Adjusting Remanufacturing Capacity Using Sales and Return Information

Abstract

<p>This paper considers a multi-period capacity adjustment problem for remanufacturing a product with a limited lifecycle. Product returns constitute a demand for remanufacturing capacity. Utilizing sales history, the problem is to determine a capacity expansion and contraction policy that maximizes the expected net revenue from remanufactured products minus all the capacity-related costs. We assume that when the returns surpass the available capacity levels then it is required to expand capacity to meet the shortage on an emergency basis. Using a Markov decision process, we formulate the current capacity level and the current number of items sold but not yet returned as the state variable. We describe a simple optimal policy of capacity expansion and contraction for the single period using properties of K-concave functions. The policy consists of threshold values and target levels that depend on the number of items yet to be returned.</p>