Defect Observation Device Automatic Parameter Determination

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Solution Overview

Problem

The existing defect observation methods and devices in semiconductor manufacturing require skilled personnel to manually adjust multiple image processing parameters for accurate defect classification, leading to inefficiencies and high barriers to use, especially for beginners or those who do not frequently use the devices.

Innovation Solution

A method and device that automatically determine suitable image processing parameter sets by calculating coincidence degrees between ideal and processed defect images, allowing for the selection of optimal parameter sets and reducing the need for manual trial and error, thereby simplifying the classification process.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If multiple image processing parameters are manually adjusted for accurate defect classification, then classification precision is improved, but device complexity and ease of operation deteriorate

Engineering Contradiction:

Improvedefect classification precisionVSAvoidparameter setting ease

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The system automatically determines optimal image processing parameters by evaluating multiple candidate parameter sets against defect images, eliminating the need for manual parameter adjustment by operators while maintaining high classification precision

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system automatically varies and evaluates multiple image processing parameters (such as threshold values, processing algorithms, and recognition conditions) to determine the optimal parameter set for accurate defect classification without manual intervention

Inventive Principle:

Principle #35Parameter changes

2Measurement precision

If multiple image processing parameters are manually adjusted for accurate defect classification, then classification precision is improved, but productivity deteriorates

Engineering Contradiction:

Improvedefect classification precisionVSAvoidparameter setting speed

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The system pre-evaluates multiple candidate parameter sets using representative defect images before actual defect classification, so that optimal parameters are ready in advance and no time is lost during production for parameter adjustment

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The automatic parameter determination system performs parameter optimization independently without requiring operator time for manual adjustment, maintaining high classification precision while preserving production throughput

Inventive Principle:

Principle #25Self-service

3Measurement precision

If multiple image processing algorithms are prepared and selected for different images, then measurement precision is improved, but device complexity increases

Engineering Contradiction:

Improvedefect recognition precisionVSAvoidalgorithm selection complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system creates a unified parameter set that can be universally applied across different defect images and types, eliminating the need for operators to select different algorithms for different cases while maintaining accurate defect recognition

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system automatically selects and configures appropriate processing algorithms and parameters based on the characteristics of each defect image, managing algorithmic complexity internally while presenting a simplified interface to operators

Inventive Principle:

Principle #35Parameter changes

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 faster and more efficient setting of image processing parameters, reducing the complexity and time required for defect classification, making the process more accessible and user-friendly, even for less experienced operators.

Implementation Method 1

irradiating a sample with an electron beam, detecting primary electrons reflected by the sample and/or secondary electrons generated by the sample

Methodology Applied

Scientific EffectElectron beam: Electron Beam

Implementation Method 2

detecting primary electrons reflected by the sample and/or secondary electrons generated by the sample

Methodology Applied

Scientific EffectSecondary electron emission: Electron Impact Desorption

Data Source

PatentUS8824773B2Defect observation method and defect observation device

Publication Date: 2014.09.02 HITACHI HIGH TECH CORP

AI summary

A defect observation device including an input-output unit supplied with information of a taught defect, and information of an ideal output of the taught defect, and configured to display a processing result based upon a determined image processing parameter set; and an automatic determination unit configured to: select image processing parameter sets which are less in number than the total number of all image processing parameter sets, out of all image processing parameter sets, calculate image processing results on an input defect image, by using the selected image processing parameter sets, calculate a coincidence degree for each of the selected image processing parameter sets, estimate distribution of an index value in all image processing parameter sets from distribution of the coincidence degree for the selected image processing parameter sets, and determine an image processing parameter set to have a high coincidence degree out of all image processing parameter sets.