Integrated spare parts logistics and operations planning for maintenance service providers

This paper considers the problem of coordinated spare-part logistics and operations planning for third-party maintenance providers. Due to the multi-indenture structure of the equipment, different types of components might randomly fail to perform at different points of time. The spare part logistics literature has been focused on spare part inventory management in an in-house maintenance context. In this article, a mathematical programming model is first developed to formulate the problem in the context of a third-party maintenance provider who is faced with strict due dates for the delivery of repaired equipment. The model seeks the optimal number of maintenance jobs that can be completed to deliver at each period, as well as the order quantity of spare parts so as to minimize the procurement, inventory, and equipment late delivery costs, while taking into account the spare part supply lead-time. Next, we model the spare part demand uncertainty as a non-stationary stochastic process in each period in the planning horizon. The deterministic model is then reformulated as a multi-stage stochastic program with recourse. We also discuss the complexity of the stochastic model and propose a preprocessing approach to reduce its size for large instances. Numerical results demonstrate how the proposed model links the spare part logistics and equipment delivery decisions under spare part demand uncertainty.