Stability Study of Robotic Drilling System Based on Digital Twin

Digital twin technology has been widely incorporated into industrial maintenance to enhance Prognostics and Health Monitoring (PHM) systems and improve system stability. However, the stability of robotic drilling system is affected by various factors such as cutting force and vibration which are difficult to control. Therefore, this paper proposes a digital twin-based stability architecture for robotic drilling systems. The overall virtual entity model of the system is studied by mathematical and physical method, and the virtual entity and physical entity of the system operates simultaneously by combining the virtual and physical mapping of the system. In order to improve the stability of the system, a quality prediction and optimization model is established to solve the quality problems in the process of system operation. The experimental results demonstrate that the twin model exhibits a high level of accuracy in robot drilling. It has the capability to monitor key parameters in real-time during the machining process and retain data throughout the operation. By leveraging mathematical models for prediction and optimization, it effectively enhances the stability of the system.