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

Authors:
Jing-Sheng Song;David D. Yao
Affiliations:
-;-
Venue:
Operations Research
Year:
2002

Citing 0
Cited 12

Production and Inventory Control of a Single Product Assemble-to-Order System with Multiple Customer Classes

Management Science
Production and Inventory Control of a Single Product Assemble-to-Order System with Multiple Customer Classes

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Optimal Component Stocking Policy for Assemble-to-Order Systems with Lead-Time-Dependent Component and Product Pricing

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The Value of Component Commonality in a Dynamic Inventory System with Lead Times

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The Effect of Lead Time and Demand Uncertainties in (r, q) Inventory Systems

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No-Holdback Allocation Rules for Continuous-Time Assemble-to-Order Systems

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The Value of Flexibility in Make-to-Order Systems: The Effect of Demand Correlation

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A Stochastic Programming Based Inventory Policy for Assemble-to-Order Systems with Application to the W Model

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TECHNICAL NOTE---Optimal Product Pricing and Component Production Quantities for an Assembly System Under Supply Uncertainty

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Comparing Markov Chains: Aggregation and Precedence Relations Applied to Sets of States, with Applications to Assemble-to-Order Systems

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Technical Note---A Note on the Structure of Joint Inventory-Pricing Control with Leadtimes

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A Supply Network's Optimal Information System and Material Flows

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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 ofM/ G/8 queues with a common arrival stream. We show that unlike the standardM/ G/8 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.