Tool Wear Prediction and Alert Technology 2026/09/29

Introductions

Tool wear during metal machining is difficult for operators to detect or predict in real time, significantly affecting productivity and quality. This technology enables accurate tool life analysis, reducing unnecessary downtime from routine inspections and improving overall production efficiency.

Technical Advantages and Features

• Real-Time Reliable Wear Alerts: Provides real-time anomaly alerts with over 85% accuracy (industry average: ~80%). Optimizes tool change scheduling to maximize tool life.
• Rapid Model Deployment: Utilizes an unsupervised AI model and requires only three full tool life cycles for training. Modeling requires only tool change timestamps and operates without disrupting production.
• Broad Adaptability: Vibration signal analysis supports wide applicability in automated drilling, turning, and milling processes. Quickly adaptable to various tool types (e.g., end mills, turning tools, twist drills) and materials (e.g., stainless steel, ceramics), reducing deployment time by up to 50%.

Industrial Applications and Business Opportunities

• Industry Applications
  • Various Metal Machining Processes such as turning, milling, and drilling.
  • Intelligent Factory.
• Application Examples
  • This technology has been applied to machining centers, milling machines, and lathes. Adopted by leading domestic manufacturers for drilling heat exchanger tubes, it extends tool life by 10% and reduces rework by 50%.
  • It also enables small and medium-sized manufacturers to predict tool failure over one minute in advance, helping them meet strict quality and throughput requirements for substrate processing. The technology has been successfully adopted by a top-tier domestic semiconductor packaging and testing company.