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.
SolVision enables visual inspection through AI image analysis, strengthening the reliability of displacement and angle information to recognize defective products and errors in the die bonding process.
With SolVision OCR identification numbers can be analyzed and converted into numerical data for database logging and connecting with automobile identification numbers in real-time
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.
Faulty wafers also usually have subtle defects randomly scattered on the surface, and this prevents AOI systems from setting rules for efficient inspections.
Excessive adhesive may remain on the chip or overflow on the circuit board and cause the chip to tilt, affecting stability of the whole semiconductor package.
For repetitive manual tasks such as in this case, an automated visual inspection can help identify defective products and improve workforce efficiency.
