optical lenses, MEMS sensors

1. Intelligent: AI and machine learning empower whole-process optimization - Adaptive Machining   -  AI algorithm analyzes cutting force, vibration, temperature and other data in real time, and dynamically adjusts feed rate and spindle speed to reduce tool wear and improve machining accuracy.     - Case study: Siemens developed an AI-driven control system that predicts tool life and provides early warnings, reducing downtime by 30%.   -  Process Parameter Optimization    - Machine learning models generate optimal cutting scenarios based on historical machining data, such as chip evacuation strategy optimization in deep hole drilling.   - Defect Prediction & Compensation:     - Combined with digital twin technology, the toolpath is compensated in advance by simulating possible distortions or errors during machining. 2. Hybrid Manufacturing: Seamless Integration of Additive and Subtractive Technologies -  3D Printing + CNC Composite Machining   - Additive manufacturing (e.g., metal 3D printing) for rapid prototyping of complex structures, CNC precision machining for surface finish and tolerance control.     - Case in point: DMG MORI's LASERTEC 3D series combines "printing + milling".   - Gradient Material Processing    - Combine multi-material 3D printing and CNC technology to manufacture parts with local performance differences (e.g. wear-resistant surface + lightweight core). 3. Ultra-precision machining: a breakthrough in nanometer precision -   Micro-nano processign technology    - The 5-axis linkage nano machine tool can process optical lenses, MEMS sensors, etc., with a surface roughness of Ra 1 nm or less.     - Applications: Semiconductor lithography machine parts, medical microrobot parts.   -  Extra Tool & Cooling Technology   - Diamond-coated tools, low-temperature liquid nitrogen cooling technology for efficient cutting of difficult-to-machine materials such as silicon carbide ceramics. 4. Green manufacturing: energy conservation and environmental protection have become the core indicators**   - Dry Cutting & Minimum Quantity Lubrication (MQL):     - Reduce the use of cutting fluid by 90%, reduce the cost of waste liquid disposal and environmental pollution.   -   Energy Recovery System   - Machine tool braking energy is fed back to the power grid, reducing energy consumption by 15%~20%. 5. Flexible Manufacturing: Efficient response for small batches and multiple varieties - Modular machine design:     - Quickly change spindles, tool magazines and fixtures to suit different parts machining needs.   -   Cloud Collaborative Production   - Through the industrial Internet platform, the processing program can be remotely issued and the status of global factory equipment can be monitored.     - Case study: FANUC's FIELD system supports multi-brand device interconnection.   - Digital Twin-Driven Changeovers:     - Virtual commissioning technology shortens the production changeover time by more than 50%, especially suitable for customized production of medical equipment. 6. Human-Robot Collaboration: From Automation to Autonomy**   - Collaborative Robot (Cobot) Integration:     - Robots are responsible for loading and unloading, testing, CNC machine tools focus on high-value machining, and man-machine collaboration improves efficiency.     - Application: The auto parts production line is unattended 24 hours a day.   -  AR/VR Assisted Operation & Training   - Augmented reality glasses guide workers to quickly master complex machine operations, reducing training cycles.   -   Autonomous Decision Making System   - Real-time data processing based on edge computing, the machine can choose the toolpath or call for maintenance independently.