Predictive digital twin-driven dynamic error control for slow-tool-servo ultraprecision diamond turning

Abstract

A predictive digital twin (DT)-driven dynamic error control approach is presented for accuracy control in high-frequency slow-tool-servo ultraprecision diamond turning processes. An explainable artificial intelligence-enabled real-time DT of the total dynamic error (inside and outside the servo loop) was established using in-line acceleration input data near the tool. A feedforward controller was used to mitigate the total dynamic errors before they came into effect. The machining trials using this approach showed that significant improvement in machining accuracy (87%, surface form accuracy; 95%, phase accuracy with precisions of 0.06 µm and 0.05°), and efficiency (8 times the state-of-the-art) were successfully achieved.