Abstract
Production systems are becoming more flexible and agile to realize the need for more individualized products. Robotics technology can accomplish these demands, but programming and re-configuration of robots are associated with high costs, especially for small- and medium-sized enterprises. The use of digital twins can significantly reduce these costs by providing monitoring and simulation capabilities for the robot and its environment using real-time data. The integration with an ontology as a knowledge base to describe the robot and its 3d-environment enables an automatic configuration of the digital twin and the particular robot. In this paper, this concept is coupled with cloud-computing to enable an effortless integration as service in existing cloud architectures and easy access using the common web-technology-stack for the end-users. A novel architecture is presented and implemented to incorporate the real system with its digital twin, the ontology and a planner to infer the actual operations from the knowledge base. Finally, the implementation is applied to the industrial manufacturing domain to assemble different THT-Devices on a PCB to evaluate the concept.
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Acknowledgment
The authors acknowledge the financial support from the “Production of the Future” program of the Austrian Ministry for Transport, Innovation and Technology under contract FFG 858707.
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Hoebert, T., Lepuschitz, W., List, E., Merdan, M. (2019). Cloud-Based Digital Twin for Industrial Robotics. In: Mařík, V., et al. Industrial Applications of Holonic and Multi-Agent Systems. HoloMAS 2019. Lecture Notes in Computer Science(), vol 11710. Springer, Cham. https://doi.org/10.1007/978-3-030-27878-6_9
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