A digital twin synchronous evolution method of CNC machine tools associated with dynamic and static errors

• Published in: International journal of advanced manufacturing technology Vol. 134; no. 5-6; pp. 2753 - 2763
• Main Authors: Sa, Guodong, Sun, Jiacheng, Hou, Mingjie, Jiang, Zhengyang, Liu, Zhenyu, Mao, Haoyang, Huang, Kun, He, Liang, Tan, Jianrong
• Format: Journal Article
• Language: English
• Published: London Springer London 01.09.2024
• Subjects: CAE) and Design; Computer-Aided Engineering (CAD; Engineering; Industrial and Production Engineering; Mechanical Engineering; Media Management; Original Article; Dynamic and static errors; Machine tools; Digital twin; Synchronous evolution
• ISSN: 0268-3768; 1433-3015
• DOI: 10.1007/s00170-024-14244-w

In the machining process of computer numerical control (CNC) machine tools, both dynamic and static errors significantly impact the machining accuracy. The ability to accurately estimate the machining quality of products in real time is of great significance for the closed-loop control of machining accuracy of CNC machine tools. For this purpose, this paper presents a digital twin synchronous evolution method of CNC machine tools by associating dynamic and static errors. Initially, a digital twin intrinsic model of CNC machine tools with static geometric errors is constructed in the virtual space, and the high-fidelity mapping of digital twin of CNC machine tools oriented to product processing path is realized. Subsequently, an acquisition method of multi-scene perception data of CNC machine tools is described, and the unified representation of multi-source heterogeneous data is achieved based on semantic mapping. Finally, dynamic errors such as spindle thermal deformation and tool wear are analyzed in real time using integrated multi-scene sensing data. These errors, along with the static geometric errors of the tool, are reflected to the workpiece through the tool machining trajectory, which provides a basis for the closed-loop control of digital twin oriented to product quality. The proposed method is integrated into the digital twin platform of CNC machine tools, and the effectiveness of the method is verified.