Abstract
One of the goals of the future manufacturing systems is autonomic and self-organized shop floors. This requires flexible manufacturing units in terms of their availability and ability so that extremely personalized products, even of lot size equal to one, can be produced. In this paper, we propose a framework, which focuses on grouping cohesion of manufacturing units and efficient routing of products to resources. Towards this, we integrate an established cultural evolution model to achieve desirable flexibility of resources considering the requirements of the products that are being manufactured. A hybrid discrete simulation environment is implemented, in which cultural evolution among the resources is modeled using discrete-time, whereas, for routing, a simple queuing system is modeled using the discrete-event method.
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References
Rajkumar, R., Lee, I., Sha, L., Stankovic, J.: Cyber-physical systems: the next computing revolution. In: Design Automation Conference, pp. 731–736. IEEE (2010)
Lasi, H., Fettke, P., Kemper, H.G., Feld, T., Hoffmann, M.: Industry 4.0. Bus. Inf. Syst. Eng. 6(4), 239–242 (2014)
Lee, J., Bagheri, B., Kao, H.A.: A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manuf. Lett. 3, 18–23 (2015)
Hu, S.J.: Evolving paradigms of manufacturing: from mass production to mass customization and personalization. Procedia CIRP 7, 3–8 (2013)
Matt, D., Rauch, E., Dallasega, P.: Trends towards distributed manufacturing systems and modern forms for their design. Procedia CIRP 33, 185–190 (2015)
Ogunsakin, R., Mehandjiev, N., Marín, C.A.: Bee-inspired self-organizing flexible manufacturing system for mass personalization. In: Manoonpong, P., Larsen, J.C., Xiong, X., Hallam, J., Triesch, J. (eds.) SAB 2018. LNCS (LNAI), vol. 10994, pp. 250–264. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-97628-0_21
Zhang, J., Ding, G., Zou, Y., Qin, S., Fu, J.: Review of job shop scheduling research and its new perspectives under industry 4.0. J. Intell. Manufact. 30(4), 1809–1830 (2019)
Beruvides, G.: Artificial cognitive architecture with self-learning and self-optimization capabilities. Case studies in micromachining processes (2017)
Ezpeleta, J., Colom, J.M., Martinez, J.: A petri net based deadlock prevention policy for flexible manufacturing systems. IEEE Trans. Robot. Autom. 11(2), 173–184 (1995)
Zia, K., Ferscha, A., Trendafilov, D.: Conceptualization of cultural diversity for efficient and flexible manufacturing systems of the future. In: CogSci, pp. 1290–1295 (2019)
Zia, K., Ferscha, A., Trendafilov, D.: Importance of coordination and cultural diversity for an efficient and flexible manufacturing system. arXiv preprint arXiv:1905.08355 (2019)
Trendafilov, D., et al.: Cognitive products: system architecture and operational principles. https://pro2future.at/start-en/
Bonabeau, E.: Agent-based modeling: methods and techniques for simulating human systems. Proc. Natl. Acad. Sci. 99(Suppl. 3), 7280–7287 (2002)
Axelrod, R.: The dissemination of culture: a model with local convergence and global polarization. J. Conflict Resolut. 41(2), 203–226 (1997)
Centola, D., Gonzalez-Avella, J.C., Eguiluz, V.M., San Miguel, M.: Homophily, cultural drift, and the co-evolution of cultural groups. J. Conflict Resolut. 51(6), 905–929 (2007)
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The authors would like to acknowledge support by FFG funded Pro2Future under contract No. 6112792.
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Zia, K., Farooq, U., Ferscha, A. (2021). A Hybrid Simulation Model for an Efficient and Flexible Shop Floor System. In: Wright, J.L., Barber, D., Scataglini, S., Rajulu, S.L. (eds) Advances in Simulation and Digital Human Modeling. AHFE 2021. Lecture Notes in Networks and Systems, vol 264. Springer, Cham. https://doi.org/10.1007/978-3-030-79763-8_25
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DOI: https://doi.org/10.1007/978-3-030-79763-8_25
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