Semiconductors

Explore how META-aivi optimizes waste management with AI, reducing errors and avoiding contamination while enhancing the efficiency of plastic parts recycling.

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.

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.

Faulty wafers also usually have subtle defects randomly scattered on the surface, and this prevents AOI systems from setting rules for efficient inspections.