System Simulation Modeling: A Case Study Illustration of the Model Development Life Cycle


  • Janice K. Wiedenbeck
  • D. Earl Kline


System simulation, animation, modeling life cycle, integrated decision-support, discrete-event, furniture rough mill


Systems simulation modeling techniques offer a method of representing the individual elements of a manufacturing system and their interactions. By developing and experimenting with simulation models, one can obtain a better understanding of the overall physical system. Forest products industries are beginning to understand the importance of simulation modeling to help improve the dynamic performance of their processing and manufacturing systems. However, much knowledge and expertise are needed to accurately represent an actual forest products processing system as a simulation model. The purpose of this paper is to describe some effective process simulation model development strategies. This description points to the depth and breadth of knowledge that are needed to create usable and valid simulation models. To assist in illustrating the simulation modeling life cycle, actual case studies in modeling furniture rough mills are used.


Anderson, R. B. 1983. Furniture rough mill costs evaluated by computer simulation. Res. Paper NE-518 USDA Forest Serv., NE Forest Exp. Station, Upper Darby, PA.nBalci, O. 1986. Guidelines for successful simulation studies. Technical Report TR-85-2, Department of Computer Science, Virginia Tech, Blacksburg, VA.nBalci, O. 1988. Simulation and modeling. Computer Science 4214 Lecture Notes, Virginia Tech, Blacksburg, VA.nBergstrom, R. P. 1988. Portrait of a profession in change. Manufact. Eng. Dec., 1988.nBrunner, C. C., M. S. White, F. M. Lamb, and J. G. Schroeder. 1989. CORY: A computer program for determining dimension stock yields. Forest Prod. J. 39(2): 23-24.nDelamare, A., and J. Ciccotelli. 1992. Flow simulation for diagnostics and process planning in furniture finishing departments. In Proceedings of the 1992 Symposium on Computers in Furniture and Cabinet Manufacturing, Wood Machining Institute, Berkeley, CA.nGatchell, C. J., J. K. Wiedenbeck, and E. S. Walker. 1992. 1992 data bank for red oak lumber. Res. Paper NE-669 USDA Forest Serv., NE Forest Exp. Station, Radnor, PA.nLaughery, R. 1990. Simulation changes the way industry thinks about planning. Ind. Eng. 22(6):50, 85.nKobayashi, H. 1978. Modeling and analysis: An introduction to system performance evaluation methodology. Addison-Wesley, Reading, MA.nMeimban, R. J., G. A. Mendoza, and H. Carino. 1992. Integrating economic performance and process simulation models in evaluating sawmill design alternatives. Wood Fiber Sci. 24(1):68-72.nNance, R. E. 1981. Model representation in discrete event simulation: The conical methodology. Tech. Rep. CS81003-R, Department of Computer Science, Virginia Tech, Blacksburg, VA.nNance, R. E., and O. Balci. 1986. The objectives and requirements of model management. In M. Singh, ed. Systems and control encyclopedia: Theory, technology, and applications. Pergamon Press, Oxford, UK.nPegden, C. D., R. E. Shannon, and R. P. Sadowski. 1990. Introduction to simulation using SIMAN. McGraw-Hill, Inc., New York, NY.nShannon, R. E. 1975. Systems simulation: The art and science. Prentice-Hall, Inc., Englewood Cliffs, NJ.nTownsend, M. A., T. W. Lamb, and P. N. Sheth. 1988. Creation of a factory simulation for a low-technology industry. Manufact. Rev. 1(4):265-274.nU.S. Department of Defense. 1990. Pentagon picks 20 critical technologies for development. Report of the Challenges Council on Competitiveness.nWiedenbeck, J. K. 1992. Simulation for rough mill options. Wood & Wood Prod. 97(12):67-71.nWiedenbeck, J. K. 1993. Short lumber: Concept and acceptance. Pages 81-91 in J. Pitcher, ed. Twenty-First Hardwood Symposium, Hardwood Research Council, Memphis, TN.nWilson, J. R., and A. B. Pritsker. 1978. A survey of research on the simulation startup problem. Simulation 31(2):55-58.nWorley, J. W., J. A. Bollinger, F. E. Woeste, and K. S. Kline. 1990. Graphic distribution analysis (GDA). Appl. Eng. Agric. 6(3):367-371.n






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