Autonomous CNC Machine Tools Powered by AI for Proactive Maintenance and Self-Restoration

In the modern manufacturing environment, ensuring the efficient operation of CNC (Computer Numerical Control) machines is vital for reducing downtime and improving productivity. This study introduces an innovative framework that combines artificial intelligence (AI) with digital twin technology to support predictive maintenance in CNC systems. Using IoT (Internet of Things) sensors, continuous operational data are gathered from CNC machines to build a dynamic digital twin that mirrors real-time machine behavior and performance. Advanced machine learning methods, particularly XGBoost, are applied to both historical and live data to identify early signs of failure and to optimize maintenance planning. The proposed approach improves the reliability of maintenance predictions while substantially lowering maintenance expenses and unexpected machine outages. This work advances smart manufacturing research and emphasizes the significance of AI-based solutions in strengthening predictive maintenance practices in industrial applications.