System and method for automatically repairing substrate defects online

Abstract

The invention provides an on-line automatic substrate defect repairing system and method. The system comprises a laser unit, an optical unit, a monitoring device and a feedback device. Through the laser unit, the optical unit and the monitoring device, defects of a substrate can be scanned accurately, and high-accuracy scanning is realized; meanwhile, the feedback device is arranged and used for receiving scanning information, transmitted by the monitoring device, of the defects of the substrate and feeding back a scanning result to the laser unit through analysis, so that the defects are removed or repaired automatically on line by adjusting the wavelength and energy of lasers; the repair time is shortened, manpower resource waste caused by manual repair is avoided, the defect repair cost is lowered, and the repairing efficiency is improved.

Description

technical field [0001] The invention relates to the field of flat panel display, in particular to a system and method for automatically repairing defects of a substrate online. Background technique [0002] Flat panel display technology is becoming mature, but the components of the display panel, such as the array substrate, inevitably have some defects during the manufacturing process. For example, the scan lines and the data lines on the array substrate are prone to breakage due to their long lengths. When the scan line and the data line are disconnected, some pixels will not be able to operate (line defects), so it is necessary to try to repair the disconnection; in addition, it is very difficult to achieve zero defect rate by improving the process technology. Therefore, the substrate The defect repair technology becomes very important. [0003] In the prior art, the defect repair of the substrate is usually performed by means of laser welding and laser cutting. First,...

AI Technical Summary

Problems solved by technology

However, AOI inspection can only detect the approximate location of the defect, and cannot accurately find out the exact defect coordinates. The staff needs to find it manually. For a 1000mm long line, it takes at least 5 minutes to complete the inspection with human eyes (Taking 5μm pixel resolution as an example), the speed is slow and labor-intensive, and it is easy to cause eye fatigue and vision loss of inspectors

Moreover, manually searching for defects and repairing them will also cause a waste of human resources and increase the cost of repairs

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