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.
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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)).
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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
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DOI: https://doi.org/10.1007/978-3-030-69373-2_35
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