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Distributed Hierarchical Production Control for Wafer Fabs Using an Agent-Based System Prototype

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Part of the book series: International Handbooks on Information Systems ((INFOSYS))

Abstract

FABMAS is a hierarchically organized multiagent system for production control of semiconductor wafer fabrication facilities (wafer fabs). The production control of wafer fabs is challenging from a complexity and coordination point of view. Semiconductor manufacturing involves one of the most complex manufacturing processes ever used. In this paper, we describe the application domain and major design decisions that lead to the FABMAS system prototype. A detailed discussion of the suggested software architecture of the agent-based system is included. Furthermore, we present the results of computational experiments that show that FABMAS outperforms dispatching based production control schemes that are currently in use. The paper also discusses some limitations and drawbacks of the suggested approach and identifies areas of future research.

For more information on the FAB Multi Agent System (FABMAS) we refer to: http://www.mirtschaft.tu-ilmenau.de/deutsch/institute/wi/wil/projekt/start.html

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References

  1. Agent-Enhanced Manufacturing System Initiative (AEMSI), 2005. http://www.altarum.org/-altarum/ESD/research_agent_complex.asp#aemsi.

    Google Scholar 

  2. Atherton, L. F.; Atherton, R. W.: Wafer Fabrication: Factory Performance and Analysis. Kluwer Academic Publishers, Boston et al., 1995.

    Google Scholar 

  3. Babiceanu, R. F.; Chen, F. F.; Sturges, R. H.: Framework for the Control of Automated Material-Handling Systems Using the Holonic Manufacturing Approach. In: International Journal of Production Research 42(2004)17, pp. 3551–3564.

    Article  Google Scholar 

  4. Bussmann, S.; Jennings, N. R.; Wooldridge, M.: On the Identification of Agents in the Design of Production Control Systems. In: Agent-Oriented Software Engineering. Springer, pp. 141–162.

    Google Scholar 

  5. Caridi, M.; Cavalieri, S.: Multi-agent Systems in Production Planning and Control: An Overview. In: Production Planning & Control 15(2004)2, pp. 106–118.

    Article  Google Scholar 

  6. El Adl, M. K.; Rodriguez, A. A.; Tsakalis, K. S.: Hierarchical Modeling and Control of Re-entrant Semiconductor Manufacturing Facilities. In: Proceedings of the 35th Conference on Decision and Control. Kobe, Japan, pp. 1736–1742.

    Google Scholar 

  7. Fargher, H. E.; Kilgore, M., A.; Kleine, P. J.; Smith, R. A.: A Planner and Scheduler for Semiconductor Manufacturing. In: IEEE Transactions on Semiconductor Manufacturing 7, pp. 117–126.

    Google Scholar 

  8. Fowler, J. W.; Feigin, G.; Leachman, R.: Semiconductor Manufacturing Testbed Data Sets. Arizona State University, 1995.

    Google Scholar 

  9. Hadavi, K. C.: A Real Time Production Scheduling System from Conception to Practice. In: Zweben, M.; Fox, M. S. (Eds.): Intelligent Scheduling. Morgan Kaufmann, San Francisco, CA, 1994, pp. 581–604.

    Google Scholar 

  10. Kempf, K.: Intelligently Scheduling Semiconductor Wafer Fabrication. In: Zweben, M.; Fox, M. S. (Eds.): Intelligent Scheduling. Morgan Kaufmann, San Francisco, CA, 1994, pp. 517–544.

    Google Scholar 

  11. Lawler, E. L.: A “Pseudopolynomial” Time Algorithm for Sequencing Jobs to Minimize Total Weighted Tardiness. In: Annals of Discrete Mathematics 1, pp. 331–342.

    Google Scholar 

  12. Mathirajan, M.; Sivakumar, A. I.: Scheduling Batch Processors in Semiconductor Manufacturing — A Review. Singapore MIT Alliance (SMA) 2003 Symposium, National University of Singapore. https://dspace.mit.edu/retrieve/3521/-IMST021.

    Google Scholar 

  13. Mason, S. J.; Fowler, J. W.; Carlyle, W. M.: A Modified Shifting Bottleneck Heuristic for Minimizing Total Weighted Tardiness in Complex Job Shops. In: Journal of Scheduling 5(2002)3, pp. 247–262.

    Article  MATH  MathSciNet  Google Scholar 

  14. McFarlane, D. C.; Bussmann, S.: Developments in Holonic Production Planning and Control. In: Production Planning & Control 11(2000)6, pp. 522–536.

    Article  Google Scholar 

  15. Mesarovic, M. D.; Macko, D.; Takahara, Y.: Theory of Hierarchical, Multilevel Systems. Academic Press, New York, London, 1970.

    MATH  Google Scholar 

  16. Min, H. S.; Yih, Y.: Development of a Real-Time Multi-Objective Scheduler for a Semiconductor Fabrication System. In: International Journal of Production Research 41(2003)10, pp. 2345–2364.

    Article  Google Scholar 

  17. Mönch, L.; Driessel, R.: A Distributed Shifting Bottleneck Heuristic for Complex Job Shops. In: Computers & Industrial Engineering 49(2005), pp. 363–380.

    Article  Google Scholar 

  18. Mönch, L.; Rose, O.: Shifting-Bottleneck-Heuristik für komplexe Produktionssysteme: softwaretechnische Realisierung und Leistungsbewertung. In: Suhl, L.; Voss, S. (Eds.): Quantitative Methoden in ERP und SCM, DSOR Beiträge zur Wirtschaftsinformatik 2, pp. 145–159.

    Google Scholar 

  19. Mönch, L.; Stehli, M.: An Ontology for Production Control of Semiconductor Manufacturing Processes. In: Proceedings of the First German Conference on Multiagent System Technologies (MATES 2003), LNAI 2831. Springer, Erfurt, Germany, pp. 156–167.

    Google Scholar 

  20. Mönch, L.; Stehli, M.: A Content Language for a Hierarchically Organized Multi-Agent-System for Production Control. In: Proceedings Coordination and Agent Technology in Value Networks. Essen, Germany, pp. 197–212.

    Google Scholar 

  21. Mönch, L.; Stehli, M.: ManufAG: a Multi-Agent-System Framework for Production Control of Complex Manufacturing Systems. To appear in Journal of Information Systems & E-Business Management.

    Google Scholar 

  22. Mönch, L.; Stehli, M.; Schulz, R.: An Agent-Based Architecture for Solving Dynamic Resource Allocation Problems in Manufacturing. In: Proceedings of the 14th European Simulation Symposium (ESS 2002). Dresden, 2002, pp. 331–337.

    Google Scholar 

  23. Mönch, L.; Rose, O.; Sturm, R.: A Simulation Framework for Accessing the Performance of Shop-Floor Control Systems. In: SIMULATION: Transactions of the Society of Modeling and Computer Simulation International 79(2003)3, pp. 163–170.

    Article  Google Scholar 

  24. Odell, J.; Parunak, H. V. D.; Fleischer, M.: Modeling Agent Organizations Using Roles. In: Software and Systems Modeling 2(2003), pp. 76–81.

    Article  Google Scholar 

  25. Pfund, M. E.; Fowler, J. W.: Survey of Scheduling and Dispatching Practice in Semiconductor Industry. Forthcoming.

    Google Scholar 

  26. Schneeweiss, C.: Distributed Decision Making. Springer, New York, Heidelberg, Berlin, 2003.

    MATH  Google Scholar 

  27. Shen, W.; Norrie, D. H.: Agent-Based Systems for Intelligent Manufacturing: a State-of-the-Art Survey. In: Knowledge and Information Systems 1(1999)2, pp. 129–156.

    Google Scholar 

  28. Srivatsan, N.; Bai, S. X.; Gershwin, S. B.: Hierarchical real-time integrated scheduling of a semiconductor fabrication facility. In: Control and Dynamic Systems 61, pp. 197–241.

    Google Scholar 

  29. Sullivan, G.; Fordyce, K.: IBM Burlington’s Logistics Management System. In: Interfaces 20(1990)1, pp. 43–64.

    Article  Google Scholar 

  30. Uzsoy, R.; Lee, C.-Y.; Martin-Vega, L. A.: A Review of Production Planning and Scheduling Models in the Semiconductor Industry, part II: Shop-Floor Control. In: IIE Transactions on Scheduling and Logistics 26(1994)5, pp. 44–55.

    Google Scholar 

  31. Van Brussel, H.; Wyns, J.; Valckenaers, P.; Bongaerts, L.; Peeters, P.: Refernce Architecture for Holonic Manufacturing Systems: PROSA. In: Computers in Industry 37(1998)3. Special Issue on Intelligent Manufacturing Systems, pp. 225–276.

    Google Scholar 

  32. Vargas-Villamil, F. D.; Rivera, D. E.: A Model Predictive Control Approach for Real-Time Optimization of Reentrant Manufacturing Lines. In: Computers in Industry 45(2001), pp. 45–57.

    Article  Google Scholar 

  33. Vargas-Villamil, F. D.; Rivera, D. E.; Kempf, K. G.: A Hierarchical Approach to Production Control of Reentrant Semiconductor Manufacturing Lines. In: IEEE Transactions on Control Systems Technology 11(2003)3, pp. 578–587.

    Article  Google Scholar 

  34. Vrba, P.: JAVA-based Agent Platform Evaluation. In: Proceedings Holonic and Multi-Agent-Systems for Manufacturing (HoloMAS), 2003, pp. 47–58.

    Google Scholar 

  35. Wooldridge, M.; Jennings, N.: Software Engineering with Agents: Pitfalls and Pratfalls. In: IEEE Internet Computing. May-June 1999, pp. 20–27.

    Google Scholar 

  36. Zambonelli, F.; Jennings, N.; Wooldridge, M.: Developing Multiagent Systems: the Gaia Methodology. In: ACM Transactions on Software Engineering and Methodology 12(2003)3, pp. 317–370.

    Article  Google Scholar 

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Mönch, L., Stehli, M., Zimmermann, J. (2006). Distributed Hierarchical Production Control for Wafer Fabs Using an Agent-Based System Prototype. In: Kirn, S., Herzog, O., Lockemann, P., Spaniol, O. (eds) Multiagent Engineering. International Handbooks on Information Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32062-8_8

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  • DOI: https://doi.org/10.1007/3-540-32062-8_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-31406-6

  • Online ISBN: 978-3-540-32062-3

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