SEM Selective ROI Scanning for Faster Defect Inspection
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Solution Overview
Problem
Current semiconductor inspection methods face inefficiencies in throughput due to the need to scan large areas beyond regions of interest (ROIs), leading to increased overhead time and reduced advantages in high-resolution detection scans as ROI count and size decrease.
Innovation Solution
A selective scanning approach using a scanning electron microscope (SEM) that groups ROIs by size, employing a beam deflector to direct the electron beam precisely onto ROIs, aided by a processor that determines ROI locations and sizes, and utilizes deep learning segmentation or design images to optimize scanning patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a low-resolution segmentation scan is performed to identify ROIs followed by a high-resolution detection scan on ROIs, then detection precision is improved, but productivity decreases due to image setup and deflection time overhead
Solution Approach 1:
The patent segments ROIs into size-based groups (small, medium, large) and processes each group with optimized scanning parameters. This segmentation allows the system to apply different scan strategies to different ROI categories, reducing overall processing time while maintaining detection precision for all ROI sizes.
Solution Approach 2:
The patent dynamically adjusts scanning parameters including pixel count, scan time, and beam deflection based on ROI size categories. The system transitions from static scanning approaches to dynamic parameter adjustment, where smaller ROIs receive fewer pixels and shorter scan times while larger ROIs receive more resources, optimizing the balance between precision and throughput.
2Measurement precision
If the high-resolution detection scan is performed on an area much larger than the ROI, then detection precision is maintained, but loss of time increases due to scanning unnecessary pixels
Solution Approach 1:
The patent applies local quality by tailoring the scanning parameters specifically to each ROI size category rather than using a uniform approach for all ROIs. Small ROIs receive optimized scan patterns with fewer pixels, while larger ROIs receive more comprehensive scanning, ensuring each region is scanned with appropriate quality without wasting time on unnecessary pixels.
Solution Approach 2:
The patent changes scanning parameters (pixel count, scan time, beam deflection settings) based on ROI size categories. This parameter adaptation allows the system to reduce scanning time for small ROIs by using fewer pixels and shorter scan durations, while maintaining sufficient detection precision through appropriate parameter selection for each size category.
3Measurement precision
If ROI count increases and ROI size decreases, then measurement precision requirements increase, but productivity advantages are reduced due to increased overhead time
Solution Approach 1:
The patent segments the large number of small ROIs into manageable size-based groups, allowing efficient batch processing. By categorizing ROIs by size, the system can apply optimized scan patterns that are specifically tuned for small features, maintaining detection precision while reducing the per-ROI overhead time through efficient grouping and processing strategies.
Solution Approach 2:
The patent applies partial action by scanning only the necessary portion of each ROI with appropriate pixel density. For small ROIs, the system uses reduced pixel counts and shorter scan times that are sufficient for detection purposes, avoiding excessive scanning that would waste time without adding value to defect detection precision.
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 method reduces processing time by 5 to 25 times by minimizing unnecessary scanning and improving throughput through precise targeting of ROIs, enhancing the efficiency of semiconductor inspection.
Implementation Method 1
an electron source configured to generate an electron beam
Implementation Method 2
a beam deflector disposed in the path of the electron beam between the electron source and the stage
Implementation Method 3
a detector configured to receive electrons formed when the electron beam impacts the workpiece on the stage
Data Source
AI summary
The system includes an electron source configured to generate an electron beam, a stage configured to hold a workpiece in the path of the electron beam, a beam deflector disposed in the path of the electron beam between the electron source and the stage, a detector configured to receive electrons formed when the electron beam impacts the workpiece on the stage, and a processor. The processor is configured to generate a workpiece image based on the electrons received by the detector, determine a size and location of each region of interest (ROI) of the workpiece, determine groups of ROIs having similar size, and send instructions to the beam deflector to direct the electron beam onto the location of each ROI and generate an ROI image for each group of ROIs.