Adoption of opto-mechanical integration solutions, machine vision instead of the human eye, and the use of deep learning on the appearance of the product defects automatic detection, can be achieved to distinguish between the depth of the division, sub-Bin shipments.
Escape(Functional defects)
%
0
Escape(Non functional defects)
%
<0.3
Overkill
%
<1
CT
s/pcs
2
Accuracy
mm
<0.0044
Items
More than 40 surface defects can be monitored, including frontal abrasion, inner circle breakage, frontal abrasion, frontal collapse, top surface scratch, top surface crush, inner circle damage, outer circle damage, top surface abrasion, top surface deformation, top surface failure, top surface leakage of precision abrasion, glass bit scratches, glass bit gouges, glass bit abrasion, glass bit whiteness, glass bit burrs, no adhesive overflow grooves, and adhesive overflow grooves with foreign objects.
Advantages
Detects defects in polished metal surfaces that are not recognisable to the naked eye. Measure the depth of scratches and distinguish between deep and shallow divisions.
Effects
Replace 10 quality inspectors.