Pattern Inspection Device Using Reference Pattern Edge Extraction
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Solution Overview
Problem
Conventional pattern inspection technologies using edge extraction with threshold values are prone to false alerts due to noise, image acquisition variations, and differences in imaging conditions, leading to unreliable defect detection in semiconductor manufacturing.
Innovation Solution
A pattern inspecting and measuring device that generates edge extraction parameters using a reference pattern, allowing for more accurate edge extraction and reduced noise influence, thereby increasing the reliability of inspection results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If edge extraction is performed using a predetermined threshold value from profile data, then the inspection process is simple and fast, but the reliability of defect detection decreases due to false alerts caused by noise and imaging variations
Solution Approach 1:
The patent changes the parameter used for edge extraction from a fixed predetermined threshold value to a reference contour line derived from design data. This parameter change eliminates the influence of noise and imaging condition variations that affect threshold-based methods, thereby improving defect detection reliability while maintaining inspection efficiency
Solution Approach 2:
The patent creates a reference contour line by copying the ideal pattern shape from design data. This reference contour serves as a noise-free standard for comparison, allowing the system to identify actual defects without being influenced by variations in image acquisition conditions
2Loss of time
If inspection is performed using low magnification ratio images with large field of view, then the evaluation time is reduced and more locations can be inspected, but the measurement precision of small defects decreases
Solution Approach 1:
The patent segments the inspection process into two stages: first, a wide-area inspection at low magnification to identify candidate defect locations efficiently; second, a focused measurement at high magnification only at the identified candidate locations. This segmentation reduces total evaluation time while maintaining measurement precision for critical defects
Solution Approach 2:
The patent performs preliminary inspection at low magnification to pre-identify candidate defect locations before conducting detailed measurements. This preliminary action filters out non-defect areas, allowing subsequent high-precision measurements to be performed only where necessary, thus reducing overall inspection time
3Measurement precision
If contour shape comparison is performed between extracted contour and design data, then shape evaluation capability is improved, but false alerts increase due to differences caused by process variations and imaging conditions
Solution Approach 1:
The patent applies partial comparison by focusing only on the reference contour line derived from design data, rather than comparing the entire extracted contour shape. This partial action approach compares only the critical edge positions, maintaining shape evaluation capability while reducing the influence of process variations and imaging conditions that affect overall contour shapes
Data Source
AI summary
Provided is a pattern inspecting and measuring device that decreases the influence of noise and the like and increases the reliability of an inspection or measurement result during inspection or measurement using the position of an edge extracted from image data obtained by imaging a pattern as the object of inspection or measurement. For this purpose, in the pattern inspecting and measuring device in which inspection or measurement of an inspection or measurement object pattern is performed using the position of the edge extracted, with the use of an edge extraction parameter, from the image data obtained by imaging the inspection or measurement object pattern, the edge extraction parameter is generated using a reference pattern having a shape as an inspection or measurement reference and the image data.