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Forecasting spare part demand using service maintenance information
Van der Auweraer, Sarah Boute, Robert
Van der Auweraer, Sarah
Boute, Robert
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Publication Type
Journal article with impact factor
Editor
Supervisor
Publication Year
2019
Journal
International Journal of Production Economics
Book
Publication Volume
213
Publication Issue
July
Publication Begin page
138
Publication End page
149
Publication Number of pages
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Abstract
We focus on the inventory management of critical spare parts that are used for service maintenance. These parts are commonly characterised by a large variety, an intermittent demand pattern and oftentimes a high shortage cost. Specialized service parts models focus on improving the availability of parts whilst limiting the investment in inventories. We develop a method to forecast the demand of these spare parts by linking it to the service maintenance policy. The demand of these parts originates from the maintenance activities that require their use, and is thus related to the number of machines in the field that make use of this part (known as the active installed base), in combination with the part's failure behaviour and the maintenance plan. We use this information to predict future demand. By tracking the active installed base and estimating the part failure behaviour, we provide a forecast of the distribution of the future spare parts demand during the upcoming lead time. This forecast is in turn used to manage inventories using a base-stock policy. Through a simulation experiment, we show that our method has the potential to improve the inventory-service trade-off, i.e., it can achieve a certain cycle service level with lower inventory levels compared to the traditional forecasting techniques for intermittent spare part demand. The magnitude of the improvement increases for spare parts that have a large installed base and for parts with longer replenishment lead times.
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Keywords
Inventory Management, Forecasting, Spare Parts, Service Maintenance, Installed Base