Metrology Data Source Separation Using PCA and ICA
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Solution Overview
Problem
In lithographic processes, accurately determining the true value of substrate measurements is challenging due to the presence of systematic errors, which complicates the assessment of measurement accuracy and precision.
Innovation Solution
A method using principal component analysis (PCA) and independent component analysis (ICA) to separate contributions from independent sources in substrate measurement results, compiling these into a matrix to identify the true value and assess the accuracy of measurement recipes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple substrate measurement recipes are used to measure overlay, then measurement coverage is improved, but measurement precision deteriorates due to systematic errors from different recipe types
Solution Approach 1:
The patent segments the measurement results into contributions from different independent sources (true overlay value, systematic errors, random errors) using independent component analysis. This allows separation of the true value from systematic errors introduced by different measurement recipes, enabling accurate determination of true overlay despite using multiple recipe types.
Solution Approach 2:
The patent introduces independent component analysis as an intermediary computational method that processes the combined measurement results from multiple recipes. This intermediary analysis separates the contributions from different sources, allowing the true overlay value to be extracted without being contaminated by systematic errors from specific recipe types.
2Adaptability or versatility
If different types of substrate measurement recipes are used, then measurement versatility is improved, but reliability of individual recipe accuracy deteriorates
Solution Approach 1:
The patent segments the measurement results into contributions from different independent sources (true overlay value, systematic errors, random errors) using independent component analysis. This allows separation of the true value from systematic errors introduced by different measurement recipes, enabling accurate determination of true overlay despite using multiple recipe types.
Solution Approach 2:
The patent uses the measurement results from multiple recipes to provide feedback about the systematic errors of each recipe type. By analyzing the variations in results across different recipes, the system can identify and quantify systematic errors, then use this feedback to determine the true overlay value and assess each recipe's accuracy.
3Device complexity
If systematic errors are present in substrate measurements, then measurement complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent introduces independent component analysis as an intermediary computational method that processes the combined measurement results from multiple recipes. This intermediary analysis separates the contributions from different sources, allowing the true overlay value to be extracted without being contaminated by systematic errors from specific recipe types.
Solution Approach 2:
The patent replaces physical measurement system modifications with a computational approach. Instead of modifying the measurement hardware to eliminate systematic errors, the patent uses independent component analysis to mathematically separate and remove the effects of systematic errors from the measurement results.
Data Source
AI summary
A method and a computer program product that relates to lithographic apparatuses and, processes, and more particularly to a method and computer program to inspect substrates produced by the lithographic apparatuses and processes. The method and/or computer program product includes determining contributions from independent sources from results measured from a lithography process or a substrate processed by the lithography process, wherein the results are measured using a plurality of different substrate measurement recipes.


