Centralized Model Predictive Control Strategies for Inventory Management in Semiconductor Manufacturing Supply Chains

Wenlin Wang, Daniel Rivera, Karl G. Kempf

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Scopus citations

Abstract

Centralized strategies based on Model Predictive Control (MPC) are applied to inventory management problems associated with semiconductor supply chains. Specifically, two benchmark problems of relevance to semiconductor manufacturing are examined. The first is a single product, two node problem consisting of a Fab/Sort and an Assembly/Test facility controlled with a predictive controller using anticipation. The performance of the control scheme under conditions of plant-model mismatch and unforecasted demand are evaluated. The insights gained from this problem are used in the design of a centralized MPC controller for a four node problem involving two interconnected Fab/Sort and Assembly/Test facilities. In this latter problem, inventory management of wafer, die, and package inventories are considered.

Original languageEnglish (US)
Title of host publicationProceedings of the American Control Conference
Pages585-590
Number of pages6
Volume1
StatePublished - 2003
Event2003 American Control Conference - Denver, CO, United States
Duration: Jun 4 2003Jun 6 2003

Other

Other2003 American Control Conference
CountryUnited States
CityDenver, CO
Period6/4/036/6/03

ASJC Scopus subject areas

  • Control and Systems Engineering

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  • Cite this

    Wang, W., Rivera, D., & Kempf, K. G. (2003). Centralized Model Predictive Control Strategies for Inventory Management in Semiconductor Manufacturing Supply Chains. In Proceedings of the American Control Conference (Vol. 1, pp. 585-590)