Inspection System Defect Detection and Error Stopping
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Solution Overview
Problem
Conventional defect-transferability consideration inspection methods face challenges in quickly detecting defects caused by errors in the inspection system, especially when a large number of defects are detected, making it difficult to stop the inspection efficiently.
Innovation Solution
An inspection method and system that scans a sample with light, acquires optical images, creates reference images, and compares them to detect first defects, while also identifying second defects caused by erroneous system operations based on differences in image distribution, allowing for timely inspection cessation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a low threshold is set in the first inspection to increase defect detection accuracy, then more true defects are detected, but an excessive number of pseudo defects are also detected
Solution Approach 1:
The inspection process is divided into two distinct stages: a first inspection that detects all potential defects using a low threshold, and a second inspection that specifically identifies pseudo-defects using a high threshold. This segmentation allows the system to capture all possible defects initially, then filter out false positives in a separate analysis phase.
Solution Approach 2:
The first inspection is performed as a preliminary step to detect all potential defects including both true defects and pseudo-defects. This preliminary detection creates a comprehensive defect list that is then refined in the second inspection stage, where pseudo-defects are identified and removed from the final defect list.
2Measurement precision
If an excessive number of defects are detected in the first inspection, then true defects are not missed, but it becomes difficult to quickly detect pseudo defects and stop the inspection
Solution Approach 1:
The system continuously monitors the distribution of detected defects during the first inspection and provides feedback to the second inspection process. When the second inspection identifies pseudo-defects, this information feeds back to stop the first inspection, preventing further waste of inspection time while maintaining complete defect detection.
Solution Approach 2:
The second inspection extracts and identifies pseudo-defects from the total defect list generated by the first inspection. By separating pseudo-defects from true defects through this extraction process, the system can quickly determine when to stop the inspection without compromising the completeness of true defect detection.
3Measurement precision
If the inspection is continued to complete the first inspection on the entire mask face, then all defects are detected, but inspection time and resources are wasted when pseudo defects are present
Solution Approach 1:
The second inspection acts as a feedback mechanism that monitors the quality of defects detected during the first inspection. When pseudo-defects are identified, this feedback triggers an automatic stop of the first inspection, preventing further waste of inspection resources while ensuring all true defects have been detected.
Solution Approach 2:
The second inspection is performed as a preliminary quality check during the first inspection process. By continuously analyzing detected defects and identifying pseudo-defects early, the system can stop the inspection at the optimal point, maintaining completeness while improving efficiency.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables quick detection and prevention of erroneous defect detection, improving inspection efficiency and reducing costs by promptly stopping the inspection when second defects are identified.
Implementation Method 1
scanning an inspection region 201 on a mask 2 with light; acquiring an optical image formed of the scanning light
Data Source
AI summary
An inspection region 201 of a sample 2 is scanned with light, an optical image formed of the scanning light is acquired according to progression of scanning with the light, a reference image as a reference for the acquired optical image is created according to progression of acquisition of the optical image, the acquired optical image is compared to the reference image for the optical image to detect first defects in the pattern according to progression of the acquisition of the optical image, second defects caused by an erroneous operation of an inspection system 1 are detected based on a distribution of differences between the acquired optical image and the reference image during progression of detection of the first defects, and an inspection is stopped when the second defects are detected.