Abstract
This research seeks through the simulation software FlexSim 2017 to model, analyze, visualize and optimize the automobile painting process in a mechanical workshop whose areas are: preparation, sanding, painting, baking, washing and storage of automobiles. The methodology used is field research, applied, qualitative and explanatory, obtaining statistical data that is analyzed through the use of software libraries such as Fluid, Time Tables, Process Flow, Expert-Fit and Experimenter. The results of Experimenter identify the bottleneck and on the basis of the simulation, productivity is improved by 27.45%, which represents the processing of another car in the sanding area. These results can be replicated to other industry workshops, achieving substantial improvements in productivity.
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References
López, A., González, A., Alcaraz, S.: Simulation-based optimization for the production of axes in assembly lines of a manufacturing company. Ingenieria investigación y tecnología 20(1), 1–9 (2019)
Simón, I., Santana, F., Granillo, R., Piedra, V.: La simulación con FlexSim, una fuente en las operaciones de un sistema híbrido. Científica 17(1), 1–12 (2013)
Forero, Y., Giraldo, J.: Simulación de un Proceso de Fabricación de Bicicletas: Aplicación Didáctica en la Enseñanza de la Ingeniería Industrial. Formación Universitaria 9(3), 39–50 (2016)
Reyes, J., Aldas, D., Alvarez, K., García, M., Ruíz, M.: The factory physics for the scheduling: application to footwear industry. In: Proceedings of the 7th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, pp. 248–254. SCITEPRESS - Science and Technology Publications, Madrid (2017)
Jurczyk-Bunkowska, M.: Using discrete event simulation for planning improvement in small batch size manufacturing system. Stud. Syst. Decis. Control 198, 19–43 (2020)
Yang, Q., Zhang, D., Zhou, H., Zhang, C.: Process simulation, analysis and optimization of a coal to ethylene glycol process. Energy 155, 521–534 (2018)
Naseem, A., Shah, S., Khan, S., Malik, A.: Decision support system for optimum decision making process in threat evaluation and weapon assignment: current status, challenges and future directions. Annu. Rev. Control 43, 169–187 (2017)
Aldas, D., Reyes, J., Morales, L., Alvarez, K., Portalanza, N., Aman, R.: Manufacturing strategies for an optimal pull-type production control system. case study in a textile industry. In: 2018 Congreso Internacional de Innovación y Tendencias en Ingeniería (CONIITI), pp. 1–6. Bogotá (2018)
Zhu, X., Zhang, R., Chu, F., He, Z., Li, J.: A flexsim-based optimization for the operation process of cold-chain logistics distribution centre. J. Appl. Res. Technol. 12(2), 270–278 (2014)
Pongjetanapong, K., O’Sullivan, M., Walker, C., Furian, N.: Implementing complex task allocation in a cytology lab via HCCM using Flexsim HC. Simul. Model. Pract. Theory 86, 139–154 (2018)
Xu, G., Feng, J., Chen, F., Wang, H., Wang, Z.: Simulation-based optimization of control policy on multi-echelon inventory system for fresh agricultural products. Int. J. Agric. Biomed. Eng. 12(2), 184–194 (2019)
Liu, T., Duan, Y., Liu, Y.: Simulation and optimization of the AS/RS based on Flexsim. In: Lecture Notes in Electrical Engineering, vol. 375, pp. 855–863 (2016)
Gołda, G., Kampa, A., Krenczyk, D.: The methodology of modeling and simulation of human resources and industrial robots in FlexSim. FlexSim in Academe: Teaching and Research, pp. 87–100 (2019)
Hoffa, P., Pawlewski, P.: Simulation of supply chain with disturbances using flexsim - case study. Commun. Comput. Inf. Sci. 524, 90–101 (2015)
Zhang, H., Li, C., Li, Y., Song, H., Li, X.: Study on seed-metering device belt mixed flow assembly line of FlexSim. In: Qi, E., Shen, J., Dou, R. (eds.) Proceedings of the 22nd International Conference on Industrial Engineering and Engineering Management 2015, pp. 633–642. Atlantis Press, Paris (2016)
Kęsek, M., Adamczyk, A., Klaś, M.: Computer simulation of the operation of a longwall complex using the “Process Flow” concept of FlexSim software. Adv. Intell. Syst. Comput. 835, 97–106 (2019)
Cantú, J., Guardado, M. del C., Balderas, J.: Simulación de procesos, una perspectiva en pro del desempeño operacional. Revista Iberoamericana de Producción Académica y Gestión educativa 3(5), 4–6 (2016)
García Criollo, R.: Estudio del Trabajo: Ingeniería de Métodos y Medición del Trabajo, 2nd edn. Mc Graw Hill, Mexico (2005)
Acknowledgments
The authors thank the Technical University of Ambato (UTA) and the Research and Development Department (DIDE)for the support provided during the execution of this work within the framework of the research project called “Socio-environmental impact of the externalities of the urban transport service in Ambato. Optimization model”. Code DIDE10.
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Reyes, J. et al. (2020). A Study on Modeling and Simulation of Automobile Painting Process Based on Flexsim. In: Nummenmaa, J., Pérez-González, F., Domenech-Lega, B., Vaunat, J., Oscar Fernández-Peña, F. (eds) Advances and Applications in Computer Science, Electronics and Industrial Engineering. CSEI 2019. Advances in Intelligent Systems and Computing, vol 1078. Springer, Cham. https://doi.org/10.1007/978-3-030-33614-1_18
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