Timely detection of defects decreases the production of defective items by up to 80% per year
To detect defects, information about the surface obtained using a laser, as well as conventional camera shots, is used.
The resulting photos of pallets are processed using a pre-trained neural network. Every time there is a defect in the image, the network reports it to the operator interface using a color signal. Yellow frame - a tile with a defect, purple - a repeating defect.