Hybrid approach to forecast returns of scrapped products to recycling and remanufacturing

Forecasting of scrapped products to recycling poses severe problems to recycling and remanufacturing companies due to uncertainties in available data. In this paper an extended prediction method to forecast return values (amount and time) of scrapped products to recycling is presented. The suggested model is based on important influencing factors and product life cycle data and has been applied to a case study (photocopiers) for evaluation. The approach employs a simulation study, the design of a fuzzy inference system for the prediction of the return in a specific planning period and the design of a neuro-fuzzy system for the prediction of return values with respect to time.