|
中文部分 1.林則孟,“系統模擬 ”,台北,華泰書局,民89。 2.徐政宏,“多能工派工法則之模擬比較-以面臨緊急訂單 之流線型生產系統為例”,朝陽大學工管研究所碩士論 文,民89。 3.郭鴻志,季延平,“系統分析與設計-由自動化到企業再 造”,台北,華泰書局,民84。 4.楊廣宜,“以基因演算法結合離散事件模擬求解最佳 CONWIP生產架構 ”,國立成功學製造工程研究所碩士論 文,民91。 5.鄭書豪, “CONWIP生產管制架構於IC封裝產業之應 用”,國立清華大學工業工程研究所碩士論文,民87。 英文部分 1.Banks, J., Carson, II., and Barry,.N.,“Discrete — Event Systen Simulation,”Prentice Hall, Inc., pp.3-13,1995. 2.Bonvik, A. M., Couch, C. E., and Gershwin, S. B., “ A comparison of production-line control mechanisms,” International Journal of Production Research, Vol. 35, No. 3, pp. 789-804 , 1997. 3.Brun, A. and Portioli, A., “Agent-Based Shop-Floor Scheduling of Multistage Systems,” Computers and Industrial Engineering, Vol.37, 恩 pp.457-460, 1999. 4.Can, D., Todd, F.M. and Steven, A.W., Simulation Modeling and Analysis of A Hardwood Sawmill, Simulation Practice and Theory, Vol.5, No.8, pp.387-403,1997. 5.Deleersnyder, J. L., Hodgson, T. J., Muller, H., and O’Grady, P. J.,“ Kanban controlled pull systems: analytic approach,”Management Science, Vol. 35, No.9, pp. 1079-1091 ,1989. 6.Gaury, E. G. A., Pierreval, H., and Kleijnen, J. P. C.,“An evolutionary approach to select a pull system among Kanban, Conwip and Hybrid,” Journal of Intelligent Manufacturing, Vol. 11, pp.157-167 , 2000. 7.Graham, I.,“Comparing trigger and kanban control of flow-time manufacture,”International Journal of Production Research, Vol. 30, No. 10, pp.351-2362 , 1992. 8.Harrell, C., Ghosh, B. K. and Bowden, R., Simulation Using ProModel , 2000. 9.Herer, Y. T. and Masin, M., “Mathematical programming formulation of CONWIP based production lines; and relationships to MRP,” International Journal of Production Research, Vol. 35, No. 4, pp. 1067-1076 , 1997. 10.Hopp, W. J. and Roof, M. L.,“ Setting WIP levels with statistical throughput control (STC) in CONWIP production lines,”International Journal of Production Research, Vol. 36, No. 4, pp. 867-882 , 1998. 11.Hopp, W. J. and Spearman, M. L., Factory Physics: Foundations of Manufacturing Management , 1996. 12.Law, A. M. and David, W. D., Simulation Modeling &Analysis ,2nd ed., McGraw-Hill, Inc.,1990. 13.Mayer, O.T., Cullinane,T. P., DeWitte, P. S., Knappenberger, W.B.,Perakath, B., and Wells, M. S.,Information Integration for Concurrent engineering (IICE) IDEF3 Process Description Capture Method Report,AL-TR-1992-0057, Armstrong Laboratory, Wright-Patterson AFB,OH. 14.Mehmet, S., “Simulation Analysis of A Pull-Push System for An ElectronicAssembly Line,” International Journal of ProductionEconomics,Vol.51,pp.205-214, 1997. 15.Monden, Y., Toyota Production System: Practical Approach to Management ,Industrial Engineering and Management Press, Norcross, GA , 1983. 16.Nelson, B. L., Kelton, W. D. and Clark, G. M., “Proceeding of the 1991 Winter Simulation Conference,”Proceeding of the 1991 Winter Simulation Conference, p.18 , 1991. 17.Pegden, C. D., Shannon, R. E., and Sadowski, R P., Introduction to Simulation Using SIMAN ,McGraw-Hill, Inc, 1990. 18.Philipoom, P. P., Rees, L. P., Taylor, B.W., III, and Huang, P. Y., “An investigation of the factors influencing the number of kanbans required in the implementation of the JIT technique with kanbans,” International Journal of Production Research, Vol. 25, No. 3, pp. 457-472 , 1987. 19.Rees, L. P., Philipoom, P. R., Taylor, B. W., III, and Huang, P. Y., 1987. Dynamically adjusting the number of kanbans in a just-in-time production system using estimated values of leadtime, IIE Transactions, Vol. 19, No. 2, pp. 199-207, 1987. 20.Roderick, L. M., Toland, J., and Rodriguez, F. P.,“ A simulation study of CONWIP versus MRP at Westinghouse, Computers and Industrial Engineering, ” Vol. 26, No. 2, pp. 237-242 , 1984. 21.Spearman, M. L., Woodruff, D. L., and Hopp, W. J.,“ CONWIP: a pull alternative to kanban,” International Journal of Production Research, Vol. 28, No. 5, pp. 879-894, 1996. 22.Wang, H. and Wang, H. P.,“ Optimum number of kanbans between two adjacent workstations in a JIT system ,” International Journal of Production Economics. Vol. 29, pp. 89-101 , 1993. 23.Zeiger, B.P.,“System theoretic representation of simulation models ”IIE Transactions , 1984.
|