Probabilistic Process Windows for Noisy SEM Edge Detection
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Solution Overview
Problem
Existing methods for edge detection in noisy SEM images, such as those used in semiconductor manufacturing, struggle to accurately distinguish feature roughness from measurement noise without applying filters that alter the measured roughness.
Innovation Solution
The development of a computer-implemented method and system that uses a probabilistic process window to account for measurement uncertainty, allowing for accurate edge detection and roughness measurement in noisy SEM images without the need for image filtering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If filters are applied to noisy SEM images to enable edge detection, then measurement noise is reduced, but the measured roughness is altered
Solution Approach 1:
The patent replaces traditional mechanical/image filtering approaches with a probabilistic modeling approach. Instead of applying filters to the image data, the system uses a process window model that incorporates measurement uncertainty to probabilistically determine whether features meet specifications, thereby avoiding the need to alter the original noisy image data while still achieving accurate edge detection and roughness measurement
Solution Approach 2:
The patent changes the parameter representation from deterministic binary (pass/fail) to probabilistic (0-1 scale). By representing compliance as a continuous probability value based on measurement uncertainty, the system can account for noisy measurements without filtering, allowing edge detection to proceed on original data while maintaining measurement integrity
2Device complexity
If measurement uncertainty is not accounted for, then process window determination is simplified, but measurement accuracy deteriorates
Solution Approach 1:
The patent implements feedback by using measurement uncertainty information to adjust the process window determination. The system calculates compliance probabilities that incorporate uncertainty margins, allowing the process window to be dynamically adjusted based on the quality and precision of individual measurements, thereby maintaining accuracy without excessive complexity
3Ease of operation
If traditional binary compliance determination is used, then decision-making is simplified, but measurement uncertainty is ignored
Solution Approach 1:
The patent transforms the static binary compliance determination into a dynamic probabilistic assessment. Instead of a fixed pass/fail threshold, the system provides a continuous probability scale that reflects the degree of compliance confidence, allowing users to adjust decision thresholds based on their specific reliability requirements while maintaining operational simplicity
Data Source
AI summary
Methods, systems, and computer-readable mediums for configuring a lithography tool to manufacture a semiconductor device. The method includes selecting a first variable, selecting a second variable, selecting at least one response variable that is a function of the first variable and second variable, determining a measurement uncertainty for each response variable, determining, based on a measurement of the response variable, and the measurement uncertainty for the response variable, a plurality of probabilities representing a plurality of indications of whether a plurality of points associated with a lithography process meet a specification requirement for each response variable, wherein the plurality of probabilities represent a process window, and configuring, based on the process window, a lithography tool to manufacture a semiconductor device.