META-aivi uses artificial intelligence to accurately identify size variations of the pipes instantaneously. Using the fast counting feature, all the different parts are classified and counted within seconds.
Automating precise grinding with SolMotion's 3D matching tech. Enhance quality, reduce waste, and boost productivity in metal component manufacturing.
SolVision’s superior recognition capabilities ensures that OCR of bicycles can be accurately carried out regardless of how the identification numbers look or light refraction levels.
With AI-based SolVision, production imperfections on club heads can be detected no matter their size, appearance, or location.
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.
The optimization dilemma: a large number of defects Hard drive metal bases are vulnerable to many defects during production, from damages to the metal surface to incorrect shape or size.
As welding positions and patterns are ever-changing, the number of possible variations makes it challenging for AOI systems to recognize welding weave patterns or locate missed welding spots and other production errors.
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.
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