Remanufacturing operations rely upon accurate forecasts of demand and returned items. Return timing and quantity forecasts help estimate net demand (demand minus returns) requirements. Based on a unique data set of serialized transactional issues and returns from the Excelitas Group and one of their defense contractors, Qioptiq, we assess the empirical performance of some key methods in the area of returns forecasting. We extend their application (for net demand forecasting), by considering that demand is also subject to uncertainty and thus needs to be forecast. Information on remanufacturing costs allows for an evaluation of the inventory implications of such forecasts under various settings. A foray into the literature on information technologies enables a discussion on the interface between information availability and forecast accuracy and utility. We find that serialization accounts for considerable forecast accuracy benefits, and that the accuracy of demand forecasts is as important as that of returns. Further, we show how the combined returns and demand forecast uncertainty affects the inventory performance. Finally, we identify opportunities for further improvements for the operations of Qioptiq, and for remanufacturing operations in general.

Additional Metadata
Keywords empirical data, forecasting, remanufacturing, simulation
Persistent URL dx.doi.org/10.1002/joom.1031, hdl.handle.net/1765/117257
Journal Journal of Operations Management
Citation
Goltsos, T.E. (Thanos E.), Syntetos, A.A. (Aris A.), & van der Laan, E.A. (2019). Forecasting for remanufacturing: The effects of serialization. Journal of Operations Management. doi:10.1002/joom.1031