Mask Defect Inspection Threshold Optimization
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Solution Overview
Problem
Current mask defect inspection methods using dark-field images face challenges in setting an optimal detection threshold, leading to either false detections or missed weak defect signals due to detection noise, which increases inspection time and labor.
Innovation Solution
A method that involves acquiring a dark-field image of a partial region at a defocus position to determine detection noise intensity and set a detection threshold, ensuring that only signals above this threshold in the desired inspection region are considered defects, thereby optimizing detection sensitivity and minimizing false detections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a low detection threshold is set to detect weak defect signals, then detection sensitivity is improved, but false detections increase due to detection noise
Solution Approach 1:
The inspection region is divided into a desired inspection region and a partial region used for noise measurement. By segmenting the region, the patent enables separate measurement of detection noise in the partial region while inspecting defects in the desired inspection region, allowing threshold optimization without compromising defect detection coverage.
Solution Approach 2:
The detection noise is measured in advance in the partial region before defect detection is performed. This preliminary measurement of noise characteristics allows the detection threshold to be set based on actual noise levels, enabling weak defect signals to be detected while minimizing false detections from noise.
2Reliability
If a high detection threshold is set to reduce false detections, then reliability is improved, but detection sensitivity decreases and weak defect signals are missed
Solution Approach 1:
The detection threshold is determined based on feedback from the measured detection noise in the partial region. The system measures noise characteristics and uses this information to set an appropriate threshold that balances false detection reduction with weak defect signal detection capability.
3Reliability
If detection threshold optimization is performed manually by accessing detection positions again, then false detections can be confirmed, but inspection time and labor increase significantly
Solution Approach 1:
The system performs self-service by automatically measuring detection noise in the partial region and determining the detection threshold without requiring manual intervention. The apparatus autonomously optimizes the threshold based on measured noise characteristics, eliminating the need for operators to access detection positions again for confirmation.
Solution Approach 2:
The manual mechanical process of accessing detection positions for confirmation is replaced by an automated optical measurement system. The apparatus uses optical measurement of the partial region to automatically determine noise levels and set thresholds, substituting manual operations with automated sensing and processing.
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
This approach allows for high detection sensitivity while keeping detection noise count below a target, reducing the need for identifying false detections and thus reducing inspection time and labor, while ensuring accurate detection of defects.
Implementation Method 1
irradiating the mask with light of an arbitrary wavelength
Data Source
AI summary
According to one embodiment, in a method for inspecting a defect of an exposure mask, using an optical system which acquires a dark-field image, an arbitrary partial region where a uniform dark-field image is obtained on the mask is allocated at a defocus position to acquire an image. A detection threshold is decided using signal intensities of the acquired image and an area ratio between a desired inspection region and the partial region, so that a signal count indicating signal intensities greater than the detection threshold in the inspection region is less than a target false detection count. The mask is allocated in a just-in-focus position to acquire an image of the inspection region. A signal having a signal intensity of the acquired image, which indicates an intensity greater than the detection threshold, is determined as a defect.