A Modified Deterministic Model for Reverse Supply Chain in Manufacturing
Technology is becoming pervasive across all facets of our lives today. Technology innovation leading to development of new products and enhancement of features in existing products is happening at a faster pace than ever. It is becoming difficult for the customers to keep up with the deluge of new technology. This trend has resulted in gross increase in use of new materials and decreased customers' interest in relatively older products. This paper deals with a novel model in which the stationary demand is fulfilled by remanufactured products along with newly manufactured products. The current model is based on the assumption that the returned items from the customers can be remanufactured at a fixed rate. The remanufactured products are assumed to be as good as the new ones in terms of features, quality, and worth. A methodology is used for the calculation of optimum level for the newly manufactured items and the optimum level of the remanufactured products simultaneously. The model is formulated depending on the relationship between different parameters. An interpretive-modelling-based approach has been employed to model the reverse logistics variables typically found in supply chains (SCs). For simplicity of calculation a deterministic approach is implemented for the proposed model.