Automatisert visuell kvalitetsinspeksjon

Manual visual inspection is slow, tiring and inconsistent – especially on fast production lines. Matomai, a member of the Hightech Kaunas cluster, develops automated quality inspection systems based on computer vision and artificial intelligence that check every product, every time, and record the results for traceability.

What automated inspection detects

• Surface defects such as scratches, cracks, stains or dents.
• Dimensional deviations and incorrect shapes.
• Missing, misplaced or incorrect components.
• Labelling, printing and packaging errors.

Benefits for manufacturers

• Consistent quality – the same criteria applied to every item.
• Lower costs – fewer defective products reaching customers and less rework.
• Traceability – images and inspection results stored for analysis and audits.
• Process insight – defect statistics that help find root causes.

Rule-based and AI-based inspection

Some inspection tasks can be solved with classic image processing and clear rules. Others – such as natural materials or defects that vary in appearance – benefit from machine learning models trained on examples. Matomai combines both approaches, using 2D and 3D vision depending on what needs to be measured or detected.

Integration on the production line

An inspection system is only useful if it fits into production. Matomai designs the camera setup, lighting and software together with integration into line controls, rejection mechanisms and production data systems, and can combine inspection with robotic solutions where automated handling is needed.

Frequently asked questions

How many defect examples are needed to train the system?

It depends on the task. The feasibility phase defines what data is needed and how it can be collected.

Can inspection run at full line speed?

Systems are designed for the required throughput; speed and accuracy targets are agreed at the start of the project.

Learn more about Matomai or contact Hightech Kaunas to automate your quality control.