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Stein–Chen approximation and error bounds for order fill rates in assemble‐to‐order systems
Authors:Wenhui Zhou  Xiuli Chao
Institution:1. School of Business Administration, South China University of Technology, Guangzhou 510640, China;2. Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan 48109
Abstract:Assemble‐to‐order (ATO) is an important operational strategy for manufacturing firms to achieve quick response to customer orders while keeping low finished good inventories. This strategy has been successfully used not only by manufacturers (e.g., Dell, IBM) but also by retailers (e.g., Amazon.com). The evaluation of order‐based performance is known to be an important but difficult task, and the existing literature has been mainly focused on stochastic comparison to obtain performance bounds. In this article, we develop an extremely simple Stein–Chen approximation as well as its error‐bound for order‐based fill rate for a multiproduct multicomponent ATO system with random leadtimes to replenish components. This approximation gives an expression for order‐based fill rate in terms of component‐based fill rates. The approximation has the property that the higher the component replenishment leadtime variability, the smaller the error bound. The result allows an operations manager to analyze the improvement in order‐based fill rates when the base‐stock level for any component changes. Numerical studies demonstrate that the approximation performs well, especially when the demand processes of different components are highly correlated; when the components have high base‐stock levels; or when the component replenishment leadtimes have high variability. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012
Keywords:assemble‐to‐order system  order fill rate  convex ordering  Stein–  Chen approximation  error bounds  M/G/∞  queue
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