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Article

Ontology-Based Production Simulation with OntologySim

wbk Institute of Production Science, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, 76131 Karlsruhe, Germany
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Academic Editors: Roque Calvo, José A. Yaguë-Fabra and Guido Tosello
Appl. Sci. 2022, 12(3), 1608; https://doi.org/10.3390/app12031608
Received: 4 January 2022 / Revised: 25 January 2022 / Accepted: 26 January 2022 / Published: 3 February 2022
Imagine the possibility to save a simulation at any time, modify or analyze it, and restart again with exactly the same state. The conceptualization and its concrete manifestation in the implementation OntologySim is demonstrated in this paper. The presented approach of a fully ontology-based simulation can solve current challenges in modeling and simulation in production science. Due to the individualization and customization of products and the resulting increase in complexity of production, a need for flexibly adaptable simulations arises. This need is exemplified in the trend towards Digital Twins and Digital Shadows. Their application to production systems, against the background of an ever increasing speed of change in such systems, is arduous. Moreover, missing understandability and human interpretability of current approaches hinders successful, goal oriented applications. The OntologySim can help solving this challenge by providing the ability to generate truly cyber physical systems, both interlocked with reality and providing a simulation framework. In a nutshell, this paper presents a discrete-event-based open-source simulation using multi-agency and ontology. View Full-Text
Keywords: ontology; production simulation; multi-agent; digital twin ontology; production simulation; multi-agent; digital twin
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MDPI and ACS Style

May, M.C.; Kiefer, L.; Kuhnle, A.; Lanza, G. Ontology-Based Production Simulation with OntologySim. Appl. Sci. 2022, 12, 1608. https://doi.org/10.3390/app12031608

AMA Style

May MC, Kiefer L, Kuhnle A, Lanza G. Ontology-Based Production Simulation with OntologySim. Applied Sciences. 2022; 12(3):1608. https://doi.org/10.3390/app12031608

Chicago/Turabian Style

May, Marvin Carl, Lars Kiefer, Andreas Kuhnle, and Gisela Lanza. 2022. "Ontology-Based Production Simulation with OntologySim" Applied Sciences 12, no. 3: 1608. https://doi.org/10.3390/app12031608

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