Semiconductor Specimen Curvature Analysis for Manufacturing Stability
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Solution Overview
Problem
Current semiconductor manufacturing processes face challenges in achieving high precision and uniformity of submicron features, requiring effective automated examination methods to detect and classify defects in semiconductor wafers.
Innovation Solution
A system and method utilizing a processor and memory circuitry to analyze the contour of semiconductor elements, generating signals for curvature, periodicity, and discontinuities to determine the similarity with expected shapes, enabling efficient detection of manufacturing anomalies and process stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If automated examination methods are implemented to detect and classify defects, then examination effectiveness is improved, but device complexity increases
Solution Approach 1:
The examination system divides the defect analysis process into distinct functional modules: contour extraction module, curvature signal generation module, periodicity analysis module, and defect classification module. Each module performs a specific function, making the overall complex system manageable and maintainable while achieving high examination effectiveness through specialized processing at each stage.
2Manufacturing precision
If shape analysis with curvature signals is used to detect manufacturing anomalies, then manufacturing precision is improved, but measurement complexity increases
Solution Approach 1:
The system replaces complex manual visual inspection and physical measurement methods with automated image processing and mathematical signal analysis. By using curvature calculations and periodicity analysis on digital contour data, the system achieves high manufacturing precision while reducing the difficulty of detection through algorithmic automation rather than manual measurement techniques.
Solution Approach 2:
The examination system performs preliminary processing of contour data by pre-calculating curvature signals and identifying key geometric features before full defect analysis. This preliminary action simplifies subsequent measurement tasks by preparing processed data that highlights critical manufacturing deviations, thereby improving detection accuracy while reducing overall analysis complexity.
Data Source
AI summary
There is provided a system and a method comprising obtaining data Dcontour informative of a contour of an element of a semiconductor specimen acquired by an examination tool, using the data Dcontour to generate a signal informative of a curvature of the contour of the element, determining at least one of data Dperiodicity informative of a periodicity of the signal, or data Ddiscontinuities informative of a number of discontinuities in the signal, wherein each discontinuity is informative of a transition between a convex portion of the contour and a concave portion of the contour, and using at least one of the data Dperiodicity or the data Ddiscontinuities to determine data informative of correct manufacturing of the element.