Knowledge Graphs in the Digital Twin: A Systematic Literature Review About the Combination of Semantic Technologies and Simulation in Industrial Automation
The ongoing digitization of the industrial sector has reached a pivotal juncture with the emergence of Digital Twins, offering a digital representation of physical assets and processes. One key aspect of these digital representations is the utilization of simulation models, enabling a deeper insight...
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| Format: | Article |
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IEEE
2024-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10788678/ |
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| author | Franz Georg Listl Daniel Dittler Gary Hildebrandt Valentin Stegmaier Nasser Jazdi Michael Weyrich |
| author_facet | Franz Georg Listl Daniel Dittler Gary Hildebrandt Valentin Stegmaier Nasser Jazdi Michael Weyrich |
| author_sort | Franz Georg Listl |
| collection | DOAJ |
| description | The ongoing digitization of the industrial sector has reached a pivotal juncture with the emergence of Digital Twins, offering a digital representation of physical assets and processes. One key aspect of these digital representations is the utilization of simulation models, enabling a deeper insight into the asset’s current state and its characteristics. This paper asserts that the next evolutionary step in this digitization journey involves the integration of intelligent linkages between diverse simulation models within the Digital Twin framework. Crucially, for the Digital Twin to be a scalable and cost-effective solution, there is a pressing need for automated adaption, (re-)configuration, and generation of simulation models. Recognizing the inherent challenges in achieving such automation, this paper analyses the utilization of knowledge graphs as a potentially very suitable technological solution. Knowledge graphs, acting as interconnected and interrelated databases, provide a means of seamlessly integrating different data sources, facilitating the efficient integration and automated adaption of data and (simulation) models in the Digital Twin. We conducted a comprehensive literature review to analyze the current landscape of knowledge graphs in the context of Digital Twins with a focus on simulation models. By addressing the challenges associated with scalability and maintenance, this research contributes to the effective adoption of Digital Twins in the industrial sector, paving the way for enhanced efficiency, adaptability, and resilience in the face of evolving technological landscapes. |
| format | Article |
| id | doaj-art-d4b1df8064dd4a688fb14c3fa4510cf9 |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-d4b1df8064dd4a688fb14c3fa4510cf92025-08-20T02:49:09ZengIEEEIEEE Access2169-35362024-01-011218782818784310.1109/ACCESS.2024.351492310788678Knowledge Graphs in the Digital Twin: A Systematic Literature Review About the Combination of Semantic Technologies and Simulation in Industrial AutomationFranz Georg Listl0https://orcid.org/0009-0007-6968-5852Daniel Dittler1https://orcid.org/0000-0002-0760-4929Gary Hildebrandt2https://orcid.org/0000-0001-6538-5667Valentin Stegmaier3https://orcid.org/0000-0001-5001-3799Nasser Jazdi4https://orcid.org/0000-0001-6722-0911Michael Weyrich5https://orcid.org/0000-0003-3176-9288Institute of Industrial Automation and Software Engineering, University of Stuttgart, Stuttgart, GermanyInstitute of Industrial Automation and Software Engineering, University of Stuttgart, Stuttgart, GermanyInstitute of Industrial Automation and Software Engineering, University of Stuttgart, Stuttgart, GermanyInstitute of Industrial Automation and Software Engineering, University of Stuttgart, Stuttgart, GermanyInstitute of Industrial Automation and Software Engineering, University of Stuttgart, Stuttgart, GermanyInstitute of Industrial Automation and Software Engineering, University of Stuttgart, Stuttgart, GermanyThe ongoing digitization of the industrial sector has reached a pivotal juncture with the emergence of Digital Twins, offering a digital representation of physical assets and processes. One key aspect of these digital representations is the utilization of simulation models, enabling a deeper insight into the asset’s current state and its characteristics. This paper asserts that the next evolutionary step in this digitization journey involves the integration of intelligent linkages between diverse simulation models within the Digital Twin framework. Crucially, for the Digital Twin to be a scalable and cost-effective solution, there is a pressing need for automated adaption, (re-)configuration, and generation of simulation models. Recognizing the inherent challenges in achieving such automation, this paper analyses the utilization of knowledge graphs as a potentially very suitable technological solution. Knowledge graphs, acting as interconnected and interrelated databases, provide a means of seamlessly integrating different data sources, facilitating the efficient integration and automated adaption of data and (simulation) models in the Digital Twin. We conducted a comprehensive literature review to analyze the current landscape of knowledge graphs in the context of Digital Twins with a focus on simulation models. By addressing the challenges associated with scalability and maintenance, this research contributes to the effective adoption of Digital Twins in the industrial sector, paving the way for enhanced efficiency, adaptability, and resilience in the face of evolving technological landscapes.https://ieeexplore.ieee.org/document/10788678/Digital twinknowledge graphsemantic technologiessimulation |
| spellingShingle | Franz Georg Listl Daniel Dittler Gary Hildebrandt Valentin Stegmaier Nasser Jazdi Michael Weyrich Knowledge Graphs in the Digital Twin: A Systematic Literature Review About the Combination of Semantic Technologies and Simulation in Industrial Automation IEEE Access Digital twin knowledge graph semantic technologies simulation |
| title | Knowledge Graphs in the Digital Twin: A Systematic Literature Review About the Combination of Semantic Technologies and Simulation in Industrial Automation |
| title_full | Knowledge Graphs in the Digital Twin: A Systematic Literature Review About the Combination of Semantic Technologies and Simulation in Industrial Automation |
| title_fullStr | Knowledge Graphs in the Digital Twin: A Systematic Literature Review About the Combination of Semantic Technologies and Simulation in Industrial Automation |
| title_full_unstemmed | Knowledge Graphs in the Digital Twin: A Systematic Literature Review About the Combination of Semantic Technologies and Simulation in Industrial Automation |
| title_short | Knowledge Graphs in the Digital Twin: A Systematic Literature Review About the Combination of Semantic Technologies and Simulation in Industrial Automation |
| title_sort | knowledge graphs in the digital twin a systematic literature review about the combination of semantic technologies and simulation in industrial automation |
| topic | Digital twin knowledge graph semantic technologies simulation |
| url | https://ieeexplore.ieee.org/document/10788678/ |
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