Forecasting and Inventory Management for Spare Parts: An Installed Base Approach

Forecasting spare part demand using service maintenance information

“…In addition, the majority of the methods makes restrictive distributional assumptions, for example on the failure behaviour of the parts. Exceptions to this are Minner (2011) and the extension of his model by Wu & Bian (2015). Their methods are applicable in every phase of the PLC and are not restrictive on the distributional assumptions.…”

“…Those works tend to focus on only a specific subset of installed base information and the combination of these different demand drivers is generally lacking. Moreover, the literature typically makes a distinction between forecasting models for spare part demand for preventive maintenance (e.g., Hu et al, 2015;Romeijnders et al, 2012;Wang & Syntetos, 2011;Wang, 2011) and forecasting demand for corrective maintenance (e.g., Hong et al, 2008;Jin & Liao, 2009;Kim et al, 2017;Minner, 2011;Stormi et al, 2018), sometimes also referred to as reliability based forecasting. Both are rarely combined, however.…”

The value of installed base information for spare part inventory control

“…We refer to those characteristics as the installed base information (IBI). In the literature the following sources of IBI have been introduced: the size of the installed base (e.g., Jalil et al, 2011;Stormi et al, 2018) and its evolution over time (e.g., Jin and Liao, 2009;Kim et al, 2017), the age of the installed base (e.g., Kim et al, 2017;, the age of the parts in the products/machines (e.g., Deshpande et al, 2006;Minner, 2011), the part reliability (e.g., Ritchie and Wilcox, 1977;Hong et al, 2008), which can be impacted by environmental factors (e.g., Ghodrati and Kumar, 2005a,b), and the maintenance policy in place (e.g., Wang and Syntetos, 2011;Zhu et al, 2020).…”

“…Other authors implicitly assume that the true size of the installed base active at a certain point in time is known and use this information to predict demand (see for example, Ghodrati and Kumar, 2005b;Jalil et al, 2011;Lin et al, 2017;Stormi et al, 2018). Some works (additionally) consider the anticipation of potential future discards, decreasing the number of active machines (see for example Chou et al, 2015Chou et al, , 2016Kim et al, 2017;Minner, 2011;Stormi et al, 2018;, or expiring service contracts (Pince et al, 2015) as a source of IBI. Similarly, Hong et al (2008), Lu and Hjelle (2016), Lu and Wang (2015), and Ritchie and Wilcox (1977) also include in their forecasts the probability of a future failed part not being replaced, based on, for example, the active machine being too old.…”

On a method to improve your service BOMs within spare parts management

“…Taking this variable into account is discussed by various authors, e.g. Jalil et al (2011), Minner (2011), Dekker et al (2013, and Kim et al (2017), and is referred to as installed base forecasting. A recent paper by van der Auweraer et al (2019) gives an overview of the literature related to this topic.…”