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Model Predictive Control in Semiconductor Supply Chain Operations

In: Planning Production and Inventories in the Extended Enterprise

Author

Listed:
  • Karl Kempf

    (Intel Corporation)

  • Kirk Smith
  • Jay Schwartz
  • Martin Braun

Abstract

Maintaining agility in a multi-echelon multi-product multi-geography supply chain with long and variable manufacturing lead times, stochastic product yields, and uncertain demand is a difficult goal to achieve. The approach advocated here is based on a practical application of control theory that includes a model of the system being controlled, feedback from previous results, feed-forward based on demand forecasts, and optimization of both the financial results and the control actions applied to achieve them. This Model Predictive Control (MPC) approach has been employed in the continuous-flow process industry for many years, and has been independently suggested for supply chains by a number of academic research teams. This chapter describes a large-scale application of the approach in the semiconductor industry.

Suggested Citation

  • Karl Kempf & Kirk Smith & Jay Schwartz & Martin Braun, 2011. "Model Predictive Control in Semiconductor Supply Chain Operations," International Series in Operations Research & Management Science, in: Karl G Kempf & Pınar Keskinocak & Reha Uzsoy (ed.), Planning Production and Inventories in the Extended Enterprise, chapter 0, pages 403-428, Springer.
    • Handle: RePEc:spr:isochp:978-1-4419-8191-2_16
    DOI: 10.1007/978-1-4419-8191-2_16
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    Cited by:

    1. Chen, Yenming J. & Sheu, Jiuh-Biing & Lirn, Taih-Cherng, 2012. "Fault tolerance modeling for an e-waste recycling supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(5), pages 897-906.

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