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Improving manufacturing processes using simulation methods

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper presents the results of simulation research on buffer space allo-cated in a flow line and operation times influence on the throughput of a manufacturing system. The production line in the study consists of four stages and is based on a real machining manufacturing system of a small production enterprise. Using Tecnomatix Plant Simulation software, a simulation model of the system was created and set of experiments was planned. Simulation experiments were prepared for different capacities of intermediate buffers located between manufacturing resources and op-eration times as input parameters, and the throughput per hour and aver-age life span of products as the output.
Rocznik
Strony
7--17
Opis fizyczny
Bibliogr. 17 poz., fig., tab.
Twórcy
autor
  • University of Zielona Góra, Faculty of Mechanical Engineering, Licealna 9, 65-417 Zielona Góra, Poland
  • University of Zielona Góra, Faculty of Mechanical Engineering, Licealna 9, 65-417 Zielona Góra, Poland
autor
  • Technical University of Kosice, Faculty of Mechanical Engineering
Bibliografia
  • 1. Demir, L., Tunali, S., Eliiyi, D. T., & Lokketangen, A. (2013). Two approaches for solving the buffer allocation problem in unreliable production lines. Computers & Operations Re-search, 40(10), 2556-2563. doi:10.1016/j.cor.2013.02.004
  • 2. Diering, M., Dyczkowski, K., & Hamrol, A. (2015). New Method for Assessment of Raters Agreement Based on Fuzzy Similarity. 10th International Conference on Soft Computing Models in Industrial and Environmental Applications, 368, 415-425. doi:10.1007/978-3-319-19719-7_36
  • 3. Fernandes, N. O., & Carmo-Silva, S. (2011). Order release in a workload controlled flow-shop with sequence-dependent set-up times. International Journal of Production Research, 49(8), 2443-2454. doi:10.1080/00207541003720376
  • 4. Gurkan, G. (2000). Simulation optimization of buffer allocations in production lines with unrelia-ble machines. Annals of Operations Research, 93, 177-216. doi:10.1023/a:1018900729338
  • 5. Huang, M. G., Chang, P. L., & Chou, Y. C. (2002). Buffer allocation in flow-shop-type production systems with general arrival and service patterns. Computers & Operations Research, 29(2), 103-121. doi:10.1016/s0305-0548(00)00060-5
  • 6. Krenczyk, D., & Skolud, B. (2014). Transient States of Cyclic Production Planning and Control. Engineering Solutions and Technologies in Manufacturing, 657, 961-965. doi:10.4028/ www.scientific.net/AMM.657.961
  • 7. Smith, J. M., & Cruz, F. R. B. (2005). The buffer allocation problem for general finite buffer queueing networks. Iie Transactions, 37(4), 343-365. doi:10.1080/07408170590916986
  • 8. Matta, A. (2008). Simulation optimization with mathematical programming repre-sentation of discrete event systems. In: Proceedings of the 2008 Winter Simulation Conference (pp. 1393-400). Institute of Electrical and Electronics Engineers, Inc. doi:10.1109/ WSC.2008.4736215
  • 9. Nahas, N., Nourelfath, M., & Ait-Kadi, D. (2009). Selecting machines and buffers in unreliable series-parallel production lines. International Journal of Production Research, 47(14), 3741–3774. doi:10.1080/00207540701806883
  • 10. Nourelfath, M., Nahas, N., & Ait-Kadi, D. (2005). Optimal design of series production lines with unreliable machines and finite buffers. Journal of Quality in Maintenance Engineering, 11(2), 121-138. doi: 10.1108/13552510510601348
  • 11. Abu Qudeiri, J., Yamamoto, H., Ramli, R., & Jamali, A. (2008). Genetic algorithm for buffer size and work station capacity in serial-parallel production lines. Artificial Life and Robotics, 12(1-2), 102-106. doi:10.1007/s10015-007-0449-5
  • 12. Seleim, A., Azab, A., & AlGeddawy, T. (2012). Simulation Methods for Changeable Manufactur-ing. 45th Cirp Conference on Manufacturing Systems 2012, 3, 179-184. doi:10.1016/ j.procir.2012.07.032
  • 13. Shi, C., & Gershwin, S. B. (2009). An efficient buffer design algorithm for production line profit maximization. International Journal of Production Economics, 122(2), 725-740. doi: 10.1016/j.ijpe.2009.06.040
  • 14. Staley, D. R., & Kim, D. S. (2012). Experimental results for the allocation of buffers in closed serial production lines. International Journal of Production Economics, 137(2), 284-291. doi:10.1016/j.ijpe.2012.02.011
  • 15. Tecnomatix Plant Simulation version 11.0.0, on-line documentation, 2011.
  • 16. Vergara, H. A., & Kim, D. S. (2009). A new method for the placement of buffers in serial produc-tion lines. International Journal of Production Research, 47(16), 4437-4456. doi:10.1080/ 00207540801939022
  • 17. Yamashita, H., & Altiok, T. (1998). Buffer capacity allocation for a desired throughput in produc-tion lines. IIE Transactions, 30(10), 883-891. doi:10.1080/07408179808966542
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-691cefa7-18a0-4031-826c-522280689414
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