Determining core acquisition quantities when products have long return lags

Abstract

An important problem faced in closed-loop supply chains is ensuring a sufficient supply of reusable products (i.e., cores) to support reuse activities. Accurate forecasting of used product returns can assist in effectively managing the sourcing activities for cores. The application of existing forecasting models to actual data provided by an Original Equipment Manufacturer (OEM) remanufacturer resulted in the following challenges: (i) inherent difficulties in estimation due to long return lags in the data and (ii) required adjustments for initial conditions. This article develops methods to address these issues and illustrates the proposed approach using the data provided by the OEM remanufacturer. The cost implications of using the proposed method to source cores are also investigated. Results of the performed analysis showed that the proposed forecasting approach performed best when the product is in the maturity or decline stages of its life cycle, with the rate of product returns balanced with the demand volume for the remanufactured product. Forecasting product returns can therefore be best leveraged for reducing the acquisition costs of cores in such settings.