Unified Stochastic Variation Measurement for Semiconductor Patterns
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods lack a unified solution for measuring stochastic variations in both 1D and 2D patterns with the same algorithm, leading to inconsistent and inefficient measurement of stochastic edge placement error (SEPE) across different SEM machines, which hinders accurate modeling and optimization of patterning processes in semiconductor manufacturing.
Innovation Solution
A method that extracts high-quality composite contours from averaged images to guide contour extraction from raw images, allowing for unified measurement of stochastic variations in both 1D and 2D patterns, enabling accurate sub-pixel alignment and statistical analysis to determine process variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If different measurement algorithms are used for 1D and 2D patterns, then measurement can be performed on both pattern types, but measurement consistency and efficiency deteriorate due to lack of unified solution
Solution Approach 1:
The patent implements a unified measurement algorithm that can handle both 1D and 2D patterns using the same processing steps. The method extracts contours from raw SEM images and calculates SEPE measurements through a single standardized procedure that adapts to different pattern geometries, eliminating the need for separate algorithms for different pattern types while maintaining measurement consistency across all pattern configurations.
2Measurement precision
If multiple separate algorithms are used for different pattern types, then each algorithm can be optimized for its specific pattern, but measurement consistency across different SEM machines deteriorates
Solution Approach 1:
The patent applies homogeneous processing steps across all pattern types, using identical contour extraction and SEPE calculation methods for both 1D and 2D patterns. This uniform approach ensures that measurements are performed consistently across different SEM machines and pattern types, improving inter-machine measurement reliability while maintaining adequate precision through the standardized procedure.
3Measurement precision
If complex separate algorithms are used for 1D and 2D patterns, then accurate measurement can be achieved for each pattern type, but device complexity increases
Solution Approach 1:
The patent employs a single unified algorithm that performs both 1D and 2D pattern measurements through the same processing steps. The method extracts contours from raw images and calculates SEPE measurements using consistent mathematical operations that work for any pattern geometry, thereby reducing overall algorithmic complexity while maintaining measurement accuracy across different pattern types.
4Adaptability or versatility
If multiple measurement algorithms are implemented, then comprehensive pattern coverage is achieved, but ease of operation deteriorates due to algorithm selection complexity
Solution Approach 1:
The patent implements a single universal measurement algorithm that automatically handles both 1D and 2D patterns without requiring user selection or configuration. The unified approach processes all pattern types through the same contour extraction and SEPE calculation steps, eliminating algorithm selection complexity and improving ease of operation while maintaining comprehensive pattern measurement coverage.
Data Source
AI summary
A method for determining measurement data of a printed pattern on a substrate. The method involves obtaining (i) images of the substrate including a printed pattern corresponding to a reference pattern, (ii) an averaged image of the images, and (iii) a composite contour based on the averaged image. Further, the composite contour is aligned with respect to a reference contour of the reference pattern and contours are extracted from the images based on both the aligned composite contour and the output of die-to-database alignment of the composite contour. Further, the method determines a plurality of pattern measurements based on the contours and the measurement data corresponding to the printed patterns based on the plurality of the pattern measurements. Further, the method determines a one or more process variations such as stochastic variation, inter-die variation, intra-die variation and/or total variation.