Semiconductor Layout Analysis Using Polygon Hashing
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Solution Overview
Problem
Current layout analysis methods in semiconductor manufacturing are inefficient in analyzing layouts and masks, leading to suboptimal pattern transfer and potential defects in the semiconductor process.
Innovation Solution
A layout analysis method that segments the layout pattern into rectangles, extracts conversion characteristic values by applying tolerance to shape information, calculates total hash values, groups patterns based on these values, and extracts unique patterns from each group.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If current layout analysis methods are used, then the analysis process is simple, but the analysis efficiency is low and pattern coverage is insufficient
Solution Approach 1:
The layout pattern is segmented into multiple rectangular polygons, and each polygon is assigned a hash value based on its shape characteristics. This segmentation approach enables efficient classification of patterns by grouping similar polygons together, significantly improving layout analysis efficiency while maintaining manageable complexity through systematic categorization
Solution Approach 2:
The method applies tolerance-based parameter adjustments to shape characteristics when calculating hash values. By modifying the parameter extraction process to include tolerance application, the system achieves better pattern matching and coverage without requiring fundamentally complex analysis algorithms
2Measurement precision
If traditional pattern classification methods are used, then the process is straightforward, but the number of unique patterns remains high and accuracy is limited
Solution Approach 1:
Instead of directly analyzing and comparing complex layout patterns, the method creates simplified hash value representations (copies) of each polygon's shape characteristics. These hash copies enable efficient comparison and grouping, reducing the number of unique patterns identified while improving classification accuracy through consistent hashing of shape features
Solution Approach 2:
The method merges multiple shape characteristics (width, height, orientation) into a single composite hash value for each polygon. By combining these parameters into unified hash representations, the system reduces the quantity of unique patterns while maintaining accurate classification through the integrated information in each hash value
Data Source
AI summary
A layout analysis method includes segmenting a layout pattern into a plurality of polygons in a shape of a rectangle, extracting a conversion characteristic value by applying tolerance to a characteristic value, the characteristic value comprising shape information of each of the plurality of polygons, extracting a total hash value of each of the plurality of polygons by using the conversion characteristic value of each of the plurality of polygons, grouping patterns of the plurality of polygons into a plurality of groups based on the total hash value of each of the plurality of polygons, and extracting a unique pattern from each of the groups.