Digital Twin–oriented real-time cutting simulation for intelligent computer numerical control machining

Author(s):  
Xian Cao ◽  
Gang Zhao ◽  
Wenlei Xiao

Digital Twin has become a frontier research topic in recent years and the important development direction of intelligent manufacturing. For numerical control machining, a Digital Twin system can be used as an intelligent monitoring and analysis center by reflecting the real machining process in a virtual environment. The machining simulation is the key technology to realize this kind of application. However, existing machining simulation systems are designed for off-line situation that cannot be used directly in Digital Twin environment. The challenges for machining simulation are analyzed and explained in this article: (1) complete process data representation in simulation system; (2) executing in cooperating with computer numerical control system; (3) more efficient simulation algorithm. In order to meet these challenges, a new machining simulation system is proposed. STEP-NC standard is used to save complete process data exported from the computer-aided manufacturing system and synchronization algorithm is developed based on the communication data of computer numerical control system. Most importantly, an optimized tri-dexel-based machining simulation algorithm is developed to perform high efficiency that can follow the real machining process. Finally, a Digital Twin system for NC machining is presented that has been tested and verified in a workshop located in COMAC (Commercial Aircraft Corporation of China Ltd).

BioResources ◽  
2020 ◽  
Vol 16 (1) ◽  
pp. 1115-1130
Author(s):  
Aleksandar Rakic ◽  
Sasa Zivanovic ◽  
Zoran Dimic ◽  
Mladen Knezevic

This paper presents an application of an open architecture control system implemented on a multi-axis wood computer numerical control milling machining center, as a digital twin control. The development of the digital twin control system was motivated by research and educational requirements, especially in the field of configuring a new control system by “virtual commissioning”, enabling the validation of the developed controls, program verification, and analysis of the machining process and monitoring. The considered wood computer numerical control (CNC) machining system is supported by an equivalent virtual machine in a computer-aided design and computer-aided manufacturing (CAD/CAM) environment, as well as in the control system, as a digital twin. The configured virtual machines are used for the verification of the machining program and programming system via machining simulation, which is extremely important in multi-axis machining. Several test wood workpieces were machined to validate the effectiveness of the developed control system based on LinuxCNC.


Author(s):  
Jie Huang ◽  
Xu Du ◽  
Li-Min Zhu

The acceleration/deceleration feedrate scheduling is one of the most important techniques in computer numerical control systems. Along with this technique, the bi-directional scanning technique is always employed. The bi-directional scanning technique consists of a backward scanning process followed by a forward scanning process. The two scanning processes in the conventional methods are executed in a serial manner by scanning through all the scheduling blocks one by one. Consequently, the feedrate scheduling will suffer from a heavy computational burden when there are massive blocks to be scanned, which deteriorates its real-time performance for computer numerical control machining. To alleviate the computational burden, a parallel acceleration/deceleration feedrate scheduling approach is proposed in this article. With this method, the scheduling blocks are splitted into several scheduling units and the feedrate for each of them is scheduled simultaneously. The feasibility of the proposed approach is validated through the feedrate scheduling for two widely used butterfly and helix paths. For a constructed example of feedrate scheduling, a significant acceleration ratio about 3.7 on a personal computer with a quad-core central processing unit is achieved.


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