Inventory Allocation at a Semiconductor Company

  • Alexander O. Brown
  • Markus Ettl
  • Grace Y. Lin
  • Raja Petrakian
  • David D. Yao
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 42)

Abstract

Properly managing inventory is a challenging but critical problem for high-technology manufacturers. Due to rapidly declining manufacturing costs and high obsolescence risk, holding inventory is very expensive and risky. Customers often require near immediate availability of a large variety of products with highly uncertain demand and long lead times. Thus, manufacturers must hold high levels of inventory despite the expense and risk. Xilinx, a firm that produces programmable logic integrated circuits (ICs) for sale to original equipment manufacturers, faces this situation. In the programmable logic industry, manufacturing costs decline at rates of anywhere from 20% to 75% annually, and obsolescence costs are on the order of 5–10% of the gross inventory. As of 1999, Xilinx had upwards of 10,000 different finished products, only about 5% of which would be classified as having stable demand; total manufacturing lead times were 2–3 months; and a significant fraction of customer orders were requests to be filled same-day. A high level of serviceability is critical since although an IC may only be one component of hundreds in a customer’s product, delays in delivery may shutdown a production line. Thus, service is a critical characteristic in supplier selection and retention. To meet this high level of service with long lead times and uncertain demands, leading programmable logic manufacturers in 1998 were holding very large inventories, 80 to 150 dollar days-of-inventory, despite the risk and expense. (The inventory measured in dollar days is the net inventory divided by the average cost of goods sold per day.)

Keywords

Supply Chain Finish Good Safety Stock Backorder Cost Supply Chain Structure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • Alexander O. Brown
    • 1
  • Markus Ettl
    • 2
  • Grace Y. Lin
    • 2
  • Raja Petrakian
    • 3
  • David D. Yao
    • 4
  1. 1.Manugistics, Inc.San MateoUSA
  2. 2.IBM Research DivisionT.J. Watson Research CenterYorktown HeightsUSA
  3. 3.Xilinx, Inc.San JoseUSA
  4. 4.IEOR DepartmentColumbia UniversityNew YorkUSA

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