Manual visual inspection is tiring and inconsistent, especially at high speeds. Computer vision uses cameras and AI models to inspect every part reliably.
Applications
- Defect detection: scratches, cracks, dents, discoloration
- Assembly verification: are all components present and correctly placed?
- Counting and measuring: parts per batch, dimensions
- Label and print inspection: readable text, correct codes
- Safety monitoring: protective equipment, restricted zones (with privacy safeguards)
How it works
- Image capture with industrial or standard cameras and consistent lighting
- Model training with images of good and defective parts
- Inference in real time on an edge device or server
- Action: reject parts, alert operators or log results
Data is key
Models need examples of defects – which are sometimes rare. Techniques like data augmentation, anomaly detection (learning only from good parts) and careful labelling help.
Accuracy and validation
Define acceptable false-positive and false-negative rates with the quality team. Validate on new images from production before going live and monitor performance continuously.
Integration
Connect to PLCs and line control systems, MES or ERP for traceability, and dashboards for quality trends.
Return on investment
- Fewer defective products reaching customers
- Less scrap and rework through early detection
- Consistent quality documentation
- Staff freed from repetitive inspection
Getting started
A feasibility study with sample images from your production shows quickly whether the defects can be detected reliably.
We develop computer vision solutions from proof of concept to production integration.