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Genetic algorithms for the scheduling in additive manufacturing

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Genetic algorithms for the scheduling in additive manufacturing

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Castillo-Rivera, S.; De Antón, J.; Del Olmo, R.; Pajares, J.; López-Paredes, A. (2020). Genetic algorithms for the scheduling in additive manufacturing. International Journal of Production Management and Engineering. 8(2):59-63. https://doi.org/10.4995/ijpme.2020.12173

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Metadatos del ítem

Título: Genetic algorithms for the scheduling in additive manufacturing
Autor: Castillo-Rivera, S. De Antón, J. del Olmo, R. Pajares, J. López-Paredes, A.
Fecha difusión:
Resumen:
[EN] Genetic Algorithms (GAs) are introduced to tackle the packing problem. The scheduling in Additive Manufacturing (AM) is also dealt with to set up a managed market, called “Lonja3D”. This will enable to determine an ...[+]
Palabras clave: Scheduling , Packing Problem , Genetic Algorithm
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.2020.12173
Editorial:
Universitat Politècnica de València
Versión del editor: https://doi.org/10.4995/ijpme.2020.12173
Código del Proyecto:
info:eu-repo/grantAgreement/Junta de Castilla y León//VA049P17/
Agradecimientos:
This research has been partially financed by the project: “Lonja de Impresión 3D para la Industria 4.0 y la Empresa Digital (LONJA3D)” funded by the Regional Government of Castile and Leon and the European Regional ...[+]
Tipo: Artículo

References

Ahsan, A., Habib, A., Khoda, B. (2015). Resource based process planning for additive manufacturing. Computer-Aided Design, 69, 112-125. https://doi.org/10.1016/j.cad.2015.03.006

Araújo, L., Özcan, E., Atkin, J., Baumers, M., Tuck, C., Hague, R. (2015). Toward better build volume packing in additive manufacturing: classification of existing problems and benchmarks. 26th Annual International Solid Freeform Fabrication Symposium - an Additive Manufacturing Conference, 401-410.

Berman, B. (2012). 3-D printing: The new industrial revolution. Business Horizons, 55: 155-162. https://doi.org/10.1016/j.bushor.2011.11.003 [+]
Ahsan, A., Habib, A., Khoda, B. (2015). Resource based process planning for additive manufacturing. Computer-Aided Design, 69, 112-125. https://doi.org/10.1016/j.cad.2015.03.006

Araújo, L., Özcan, E., Atkin, J., Baumers, M., Tuck, C., Hague, R. (2015). Toward better build volume packing in additive manufacturing: classification of existing problems and benchmarks. 26th Annual International Solid Freeform Fabrication Symposium - an Additive Manufacturing Conference, 401-410.

Berman, B. (2012). 3-D printing: The new industrial revolution. Business Horizons, 55: 155-162. https://doi.org/10.1016/j.bushor.2011.11.003

Canellidis, V., Dedoussis, V., Mantzouratos, N., Sofianopoulou, S. (2006). Preprocessing methodology for optimizing stereolithography apparatus build performance. Computers in Industry, 57, 424-436. https://doi.org/10.1016/j.compind.2006.02.004

Chergui, A., Hadj-Hamoub, K., Vignata, F. (2018). Production scheduling and nesting in additive manufacturing. Computers & Industrial Engineering, 126, 292-301. https://doi.org/10.1016/j.cie.2018.09.048

Demirel, E., Özelkan, E.C., Lim, C. (2018). Aggregate planning with flexibility requirements profile. International Journal of Production Economics, 202, 45-58. https://doi.org/10.1016/j.ijpe.2018.05.001

Fera, M., Fruggiero, F., Lambiase, A., Macchiaroli, R., Todisco, V. (2018). A modified genetic algorithm for time and cost optimization of an additive manufacturing single-machine scheduling. International Journal of Industrial Engineering Computations, 9, 423-438. https://doi.org/10.5267/j.ijiec.2018.1.001

Hopper, E., Turton, B. (1997). Application of genetic algorithms to packing problems - A Review. Proceedings of the 2nd Online World Conference on Soft Computing in Engineering Design and Manufacturing, Springer Verlag, London, 279-288. https://doi.org/10.1007/978-1-4471-0427-8_30

Ikonen, I., Biles, W.E., Kumar, A., Wissel, J.C., Ragade, R.K. (1997). A genetic algorithm for packing three-dimensional non-convex objects having cavities and holes. ICGA, 591-598.

Kim, K.H., Egbelu, P.J. (1999). Scheduling in a production environment with multiple process plans per job. International Journal of Production Research, 37, 2725-2753. https://doi.org/10.1080/002075499190491

Lawrynowicz, A. (2011). Genetic algorithms for solving scheduling problems in manufacturing systems. Foundations of Management, 3(2), 7-26. https://doi.org/10.2478/v10238-012-0039-2

Li, Q., Kucukkoc, I., Zhang, D. (2017). Production planning in additive manufacturing and 3D printing. Computers and Operations Research, 83, 157-172. https://doi.org/10.1016/j.cor.2017.01.013

Milošević, M., Lukić, D., Đurđev, M., Vukman, J., Antić, A. (2016). Genetic Algorithms in Integrated Process Planning and Scheduling-A State of The Art Review. Proceedings in Manufacturing Systems, 11(2), 83-88.

Pour, M.A., Zanardini, M., Bacchetti, A., Zanoni, S. (2016). Additive manufacturing impacts on productions and logistics systems. IFAC, 49(12), 1679-1684. https://doi.org/10.1016/j.ifacol.2016.07.822

Wilhelm, W.E., Shin, H.M. (1985). Effectiveness of Alternate Operations in a Flexible Manufacturing System. International Journal of Production Research, 23(1), 65-79. https://doi.org/10.1080/00207548508904691

Xirouchakis, P., Kiritsis, D., Persson, J.G. (1998). A Petri net Technique for Process Planning Cost Estimation. Annals of the CIRP, 47(1), 427-430. https://doi.org/10.1016/S0007-8506(07)62867-4

Zhang, Y., Bernard, A., Gupta, R.K., Harik, R. (2014). Evaluating the design for additive manufacturing: a process planning perspective. Procedia CIRP, 21, 144-150. https://doi.org/10.1016/j.procir.2014.03.179

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