Swath Image Noise Diagnostics for Electron Beam Inspection
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Solution Overview
Problem
Existing electron beam inspection systems face challenges in accurately diagnosing system noise, particularly mechanical vibrations and electromagnetic interference, during swath imaging mode, which affects image quality and throughput.
Innovation Solution
A method and system that utilize edge detection and Fast Fourier Transform (FFT) analysis on swath images to determine X-direction and Y-direction vibration spectra, isolating noise frequencies for tool diagnostics without additional equipment, enabling faster and more accurate identification of vibration sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If kernel alignment technique is used to measure vibration frequencies from swath images, then vibration frequencies can be detected, but the method is computationally expensive and takes more than ten minutes to complete a single image
Solution Approach 1:
The patent extracts only the essential information needed for vibration analysis from swath images by detecting edges and measuring deviations from ideal raster scan positions, rather than performing comprehensive kernel alignment analysis on entire images. This extraction approach reduces computational complexity while maintaining the ability to detect vibration frequencies.
Solution Approach 2:
The patent segments the vibration analysis process into distinct steps: edge detection, position measurement, deviation calculation, and frequency analysis. By breaking down the complex kernel alignment technique into these simpler sequential operations, the computational burden is reduced while preserving the essential measurement capability.
2Measurement precision
If traditional vibration measurement technique is used requiring straight edge pattern and stationary stage, then vibration frequencies can be measured, but the technique cannot be applied to swath mode of operation
Solution Approach 1:
The patent develops a vibration measurement technique that works universally across different operating modes of the electron beam inspection system, including both step-and-settle mode and swath mode. By using edges from actual inspection images rather than requiring specific test patterns, the method becomes adaptable to various operational contexts.
Solution Approach 2:
The patent uses copies of edges from regular inspection images to perform vibration analysis, rather than requiring dedicated test patterns or straight edge structures. This approach allows vibration measurement to be performed on routine inspection data, eliminating the need for separate measurement procedures.
3Measurement precision
If comprehensive defect inspection is performed to detect all defects, then more defects are detected including yield-relevant and nuisance defects, but correcting all defects becomes difficult and expensive
Solution Approach 1:
The patent extracts and analyzes specific characteristics of detected defects, such as their spatial distribution patterns and correlation with tool vibrations. By identifying which defects are systematically related to process variations versus random nuisance defects, the method enables focused correction efforts on the most critical defect types.
Solution Approach 2:
The patent implements feedback by using vibration analysis from inspection images to identify systematic process issues, then using this information to guide process corrections. The vibration frequency data provides feedback about tool condition that can be used to adjust process parameters and reduce yield-relevant defects.
Data Source
AI summary
Parameters from an inspection image representing mechanical vibrations and electromagnetic interference can be determined. An X-direction vibration spectrum can be determined based on the X-direction offsets. A Y-direction vibration spectrum can be determined based on the Y-direction offsets. The determinations can be based on a swath image of a workpiece, such as a semiconductor wafer or reticle.