1. Web-based architecture, allowing multiple users to log in remotely through the domain
2. Integrate and store a large amount of defect data and images detected by AOI equipment, which can be used for production history statistical analysis, real-time monitoring of online AOI equipment defect detection status, defect photo viewing, product defect Map overlay and defect type judgment Code and other functions
3. Can be combined with AI for big data analysis and feedback to production equipment to issue warnings for production anomalies

1. Resolution and defect detection capability range can reach 1.5um~5um
2. Zero dead angle detection area, can achieve 100% full panel coverage
3. Excellent autonomous image detection technology can support all sizes and different touch image designs
4. Intelligent defect classification function
5. Provide professional and customized services

Cognex's AI tools help minimize defects related to assembly processes in mini LED screen manufacturing, including solder volume and alignment of LED chips on bonding pads. The detection system uses a series of images representing both good and NG (defective) results during its training phase. It learns to tag notable defects while disregarding abnormal situations within acceptable tolerances. These tools are capable of precisely locating and identifying targeted inspection zones (ROIs) along with any potential critical defects present within those regions. Manufacturing managers can use this information to more efficiently manage the quality of displays, thereby reducing costs and increasing profitability.

1. Flaw detection for various sizes of polarizing plates, brightness films, light guide plates or color filters
2. Detection of various defects, such as foreign objects, creases, indentations, PVA patterns, etc.
3. Three-part mobile inspection, using multiple angles, different light sources and multi-directional methods for measurement
4. CCD can choose different resolutions according to pixel and pitch size, as a judgment for defect measurement
5. Linear and area cameras can be selected for mixed detection of different defects and different accuracies
6. Integrated and customized design to reduce unnecessary adjustment and development costs
7. Can be integrated with production history, scan barcode to link work orders and serial numbers, and complete traceability system with customized database

1. Resolution and defect detection capability range can reach 3um~5um
2. Detection area can cover both the mask area and the frame area at the same time
3. Inspection technology can support mask products with different image designs and any shape
4. Intelligent defect classification function

1. Common appearance defect inspection of optical films: creases, hand sweat, residual glue, water stains, foreign objects, black lines, oil stains, etc.
2. Inspectable materials: upper diffusion film, lower diffusion film, composite film, lamination film and brightening film, etc.

1. Real-time autofocus
2. Real-time image stabilization function
3. Smart measurement function
4. Comprehensive observation of bright field and DIC
5. Ultra-long depth of field synthesis function
6. Ultra-large range puzzle
7. Image target navigation
8. AI defect target detection
9. 3D profile measurement

Cognex's AI technology helps microLED manufacturers identify defective chips on display panels by being trained with a range of images showing both good and NG (defective) outcomes, enabling the software to skip over insignificant variations within tolerance ranges and instead flag major defects. This analysis tool scans specific areas of the panel, locating subtle imperfections in microLED components. Production managers can utilize a classification tool to categorize various defect types, optimizing upstream processes and boosting overall manufacturing efficiency. By detecting and resolving defects early in the process at an economically viable cost, this solution enables manufacturers to supply their customers with higher quality panels.

1. AI real-time detection; detection calculation speed can reach up to 50 FPS or more
2. Detection items: copper pad defects, offset, LED bonding abnormalities (chip position displacement/rotation)
3. Can support different sizes of substrates/panels according to customer needs

1. Ultra-high-speed AI real-time detection
2. Detection items: Chip defects, damage, dirt, scratches, missing chips
3. Post-mass transfer chip position displacement/rotation measurement
4. Can support “4~8" wafers and different sizes of panels according to customer needs

1. High-speed detection + AI defect classification
2. Detection items: Open/short circuits, foreign objects, dirt, scratches in the display area and peripheral Fan-Out area
3. Can support different sizes of substrates/panels according to customer needs

Cognex's AI visual system and software assist manufacturers in identifying and classifying genuine LED chip defects through training with a series of images representing good and NG (no-good or defective) results. The software is then able to mark only significant defects within the target inspection area (ROI), which the defect detection tool identifies. Following this, the classification tool categorizes the defects based on the information gathered. With this information, production managers can increase the yield rate of high-quality LED products, address and solve production issues by utilizing classification data, ultimately enhancing profitability.

1. Can provide images of different magnifications
2. Composite camera head design (supports 1-4 Review Head groups)
3. Can correspond to defect data produced by different AOI equipment
4. Intelligent defect classification function

Cognex's AI-based solutions can help high-power LED manufacturers identify and classify significant packaging defects. We train this advanced vision solution using a set of images representing good and defective (NG) results, allowing the software to filter out anomalies within the acceptable range and only flag relevant defects. The location tools can identify the regions of interest (ROI) to inspect. Once the ROI is defined, the defect detection tool identifies any major defects within that area.

1. Applicable products: G+G, TP+LCM
2. Detection resolution: 10μm
3. Detection accuracy: 30μm or above in length or width
4. Inspection items: internal bubbles, foreign objects, bonding accuracy
5. Special function: can be used for product stratification to detect only internal defects
6. The machine software establishes a basic AOI framework, which can plan for the machine to learn the software by itself. The client can establish the defect code by itself, so that the machine can deeply identify and learn, so as to achieve the final intelligent judgment and classification inspection machine.

1. 5-8inch≤12S，1-12inch≤20S，12.1-17inch≤35S
2. False detection rate ≤ 3%, missed detection rate ≤ 0 PPM, to meet customer's outgoing quality control rate
3. Use advanced algorithms to stably detect ITO micro scratches
4. Can generate daily production inspection details and has MES upload function for convenient product information query

1. Extensive experience in inspection of various sizes and products in the industry
2. Can be planned according to various needs such as buffer zone, cassette, manual inspection station, drawer, overhead conveyor, scrap car, etc.
3. Flexible software design to meet customer operation habits
4. Statistical data can be uploaded to the factory manufacturing system or directly output as a report
5. Complete education and training and technical support service system

Cognex's VisionPro software provides a fast and accurate way to count Mini LEDs before packaging. Operators can easily train the software to identify, locate and count patterns of extremely small LED die. The pattern counting tool looks for grayscale pixel value patterns defined by features. Regardless of how pixel intensities vary between images, it can quickly and accurately find the patterns. Each time it runs, it can locate and identify thousands of die, even patterns as small as 4x4 pixels. The control system stores manufacturing history records and results tied to barcoded labels on finished packages.

Adopting X/Y gantry moving platform, it can be individually or integrated with color/film thickness/OD spectrometer measurement modules, applied to the automatic precision measurement of color/film thickness/OD unevenness and abnormality after each coating process

1. Resolution and defect detection capability range can reach 3um~10um
2. Can support LTPS products, and can support peripheral line inspection for COA products
3. Area inspection, and also supports BM area inspection function
4. Excellent autonomous image detection technology can support all sizes, different image designs and any shape of panel products
5. Intelligent defect classification function

1. Resolution and defect detection capability range can reach 10um~100um
2. Can support pre-cut panel size, post-cut “12~75” panel size and shaped products
3. Detection area can cover both the inner area and the glass cutting edge at the same time
4. Defect classification function

Adopting high-precision optical imaging measurement modules and combining special platform and light source design can provide high-precision CD/Overlay measurement

AI defect classification and judgment solutions can be provided according to the needs of different customers in the production and manufacturing process

1. Resolution and defect detection capability range can reach 1um~5um
2. Can support substrate sizes from G3.5 to G10.5
3. Zero dead angle detection area, can achieve 100% full panel coverage
4. Excellent autonomous image detection technology can support all sizes, different image designs and any shape of panel products
5. Intelligent defect classification function
6. Provide professional and customized services

1. AI real-time defect detection; high-speed photography, instant inspection and classification
2. Automatic linewidth/aperture measurement

By applying Solomon SolVision AI image platform's Segmentation technology, AI models are trained with various LED substrate defect image samples. After deep learning, AI can accurately detect and annotate defects. In addition, the Detect Region tool can be used to divide the field of view into zones. In addition to masking areas that do not need to be detected, it can also identify the area where the defect is generated to achieve the purpose of zoned detection.

1. Prediction accuracy > 95%
2. False positive rate < 5%
3. Detect 100 images within 60 seconds (including download, preprocessing, prediction and upload)