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2011 | 2 | nr 3 | 63--70
Tytuł artykułu

A Simulation Approach to Evaluating Manufacturing System Performance

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Since testing wide range of management decision in real-world production is absolutely impossible, discrete-event simulation has often been adopted to evaluate the manufacturing system performance. Performance of various layout alternatives can be studied using simulation. In this paper there are presented reasons to use simulation in order to evaluate manufacturing system performance. Paper presents a simulation approach to assessing the impact of management decision on a production process and the associated impact on costs and on potential gain. (original abstract)
Rocznik
Tom
2
Numer
Strony
63--70
Opis fizyczny
Twórcy
  • West Pomeranian University of Technology in Szczecin, Szczecin, Poland
autor
  • Warsaw School of Computer Science, Warszawa, Poland
Bibliografia
  • Scott L.R., Harmonosky C.M., "An improved simulated annealing simulation optimization method for discrete parameter stochastic systems", Computers & Operations Research, 32, 343-358, 2005.
  • Hon K.K.B., "Performance and Evaluation of Manufacturing Systems", CIRP Annals - Manufacturing Technology, 54 (2), 139-154, 2005.
  • Pidd M., "Computer Simulation in Management Science", fourth ed. Wiley, Chichester, UK, 1998.
  • Law A.M., Kelton W.D., "Simulation Modeling and Analysis", third ed. McGraw-Hill, New York, 2000.
  • Robinson S., "General concepts of quality for discrete-event simulation", European Journal of Operational Research. 138, 103-117, 2002.
  • Monch L., "Simulation-based benchmarking of production control schemes for complex manufacturing systems", Control Engineering Practice, 15, 1381- 1393, 2007.
  • Ball P., "Abstracting performance in hierarchical manufacturing simulation", Journal of Materials Processing Technology, 76, 246-251, 1998.
  • Sooyoung K., Youngshin P., Chi-Hyuck J., "Performance evaluation of re-entrant manufacturing system with production loss using mean value analysis production loss using mean value analysis", Computers & Operations Research, 33, 1308-1325, 2006.
  • Gregor M., Skorik P., "Simulation and emulation of manufacturing systems behaviour", Management and Production Engineering Review, 1 (2), 11-21, 2010.
  • Sun L., Heragu S.S., Chen L., Spearman M.L., "Simulation analysis of a multi-item mrp system based on factorial design", Proceedings of the 2009 Winter Simulation Conference.
  • Lee T.S., Adam E.E.J., "Forecasting error evaluation in material requirements planning (MRP) production-inventory systems", Management Science, 32 (9), 1186-1205, 1986.
  • Enns S.T., "MRP performance effects due to lot size and planned lead time settings", International Journal of Produc-tion Research, 39 (3), 461-480, 2001.
  • Yeung J.H.Y, Wong W.C.K., Ma L., "Parameters affecting the effectiveness of MRP systems: a review", Inter-national Journal of Production Research, 36 (2),313-332, 1998.
  • Habchi G., Labrune Ch., "Study of lot sizes on job shop systems performance using simulation", Practice and Theory, 2, 277-289, 1995.
  • Kumar P.R., "Scheduling semiconductor manufacturing plants", IEEE Control Systems Magazine, 14 (6), 33-40, 1994.
  • Li S., Tang T., Collins D.W., "Minimum inventory variability schedule with applications in semiconductor fabrication", IEEE Transactions on Semiconductor Manufacturing, 9 (1), 145-149, 1996.
  • Lu S.H., Ramaswamy D., Kumar P.R., "Efficient scheduling policies to reduce mean and variance of cycle-time in semiconductor manufacturing plants", IEEE Transactions on Semiconductor Manufacturing, 7 (3), 374-388, 1994.
  • Zhang H., Jiang Z., Guo C., "Simulation-based optimization of dispatching rules for semiconductor wafer fabrication system scheduling by the response surface methodology", International Journal of Advanced Manufacturing Technology, 41, 10-121, 2009.
  • Van Volsem S., Dullaert W., Van Landeghem H., "An Evolutionary Algorithm and discrete event simulation for optimizing inspection strategies for multi-stage processes", European Journal of Operational Research, 179, 621-633, 2007.
  • Kaplan R., Norton D., "The Balanced Scorecard: Translating Strategy into Action", Harvard Business School Press, 1996.
  • Shi C., Gershwin S.B., "An efficient buffer design algorithm for production line profit maximization", International Journal Production Economics, 122, 725-740, 2009.
  • Korytkowski P., Wiśniewski T., Zaikin O., "Optimal buffer allocation in re-entrant job shop production using simulated annealing", Management and Production Engineering Review, 1 (3), 30-40, 2010.
  • Montgomety D.C., "Design and Analtysis of Experiments", New York, Wiley, 2009.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171570683

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