Dynamic priority repair policy for service parts supply chain

We study a repairable service parts inventory system with a central repair facility and several inventory holding locations. In case of a part failure, the failed part is identified and replaced with a ready-to-use part. Afterwards, the failed part is sent to the repair facility, where it is repaired and allocated to one of the bases. The objective is to identify the base with the most urgent need of a service part in order to minimize the expected backorder cost. To this aim, we investigate the initial base-stock provisioning problem in conjunction with the real time stock allocation decision making. We propose a heuristic technique for stock allocation based on relative value function and average backorder cost. We compare the performance of the heuristic model against the myopic policy to validate the efficiency of our proposed mechanism. Results reveal that the proposed stock allocation policy outperforms the myopic policy.