Pattern Inspection Apparatus for Semiconductor Mask Defect Detection
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Solution Overview
Problem
Current pattern inspection methods for semiconductor masks face challenges in accurately and efficiently detecting defects on large-area masks, particularly due to thermal expansion and measurement errors caused by inspection light and environmental changes, leading to degraded uniformity of pattern position accuracy and dimension errors across the mask surface.
Innovation Solution
The proposed solution involves a pattern inspection apparatus and method that divides the inspection region into discrete small regions, acquiring optical images in each region while moving the stage and sensor, calculating positional deviation amounts, and generating maps to differentiate between apparatus-induced errors and actual pattern errors, allowing for rapid inspection and correction of measurement variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the inspection region is divided into discrete small regions for rapid inspection, then productivity is improved, but measurement precision deteriorates due to thermal expansion and environmental changes during the inspection process
Solution Approach 1:
The inspection region is divided into multiple discrete small regions that are inspected separately. This segmentation allows the inspection system to cover large areas quickly while maintaining measurement precision through localized measurements that are less susceptible to thermal expansion and environmental changes affecting the entire mask surface simultaneously.
Solution Approach 2:
Reference images are generated from design data before the actual inspection process. These pre-generated reference images serve as a baseline for comparison, allowing the system to quickly identify deviations without being affected by thermal expansion during the inspection. The preliminary creation of reference data enables rapid defect detection while maintaining accuracy.
2Loss of time
If the inspection region is divided into discrete small regions, then inspection time is reduced, but manufacturing precision deteriorates due to accumulated measurement errors across regions
Solution Approach 1:
The system compares optical images against pre-generated reference images and provides feedback on deviations. This feedback mechanism allows for quick identification of defects while maintaining manufacturing precision through systematic comparison rather than absolute measurement, reducing the impact of accumulated errors across discrete inspection regions.
Solution Approach 2:
Reference images are generated in advance from design data, establishing a known baseline before inspection begins. This preliminary action enables rapid comparison during inspection without requiring complex real-time calculations, thus reducing inspection time while maintaining the precision needed to detect manufacturing defects.
3Reliability
If optical images are acquired across the whole inspection region, then measurement completeness is improved, but productivity deteriorates due to the time required to scan large areas
Solution Approach 1:
The inspection region is divided into multiple discrete small regions that are inspected separately rather than scanning the entire area continuously. This segmentation maintains inspection completeness by ensuring each region is thoroughly examined while significantly improving productivity by reducing the total scanning time and allowing parallel processing of multiple regions.
Solution Approach 2:
Instead of performing a complete continuous scan of the entire inspection region, the system performs partial inspections of discrete small regions. This partial action approach maintains sufficient inspection completeness for quality control while dramatically improving productivity by eliminating unnecessary scanning of areas that have already been inspected or do not require full scrutiny.
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 highly reliable and efficient inspection of mask uniformity, reducing the impact of thermal and measurement errors, and providing accurate data for pattern position and dimension errors, thereby improving the quality precision of the mask inspection process.
Implementation Method 1
Light transmitted through the target object or reflected therefrom is focused on a sensor through the optical system
Implementation Method 2
Light transmitted through the target object or reflected therefrom is focused on a sensor through the optical system
Data Source
AI summary
A pattern inspection method according to one aspect of the present invention includes generating a first positional deviation amount map by using data acquired by a pre-scan, generating a second positional deviation amount map by using data acquired by a full scan, generating a first positional deviation difference map by calculating a difference between the first positional deviation amount map and the second positional deviation amount map, generating a third positional deviation amount map from the first positional deviation difference map and the second positional deviation amount map, and judging existence of a value exceeding an allowable value, in values defined by the third positional deviation amount map.