Production planning for bulk recycling in electronics take-back centers

The amount of End-Of-Life (EOL) electronic equipment has grown rapidly in recent years while government legislations and penalties to prevent them from landfill are either being implemented or pending in many countries. Consequently, more companies are beginning to remanufacture and bulk recycle EOL electronic products. Several analytical models have been presented to address production planning and inventory control in remanufacturing. However, literature in bulk recycling is sparse, with only a few product and specific process-step focused models. This dissertation develops a new analytical approach to address short-term bulk recycling planning from a process perspective.; Currently, recyclers depend on experience to make the following short-term bulk recycling planning decisions: (1) determine processing and reprocessing level, (2) select products to accept or to direct ship, and (3) select products to process and to carry in inventory. In practice, production line personnel make decision (1) and marketing personnel make decisions (2) and (3). However, as the quantities and varieties of EOL product returns increase, it becomes more challenging to make these decisions only based on experience. Adding to these challenges are the variation of the quantity and variety of EOL products and the volatility of the price of recycled materials. Analytical models are needed to help recyclers make decisions (1) to (3). We initially develop two separate models to address decision (1) and decisions (2) and (3) independently. Due to the potential for increased EOL product returns, we further investigate the impact of the capacity constraints and develop an integrated model to address all three decisions simultaneously. We present a heuristic to find a lower bound to enhance the branch-and-search solution procedure for our model. Analytical and computational results are presented to verify the performance of the heuristic.; Finally a case study is performed to validate the integrated model and investigate the sensitivity of the three bulk recycling decisions to products from two different sources: industrial returns versus residential returns. The results of the case study show that the bulk recycling decisions are sensitive to the return sources.