Charged Particle Microscope Overlay Shift Detection
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Solution Overview
Problem
Current methods for inspecting overlay shift defects in semiconductor manufacturing are inefficient and inaccurate, often relying on human observation of charged particle microscopic images, leading to poor detection accuracy and increased manufacturing costs due to unnecessary waste.
Innovation Solution
A method involving a charged particle beam inspection system that forms microscopic images, identifies and averages inspection patterns, estimates the average width of these patterns, and compares them to a threshold value to determine the presence of overlay shift defects, eliminating the need for human interpretation and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human observation and interpretation of charged particle microscopic images is used for overlay shift defect detection, then the inspection process is simple, but the detection accuracy is poor and results are arbitrary
Solution Approach 1:
The patent replaces the mechanical human observation system with an automated image processing system that uses computational algorithms to detect overlay shift defects. The system processes charged particle microscopic images through automated steps including pattern identification, periodicity detection, and shift calculation, eliminating subjective human interpretation and achieving consistent, high-accuracy defect detection
Solution Approach 2:
The patent transforms the inspection approach by changing from qualitative human visual assessment to quantitative automated measurement. It extracts specific parameters such as pattern periodicity, overlay shift distance, and defect presence from images using computational methods, converting subjective observation into objective, measurable data with defined thresholds for defect determination
2Reliability
If automated image processing methods are implemented for overlay shift defect detection, then detection accuracy improves, but the device complexity increases
Solution Approach 1:
The patent segments the image processing task into distinct modular steps: pattern identification, periodicity detection, overlay shift calculation, and defect determination. Each module performs a specific function independently, making the complex system manageable and maintainable while ensuring reliable defect detection through systematic processing of each image component
Solution Approach 2:
The patent introduces an intermediary image processing system between the charged particle microscope and the final defect assessment. This intermediary layer automatically analyzes images, calculates overlay shifts, and determines defects, serving as a bridge that translates raw image data into reliable defect information without requiring direct human intervention
3Loss of substance
If human inspection methods are used, then equipment cost is lower, but manufacturing waste increases due to poor detection accuracy
Solution Approach 1:
The patent implements feedback by using detected overlay shift defects to control the semiconductor manufacturing process. The automated inspection system provides real-time information about alignment errors, enabling process adjustments that prevent defective products from being manufactured, thereby reducing manufacturing waste through data-driven process optimization
Solution Approach 2:
The patent performs preliminary defect detection after each layer formation step in the semiconductor manufacturing process. By identifying overlay shift defects early, before subsequent processing steps are applied, the system prevents waste of materials and processing time that would occur if defects were discovered later in production
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables timely and reliable detection of overlay shift defects, reducing manufacturing waste and improving process control by enhancing the accuracy of inspections.
Implementation Method 1
A charged particle beam source 210 generates a charged particle beam, and then the charged particle beam is condensed and focused by a condenser lens module 220 and an objective lens module 230, respectively, to form a charged particle beam probe 240
Implementation Method 2
After charged particle beam probe 240 bombards the surface of sample 295, secondary charged particles 260 are induced to emit from the sample surface along with other charged particles of beam probe 240 reflected by sample 295
Data Source
AI summary
A method of inspecting for overlay shift defects during semiconductor manufacturing is disclosed. The method can include the steps of providing a charged particle microscopic image of a sample, identifying an inspection pattern period in the charged particle microscopic image, averaging the charged particle microscopic image by using the inspection pattern period to form an averaged inspection pattern period, estimating an average width from the averaged inspection pattern period, and comparing the average width with a predefined threshold value to determine the presence of an overlay shift defect.