Remanufacturing Planning with Different Quality Levels for Product Returns

In this paper we consider a tactical production planning problem for remanufacturing when returned products have different quality levels due to different conditions of the returns. The remanufacturing cost increases as the quality level decreases, and any unused returns may be salvaged at a fixed salvage value per unit. Decision variables include the amount to remanufacture each period for each return quality level and the amount of inventory to carry over for future periods for both returns (unremanufactured), and finished remanufactured products. Our model is grounded with data collected at Pitney Bowes from their mailing systems remanufacturing operations. The problem may be formulated as a linear program, given demand forecasts over a planning horizon, and it has a network-like structure. We derive some analytic properties for the optimal solution. We find that, given some conditions on holding costs, the firm always remanufactures the exact demand in each period. We also study the value of a nominal quality grading system in planning production. Based on data obtained from Pitney Bowes and other large remanufacturers, we analyze, via a numerical study, the increase in costs observed by the firm if it does not maintain separate inventory levels for each quality grade. The results show that a grading system decreases cost by 11% over a wide range of parameter values commonly found in the remanufacturing industry. We also numerically explore the case where there are capacity constraints and find the average improvement of a grading system remains around 11%. Finally, we test a simple heuristic policy where a grading system is utilized but no inventory may be carried for demand in future periods. Our numerical tests show a cost increase of only 3% over the cost of the optimal policy