Abstract
Industry 4.0 is focused on creating smart products, procedures and processes and calls for the need to create fully dynamic reconfiguration production lines in which products move autonomously through the system from one available resource to another. Planers should be equipped with the methods and IT tools required to develop a complex planning and explanatory models to control and re-configure manufacturing resource networks and production flow based on situation. In this paper a heuristics and simulation based approach for balancing of mixed and multi model assembly line is presented. The proposed IT solution is a computer hybrid implementation of combined data-driven automatic simulation models generation and heuristic for line balancing methods. A computer implementation of the proposed solution using the FlexSim simulation software with a practical example of its application are presented as well.
Similar content being viewed by others
References
Zuehlke, D.: SmartFactory—towards a factory-of–things. Ann. Rev. Control 34, 129–138 (2010)
Madsen, E.S., Bilberg, A., Hansen, D.G.: Industry 4.0 and digitalization call for vocational skills, applied industrial engineering, and less for pure academics. In: Proceedings of the 5th P&OM World Conference, Production and Operations Management, P&OM (2016)
Kagermann, H., Wahlster, W., Helbig, J.: Recommendations for implementing the strategic initiative industrie 4.0: final report of the industrie 4.0 working group (2013)
Hermann, M., Pentek, T., Otto, B.: Design principles for industrie 4.0 scenarios. In: 49th Hawaii International Conference on System Sciences (HICSS), Koloa, HI, pp. 3928–3937 (2016)
Skolud, B., Krenczyk, D.: Rhythmic production planning in the context of flow logic. In: Manufacturing 2014: Contemporary Problems of Manufacturing and Production Management, pp. 35–43 (2016)
Krenczyk, D., Skolud, B.: Transient states of cyclic production planning and control. Appl. Mech. Mater. 657, 961–965 (2014)
Grzechca, W. (ed.): Assembly Line—Theory and Practice. InTech (2011). http://www.intechopen.com/books/assembly-line-theory-and-practice
Zemczak, M., Skolud, B., Krenczyk, D: Two-Stage orders sequencing system for mixed-model assembly. In: IOP Conference Series: Materials Science and Engineering, 95, 012130 (2015)
Ponnambalam, S.G., Aravindan, P., Naidu, G.M.: A comparative evaluation of assembly line balancing heuristics. Int. J. Adv. Manuf. Technol. 15, 577–586 (1999)
Grzechca, W.: Assembly line balancing problem with reduced number of workstations. IFAC Proc. Vol. 47(3), 6180–6185 (2014)
Pidd, M.: Guidelines for the design of data driven generic simulators for specific domains. Simulation 59(4), 237–243 (1992)
Wang, J., et al.: Data driven production modeling and simulation of complex automobile general assembly plant. Comput. Ind. 62(7), 765–775 (2011)
Bergmann, S., Strassburger, S.: Challenges for the automatic generation of simulation models for production systems. In: SCSC 2010 Proceedings of the 2010 Summer Computer Simulation Conference, Ottawa, Canada, pp. 545–549 (2010)
Krenczyk, D., Jagodzinski, M.: ERP, APS and simulation systems integration to support production planning and scheduling. Adv. Intell. Syst. Comput. 368, 451–461 (2015)
Beaverstock, M., Greenwood, A.G., Lavery, E., Nordgren, B.: Applied Simulation: Modeling and Analysis Using FlexSim. FlexSim Software Products Inc, Orem (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Krenczyk, D., Skolud, B., Herok, A. (2018). A Heuristic and Simulation Hybrid Approach for Mixed and Multi Model Assembly Line Balancing. In: Burduk, A., Mazurkiewicz, D. (eds) Intelligent Systems in Production Engineering and Maintenance – ISPEM 2017. ISPEM 2017. Advances in Intelligent Systems and Computing, vol 637. Springer, Cham. https://doi.org/10.1007/978-3-319-64465-3_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-64465-3_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-64464-6
Online ISBN: 978-3-319-64465-3
eBook Packages: EngineeringEngineering (R0)