Abstract
The successful improvement of the competitiveness of companies depends largely on the efficiency of assembly and handling systems and processes. Their efficiency can be increased by various optimization methods, especially with regard to cost reduction, shortening of throughput times, delivery times, increased utilization of plant capacity, etc. One of the most effective methods for optimizing such systems is optimization with online simulation. In this paper we present an innovative expert system and an innovative methodology of online simulation, where we have extended the conventional offline simulation with digital twin and digital agents. This has enabled the continuous control and ongoing optimization of the real production system and process. We have combined the digital AHSP with the real system via the cloud, thus creating all the necessary framework conditions for the online simulation and thus developing an expert system. The expert system is in constant connection with the real system and constantly monitors and optimizes it. The methodology for intelligent algorithms, digital agents and digital twins provides a framework for their practical application in a real production environment.
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
Ylipää, T.: Correction, prevention and elimination of production disturbances. PROPER project description, Department of Product and Production Development (PPD), Chalmers University of Technology, Gothenburg (2002)
Andersson, C., Bellgran, M.: On the complexity of using performance measures: enhancing sustained production improvement capability by combining OEE and productivity. J. Manuf. Syst. 35, 144–154 (2015)
Bellgran, M., Aresu, E.: Handling disturbances in small volume production. Robot. Comput.-Integr. Manuf. 19, 123–134 (2003)
Pinedo, M.L.: Scheduling: Theory, Algorithms, and Systems. Springer Science + Business Media, LLC (2012)
Rao, Y., He, F., Shao, X., Zhang, C.: On-line simulation for shop floor control in manufacturing execution system. In: Xiong, C., Liu, H., Huang, Y., Xiong, Y. (eds.) Intelligent Robotics and Applications, pp. 141–150. Springer, Berlin (2008)
Kamat, V.R., Menassa, C.C., Lee, S.H.: On-line simulation of building energy processes: need and research requirements. In: Proceedings of the 2013 Winter Simulation Conference: Simulation: Making Decisions in a Complex World, pp. 3008–3017 (2013)
Ang, A.T.H., Sivakumar, A.I.: Online multi objective single machine dynamic scheduling with sequence-dependent setups using simulation-based genetic algorithm with desirability function. In: Winter Simulation Conference, pp. 1828–1834 (2007)
Zupan, H., Herakovič, N., Starbek, M.: Hybrid algorithm based on priority rules for simulation of workshop production. Int. J. Simul. Model. 15, 29–41 (2016)
Zupan, H., Herakovič, N., Žerovnik, J., Berlec, T.: Layout optimization of a production cell. Int. J. Simul. Model. 16, 603–616 (2016)
Zupan, H., Herakovič, N., Žerovnik, J.: A hybrid metaheuristic for job–shop scheduling with machine and sequence-dependent setup times. In: 13th International Symposium on Operational Research in Slovenia, Bled, Slovenia, pp. 129–134 (2015)
Acknowledgment
The work was carried out in the framework of the GOSTOP programme (OP20.00361), which is partially financed by the Republic of Slovenia – Ministry of Education, Science and Sport, and the European Union – European Regional Development Fund. The authors also acknowledge the financial support from the Slovenian Research Agency (research core funding No. (P2-0248)).
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
Zupan, H., Šimic, M., Herakovič, N. (2021). Realization of an Optimal Production Plan in a Smart Factory with On-line Simulation. In: Borangiu, T., Trentesaux, D., Leitão, P., Cardin, O., Lamouri, S. (eds) Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future. SOHOMA 2020. Studies in Computational Intelligence, vol 952. Springer, Cham. https://doi.org/10.1007/978-3-030-69373-2_35
Download citation
DOI: https://doi.org/10.1007/978-3-030-69373-2_35
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-69372-5
Online ISBN: 978-3-030-69373-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)