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    The value of installed base information for spare part inventory control

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    Publication type
    Vlerick strategic journal article
    Author
    Van der Auweraer, Sarah
    Zhu, Sha
    Boute, Robert
    Publication Year
    2021
    Journal
    International Journal of Production Economics
    Publication Volume
    239
    Publication Issue
    September
    
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    Abstract
    This paper analyzes the value of different sources of installed base information for spare part demand forecasting and inventory control. The installed base is defined as the set of products (or machines) in use where the part is installed. Information on the number of products still in use, the age of the products, the age of their parts, as well as the part reliability may indicate when a part will fail and trigger a demand for a new spare part. The current literature is unclear which of this installed base information adds most value – and should thus be collected – for inventory control purposes. For this reason, we evaluate the inventory performance of eight methods that include different sets of installed base information in their demand forecasts. Using a comparative simulation study we identify that knowing the size of the active installed base is most valuable, especially when the installed base changes over time. We also find that when a failure-based prediction model is used, it is important to work with the part age itself, rather than the machine age. When one is not able to collect information on the part age, a logistic regression on the machine age might be a valuable alternative to a failure-based prediction model. Our findings may support the prioritization of data collection for spare part demand forecasting and inventory control.
    Keyword
    Installed Base Information, Forecasting, Dynamic Inventory Control, Spare Parts, Value of Information
    Knowledge Domain/Industry
    Operations & Supply Chain Management
    DOI
    10.1016/j.ijpe.2021.108186
    URI
    http://hdl.handle.net/20.500.12127/6946
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.ijpe.2021.108186
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