| Hybrid discrete event simulation with model predictive control for semiconductor supply-chain manufacturing |
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Winter Simulation Conference
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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
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Authors
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Hessam S. Sarjoughian
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Arizona State University, Tempe, AZ
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Dongping Huang
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Arizona State University, Tempe, AZ
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Gary W. Godding
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Arizona State University, Tempe, AZ
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Karl G. Kempf
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Decision Technologies Intel Corporation, Chandler, AZ
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Wenlin Wang
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Arizona State University, Tempe, AZ
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Daniel E. Rivera
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Arizona State University, Tempe, AZ
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Hans D. Mittelmann
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Arizona State University, Tempe, AZ
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Winter Simulation Conference
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| Bibliometrics |
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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Singh, R., H. S. Sarjoughian and G. W. Godding. 2004. Design of Scalable Simulation Models for Semiconductor Manufacturing Processes. Summer Computer Simulation Conference, San Jose, CA.
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CITED BY 4
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Dongping Huang , Hessam S. Sarjoughain , Gary W. Godding , Daniel E. Rivera , Karl G. Kempf, Flexible experimentation and analysis for hybrid DEVS and MPC models, Proceedings of the 37th conference on Winter simulation, December 03-06, 2006, Monterey, California
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