Repeater Defect Detection Using Hot Threshold Segmentation
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Solution Overview
Problem
Current repeater defect detection methods in semiconductor manufacturing are limited by bandwidth and disk space constraints, leading to the inability to detect weak repeater defects effectively due to high filtering rates and limited data handling capacity, resulting in missed detections and tool choking issues.
Innovation Solution
The system moves repeater defect detection to the image processing components at the lower levels of the inspection tool, using a hot threshold algorithm to identify repeater defects and store all defect candidates closer to the detection hardware, allowing for increased sensitivity and capacity to handle high defect densities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a hot threshold is used to detect weak repeater defects, then defect detection sensitivity is improved, but the number of defects stored in the lot result exceeds bandwidth and disk space capacity
Solution Approach 1:
The system segments the defect detection process into two stages: first detecting all defects with a hot threshold to ensure sensitivity, then performing repeater defect analysis as a separate post-processing operation. This segmentation allows the system to capture all potential defects including weak ones while managing data volume through subsequent filtering operations.
Solution Approach 2:
The system performs preliminary defect detection with a hot threshold to capture all potential defects including weak repeaters, then applies repeater analysis as a subsequent filtering step. This preliminary action ensures no weak repeaters are missed while the post-processing step manages data volume by identifying and focusing only on repeating defect patterns.
2Productivity
If location filtering is applied to eliminate majority of events in lot results, then data processing efficiency is improved, but weak repeater defects are filtered out and missed detections occur
Solution Approach 1:
The system performs preliminary defect detection without aggressive location filtering to ensure all potential defects are captured, then applies repeater analysis as a subsequent step. This preliminary detection phase maintains high sensitivity by not filtering out weak repeaters that may have slightly different locations, while the post-processing repeater analysis provides the efficiency benefit by identifying repeating patterns.
Solution Approach 2:
The system uses repeater analysis as a feedback mechanism that examines defect patterns across multiple locations. Rather than using location as a simple filter that eliminates data, the repeater analysis uses location information constructively to identify systematic repeating defects, providing feedback that maintains detection accuracy while managing data volume.
3Device complexity
If repeater defect detection is performed as a post-processing operation in the user interface, then system complexity is reduced, but bandwidth and disk space constraints limit detection sensitivity
Solution Approach 1:
The system segments the overall defect detection functionality into core inspection components that perform initial defect identification, and a separate post-processing repeater analysis component. This segmentation maintains relative system simplicity while enabling sensitive repeater detection through dedicated analysis logic that operates on the collected defect data.
Solution Approach 2:
The inspection tool performs preliminary defect detection and collects all defects including weak ones before performing repeater analysis in post-processing. This preliminary data collection ensures sufficient data is available for sensitive repeater detection, while the post-processing timing maintains system simplicity by using existing inspection infrastructure.
Data Source
AI summary
Systems and methods for detecting defects on a reticle are provided. One system includes computer subsystem(s) that include one or more image processing components that acquire images generated by an inspection subsystem for a wafer, a main user interface component that provides information generated for the wafer and the reticle to a user and receives instructions from the user, and an interface component that provides an interface between the one or more image processing components and the main user interface. Unlike currently used systems, the one or more image processing components are configured for performing repeater defect detection by applying a repeater defect detection algorithm to the images acquired by the one or more image processing components, and the repeater defect detection algorithm is configured to detect defects on the wafer using a hot threshold and to identify the defects that are repeater defects.