The ontology-based modeling and evolution of digital twin for assembly workshop

Digital twin (DT) technology has been entrusted with the tasks of modeling and monitoring of the product, process, and production system. Moreover, the development of semantic modeling and digital perception provides the feasibility for the application of DT in the manufacturing industry. However, the application of DT technology in assembly workshop modeling and management is immature for the discreteness of assembly process, diversity of assembly resource, and complexity of dataflow in the assembly task execution. A method of ontology-based modeling and evolution of DT for the assembly workshop is proposed to deal with this situation. Firstly, the ontology-based modeling method is given for the assembly resource and process. By instantiating in the ontology, resources and processes can be involved in the modeling and evolution of the DT workshop. Secondly, the DT assembly workshop framework is introduced with the detailed discussions of dataflow mapping, DT evolution, storage, and tracing of historical data generated during the operation of the workshop. In addition, a case study is illustrated to show the entire process of construction and evolution of the DT modeled on an experimental field, indicating the feasibility and validity of the method proposed.

Automated summary

Digital twin technology is utilized for modeling and monitoring in the manufacturing industry, with a focus on assembly workshop modeling and management. An ontology-based method is proposed to address the immaturity in this area, including modeling processes and resources, and introducing a framework for the assembly workshop. A case study is provided to demonstrate the feasibility and validity of the proposed method.