Forecasting spare part demand with installed base information: a Review

Abstract

The classical spare part demand forecasting literature studies methods to forecast intermittent demand. The majority of these methods do not consider the underlying demand generating factors. Demand for spare parts originates from the part replacements of the installed base of machines, which are either done 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 future spare part demand. In this paper we review the literature on the use of such installed base information for spare part demand forecasting to asses (1) what type of installed base information can be useful; (2) how this information can be used to derive forecasts; (3) what is the value of using installed base information to improve forecasting; and (4) what are the limits of the currently existing methods. The latter serve as motivation for future research.