Semiconductor Wafer Image Encoding for Faster Defect Inspection
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Solution Overview
Problem
Existing semiconductor wafer inspection methods struggle to efficiently detect defects as dimensions shrink, leading to potential device failures and yield losses, necessitating improved defect detection in the manufacturing process.
Innovation Solution
A method utilizing sparse coding and hebbian strengthening to encode semiconductor wafer images into an encoding matrix, enabling efficient retrieval of similar images from an indexed database for defect detection, thereby improving defect inspection accuracy and yield.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional inspection methods are used, then the inspection process is simple, but defect detection accuracy deteriorates as dimensions shrink
Solution Approach 1:
The patent creates a virtual copy of the semiconductor wafer by capturing an image and encoding it into a compact representation (encoding matrix). This virtual model allows for defect detection without physically examining every pixel of the original high-resolution image, thereby maintaining detection accuracy while reducing system complexity.
Solution Approach 2:
The patent introduces an encoding matrix as an intermediary between the original wafer image and the defect detection process. This intermediate representation captures essential features while filtering out redundant information, enabling accurate defect detection with simpler processing systems.
2Productivity
If manual inspection is performed, then flexibility is maintained, but productivity decreases due to human workload
Solution Approach 1:
The system performs automated defect detection by encoding wafer images and comparing them against known defect patterns stored in the database. The inspection process serves itself without human intervention, automatically identifying defects and generating results, thereby increasing productivity while eliminating manual inspection workload.
Solution Approach 2:
The system uses a database of previously identified defects to compare against current wafer images. This feedback mechanism allows the system to learn from past inspections and continuously improve defect detection accuracy, automating the process while maintaining high productivity.
3Measurement precision
If full image analysis is performed, then comprehensive defect detection is achieved, but processing time increases
Solution Approach 1:
The patent extracts only the essential features from the full wafer image by encoding it into a compact matrix representation. This extraction process removes redundant information while preserving defect-related characteristics, enabling fast processing without sacrificing inspection accuracy.
Solution Approach 2:
The inspection process is segmented into distinct stages: image capture, encoding into matrix form, database comparison, and defect identification. This segmentation allows each stage to be optimized independently, with the encoding step specifically designed to reduce data volume while maintaining detection capability, thereby reducing overall processing time.
Data Source
AI summary
Methods for processing a semiconductor wafer are provided. A plurality of patches are extracted from the query image related to the semiconductor wafer. The patches are encoded with a set of weightings to obtain an encoding matrix. The database is searched based on the encoding matrix to retrieve the images corresponding to the query image. The retrieved images is used to inspect of defects of the semiconductor wafer, so as to generate an inspection result. A semiconductor process is performed on the semiconductor wafer when the inspection result is normal.