Automated Component Carrier Quality Testing via AI Defect Evaluation
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Solution Overview
Problem
Current methods for testing the quality of component carrier structures, such as printed circuit boards, are labor-intensive, lack precision, and have limited throughput, making them inefficient for industrial-scale quality assessment.
Innovation Solution
An automated system that includes a material removal unit, a detection unit, and an evaluation unit to expose internal planes of component carriers, detect specific data, determine pre-defined test targets, and evaluate defects, utilizing artificial intelligence for defect identification and classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual testing methods are used for component carrier quality assessment, then human engineers can perform detailed inspection, but the process involves high effort and limited precision
Solution Approach 1:
The patent replaces manual mechanical inspection with an automated system comprising a material removal unit, detection unit, and evaluation unit. The material removal unit automatically exposes internal planes, the detection unit captures images, and the evaluation unit with AI algorithms automatically identifies and evaluates defects, eliminating manual intervention entirely and achieving both high precision and high throughput
Solution Approach 2:
The system enables self-service quality testing where the component carrier itself is processed through automated material removal and self-inspection. The evaluation unit autonomously analyzes the exposed planes, identifies defects, and generates quality assessments without requiring human engineers, thereby increasing both precision and productivity simultaneously
2Productivity
If manual cross-sectioning and inspection methods are used, then detailed internal structure analysis is possible, but the process is labor-intensive and has limited throughput for industrial scale
Solution Approach 1:
The patent replaces manual cross-sectioning operations with an automated material removal unit that systematically exposes internal planes of component carriers. The detection unit automatically captures images of the exposed planes, and the evaluation unit with AI algorithms automatically identifies and evaluates defects, completely eliminating manual labor while maintaining detailed inspection capabilities and achieving industrial-scale throughput
3Reliability
If conventional manual testing methods are used, then quality assessment can be performed, but reliability and consistency are limited due to human factors
Solution Approach 1:
The patent replaces manual testing with an automated system that ensures consistent and reliable quality assessment. The material removal unit, detection unit, and AI-based evaluation unit work together to eliminate human variability, providing repeatable and objective defect identification and evaluation across all component carriers, thereby significantly improving reliability despite increased system complexity
Data Source
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AI summary
Apparatus (100) for testing quality of a component carrier structure (102), wherein the apparatus (100) comprises a material removal unit (112) configured for removing material of the component carrier structure (102) for exposing a plane in an interior of the component carrier structure (102), a detection unit (162) configured for detecting component carrier structure specific data (in particular image data) of the exposed plane of the component carrier structure (102), a determining unit (114) configured for determining at least one pre-defined test target (116) of the component carrier structure (102) at the exposed plane based on the component carrier structure specific data, and an evaluation unit (118) configured for identifying and evaluating at least one defect of the at least one determined test target (116) for assessing quality of the component carrier structure (102).