Automated LCD Defect Detection via Image Analysis
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Solution Overview
Problem
Existing liquid crystal display (LCD) device testing systems require extensive manual intervention, leading to inefficiencies and increased time and labor costs due to the need for multiple workers and downtime during breaks, as they rely on human operators to detect and repair defects in thin film transistor and color filter substrates.
Innovation Solution
An automated testing system that includes a testing device capturing images of defects, an automatic review host (ARPC) to determine defectiveness using a defect determining automation program, and a passive review host (PRPC) for undeterminable defects, allowing for automatic repair and improved productivity by reducing reliance on human operators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual testing methods are used to detect defects in substrates, then workers can identify defectiveness, but testing time and number of workers increase significantly
Solution Approach 1:
The patent replaces the mechanical human visual inspection system with an automated imaging and analysis system. The testing device captures images of substrate defects, and the automatic review host processes these images through digital analysis to determine defectiveness, eliminating the need for manual worker inspection and significantly reducing testing time.
Solution Approach 2:
The patent creates a digital copy of the substrate defect through image capture. Instead of requiring workers to directly observe physical defects, the system captures visual information and analyzes it digitally, allowing for rapid processing without time loss and enabling multiple substrates to be tested simultaneously.
2Measurement precision
If manual testing methods are used, then workers can determine defectiveness, but labor costs and number of workers increase
Solution Approach 1:
The patent substitutes human labor with an automated system consisting of a testing device for image capture and an automatic review host for defect determination. This replacement eliminates the need for multiple workers while maintaining or improving defect detection accuracy through digital image analysis algorithms.
Solution Approach 2:
The automatic review host performs self-service by autonomously analyzing captured images and determining defectiveness without human intervention. The system processes defects independently, eliminating the need for workers and reducing labor costs while maintaining consistent determination accuracy.
3Reliability
If manual testing is performed continuously, then defect detection can be maintained, but downtime during breaks reduces productivity
Solution Approach 1:
The automated testing system enables continuous operation without interruption. The testing device and automatic review host can continuously process substrate defects without the breaks and downtime required by human workers, maintaining constant productivity and eliminating losses associated with worker rest periods.
Solution Approach 2:
By replacing human operators with an automated system, the patent eliminates the productivity interruption caused by human breaks. The mechanical and digital components of the testing system operate continuously without fatigue, ensuring uninterrupted defect detection and maximizing testing throughput.
Data Source
AI summary
A system for testing a liquid crystal display (LCD) device includes a testing device photographing and capturing an image of a defect generated on a substrate having a thin film array formed thereon, the testing device providing testing information on the defect, a ARPC automatically determining defectiveness of the substrate by an automatic determination method using a defect determining automation program designed based on a testing worker's determination method and behavior aspect, the captured image and the testing information on the defect, a PRPC determining defectiveness of the substrate based on the captured image and the testing information on the defect, if the defectiveness of the substrate is undeterminable by the ARPC, and a main server connecting the ARPC with the PRPC and storing the captured image and the testing information on the defect. The ARPC extracts characteristics of the defect by using the testing information on the defect and the ARPC analyzes the extracted characteristics of the defect to classify and calculate the degree of the defect.