Managing an Assemble-to-Order System with Returns

Abstract

We consider a multiproduct assemble-to-order (ATO) system, in which inventory is kept only at the component level and the finished products are assembled in response to customer demands. In addition to stochastic demand for finished products, the system experiences stochastic returns of subsets of components, which can then be used to satisfy subsequent demands. The system is managed over an infinite horizon using a component-level base-stock policy. We identify several ways in which returns complicate the behavior of the system, and we demonstrate how to handle these additional complexities when calculating or approximating key order-based performance metrics, including the immediate fill rate, the fill rate within a time window, and average backorders. We also present a method for computing a near-optimal base-stock policy. We use these results to address managerial questions on both operational and product-design levels. For example, we find that tracking product-based (as opposed to component-based) return information appears to provide much less value than tracking product-based demand information, and we explore the impact of the number of products, component lead times, and different patterns of component returns (joint versus independent returns, returns of common versus dedicated components) on the value of component commonality.