Dynamic Micro Care Areas for Repeater Defect Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current semiconductor manufacturing metrology and inspection systems face challenges in accurately detecting repeater defects due to high noise levels and limited capability to handle large defect counts, leading to missed detections and high nuisance rates, especially in reticle repeater inspections.
Innovation Solution
A method and system utilizing dynamic micro care areas and attribute comparison to classify repeater defects, where micro care areas are created around defect locations, inspected, and attributes such as shape, size, and feature vectors are compared to identify and separate nuisance defects from defects of interest, enhancing sensitivity and reducing nuisance rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If die-to-die or reticle-to-reticle inspection is performed for repeater defect detection, then the inspection coverage is improved, but the surrounding noise increases and sensitivity decreases
Solution Approach 1:
The patent segments the wafer inspection into two distinct phases: first identifying repeater candidate locations using robust average algorithms, then performing targeted inspection only in those specific regions. This segmentation isolates the inspection from surrounding noise while maintaining comprehensive coverage, directly resolving the contradiction between inspection coverage and noise reduction.
2Reliability
If robust average algorithms are used for repeater detection, then random events are reduced, but the ability to identify printability variations is compromised
Solution Approach 1:
The patent implements a feedback mechanism where the output of the robust average algorithm (repeater candidate locations) feeds into a second-stage inspection process that specifically evaluates printability variations at those locations. This two-stage feedback approach maintains the robustness of the first stage while enabling precise printability analysis in the second stage, resolving the contradiction between reliability and measurement precision.
3Quantity of substance
If the inspection tool handles high defect counts, then comprehensive defect detection is achieved, but the tool capability is exceeded and repeater events with signal fail to be detected
Solution Approach 1:
The patent extracts repeater candidate locations from the full wafer inspection data using robust average algorithms, separating these specific locations from the rest of the defect data. This extraction reduces the data volume for detailed inspection from millions of defects to only the relevant repeater candidate regions, allowing the tool to maintain high detection accuracy without being overwhelmed by the total defect count.
4Measurement precision
If dynamic micro care areas are created and inspected, then sensitivity for repeater defect detection is improved, but the inspection complexity increases
Solution Approach 1:
The patent performs preliminary identification of repeater candidate locations using robust average algorithms before creating dynamic micro care areas for detailed inspection. This preliminary action prepares the inspection by pre-identifying regions of interest, so that the subsequent micro care area inspection focuses only on these predetermined locations, improving sensitivity while managing complexity through structured preprocessing.
Data Source
AI summary
Systems and methods of a two-pass inspection methodology that dynamically creates micro care areas for inspection of repeater defects. Micro care areas can be formed around each location of a repeater defect. After inspection, additional repeater defects in the micro care areas can be identified. Attributes of the repeater defects can be compared and any repeater defects with attributes that deviate from an expected group attribute distribution can be classified as nuisance.