In this paper, a method to determine the number of kanbans in a pull production system by using simulation metamodeling is described. The method is demonstrated on a two-card kanban- controlled manufacturing system. Through meta modeling, a relationship between the number of kanbans and the average time to fill a customer order is determined. Later this relationship is used in a model to determine the number of kanbans while minimizing costs.
Abdou, G. and Dutta, S.P. (1993), "A Systematic Simulation Approach for the Design of JIT Manufacturing Systems", Journal of Operations Management , 11, 225-238.
2.
Barton, R.R. (1992), "Metamodels for Simulation Input-Output Relations ", Proceedings of the 1992 Winter Simulation Conference , ed. J.J. Swain, D. Goldsman, R.C. Crain, and J.R. Wilson, 289-299.
3.
Berkley, B.J. (1993), "A Review of the Kanban Production Control Research Literature", to appear in Production and Operations Management .
4.
Blanning, R.W. (1975), " The Construction and Implementation of Metamodels ", SIMULATION, June, 177-184.
5.
Friedman, L.W. and Friedman, H.H. (1985), "Validating the Simulation Metamodel: Some Practical Approaches", SIMULATION, September, 144-146.
6.
Friedman, L.W. and Pressman, I. (1988), "The Metamodel in Simulation Analysis: Can It Be Trusted?", Journal of Operational Research Society, vol. 39, no. 10, 939-948.
7.
Fukukawa, T. and Sung-Chan, H. (1993), "The Determination of the Optimal Number of Kanbans in a Just-In-Time Production System", Computers and Industrial Engineering, vol. 24, no. 4, 551-559.
8.
Kleijnen, J.P.C. (1979), "Regression Metamodels for Generalizing Simulation Results", IEEE Transactions on Systems, Man, and Cybernetics , vol. SMC9, no. 2, February, 93-96.
9.
Kleijnen, J.P.C. and Standridge, C.R. (1988), "Experimental Design and Regression Analysis in Simulation: An FMS Case Study", European Journal of Operational Research,33, 257-261.
10.
Lin, L. and Cochran, J.K. (1990), "Estimating Simulation Metamodel Parameters for Unexpected Shop Floor Real Time Events", Computers and Industrial Engineering, vol.19, nos. 1-4, 62-66.
11.
Lin, L. and Chiu, F. (1993), "Manufacturing Cell Operating Characteristics ", European Journal of Operational Research,69,424-437.
12.
Madu, C.N. (1990), "Simulation in Manufacturing: A Regression Metamodel Approach", Computers and Industrial Engineering, vol. 18, no. 3, 381-389.
13.
Madu, C.N. and Kuei, C. (1992), "Group Screening and Taguchi Design in the Optimization of Multi-Echelon Maintenance Float Simulation Metamodels", Computers Operations Research, vol. 19, no. 3, 95-105.
14.
Pegden, C.D., Shannon, R.E., and Sadowski, R.P. (1995), Introduction to Simulation Using SIMAN, Second Edition, McGraw-Hill Inc.
15.
Philipoom, P.R., Rees, L.P., Taylor, B.W. and Huang, P.Y. (1987), "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, 457-472.
16.
Rees, L.P., Philipoom, P.R., Taylor, B.W. and Huang, P.Y. (1987), "Dynamically Adjusting the Number of Kanbans in a Just-in-Time Production System using Estimated Values of Lead-time", IIE Transactions, vol. 19, no. 2, 199-207.
17.
Rotmans, J., Vrieze, O.J. (1990), "Metamodeling and Experimental Design: Case Study of the Greenhouse Effect", European Journal of Operational Research,47, 317-329.
18.
Wang, H. and Wang, H. (1991), "Optimum Number of Kanbans Between Two Adjacent Workstations in a JIT System", International Journal of Production Economics, vol. 22, no. 3, 179-188.
19.
Yu, B. and Popplewell, K., "Metamodels in Manufacturing: A Review", International Journal of Production Research, vol.32, no. 4, 787-796.
