Abstract
This research develops the integration between the simulation of a flexible manufacturing system and the optimization of one of its resulting parameters by applying a meta-heuristic method based on genetic algorithms and discrete event simulation. The project focuses on the application of open-source software because the costs in implementing this integration with commercial software are high for the majority of existing companies in the country. The team used Jaamsim software in the simulation stage. It is a powerful simulator with a programmer-friendly graphical interface, developed in Java. For the construction and validation of the algorithm, the same program was used. The research provides a reference for the application of a tool that improves the productivity and competitiveness of companies in the market, focusing on the analysis of resources, planning, and observation in the behavior of a flexible manufacturing system to evaluate the accumulated times in their processes.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bernal, M., Sarmiento, C., Restrepo, J.: Productividad en una celda de manufactura flexible simulada en promodel utilizando path networks type crane. Universidad Distrital Francisco José de Caldas (2015). https://www.redalyc.org/pdf/2570/257036222011.pdf
Caceres, R., Rivas, W.: Desarrollar un software planificador de rutas, para encontrar una ruta óptima, mediante algoritmos genéticos (jgap) con interfaz desarrollada en java. Unidad Académica de Ingeniería Civil - UTMACH (2017)
Caldas, A., Carpente, M., Lorenzo, S.: Aplicación de algoritmos heurísticos para optimizar el coste de doblaje de películas. Universidade da Coruña (2014)
Cruz, J., Badii, M.: SMED: El camino a la flexibilidad total, vol. 1 (2004)
EAE Business School: Tipos de sistemas de producción industrial y sus características (2018). https://retos-operaciones-logistica.eae.es/tipos-de-sistemas-de-produccion-industrial-y-sus-caracteristicas/
Escobar, L.F.: Adaptive scheduling of flexible manufacturing systems with material handling constraints using GA and Colored Timed Petri Net. Japón (2015). http://www.f.waseda.jp/t-murata/Alumni.htm
Flores, K., Medina, P.: Desarrollo de un software académico para programar la producción en los sistemas de manufactura flexible. Universidad Tecnológica de Pereira Facultad de Ingeniería Industrial (2013). http://recursosbiblioteca.utp.edu.co/tesisd/textoyanexos/0053F634.pdf
García, E., Escobar, L.: Desarrollo de un simulador de sistemas de manufactura con interfaz gráfica basado en redes de petri. Revista iberoamericana de ingeniería mecánica (2018). https://dialnet.unirioja.es/servlet/articulo?codigo=6484717
Gestal, M., Cebrián, D., Rabuñal, J., Pazos, A.: Introducción a los algoritmos genéticos y la programación genética, 1st edn. Universidade da Coruña, Servizo de Publicacións, España (2010)
Groover, M.: Introducción a los algoritmos genéticos y la programación genética, 1st edn. Prentice Hall Press Upper Saddle River, New Jersey (2002)
Huang, J., Segura, L.J., Wang, T., Zhao, G., Sun, H., Zhou, C.: Unsupervised learning for the droplet evolution prediction and process dynamics understanding in inkjet printing. Addit. Manuf. 35, 101197 (2020)
JaamSim Software Inc: JaamSim User Manual (2017). https://jaamsim.com/docs/JaamSim%20User%20Manual%202017-10.pdf
Matt, D.T., Rauch, E., Dallasega, P.: Trends towards distributed manufacturing systems and modern forms for their design. Procedia cirp 33, 185–190 (2015)
Rabanal, P., Rodríguez, I., Rubio, F.: Algoritmos heurísticos y aplicaciones a métodos formales. Universidad Cumplutense de Madrid Facultad de Informática (2010). https://eprints.ucm.es/12027/1/T32515.pdf
Segura, L.J., Zhao, G., Sun, H., Zhou, C.: Gaussian process tensor responses emulation for droplet solidification in freeze nano 3D printing of energy products. In: International Manufacturing Science and Engineering Conference, vol. 58745, p. V001T01A024. American Society of Mechanical Engineers (2019)
Segura, L.J., Zhao, G., Zhou, C., Sun, H.: Nearest neighbor gaussian process emulation for multi-dimensional array responses in freeze nano 3d printing of energy devices. J. Comput. Inf. Sci. Eng. 20(4), (2020)
Teruel, E., Aragüés, R.: Aprendiendo simulación de eventos discretos con jaamsim. pp. 522–527. Servicio de Publicaciones de la Universidad de Oviedo (2017). https://dialnet.unirioja.es/servlet/articulo?codigo=6591655
Valtierra, J., Sausedo, J.: Reconfiguración autónoma de sistemas de manufactura mediante la optimización de funciones de desempeño del proceso. 12th Latin American and Caribbean Conference for Engineering and Technology (2014). http://www.laccei.org/LACCEI2014-Guayaquil/RefereedPapers/RP016.pdf
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Izquierdo, F., Garcia, E., Cortez, B., Escobar, L. (2021). Flexible Manufacturing Systems Optimization with Meta-heuristic Algorithm Using Open Source Software. In: Botto Tobar, M., Cruz, H., Díaz Cadena, A. (eds) Recent Advances in Electrical Engineering, Electronics and Energy. CIT 2020. Lecture Notes in Electrical Engineering, vol 763. Springer, Cham. https://doi.org/10.1007/978-3-030-72212-8_18
Download citation
DOI: https://doi.org/10.1007/978-3-030-72212-8_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-72211-1
Online ISBN: 978-3-030-72212-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)