Pipeline for ontology-based modeling and automated deployment of digital twins for planning and control of manufacturing systems

• Published in: Journal of intelligent manufacturing 2023-06, Vol.34 (5), p.1-20
• Main Authors: Göppert, Amon, Grahn, Lea, Rachner, Jonas, Grunert, Dennis, Hort, Simon, Schmitt, Robert H
• Format: Article
• Language: English
• Subjects: Adaptability; Automation; Business and Management; Control; Cyber-physical systems; Data exchange; Deployment; Digital twin; Digital twins; Machines; Manufacturing; Mechatronics; Modelling; Ontology; Planning; Processes; Production; Robotics; Standardization; Workflow
• ISSN: 1572-8145; 0956-5515; 1572-8145
• DOI: 10.1007/s10845-021-01860-6

The demand for individualized products drives modern manufacturing systems towards greater adaptability and flexibility. This increases the focus on data-driven digital twins enabling swift adaptations. Within the framework of cyber-physical systems, the digital twin is a digital model that is fully connected to the physical and digital assets. A digital model must follow a standardization for interoperable data exchange. Established ontologies and meta-models offer a basis in the definition of a schema, which is the first phase of creating a digital twin. The next phase is the standardized and structured modeling with static use-case specific data. The final phase is the deployment of digital twins into operation with a full connection of the digital model with the remaining cyber-physical system. In this deployment phase communication standards and protocols provide a standardized data exchange. A survey on the state-of-the-art of these three digital twin phases reveals the lack of a consistent workflow from ontology-driven definition to standardized modeling. Therefore, one goal of this paper is the design of an end-to-end digital twin pipeline to lower the threshold of creating and deploying digital twins. As the task of establishing a communication connection is highly repetitive, an automation concept by providing structured protocol data is the second goal. The planning and control of a line-less assembly system with manual stations and a mobile robot as resources and an industrial dog as the product serve as exemplary digital twin applications. Along this use-case the digital twin pipeline is transparently explained.