Automated Grid Post Validation for Charged Particle Microscopy

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Solution Overview

Problem

The industrial use of charged particle microscopes requires manual validation of grid posts for lamella attachment, which is time-consuming and prone to user error, leading to inefficiencies and potential contamination issues.

Innovation Solution

Automated grid validation using image analysis algorithms and machine learning techniques to assess the condition and orientation of grid posts, determining viable weld locations and storing associated stage coordinates for automated lamella attachment.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual validation of grid posts is performed by skilled users, then the evaluation can be performed with human judgment and adaptability, but the process is time-consuming and subjective

Engineering Contradiction:

Improvevalidation accuracyVSAvoidvalidation time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent replaces the manual mechanical inspection process with an automated image analysis system using machine learning algorithms. The system captures images of grid posts and automatically analyzes them to determine validity, substituting human visual inspection with computational image processing to eliminate subjectivity and reduce time consumption

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-validation of grid posts through automated image capture and analysis. The microscope system itself performs the validation function by capturing images and processing them through algorithms that automatically determine post validity without requiring external human intervention for each validation task

Inventive Principle:

Principle #25Self-service

2Measurement precision

If manual inspection is used to evaluate grid posts, then user expertise can be applied to identify defects, but the process is prone to user error and subjectivity

Engineering Contradiction:

Improvedefect detection accuracyVSAvoidconsistency of evaluation

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

The patent replaces subjective human judgment with objective machine-based image analysis. The system uses standardized algorithms to consistently evaluate grid posts across different samples and operators, eliminating variability introduced by human expertise levels and reducing subjectivity in defect identification

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system provides automated feedback through image analysis results, clearly indicating whether grid posts are valid or defective based on objective criteria. This feedback mechanism ensures consistent evaluation standards are applied uniformly across all grid posts, improving both precision and reliability of defect detection

Inventive Principle:

Principle #23Feedback

3Productivity

If automated image analysis is implemented, then validation speed and consistency are improved, but the system complexity increases

Engineering Contradiction:

Improvevalidation throughputVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent integrates multiple functions into a unified automated system that combines image capture, image processing, and validation decision-making. The system serves multiple purposes: capturing grid post images, analyzing them through machine learning algorithms, and determining validity, thereby increasing productivity while managing complexity through functional integration

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system introduces an intermediary layer of automated image analysis between the physical grid posts and the validation decision. This intermediary processing layer handles the complexity of defect detection through standardized algorithms, allowing the system to maintain high throughput while managing complexity through abstraction

Inventive Principle:

Principle #24Intermediary (Mediator)

4Object-affected harmful factors

If thorough validation of each grid post is performed, then contamination and defects are detected, but the process becomes more time-consuming

Engineering Contradiction:

Improvecontamination detectionVSAvoidinspection time

Core Design Contradiction:

Object-affected harmful factorsVSLoss of time

Solution Approach 1:

The patent replaces time-consuming manual inspection with rapid automated image analysis. The system captures images and processes them through algorithms that quickly identify contamination and defects on grid posts, maintaining thorough validation capability while dramatically reducing the time required to detect harmful factors

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20230093535A1Apparatus and method for automated grid validation

Publication Date: 2023.03.23 FEI CO

AI summary

Apparatuses and methods for automated grid validation are disclosed herein. An example method at least includes imaging a grid, the grid including a support portion and a plurality of posts extending from the support portion, wherein each post of the plurality of posts has a designated weld location, and determining, based on the image, whether the designated weld location of each post of the plurality of posts is valid.