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Hybrid discrete event simulation with model predictive control for semiconductor supply-chain manufacturing
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Source Winter Simulation Conference archive
Proceedings of the 37th conference on Winter simulation table of contents
Orlando, Florida
SESSION: Modeling methodology A: DEVS and multi-formalism modeling table of contents
Pages: 256 - 266  
Year of Publication: 2005
ISBN:0-7803-9519-0
Authors
Hessam S. Sarjoughian  Arizona State University, Tempe, AZ
Dongping Huang  Arizona State University, Tempe, AZ
Gary W. Godding  Arizona State University, Tempe, AZ
Karl G. Kempf  Decision Technologies Intel Corporation, Chandler, AZ
Wenlin Wang  Arizona State University, Tempe, AZ
Daniel E. Rivera  Arizona State University, Tempe, AZ
Hans D. Mittelmann  Arizona State University, Tempe, AZ
Publisher
Winter Simulation Conference 
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Downloads (6 Weeks): 5,   Downloads (12 Months): 58,   Citation Count: 4
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ABSTRACT

Simulation modeling combined with decision control can offer important benefits for analysis, design, and operation of semiconductor supply-chain network systems. Detailed simulation of physical processes provides information for its controller to account for (expected) stochasticity present in the manufacturing processes. In turn, the controller can provide (near) optimal decisions for the operation of the processes and thus handle uncertainty in customer demands. In this paper, we describe an environment that synthesizes Discrete-EVent System specification (DEVS) with Model Predictive Control (MPC) paradigms using a Knowledge Interchange Broker (KIB). This environment uses the KIB to compose discrete event simulation and model predictive control models. This approach to composability affords flexibility for studying semiconductor supply-chain manufacturing at varying levels of detail. We describe a hybrid DEVS/MPC environments via a knowledge interchange broker. We conclude with a comparison of this work with another that employs the Simulink/MATLAB environment.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Sarjoughian, H. S. and F. E. Cellier, eds. 2001. Discrete Event Modeling and Simulation Technologies: A Tapestry of Systems and AI-Based Theories and Methodologies, Springer Verlag.
 
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Collaborative Colleagues:
Hessam S. Sarjoughian: colleagues
Dongping Huang: colleagues
Gary W. Godding: colleagues
Karl G. Kempf: colleagues
Wenlin Wang: colleagues
Daniel E. Rivera: colleagues
Hans D. Mittelmann: colleagues