Application of Spreadsheet and Queuing Network Model to Capacity Optimization in Product Development

Modeling of a manufacturing system enables one to identify the effects of key design parameters on the system performance and as a result to make correct decision. This paper proposes a manufacturing system modeling approach using a spreadsheet model based on queuing network theory, in which a static capacity planning model and stochastic queuing model are integrated. The model was used to improve the existing system utilization in relation to product design. The model incorporates few parameters such as utilization, cycle time, throughput, and batch size. The study also showed that the validity of developed model is good enough to apply and the maximum value of relative error is 10%, far below the limit value 32%. Therefore, the model developed in this study is a valuable alternative model in evaluating a manufacturing system




References:
[1] Fowler, John, W., and Rose, O., "Grand challenges in modeling and
simulation of complex manufacturing system", Simulation, Vol. 80, No.
9, pp. 469-476, 2004
[2] Cooper, R.G., "Third - Generation new product process", Journal of
Product Innovation Management, Vol. 11, No. 1, pp. 3-14, 1994
[3] Koo, P.H., Moodie, C.L., and Talavage, J.J., "A spreadsheet model
approach for integrating static capacity planning and stochastic queuing
models", International Journal of Production Research, Vol. 33, No. 5, pp. 1369-1385, 1995
[4] Law, A.M., and McComas, M.G., " Simulation of manufacturing
system", Proceedings of the Winter Simulation Conference, pp.56-59,1998
[5] Taylor, D.G., English, J.R., and Graves, R.J., "Designing new products:
Compatibility with existing product facilities and anticipated product
mix", Integrated Manufacturing Systems, Vol. 5, No. (4/5), pp. 13-21,1994
[6] Bermon, S., Feigen, G., and Hood, S., "Capacity analysis of complex
manufacturing facilities", Proceedings of 34th Conference on Decision &
Control, New Orleans, December 1995.
[7] Soundar, P., Han, P.B., "Concurrent design of products for manufacturing system performance", Proceedings IEEE International Engineering Management Conference. Ohio, Dayton. 1994
[8] Shady, R., Spake, G., and Armstrong, B., "Simulation of a new product
work cell", Proceedings of Winter Simulation Conference, USA. 1997
[9] Hopp, W.J., Mark, L.S., "Factory Physics", Irwin/McGraw Hill, Boston.
1996
[10] Vollmann, T.E., Berry, W.L., and Whybark, D.C., "Manufacturing
planning and control systems", 4th edition., Irwin/McGraw-Hill, New
York, 1997
[11] Aomar, R., "Product-mix analysis with discrete event simulation",
Proceedings 2000 Winter Simulation Conference, USA. 2000.
[12] Walid Abdul Kader, "Capacity improvement of an unreliable production
line - An analytical approach", Computer & Operations Research, No.
33, pp. 1695-1712, 2008
[13] Chincholkar, M.M., Burroughs, T., and Herrmann, J.W., "Estimating
manufacturing cycle time and throughput in flow shops with process drift
and inspection", Institutes of Systems Research and Department of Mechanical Engineering University of Maryland,2004
[14] Papadopoulos, H.T., Heavey, C., and Browne, J. "Queuing theory in
manufacturing systems analysis and design ", Chapman and Hall,
London, 1993
[15] Yu-Feng,W. and Thornton, A.C., "Concurrent design for optimal
production performance", Paper DETC2002/DFM-34163 in CD-ROM
Proceedings of 2002 ASME Design Engineering Technical Conference,
Montreal, Canada. 2002.
[16] Herrmann, J.W., and Chincholkar, M., "Design for Production: A Tool
for reducing manufacturing cycle Time", Paper DETC2000/DFM-14002
in CD-ROM Proceedings of DETC 2000, 2000 ASME Design Engineering Technical Conference. Baltimore, September, 2000