The ITO line AOI inspection machine (also known as the step electrode automatic inspection machine, terminal scratch automatic inspection machine) is mainly used for defect detection of ITO in the exposed area of TFT-LCD lines, improving production line yield and the process control capability of manufacturers. Mainly detecting scratches, short circuits, open circuits, micro breaks, foreign objects (dirt), corrosion, burrs, etc. The equipment can be widely used in fields such as TFT-LCD industry, touch screen industry, photovoltaic industry, and LED industry, achieving rapid detection of ITO lines, silver paste lines, etc. on glass substrates or flexible substrates (PET, CPI, etc.).

TFT-LCD online foreign object line inspection machine is an AOI equipment used to detect product defects before and after bonding of LCD panels. It mainly detects foreign objects, corrosion, scratches and other defects, thereby improving production line yield and the manufacturer's process control capabilities.

The ACF conductive particle indentation+foreign object inspection machine is used to detect the ACF conductive particle indentation and bonding foreign objects on the COG and FOG parts of the bonding section of the LCD panel, including the number, distribution, indentation strength, deviation, and various foreign objects of the conductive particles. Its core technology is the use of infrared and differential interferometry techniques, using a line scan camera to optically image the bump area on the COG and FOG of the liquid crystal panel. The image is analyzed using traditional image algorithms and AI deep learning algorithms to ultimately confirm whether the target detection object is qualified.

The TFT-LCD edge inspection machine is developed and produced by Fuxin Optoelectronics. Based on machine vision and AI artificial intelligence technology, the TFT-LCD edge inspection machine integrates optics, mechanics, electronics, software, and algorithms. It is mainly used for automatic detection of edge defects in the TFT-LCD production process, achieving machine replacement. In practical applications, suspected defect areas are extracted from the edge sample images of TFT-LCDs after image processing, and judgment criteria are established to effectively eliminate interference. The types of defects such as edge extension, shell, edge collapse, and corner collapse are successfully determined, and the criteria are established to avoid repeated judgments and detect multiple defects simultaneously.

The glass cover of a mobile phone is the outermost glass of the touch screen. With the rise of smartphones, glass covers are widely used in the electronics industry. They are attached to the surface of touch screens to protect the screen and beautify products. The automatic detection of cover defects in the field of smartphones is considered a technological bottleneck that has plagued the industry for many years. The detection of surface defects in products requires high detection accuracy and reliable lighting effects to ensure, especially for the detection of glass cover plates after lamination, which is more difficult. At present, the device can detect white film and silk screened cover plates, and is compatible with the detection of 3D glass cover plates. It can also detect defects in car glass screens and TFT-LCDs.

The FPC flexible circuit board bonding foreign object inspection machine is used to detect defects such as FPC misalignment, bubbles, various foreign objects, and missing particles after FPC bonding. Using an array camera for double-sided shooting, taking defective images, extracting defects through software algorithms, designing different software algorithms for processing and classification according to different defects, and adjusting detection specifications based on algorithm thresholds. Real time monitoring of the bonding quality of the production line, equipment alarms remind employees to handle batch defects in a timely manner, greatly reducing the occurrence of defective products and preventing them from flowing to the next post.