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Validation of production system throughput potential and simulation experiment design

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Validation of production system throughput potential and simulation experiment design

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Standridge, C.; Wynne, M. (2021). Validation of production system throughput potential and simulation experiment design. International Journal of Production Management and Engineering. 9(1):15-23. https://doi.org/10.4995/ijpme.2021.14483

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Título: Validation of production system throughput potential and simulation experiment design
Autor: Standridge, C. Wynne, M.
Fecha difusión:
Resumen:
[EN] The throughput potential of a production system must be designed and validated before implementation.  Design includes creating product flow by setting the takt time consistent with meeting customer demand per time ...[+]
Palabras clave: Throughput potential validation , Kingman’s equation , Discrete event simulation
Derechos de uso: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
Fuente:
International Journal of Production Management and Engineering. (eissn: 2340-4876 )
DOI: 10.4995/ijpme.2021.14483
Editorial:
Universitat Politècnica de València
Versión del editor: https://doi.org/10.4995/ijpme.2021.14483
Tipo: Artículo

References

Atalan, A., Dönmez, C.C. (2020). Optimizing experimental simulation design for the emergency departments. Brazilian Journal of Operations & Production Management, 17(4), e2020854. https://doi.org/10.14488/BJOPM.2020.026

Askin, R.G., Standridge, C.R. (1993). Modeling and analysis of manufacturing systems. New York: John Wiley and Sons.

Dagkakis, G., Rotondo, A., Heavey, C. (2019). Embedding optimization with deterministic discrete event simulation for assignment of cross-trained operators: an assembly line case study. Computers and Operations Research, 111, 99-115. https://doi.org/10.1016/j.cor.2019.06.008 [+]
Atalan, A., Dönmez, C.C. (2020). Optimizing experimental simulation design for the emergency departments. Brazilian Journal of Operations & Production Management, 17(4), e2020854. https://doi.org/10.14488/BJOPM.2020.026

Askin, R.G., Standridge, C.R. (1993). Modeling and analysis of manufacturing systems. New York: John Wiley and Sons.

Dagkakis, G., Rotondo, A., Heavey, C. (2019). Embedding optimization with deterministic discrete event simulation for assignment of cross-trained operators: an assembly line case study. Computers and Operations Research, 111, 99-115. https://doi.org/10.1016/j.cor.2019.06.008

Ferrin, D.M., Miller M.J., Muthler D. (2005). Lean sigma and simulation, so what's the correlation?, in Proceedings of the 2005 Winter Simulation Conference, IEEE, USA. Retrieved July 22, 2020 from: https://informs-sim.org/wsc05papers/249.pdf

Hopp, W.J., Spearman, M.L. (2011). Factory Physics: Foundations of manufacturing management, 3rd ed. Long Grove, IL: Waveland Press.

Jayaraman, A., Gunal, A.K. (1997). Applications of discrete event simulation in the design of automotive powertrain manufacturing systems". In Proceedings of the 1997 Winter Simulation Conference, IEEE, USA. https://doi.org/10.1145/268437.268620

Khan, S., Standridge, C.R. (2019). Aggregate simulation modeling with application to setting the CONWIP limit in an HMLV cell. International Journal of Industrial Engineering Computation, 10(2), 149-160. https://doi.org/10.5267/j.ijiec.2018.10.002

Kingman, J.F.C. (1961). The single server queue in heavy traffic. Mathematical Proceedings of the Cambridge Philosophical Society, 57(4), 902. https://doi.org/10.1017/S0305004100036094

Kleijnen, J.P.C. (2015). Design and analysis of simulation experiments. New York: Springer. https://doi.org/10.1007/978-3-319-18087-8

Kleijnen, J.P.C., Standridge, C.R. (1988). Experimental design and regression analysis in simulation: an FMS case study. European Journal of Operations Research, 33, 257-261. https://doi.org/10.1016/0377-2217(88)90168-3

Law, A.M. (2014). Simulation modeling and analysis, 5th ed. New York: McGraw-Hill.

Little, J.D.C. (1961). A proof for the queuing formula: L = λW. Operations Research, 9(3), 383-387. https://doi.org/10.1287/opre.9.3.383

Marvel, J.H., Standridge, C.R. (2009). A simulation enhanced lean design process. Journal of Industrial Engineering and Management, 2(1), 90-113. https://doi.org/10.3926/jiem.2009.v2n1.p90-113

Mourtzis, D. (2019) Simulation in the design and operation of manufacturing systems: state of the art and new trends. International Journal of Production Research, 58(7), 1927-1949. https://doi.org/10.1080/00207543.2019.1636321

Pinheiro, N.M.G, Cleto, M.G., Zattar, I.C., Muller, S.I.M.G. (2019). Performance evaluation of pulled, pushed and hybrid production through simulation: a case study. Brazilian Journal of Operations & Production Management, 16, 685-697. https://doi.org/10.14488/BJOPM.2019.v16.n4.a13

Pritsker, A.A.B. (1989). Why simulation works. In Proceedings of the 1989 Winter Simulation Conference, IEEE, USA. https://doi.org/10.1145/76738.76739

Puvanasvaran, P., Teoh, Y.S., Ito, K. (2020). Novel availability and performance ratio for internal transportation and manufacturing processes in job shop company. Journal of Industrial Engineering and Management, 13(1), 1-17. https://doi.org/10.3926/jiem.2755

Sanchez, S.M., Sanchez, P.J., Wan, H. (2020). Work smarter, not harder: a tutorial on designing and conducting simulation experiments. In Proceedings of the 2020 Winter Simulation Conference, IEEE, USA. Retrieved December 23, 2020 from https://informs-sim.org/ wsc20papers/135.pdf

Schruben, L. (1983). Simulation modeling with event graphs. Communications of the A.C.M., 26(11). https://doi.org/10.1145/182.358460

Spearman, M.L., Woodruff, D.L., Hopp, W.J. (1990). CONWIP: A pull alternative to Kanban, International Journal of Production Research, 28(5), 879-894. https://doi.org/10.1080/00207549008942761

Standridge, C.R. (2019). Introduction to production: philosophies, flow, and analysis. Allendale Michigan: Grand Valley State University Libraries. Retrieved July 22, 2020 from: https://scholarworks.gvsu.edu/books/22/

Tapping, D., Luyster, T., Shuker, T. (2002). Value stream management. Boca Raton: CRC Press. https://doi.org/10.4324/9781482278163

Tribastone, M., Vandin, A. (2018). Speeding up stochastic and deterministic simulation by aggregation: an advanced tutorial. . In Proceedings of the 2018 Winter Simulation Conference, IEEE, USA. https://doi.org/10.1109/WSC.2018.8632364

Uriarte, A.G., Ng, A.H.C., Moris, M.U. (2020). Bringing together Lean and simulation: a comprehensive review, International Journal of Production Research, 58(1), 87-117. https://doi.org/10.1080/00207543.2019.1643512

Zupan, H., Herakovic. N. (2015). Production line balancing with discrete event simulation: a case study", IFAC-PapersOnLine, 48(3), 2305- 2311. https://doi.org/10.1016/j.ifacol.2015.06.431

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