There are many types of defects that may appear differently each time on the stamped parts, in particular oil or water stains, which are not easily detected.
For repetitive manual tasks such as in this case, an automated visual inspection can help identify defective products and improve workforce efficiency.
Small, spiral-surfaced metal parts can be inspected using SolVision’s Instance Segmentation tool to learn the different types of cut marks or collision faults from sample images, then building an AI model to recognize these subtle defects.
Powered by AI, Solomon SolVision can automate welding inspection processes by learning the different shapes and features of weld beads from sample images.
Using OCR with AI deep learning, SolVision reads and detects various text and number defects on printed labels, enhancing electronics product label inspection.
