Products
Features

- Utilizing artificial intelligence to maximize Mura inspection performance

- Extensible Mura inspection with the application of training data using AI Trainer

- Fast inspection speed using NAVI AI

- Service pixel inspection using the high-resolution 50M camera

- High-resolution mobile LCD/OLED panel inspection (Full HD, QHD, UHD)

- Image conversion and applying control without the intervention of automatic inspection solution worker

Overviews

AIDi (Display inspection solution using artificial intelligence)


AIDi(AI Solution for Display Inspection) of Laon People is a special solution for OLED display inspection based on artificial intelligence designed specifically for fast and accurate inspection of atypical Mura, Bit, and Dot in OLED manufacturing using AI.

AIDi applies AIDi Trainer to atypical Mura, Bit, and Dot, and proceeds with advance learning and applies Mura Classifier to study the defect type through Mura detailed classification, and presents the criteria of the defect type at the time of inspection.




AIDi Inspection Flow



AIDi Mura Inspection

Key Functions

High-quality AI Software Specifically For Oled Inspection

- AIDi TrainerTM: Image learning process from OLED inspection

- AIDi ClassfierTM: Additional classification of defective elements, and their learning process

- AIDi Training Image GeneratorTM: Active learning processing for new types of Mura images



Effective Stabilization of Production Yield and Cost Reduction through Conversion of the Inspection Method

- Multi-GPU/Multi-Thread: 15 seconds (Total Inspection Time - QHD, 9 Pattern Use)



LPMVC-CL50M Camera System with Low Illumination Characteristics

- Precision Sub-Pixel Feature Measure: Precise Sub-Pixel Measure at QHD, UHD resolution

- AIDi ClassfierTM: Additional classification of defective elements, and their learning process

- Luminance Measure / JND Calculation: Precise Luminance Measure/Stable JND Calculation



Introduction Effect

-Increased yield and cost minimization by strengthening inspection capacity


Stable yield management
Accurate inspection and short inspection time realizes production yield and predicts inspection yield through AI inspection, which enables stable yield management and manpower management
Minimization of applying mass production
Minimize costs by minimizing time to mass-production by utilizing automatic AI Training, Training Update, Classifier, etc.
Standardization of quality criteria
Resolve the quality deviation problem by the worker for atypical Mura, Bit, and Dot inspection through the application of quantified inspection spec.
Improve quality and improve product reliability by standardizing quality standards
Efficient quality control
Effective process management is possible through improvement of defective elements caused by lot through defect type analysis using inspection result data
Specifications

Camera Spec

Camera LPMVC-CL50M Specification
Sensor Type CMOS
Sensor Size 35mm full frame
Mono/Color Mono
Pixel Size 4.6㎛ x 4.6㎛
Pixel Resolution 7920(H) x 6004(V)
Frame Rate 15fps
ADC Resolution 12 bit
Shutter Type Global shutter
Interface Camera Link
Lens Mount M72 mount


PC Spec

S/W system Specification
CPU Intel core i5/i7/XEON
Memory 16GB or more
Mono/Color Mono
Disk Space SSD 256GB & HDD 2TB
USB 1ea (for Dongle)
GPU NVIDIA GTX1080ti or more
Power 800W
Frame Grabber Camera Link
Interface Camera Link
OS Windows 7 / Windows 10 (64bit)


Software Spec


- Atypical Mura and Bit, Dot Inspection

- Training Data Set is created using accepted and defective images to AIDi Trainer and AIDi Classifier and proceed the display inspection

- Inspect Red, Green, Blue and three levels of Intensity(64,128,192)

- Intensity setting can be changed according to inspection criteria


Function Inspection Specification
Resolution QHD(2560 x 1440)
Defect Bit, Dot defect
Mura Horizontal, Vertical, Spot, Mesh, Butterfly, Back, Corner, Edge, Light Leak, Stain, Non-uniformity
Image analysis Active OLED Area Extraction, Luminance Measure, JND Calculation
Inspection Multi Inspection, Sequence Edit
Composition of Solutions





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