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

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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

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Description

<jats:p> 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. </jats:p>

Journal

  • Operations Research

    Operations Research 51 (2), 292-308, 2003-04

    Institute for Operations Research and the Management Sciences (INFORMS)

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