Abstract
This paper considers an inventory system responsible for repairable equipments located at several operational sites, each in different area. When a failure occurs at the operational site, spare parts are required. We analyze a multiple-supplier inventory system that includes an internal repair shop that offers several modes of repair with different repair times and an external supplier of spare parts. The network model of the problem presented here efficiently solves the problem for deterministic demands that vary over time with backorders taken into account.
Highlights
Inventory systems where units which fail are repaired at a repair shop, rather than discarded, are called repairable-item inventory systems
This paper considers an inventory system responsible for repairable equipments located at several operational sites, each in different area
When the fast repair time equals the lead-time from an external supplier, and since the cost of the fast repair is much cheaper than the purchase cost, almost all the spare parts that are needed come from the fast repair service
Summary
Inventory systems where units which fail are repaired at a repair shop, rather than discarded, are called repairable-item inventory systems. We assume a multi-echelon inventory system with several operational sites (the bases) and two supply modes: an external supplier and a repair shop (the depot). The motivation of our study is to develop a model for planning and predicting how many spare parts must be purchased from the external supplier and how many failed items need to be repaired, at either the fast, expedited track or the regular track, in order to achieve minimum operating costs. A different stream of literature (e.g., Abdul-Jalbar et al [14] and Federgruen et al [15]) focuses on studying the models where demands are predictable and deterministic Following this line of research, in this paper we assume that demand forecast in the forthcoming period is known. We describe the spare part supply system, introduce the parameters and variables and show how the objective function and the constraints are calculated
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