Wafer Defect Classification Using Metrology Data Attributes
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Solution Overview
Problem
As semiconductor device dimensions shrink, identifying nuisances and defects of interest on wafers becomes increasingly challenging due to higher nuisance rates, which obscure the detection of smaller defects, and existing methods like SEM and TEM imaging are time-consuming and inefficient.
Innovation Solution
A system and method utilizing an inspection subsystem with an energy source and detector, coupled with computer subsystems that acquire metrology data and determine defect locations, assign metrology data as defect attributes, and differentiate between nuisances and defects of interest by analyzing these attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If inspection sensitivity is increased to detect smaller defects, then defect detection capability is improved, but nuisance defect rate increases
Solution Approach 1:
The patent introduces metrology data as an intermediary between inspection data and defect classification. This metrology data serves as a mediator that provides additional contextual information about the wafer characteristics, enabling more accurate differentiation between true defects and nuisance signals without requiring increased inspection sensitivity
2Loss of information
If SEM or TEM imaging is used to identify nuisance defects, then defect origin analysis is improved, but analysis time increases
Solution Approach 1:
The patent uses metrology measurements as a simplified copy or representation of the physical wafer characteristics, replacing the need for time-consuming SEM or TEM imaging. The metrology data captures essential wafer information that can be used to identify nuisance defect origins without requiring detailed microscopic imaging
Solution Approach 2:
The patent replaces the mechanical imaging process (SEM/TEM) with a metrology-based measurement system. This substitution uses non-imaging measurement techniques to gather wafer characteristic data, eliminating the time-consuming imaging step while still providing information about defect origins
3Quantity of substance
If design rules are shrunk to increase device density, then manufacturing capacity is improved, but defect detection difficulty increases
Solution Approach 1:
The patent moves the analysis from the spatial dimension (inspecting smaller features) to a different dimension by incorporating metrology data about wafer characteristics. This dimensional shift allows detection of defects in high-density designs by using contextual wafer information rather than relying solely on direct imaging of small features
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 efficient identification and separation of nuisances and defects of interest, improving defect detection accuracy and reducing the time required for analysis, thereby enhancing semiconductor manufacturing yield.
Implementation Method 1
The energy source is configured to generate energy that is directed to a wafer. The detector is configured to detect energy from the wafer and to generate output responsive to the detected energy.
Data Source
AI summary
Methods and systems fir identifying nuisances and defects of interest (DOIs) in defects detected on a wafer are provided. One method includes acquiring metrology data for the wafer generated by a metrology tool that performs measurements on the wafer at an array of measurement points. In one embodiment, the measurement points are determined prior to detecting the defects on the wafer and independently of the defects detected on the wafer. The method also includes determining locations of defects detected on the wafer with respect to locations of the measurement points on the wafer and assigning metrology data to the defects as a defect attribute based on the locations of the defects determined with respect to the locations of the measurement points. In addition, the method includes determining if the defects are nuisances or DOIs based on the defect attributes assigned to the defects.