Multi-Mode Optical Inspection for Weak Defect Detection
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Solution Overview
Problem
As semiconductor feature sizes shrink, defect inspection systems face challenges with weaker measurable signals and lower signal-to-noise ratios, making it difficult to effectively identify defects using single optical modes, which can lead to missed defects or false positives due to limited sensitivity.
Innovation Solution
The development of a multi-mode inspection system that generates inspection recipes by combining probabilities from multiple optical inspection modes, using a classifier to distinguish between background and defect classes, allowing for the selection of optimal optical modes for defect identification, thereby enhancing sensitivity and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple optical inspection modes are combined to improve defect detection sensitivity, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The inspection system is divided into multiple independent optical inspection modes (e.g., brightfield, darkfield, oblique illumination) that can be selectively activated. Each mode operates as a separate detection channel with its own optimization parameters, allowing the system to segment the inspection task into specialized sub-tasks that collectively improve measurement precision without requiring all modes to operate simultaneously, thus managing device complexity.
Solution Approach 2:
The inspection system is designed with multi-functional optical inspection modes that can detect different types of defects using the same basic hardware platform. By making the system universal across multiple inspection modes, it achieves improved measurement precision for various defect types while avoiding the need for completely separate inspection systems for each defect type, thereby controlling overall device complexity.
2Measurement precision
If multiple optical inspection modes are used to enhance defect identification accuracy, then measurement precision is improved, but inspection time increases
Solution Approach 1:
The inspection system dynamically selects and activates only the optical modes necessary for the current inspection task based on sample characteristics, defect types being sought, and preliminary analysis results. This dynamic adaptation allows the system to achieve high measurement precision when needed while minimizing inspection time by avoiding unnecessary mode activations, effectively balancing accuracy and speed.
Solution Approach 2:
The system applies partial action by using only the subset of optical modes required for each specific inspection scenario rather than activating all available modes. For example, if brightfield mode is sufficient for the current sample, other modes remain inactive. This approach maintains high defect identification accuracy when needed while significantly reducing inspection time by avoiding excessive use of all possible inspection modes.
3Measurement precision
If more optical inspection modes are combined to detect weaker defects, then measurement precision is improved, but productivity decreases
Solution Approach 1:
The system performs preliminary analysis using a subset of optical modes or preliminary scanning to identify samples or regions that require enhanced inspection. This preliminary action allows the system to prepare in advance by selecting appropriate full inspection mode combinations only for cases where weaker defects are suspected, thereby improving measurement precision for critical cases while maintaining high productivity by avoiding exhaustive multi-mode inspection of all samples.
Solution Approach 2:
The inspection system changes operational parameters by adjusting which optical modes are active based on the inspection requirements. For samples requiring high sensitivity to detect weaker defects, the system activates multiple modes with optimized parameters. For routine samples, it uses fewer modes with standard parameters. This dynamic parameter changing allows the system to achieve high measurement precision when needed while maintaining high productivity through efficient parameter selection.
Data Source
AI summary
An inspection system may develop an inspection recipe by generating N inspection images of a preliminary sample with one or more optical inspection sub-systems associated with N different optical inspection modes, generating probabilities that each of the locations of the preliminary sample are in background or defect classes using a classifier with the inspection images from at least some combinations of a number M of the optical inspection modes, where M is greater than one and less than N and corresponds to a number of the optical inspection modes to include in the inspection recipe, and selecting one of the combinations of M of the optical inspection modes based on a metric describing a distinction between the background and defect classes. The inspection system may further identify defects on a test sample using M inspection images generated with the selected combination of M of the optical inspection modes.