市場前線｜智慧製造AI 驅動CNC 精度補償技術發展與趨勢

隨著智慧製造與工業4.0 快速發展，CNC 工具機加工精度已成為精密製造與高階製造競爭力的重要指標。傳 統精度補償多依賴離線量測、固定數學模型及人工經驗，面對熱變形、動態誤差、刀具磨耗與多變量耦合等非線性 與時間變量問題，已逐漸受到限制。本文探討AI 驅動CNC 精度補償技術之發展，分析靜態幾何、熱變形、動態及 控制量測等主要誤差來源，並介紹SVR、MLP、LSTM、CNN、強化學習、資料同化及數位雙生等方法於誤差預測 與即時補償之應用。同時，以工研院AI 物理導引精度補償技術為例，說明精度量測、誤差建模與控制器補償之閉環 整合。最後探討邊緣AI、聯邦學習、物理資訊神經網路 (PINN) 及智慧感測器等發展趨勢，期望推動CNC 精度補償 由被動校正朝向即時預測、自適應補償與AI 智慧化調機發展。

With the rapid development of smart manufacturing and Industry 4.0, machining accuracy of CNC machine tools has become a critical indicator of competitiveness in precision and advanced manufacturing. Traditional accuracy compensation approaches largely rely on offline measurements, fixed mathematical models, and human expertise. However, these methods face increasing limitations in addressing nonlinear and time-varying factors, including thermal deformation, dynamic errors, tool wear, and multivariable coupling effects. This study investigates the development of AI-driven CNC accuracy compensation technologies and analyzes major sources of machining errors, including static geometric errors, thermal deformation, dynamic errors, and control and measurement errors. Various AI-based approaches, including Support Vector Regression (SVR), Multilayer Perceptron (MLP), Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN), reinforcement learning, data assimilation, and digital twins, are reviewed for their applications in error prediction and real-time compensation. In addition, an AI-enabled physics-guided accuracy compensation approach developed by the Industrial Technology Research Institute (ITRI) is presented to illustrate the closed-loop integration of precision measurement, error modeling, and CNC controller compensation. Finally, emerging trends including edge AI, federated learning, Physics-Informed Neural Networks (PINNs), and intelligent sensing technologies are discussed. These developments are expected to drive CNC accuracy compensation from passive calibration toward real-time prediction, adaptive compensation, and intelligent machine-tool tuning.