The flat panel display industry, as a key sector of modern information technology, the precision of its manufacturing process directly affects the visual experience and reliability of the end products. In the mainstream display technology routes such as TFT, OLED, and LCD, the quality control throughout the entire process from substrate preparation to module assembly cannot be achieved without the deep involvement of advanced optical detection technologies.

The intelligent optical inspection system integrates high-resolution imaging, multispectral analysis and deep learning algorithms, enabling micro-metric defect identification and quantitative assessment of display panels. The system uses multi-dimensional optical acquisition modules to capture key indicators such as uneven brightness, pixel anomalies, and circuit defects on the panel surface, and builds a three-dimensional topography data model to achieve comprehensive detection from the macroscopic panel to the microscopic circuit.
In the manufacturing process of the display panel, the system focuses on detecting the following aspects: the accuracy of line width and spacing on the substrate circuit, the uniformity of the thickness of the film deposition layer, the airtightness and integrity of the packaging process, and the alignment accuracy of the module bonding. For the bending area of the flexible OLED screen, a special optical compensation technology is adopted to overcome the problem of perspective distortion in curved surface detection, ensuring the reliable evaluation of the irregular structure.
Compared with traditional manual inspection or single-dimensional detection equipment, the intelligent optical inspection system has significant advantages such as non-contact, high efficiency, and traceable data. It has been widely applied in high-generation liquid crystal panel production lines, flexible display mass production workshops, and other high-end manufacturing scenarios, providing key technical support for the quality upgrade of the display industry.