Messe Demo
Visual anomaly detection
Automating quality control for small and medium production runs.
Claiber brings automated quality inspection to smaller batch sizes by reducing setup effort and removing key hurdles of classic optical inspection systems.
1. Challenge
Manual inspection causes cognitive load and inconsistent results.
Rule-based image processing becomes brittle with angles, textures and lighting changes.
2. Solution
Train instead of hard-code: anomaly detection with deep learning.
Reference images of the normal state are enough for a first model.
Simple labeling: OK and NOK.
System learns variants and stays deployable close to the line.
3. Validated results
More than 98% detection rate for surface inspection on gears.
More than 99% detection rate for defect detection on PCBs.
4. Technology and people
Visual AI with heatmaps for explainable results.
Assistant system to support workers, not replace them.
Shorter setup times compared with classic rule-based vision.
5. Technical specs
Connectivity: REST API, OPC UA, Modbus TCP and RTU, digital I/O.
Latency: from image to result in under 50 ms on local hardware.
Lighting: coaxial ring and flash options, plus polarization for reflective surfaces.
6. Goal of the pilot project
Validate the AI solution in real production: for complex surfaces, changing series conditions and as an assistance system for shop-floor teams.