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Simulation of Manufacturing Systems

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Book cover Applied System Simulation

Abstract

Today’s manufacturing systems are highly complex and many are very costly to build and maintain. Discrete Event Simulation (DES) has an important role to play in managing these systems. The process of simulating manufacturing systems and some key application areas are discussed. Finally, some things that have limited the proliferation of DES in manufacturing systems are discussed.

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References

  1. Naylor, T. H., J. L. Balintfy, D. S. Burdick, and K. Chu. Computer Simulation Techniques. John Wiley and Sons, New York, New York, 1996.

    Google Scholar 

  2. Chance, F., Robinson, J., and J. Fowler, “Supporting manufacturing with simulation: model design, development, and deployment”, Proceedings of the 1996 Winter Simulation Conference, San Diego, CA, 1996, pp. 1–8.

    Google Scholar 

  3. Yücesan, E. and J. Fowler, “Simulation analysis of manufacturing and logistics systems“, Encyclopedia of Production and Manufacturing Management, Kluwer Academic Publishers, Boston, P. Swamidass ed., 2000, pp. 687–697.

    Chapter  Google Scholar 

  4. Shantikumar, J.G. and R.G. Sargent, “A unifying view of hybrid simulation/analytic models and modeling.” Operations Research, vol. 31, pp. 1030–1052, 1983.

    Article  Google Scholar 

  5. Pritsker, A.A.B., “Developing analytic models based on simulation results.” Proceedings of the 1989 Winter Simulation Conference, 1989, pp. 653–660.

    Google Scholar 

  6. Yücesan, E. and J. Fowler, “Simulation software selection“, Encyclopedia of Production and Manufacturing Management, Kluwer Academic Publishers, Boston, P. Swamidass ed., 2000, pp. 709–712.

    Chapter  Google Scholar 

  7. Hyden, P., Schruben, L., and T. Roeder, “Resource graphs for modeling large-scale, highly congested systems”, Proceedings of the 2001 Winter Simulation Conference, 2001, pp. 523–529.

    Google Scholar 

  8. Bratley, P., B. Fox and L. Schrage, A Guide to Simulation (2nd Ed.), Springer-Verlag. New York, 1987.

    MATH  Google Scholar 

  9. Law, A.M. and D.W. Kelton. Simulation Modeling and Analysis (2nd Ed.), McGraw-Hill, New York, 1991.

    Google Scholar 

  10. Jankauskas, L. and S. McLafferty, “BESTFIT, Distribution fitting software by Palisade Corporation.” Proceedings of the 1996 Winter Simulation Conference, 1996, pp. 551–555.

    Google Scholar 

  11. Law, A.M. and M.G. McComas, “Pitfalls to avoid in the simulation of manufacturing systems.” Industrial Engineering, vol. 31, 1989, pp. 28–31,69.

    Google Scholar 

  12. Cheng, R.H.C., W. Holland, and N.A. Hughes, “Selection of input models using bootstrap goodness of fit.” Proceedings of the 1996 Winter Simulation Conference, 1996, pp. 199–206.

    Google Scholar 

  13. Leemis, L., “Input modelling techniques for discrete-event simulation,” Proceedings of the 2001 Winter Simulation Conference, 2001, 62–73.

    Google Scholar 

  14. Yücesan, E. and S.H. Jacobson, “Computational issues for accessibility in discrete event simulation.” ACM Transactions on Modeling and Computer Simulation, vol. 6, 1996, pp. 53–75.

    Article  Google Scholar 

  15. Balci, O., “Model validation, verification, and testing techniques throughout the life cycle of a simulation study.” Annals of Operations Research, vol. 53, 1994, pp. 121–173.

    Article  MathSciNet  Google Scholar 

  16. Krajewski, L.J., B.E. King, L.P. Ritzman, and D.S. Wong, “Kanban, MRP, and shaping the manufacturing environment.” Management Science, vol. 33, 1987, pp. 39–57.

    Article  Google Scholar 

  17. Chance, F.,“Conjectured upper bounds on transient mean total waiting times in queueing networks.” Proceedings of the 1993 Winter Simulation Conference, 1993, pp. 414–421.

    Google Scholar 

  18. Nuyens, R.P.A., N.M. Van Dijk, L. Van Wassenhove, and E. Yiicesan, “Transient behavior of simple queueing systems: implications for FMS models.” Simulation: Application and Theory, vol. 4, 1996, pp. 1–29.

    Article  Google Scholar 

  19. Schmeiser, B.W., “Batch size effects in the analysis of simulation output.” Operations Research, vol. 31, 1983, pp. 565–568.

    MathSciNet  Google Scholar 

  20. Yücesan, E., “Randomization tests for initialization bias in simulation output.” Naval Research Logistics, vol. 40, 1993, pp. 643–664.

    Article  MATH  Google Scholar 

  21. Yücesan, E., “Evaluating alternative system configurations using simulation: a non-parametric approach.” Annals of Operations Research, vol. 53, 1984, pp. 471–484.

    Article  Google Scholar 

  22. Glasserman, P. and D.D. Yao, “Some guidelines and guarantees for common random numbers.” Management Science, vol. 38, 1992, pp. 884–908.

    Article  MATH  Google Scholar 

  23. Aybar, M., Potti, K., and T. LeBaron, “Using simulation to understand capacity constraints and improve efficiency on process toola”, Proceedings of the 2002 Winter Simulation Conference, 2002, pp. 1431–1435.

    Google Scholar 

  24. Smith, J., Li, Y., and J. Gjesvold, “Simulation-based analysis of a complex printed circuit board testing process” Proceedings of the 2002 Winter Simulation Conference, 2002, pp. 993–998.

    Google Scholar 

  25. Williams, C. and P. Chompuming, “A simulation study of robotic welding system with parallel and serial processes in the metal fabrication industry”, Proceedings of the 2002Winter Simulation Conference, 2002, pp. 1018–1025.

    Google Scholar 

  26. Patel, V., Ashby, J., and J. Ma, “Discrete event simulation in automotive final process system”, Proceedings of the 2002 Winter Simulation Conference, 2002, pp. 1030–1034.

    Google Scholar 

  27. Schömig, A. and J. Fowler, “Modelling Semiconductor Manufacturing Operations”, Proceedings of the 9 th ASIM Simulation in Production and Logistics Conference, Berlin, Germany, March 8-9, 2000, pp. 55–64.

    Google Scholar 

  28. Saraph, P., “Capacity analysis of multi-product, multi-resource biotech facility using discrete event simulation”, Proceedings of the 2002 Winter Simulation Conference, 2002, pp. 1007–1012.

    Google Scholar 

  29. Lu., R., and S. Sundaram, “Manufacturing process modeling of Boeing 747 moving line concepts”, Proceedings of the 2002 Winter Simulation Conference, 2002, pp. 1041–1045.

    Google Scholar 

  30. Thomas, J., J. Todi, J., and A. Paranjpe, “Optimization of operations in a steel wire manufacturing company”, Proceedings of the 2002 Winter Simulation Conference, 2002, pp. 1151–1156.

    Google Scholar 

  31. Choi, S., Kumar, A., and A. Houshyar, “A simulation study of an automotive foundry plant manufacturing engine blocks”, Proceedings of the 2002 Winter Simulation Conference, 2002, 1035–1040.

    Google Scholar 

  32. Schoemig, A., “On the corrupting influence of variability in semiconductor manufacturing,” Proceedings of the 1999 Winter Simulation Conference, 1999, pp. 837–842.

    Google Scholar 

  33. Kumar, P.R. “Re-entrant lines”, Queueing Systems Theory and Applications, Vol. 13, No. 1-3, 1993, pp. 87–110.

    Article  MathSciNet  MATH  Google Scholar 

  34. Fowler, J.W., Hogg, G.L., and D.T. Phillips, “Control of multiproduct bulk server diffusion/oxidation processes part two: multiple servers”, IIE Transactions on Scheduling and Logistics, Vol. 32, No. 2, 2000, pp. 167–176.

    Google Scholar 

  35. Brown, S., Domaschke, J., and F. Leibl, “No cost applications for assembly cycle time reduction”, International Conference on Semiconductor Manufacturing Operational Modeling and Simulation, 1999, pp. 159–163.

    Google Scholar 

  36. Ovacik, I. M. and Weng, W. “A framework for supply chain management in semiconductor manufacturing industry”, IEEE/CPMT International Electronics Manufacturing Technology Symposium, 1995, pp. 47–50.

    Google Scholar 

  37. Frederix, F. “Planning and scheduling multi-site semiconductor production chains: A survey of needs, current practices and integration issues”, Manufacturing Partnerships: Delivering the Promise, 1996, pp. 107–116.

    Google Scholar 

  38. Cooper, M. C. and Ellram, L. M. “Characteristics of supply chain management and the implications for purchasing and logistics strategy”, International Journal of Logistics Management, Vol. 1, No. 2, 1993, pp. 13–24.

    Article  Google Scholar 

  39. Hicks, D. A. “The manager’s guide to supply chain and logistics problem-solving tools and techniques part I: understanding the techniques”, IEE Solutions, Vol. 29, No. 9, 1997, pp. 43–47.

    Google Scholar 

  40. Barker, R.C., “Value chain development: an account of Some Implementation Problems”, International Journal of Operations & Production Management, Vol. 16, No. 10, 1996, pp. 23–36.

    Article  Google Scholar 

  41. Umeda, S., and A. Jones, “An integration test-bed system for supply chain management,” Proceedings of the 1998 Winter Simulation Conference, 1998, pp. 1377–1385.

    Google Scholar 

  42. Heita, S., “Supply chain simulation with LOGSIM-Simulator,” Proceedings of the 1998 Winter Simulation Conference, 1998, pp. 323–326.

    Google Scholar 

  43. Jain, S., Lim, C, Gan, B., and Y. Low, “Criticality of detailed modeling in semiconductor supply chain simulation,” Proceedings of the 1999 Winter Simulation Conference, 1999, pp. 888–896.

    Google Scholar 

  44. Duarte, B.M., Fowler, J.W., Knutson, K., Gel, E., and D. Shunk, “Parameterization of fast and accurate simulations for complex supply networks”, Proceedings of the 2002 Winter Simulation Conference, 2002, pp. 1327–1336.

    Google Scholar 

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Fowler, J.W., Schömig, A.K. (2003). Simulation of Manufacturing Systems. In: Obaidat, M.S., Papadimitriou, G.I. (eds) Applied System Simulation. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-9218-5_15

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  • DOI: https://doi.org/10.1007/978-1-4419-9218-5_15

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-4843-6

  • Online ISBN: 978-1-4419-9218-5

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