Digital Twin Model Construction of CNC Machine Tools for Service Performance - LI Yilin; ZUO Ying; ZHANG Yongping; TAO Fei (Journal of Harbin University of Science and Technology, 2025)
CNC machine tools are key core equipment that are urgently needed for manufacturing. In recent years, the factory performance of high-end CNC machine tools in China has been significantly improved, but the lack of service performance such as accuracy retention has restricted the process of domestic substitution in key areas, and it is urgent to achieve accurate characterization of service performance through digital means. Digital twin technology deeply integrates model-driven and data-driven methods, integrates multi-dimensional and multi-scale models and multi-source heterogeneous data, and constructs high-fidelity holographic mapping virtual machine tools, providing an effective means for accurate characterization of the service performance of CNC machine tools. This paper proposes a theoretical framework for digital twin modeling of CNC machine tools for service performance. On this basis, three key technologies are proposed for high-end CNC machine tools: analysis of service performance influencing factors and model components, construction of multi-dimensional and multi-scale digital twin models, and verification of multi-dimensional and multi-scale digital twin models under variable working conditions. The relevant work is expected to provide a theoretical reference for improving the service performance of CNC machine tools.