Spotting the blind spot
“In the case of Niko, we used a few hundred images of perfect and defective faceplates to train the algorithm. On the unacceptable faceplates, we indicated the defects down to the single-pixel level. Thanks to AI and computer vision, we could spot defects that weren’t even visible to the naked eye. With a high speed camera, the algorithm immediately and correctly identified every defective faceplate,” explains Sven Arnauts, manager of delaware.ai.
“The AI platform wrote its own algorithm in only a few hours. The big advantages are accuracy, cost efficiency and time savings, but you also don’t need any programming knowledge to create an algorithm. Even more, this technology runs in the Microsoft Azure cloud, so it doesn’t require an expensive server farm,” according to Sven.
“With the help of Robovision, Niko was able to decrease the number of ‘good’ products that were wrongly taken off the conveyor belt by 72%. The number of ‘bad’ products that wrongfully remained on the conveyor belt was cut by 33%,” Sven reveals.