Case

Technology type: Appearance inspection

Industry: 3C

Project: Visual AI deep learning

The project is based on Jie Xiang's self-developed intelligent algorithm platform, which can realize 360° autonomous inspection of the glass surface, back cover, and sides of mobile phones of different sizes and models; it can switch product colors according to production lines; set parameters for font deviation; and adjust parameters for defective size definitions according to inspection standards.

Main parameters:

1. Applicable products: mobile phone camera cover, wearable cover, touch glass cover

2. Applicable size: 1-8 inches

3. Inspection items: scratches, white lines, visible foreign matter, black spots, white spots, convex spots, concave spots, point-shaped foreign matter, edge collapse, corner collapse, hole collapse, sand edge, sand hole, oil overflow, offset bright edge, contour line, CD ripple, double step.

4. Inspection beat: 2-5 seconds/piece

5. Inspection accuracy: 0.03mm

6. False positive rate: <5%

7. Missed detection rate: <0.5%

8. Feeding method: automatic