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Forecasting spare part demand with installed base information: A review

Van der Auweraer, Sarah, Boute, Robert N. and Syntetos, Argyrios 2019. Forecasting spare part demand with installed base information: A review. International Journal of Forecasting 35 (1) , pp. 181-196. 10.1016/j.ijforecast.2018.09.002
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Abstract

The classical spare part demand forecasting literature studies methods for forecasting intermittent demand. However, the majority of these methods do not consider the underlying demand-generating factors. The demand for spare parts originates from the replacement of parts in the installed base of machines, either preventively or upon breakdown of the part. This information from service operations, which we refer to as installed base information, can be used to forecast the future demand for spare parts. This paper reviews the literature on the use of such installed base information for spare part demand forecasting in order to asses (1) what type of installed base information can be useful; (2) how this information can be used to derive forecasts; (3) the value of using installed base information to improve forecasting; and (4) the limits of the existing methods. This serves as motivation for future research.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Publisher: Elsevier
ISSN: 0169-2070
Date of First Compliant Deposit: 26 November 2018
Date of Acceptance: 25 September 2018
Last Modified: 13 Feb 2019 14:39
URI: http://orca.cf.ac.uk/id/eprint/117050

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