Order Fill Rate, Leadtime Variability, and Advance Demand Information in an Assemble-to-Order System

Yingdong Lu (), Jing-Sheng Song () and David D. Yao ()
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Yingdong Lu: IBM Research Division, T. J. Watson Research Center, Yorktown Heights, New York 10598
Jing-Sheng Song: Graduate School of Management, University of California, Irvine, California 92697
David D. Yao: Department of Industrial Engineering and Operations Research, Columbia University, New York, New York 10027

Operations Research, 2003, vol. 51, issue 2, 292-308

Abstract: We study an assemble-to-order system with stochastic leadtimes for component replenishment. There are multiple product types, of which orders arrive at the system following batch Poisson processes. Base-stock policies are used to control component inventories. We analyze the system as a set of queues driven by a common, multiclass batch Poisson input, and derive the joint queue-length distribution. The result leads to simple, closed-form expressions of the first two moments, in particular the covariances, which capture the dependence structure of the system. Based on the joint distribution and the moments, we derive easy-to-compute approximations and bounds for the order fulfillment performance measures. We also examine the impact of demand and leadtime variability, and investigate the value of advance demand information.

Keywords: Inventory/production: assemble-to-order; multi-item; operating characteristics; Queues: simultaneous arrivals; infinite server; Probability: generating functions; moments; stochastic comparison (search for similar items in EconPapers)
Date: 2003
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Citations: View citations in EconPapers (45)

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