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Performance Analysis and Optimization of Assemble-to-Order Systems with Random Lead Times

Author

Listed:
  • 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)

Abstract

We study a single-product assembly system in which the final product is assembled to order whereas the components (subassemblies) are built to stock. Customer demand follows a Poisson process, and replenishment lead times for each component are independent and identically distributed random variables. For any given base-stock policy, the exact performance analysis reduces to the evaluation of a set of M / G /(infinity) queues with a common arrival stream. We show that unlike the standard M / G /(infinity) queueing system, lead time (service time) variability degrades performance in this assembly system. We also show that it is desirable to keep higher base-stock levels for components with longer mean lead times (and lower unit costs). We derive easy-to-compute performance bounds and use them as surrogates for the performance measures in several optimization problems that seek the best trade-off between inventory and customer service. Greedy-type algorithms are developed to solve the surrogate problems. Numerical examples indicate that these algorithms provide efficient solutions and valuable insights to the optimal inventory/service trade-off in the original problems.

Suggested Citation

  • Jing-Sheng Song & David D. Yao, 2002. "Performance Analysis and Optimization of Assemble-to-Order Systems with Random Lead Times," Operations Research, INFORMS, vol. 50(5), pages 889-903, October.
    • Handle: RePEc:inm:oropre:v:50:y:2002:i:5:p:889-903
    DOI: 10.1287/opre.50.5.889.372
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    References listed on IDEAS

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