This thesis involves the research on the automation of the inspection of circular saw blades using machine vision techniques combined with artificial intelligence. A background study related to the topic of sawblade inspection was initially conducted before carrying out this thesis work.

Saw blade samples were collected for the creation of image data to be used for the training of the AI of the Cognex vision system that was used. An inspection rig was built onto which the saw blades were mounted for both image acquisition and inspection. The inspection was but in an ABB robot cell. A saw blade with 54 teeth that contained defective and non-defective teeth was used for testing the proposed solution and it could be seen in the results section that the saw blade was successfully inspected for flatness, wear and tear by measuring tooth tip angles, surface defects on the tooth and finally the presence of burn marks.