Pattern Image Registration With Weighted Elements for Variation Measurement
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Solution Overview
Problem
Existing methods for assessing variation across multiple instances of a pattern in lithographic processes are unreliable, leading to errors in registration and measurement of parameters such as line edge roughness and line width roughness.
Innovation Solution
A method involving the registration of images using different weightings for pattern elements based on their expected variation, and setting a common boundary box for all images, to accurately superimpose and measure variations across multiple instances of a pattern.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If uniform weighting is applied to all pattern elements during registration, then the registration process is simple and fast, but measurement precision deteriorates due to unreliable variation assessment
Solution Approach 1:
The patent applies different weightings to different pattern elements based on their individual characteristics and expected variation. This local differentiation allows the registration process to focus more on stable, reliable pattern elements while reducing the influence of variable elements, thereby improving measurement precision without requiring complete redesign of the registration system.
Solution Approach 2:
The patent changes the weighting parameter for each pattern element based on its expected variation and reliability. By dynamically adjusting these parameters rather than using uniform weighting, the system achieves better measurement precision. The weighting parameters are determined through analysis of pattern element stability and are applied during the registration process to optimize variation assessment.
2Reliability
If all pattern elements are used equally in registration, then processing time is reduced, but reliability deteriorates due to errors from high-variation elements
Solution Approach 1:
The patent identifies and treats different pattern elements differently based on their reliability characteristics. Pattern elements with low expected variation are given higher weightings and contribute more to registration, while elements with high expected variation receive lower weightings. This selective approach improves registration reliability by reducing the influence of unreliable elements without requiring manual intervention or extensive processing time.
Solution Approach 2:
The patent performs preliminary analysis to determine the expected variation of each pattern element before the registration process. This pre-characterization of pattern element reliability allows the system to automatically assign appropriate weightings, improving registration reliability without adding significant processing time during the actual measurement phase.
3Measurement precision
If uniform weighting is used for all pattern elements, then the method is easy to implement, but measurement precision deteriorates due to inability to account for element variability
Solution Approach 1:
The patent implements local quality assessment by assigning different weightings to different pattern elements based on their expected variation. This allows the measurement process to account for the inherent variability of each pattern element, improving measurement precision for parameters such as line edge roughness and line width roughness. The implementation maintains automation and does not require complex manual intervention.
Solution Approach 2:
The patent changes the weighting parameters for each pattern element based on their individual characteristics. This parameter differentiation enables more precise measurement by accounting for element-specific variability. The system automatically determines and applies these parameters, maintaining ease of implementation while significantly improving measurement precision compared to uniform weighting approaches.
Data Source
AI summary
Methods of measuring variation across multiple instances of a pattern on a substrate or substrates after a step in a device manufacturing process are disclosed. In one arrangement, data representing a set of images is received. Each image represents a different instance of the pattern. The set of images are registered relative to each other to superimpose the instances of the pattern. Variation in the pattern is measured using the registered set of images. The pattern comprises a plurality of pattern elements and the registration comprises applying different weightings to two or more of the plurality of pattern elements. The weightings control the extent to which each pattern element contributes to the registration of the set of images. Each weighting is based on an expected variation of the pattern element to which the weighting is applied.