Semiconductor Defect Inspection Using Hot Spot Detection
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Solution Overview
Problem
Current semiconductor manufacturing processes lack an efficient method for automatically inspecting defects in photoresist patterns, which are critical for determining the critical dimension of semiconductor devices and ensuring quality.
Innovation Solution
A method and apparatus that include a spinner for forming photoresist on a substrate, an exposure unit for exposing the photoresist, and an inspection unit capable of detecting defects by measuring images and identifying 'hot spots' representing ghost images and their wider counterparts, using binarization and differentiation techniques to record and confirm defect presence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automatic defect inspection is implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The inspection system segments the defect detection process into distinct functional modules: a measurement unit for capturing substrate images, a control unit for processing images through binarization and differentiation algorithms, and a defect identification unit for locating hot spots. This modular segmentation enables automated inspection while managing system complexity through functional decomposition.
Solution Approach 2:
The patent replaces manual mechanical inspection methods with an automated optical-mechanical system using measurement units, control units with image processing algorithms (binarization, differentiation), and automated defect identification. This substitution significantly improves productivity while the systematic organization of the automated system keeps complexity manageable.
2Measurement precision
If manual defect detection is used, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent replaces manual inspection with an automated system incorporating measurement units for image capture, control units executing binarization and differentiation algorithms, and automated defect identification. This mechanical-to-automated substitution dramatically improves measurement precision for defect detection while the systematic structure manages the inherent complexity.
Solution Approach 2:
The inspection system changes parameters through image processing transformations: converting grayscale images to binary images (binarization) and applying differentiation operations to enhance edge detection. These parameter changes in the image data enable precise defect identification, improving measurement precision while the automated processing manages complexity.
3Manufacturing precision
If simple inspection methods are used, then device complexity is reduced, but manufacturing precision deteriorates
Solution Approach 1:
The inspection system segments the quality assessment process into specialized functional units: measurement for image acquisition, control for applying binarization and differentiation algorithms, and defect identification for hot spot detection. This segmentation enables comprehensive manufacturing precision verification while managing system complexity through modular design.
Solution Approach 2:
The system applies parameter changes through image processing techniques (binarization converting to black-and-white, differentiation enhancing edges) to detect subtle defects in photoresist patterns. These transformations enable precise manufacturing quality assessment, ensuring high manufacturing precision while the automated systematic approach manages complexity.
Data Source
AI summary
The inventive concepts provide a method for inspecting a pattern, a method for manufacturing a semiconductor device, and an apparatus used according to the methods. The method for inspecting a pattern includes detecting a measured image corresponding to a pattern formed on a substrate, detecting a first hot spot corresponding to a ghost image of the measured image, with the first hot spot representing a defect of the pattern, and detecting a second hot spot that has an area that is wider than that of the first hot spot.