Technical Note—Optimal Procurement in Remanufacturing Systems with Uncertain Used-Item Condition
Emre Nadar, Mustafa Akan, Laurens Debo, Alan Scheller-Wolf
Operations Research · 2023 · Volume 71 · Issue 5
Abstract
We consider a single-product remanufacture-to-order system with multiple uncertain quality levels for used items, random procurement lead times, and lost sales. The quality level of a used item is revealed only after it is acquired and inspected; the remanufacturing cost is lower for a higher-quality item. We model this system as a Markov decision process and seek an optimal policy that specifies when a used item should be procured, whether an arriving demand for the remanufactured product should be satisfied, and which available item should be remanufactured to meet this demand. We characterize the optimal procurement policy as following a new type of strategy: state-dependent noncongestive acquisition. This strategy makes decisions, taking into account the system congestion level measured as the number of available items and their quality levels. We also show that it is always optimal to meet the demand with the highest-quality item among the available ones. We conclude with extensions of our model to limited cases when the used-item condition is known a priori (for two quality levels) and remanufacture-to-stock systems in which the standard push strategy is optimal in the remanufacturing stage. Supplemental Material: The e-companion is available at https://doi.org/10.1287/opre.2023.2483 .
Keywords
Operations and Supply Chains, used-item acquisition, inspection, remanufacturing, Markov decision processes, optimal control
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