Operations Management and Econometrics

Managing an Available-to-Promise Assembly System with Dynamic Short-Term Pseudo Order Forecast

Long Gao, Assistant Professor of Operations Management, AGSM, University of California

10th Jun 2011  11:00 am - Room 498, Merewether Building (H04)

We study an order promising problem in a multi-class, Available-to-Promise (ATP) assembly system in the presence of pseudo orders. A pseudo order refers to a tentative customer order whose attributes, such as the likelihood of an actual order, order quantity and con¯rmation timing, can change dynamically over time. Each product is assembled from two major components, with one component requiring one unit of production capacity and one unit of component inventory. An accepted order must be ¯lled before a positive delivery lead time. The underlying order acceptance decisions involve tradeo®s between committing resources (production capacity and component inventory) to low-reward ¯rm orders and reserving resources for high-reward orders. We develop a Markov chain model that captures the key characteristics of pseudo orders, including demand lumpiness, non-stationarity and volatility. We then formulate a stochastic dynamic program for the ATP assembly (ATP-A) system that embeds the Markov chain model as a short-term forecast for pseudo orders. We show that the optimal order acceptance policy is characterized by class prioritization, resource imbalance-based rationing and capacity-inventory-demand matching. In particular, the rationing level for each class is determined by a critical value that depends on the resource imbalance level, de¯ned as the net di®erence between the production capacity and component inventory levels. Extensive numerical tests underscore the importance of the key properties of the optimal policy and provide operational and managerial insights on the value of the short-term demand forecast and the robustness of the optimal policy.

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