Machine vision is utilized to perform Optical Character Recognition (OCR). This information is sent to the cloud to create an inspection report, allowing plant operators to easily monitor facility inspection through mobile devices.
Powered by deep learning, SolVision recognizes soldering defects in overlapped solder balls through labeling of sample images
With SolVision’s Instance Segmentation tool, the various placement possibilities of chips on carrier trays can be learned by AI image processing.
The Anomaly Detection tool uses deep learning technology to teach the AI model sample images of “perfect” wafers.
The location, size and shape of cracks vary each time, and traditional optical inspection cannot accurately identify such unpredictable defects.
Using SolVision’s Instance Segmentation tool, irregular lines and multi-drilling defects are labeled in sample images to train the AI model.
Using SolVision’s AI Inspection Solution, minute defects such as fine scratches can be located and marked on sample images to train the AI model.
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.
SMT is a critical soldering process in the electronics industry. SolVision detects defects on PCBs which are known to have numerous small, complex components
Faulty wafers also usually have subtle defects randomly scattered on the surface, and this prevents AOI systems from setting rules for efficient inspections.
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