Construction Method of CNC Machine Tool Digital Twin Model Based on the Four-Layer Framework
Digital twin (DT) has become a key technology to promote the development of intelligent manufacturing and has been widely used in the manufacturing industry. Computer numerical control (CNC) machine tool as an important equipment of intelligent manufacturing, due to its complex structure and complic...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10965695/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Digital twin (DT) has become a key technology to promote the development of intelligent manufacturing and has been widely used in the manufacturing industry. Computer numerical control (CNC) machine tool as an important equipment of intelligent manufacturing, due to its complex structure and complicated working conditions, DT technology is troubled by model consistency in application. To construct the DT model more effectively and accurately, a four-layer modeling framework is proposed based on the working characteristics of CNC machine tools, including requirement layer, representation layer, interaction layer and implementation layer. By taking the construction of the DT system of CNC machine tool for machining process as an example, the collection and processing of multi-source heterogeneous data and the monitoring of data-driven twin models are realized, a real-time dynamic cutting algorithm is developed on the basis of collision detection and mesh generation, the physical properties and working states of the model are verified by Fuzzy Analytic Hierarchy Process (FAHP) and Martens’ Distance Judgment, and the detection of tool wear status is completed by CNN-LSTM-Attention network model. Finally, the effectiveness and feasibility of the proposed framework are verified by a case of DT system construction of CNC lathe. |
|---|---|
| ISSN: | 2169-3536 |