useful Life (RUL) predictions of functioning machines obtained from a Prognostics and Health Monitoring (PHM) system. An inventory system comprising a finite number of machines, one warehouse, and one single-server repair station is considered. Numerical experiments were conducted to compare the performance of the proposed model with the performance of three existing priority rules: a first-come, first-served (FCFS) rule, a static priority rule, and a dynamic priority rule. A testbed with 20 instances of the problem was considered. The results showed that the proposed PHM-based rule consistently reduces the inventory system cost.