Parametric Approaches for Spare Parts Demand

Oumaima Bounou (Faculty of Sciences and Techniques, Mechanical Engineering Laboratory, Sidi Mohammed Ben Abdellah University, FEZ, Morocco)
Abdellah El Barkany (Faculty of Sciences and Techniques, Mechanical Engineering Laboratory, Sidi Mohammed Ben Abdellah University, FEZ, Morocco)
Ahmed El Biyaali (Faculty of Sciences and Techniques, Mechanical Engineering Laboratory, Sidi Mohammed Ben Abdellah University, FEZ, Morocco)

International Journal of Supply Chain Management
Vol 7, No 4 (2018): International Journal of Supply Chain Management (IJSCM)

Forecasting of the spare parts needs is an important operational question. The problem in the needs forecast is that the demand is intermittent. In stock management, there are several forecasting tools based on demand history such as: linear regression, basic and modified Croston methods, simple and weighted moving average, exponential smoothing, and finally the bootstrap method. In this paper, we will treat the last method through three sections: literature review, procedure of the method and finally an application of the method which will be compared to simple exponential smoothing and hybrid method.