THE SHOW | THE MICROTECHNOLOGY INFORMATION PORTAL
20.04.2026
K - Organizations
Intelligent Sensor Fusion for Tool Condition Monitoring in Milling
What if you could detect tool wear before it impacts your parts?
This project develops an intelligent multi-sensor monitoring system for milling operations, combining acoustic, vibration, and strain data with AI to predict tool condition in real production environments—without complex manual tuning.
👉 Who is it for?
Machine tool builders, precision machining companies (aerospace, medical, automotive, mould & die), tooling manufacturers, and sensor providers.
👉 Key benefits:
Detect tool wear and failure before damage occurs
Reduce scrap and rework on high-value parts
Optimize tool lifetime (avoid premature replacement)
Decrease machine downtime (today up to 20% linked to tools)
Move towards autonomous and data-driven machining
👉 Project objective:
Develop and validate a robust, AI-based multi-sensor system that works across machines, tools, and materials—ready for industrial integration.
👉 Partners are invited to:
test the solution on their own machines and processes,
access advanced know-how in sensor fusion and AI,
actively steer the project and gain early competitive advantage.
Led by inspire AG (ETH Zurich partner), the project combines expertise in machining, signal processing, and AI to bring next-generation tool monitoring closer to industrial reality.
Details and participation: https://cobooster.ch/