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Knowledge-graph-based multi-domain model integration method for digital-twin workshops

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Abstract

The digital twin workshop is a new workshop operation paradigm that enables precise decision-making by fusing virtual and physical space. As a complex manufacturing system, the digital twin model of the workshop must integrate models from different domains in order to provide personalized services. The interoperability of multi-domain models and the dynamic update of parameters become obstacles. In this paper, a knowledge graph (KG)-based multi-domain model integration method for digital twin workshops is proposed. The multi-domain model integration architecture based on KG is consisted of model element, model ontology, model data, semantic integration, and network connection. Then, the KG of multi-domain model for design, manufacturing, and simulation is constructed through ontology modeling and knowledge extraction. On this basis, multi-domain model integration is realized through semantic inference and knowledge query. The model parameters are updated through file exchange during the dynamic simulation. Finally, multiple scenarios in the subassembly workshop for hull construction are used to verify the efficacy of the proposed method. During the assembly and welding of hull parts, the integration of the product model, equipment model, and simulation model is realized, which assists in meeting the service requirements of multiple business scenarios.

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Funding

This work was supported by the National Key Research and Development Program of China (2020YFB1711300), and the Special Project on Cooperation and Exchange of Shanxi Province Science and Technology, China (No. 202204041101036).

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Authors and Affiliations

  1. Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China

    Xiangdong Wang

  2. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China

    Xiaofeng Hu

  3. Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing, School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China

    Zijie Ren, Tianci Tian & Jiafu Wan

Authors
  1. Xiangdong Wang
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  2. Xiaofeng Hu
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  3. Zijie Ren
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  4. Tianci Tian
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  5. Jiafu Wan
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Contributions

The first draft of the manuscript was written by Xiangdong Wang. The suggestions on revision were provided by Jiafu Wan and Xiaofeng Hu. The experimental assistance was provided by Zijie Ren and Tianci Tian. All authors read and approved the final manuscript.

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Correspondence to Jiafu Wan.

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Wang, X., Hu, X., Ren, Z. et al. Knowledge-graph-based multi-domain model integration method for digital-twin workshops. Int J Adv Manuf Technol 128, 405–421 (2023). https://doi.org/10.1007/s00170-023-11874-4

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