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Industrial Communication with Semantic Integration Patterns

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Innovative Intelligent Industrial Production and Logistics (IN4PL 2023)

Abstract

Digital twins have emerged as a key technological concept in the manufacturing industry. They form an information hub for industrial equipment and interact with dedicated applications in the operational manufacturing network. Digital twins consume and deliver information from machines to basically all connected applications. This results in complex integration requirements. The paper builds on previously designed semantic interoperability concepts for data-driven digital twins. It gives an overview of semantic data integration standards and provides insights into the current implementation of semantic integration patterns. Based on the challenges of the underlying research project “i-Twin”, semantic integration patterns provide standardized communication channels for operational management systems and connected assets. They build on the services of the semantic data integration middleware and use semantic connectors to bridge the proprietary data objects with an I4.0 compliant information model based on the asset administration shell (AAS). Semantic integration patterns will reduce the integration effort for equipment manufacturers and software providers, thereby accelerating automation and digitalization processes.

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Acknowledgements

The research presented in this paper has been conducted in the i-Twin project (title: “Semantic Integration Patterns for Data-driven Digital Twins in the Manufacturing Industry”), which is funded by the Austrian Federal Ministry for Climate Action, Environment, Energy, Mobility, Innovation and Technology (BMK) and the Austrian Research Promotion Agency (FFG) within the research programme “ICT of the Future”. The project has a duration of 27 months and will end in March 2024.

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Correspondence to Georg Güntner .

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Güntner, G., Glachs, D., Linecker, S., Strohmeier, F. (2023). Industrial Communication with Semantic Integration Patterns. In: Terzi, S., Madani, K., Gusikhin, O., Panetto, H. (eds) Innovative Intelligent Industrial Production and Logistics. IN4PL 2023. Communications in Computer and Information Science, vol 1886. Springer, Cham. https://doi.org/10.1007/978-3-031-49339-3_20

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  • DOI: https://doi.org/10.1007/978-3-031-49339-3_20

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-031-49339-3

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