Performance analysis and optimization of assemble-to-order systems with random lead times

Published

Journal Article

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/∞ queues with a common arrival stream. We show that unlike the standard M/G/∞ 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.

Full Text

Duke Authors

Cited Authors

  • Song, JS; Yao, DD

Published Date

  • January 1, 2002

Published In

Volume / Issue

  • 50 / 5

International Standard Serial Number (ISSN)

  • 0030-364X

Digital Object Identifier (DOI)

  • 10.1287/opre.50.5.889.372

Citation Source

  • Scopus