Cutting model integrated digital twin-based process monitoring in small-batch machining
Abstract
The success of machining process automation hinges primarily on the effectiveness of the monitoring and adaptive control systems. A new digital twin-based process monitoring method and system in small batch machining is presented, and the cutting model is integrated into the monitoring method to improve the diagnosis accuracy. Model-based and signal-based monitoring indicators are developed, and indicators of the residual force component for the tool wear monitoring and energy ratio for the chatter detection are introduced to the digital twin-based monitoring. The critical monitoring algorithm is verified in two cases: tool wear monitoring and chatter detection. The results show that the method proposed can accurately evaluate the percentages of the residual useful life of the tool and the chatter. Moreover, a new process monitoring system in small batch machining is developed by integrating the advanced algorithm. This study can provide a critical reference for intelligent machining monitoring and control in industry.
