Solder Joint Defect Detection via X-Ray Measurement Training
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Solution Overview
Problem
Current inspection methods for solder joints in electronic devices are either subjective and non-destructive, allowing defective joints to bypass quality testing, or destructive and costly, requiring sample breakdown for analysis.
Innovation Solution
Training a measurement machine, such as an X-ray machine, to accurately measure solder joint lengths using training data from optical microscopy, enabling non-destructive detection of defective joints by comparing measured lengths with pre-defined thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current inspection methods are used for solder joints, then non-destructive inspection is maintained, but defective joints bypass quality testing due to subjective evaluation
Solution Approach 1:
The patent replaces subjective human inspection with an automated measurement machine that uses optical imaging and algorithmic analysis to objectively measure solder joint lengths and detect defects, eliminating the unreliability of subjective evaluation while maintaining non-destructive inspection
Solution Approach 2:
The patent introduces a measurement machine as an intermediary between the solder joints and the inspection process, using trained algorithms to serve as a mediator that objectively evaluates joint quality based on measured dimensions rather than human subjectivity
2Measurement precision
If destructive inspection methods are used for solder joints, then accurate defect detection is achieved, but electronic components are damaged and costs increase
Solution Approach 1:
The patent replaces destructive physical analysis with non-destructive optical measurement and algorithmic evaluation, achieving accurate defect detection through automated measurement of solder joint lengths without requiring sample breakdown or component damage
Solution Approach 2:
The patent creates a digital copy or representation of the solder joint through optical imaging and measurement, allowing accurate evaluation of joint quality through algorithmic analysis of the digital model rather than physical destruction of the actual component
3Measurement precision
If automated measurement machines are trained using optical microscopy data, then measurement accuracy improves, but training complexity and time increase
Solution Approach 1:
The patent performs preliminary training of the measurement machine algorithm using optical microscopy data before actual inspection, preparing the system in advance with learned parameters and thresholds that enable rapid accurate measurement during production without time loss during actual inspection
Solution Approach 2:
The patent cushions against future measurement inaccuracies by pre-training the algorithm with comprehensive optical microscopy data, establishing robust measurement criteria and defect thresholds beforehand that protect against variability during actual production inspection
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
The method provides a reliable, non-destructive, and cost-effective means to objectively identify defective solder joints, preventing failures and reducing maintenance costs by ensuring quality control without damaging electronic components.
Implementation Method 1
Training a measurement machine, such as an X-ray machine, to accurately measure solder joint lengths
Data Source
AI summary
Example implementations relate to an inspection method for training a measurement machine to accurately measure side joint lengths and detecting a defect among a plurality of solder joints. The method includes receiving a first data representing the side joint lengths of the plurality of solder joints measured by a first measurement machine and a second data representing the side joint lengths measured by a second measurement machine. Further, the method includes determining a correlation value based on a statistical analysis of a relationship between the first data and the second data. The method further includes updating an algorithm used by the first measurement machine to measure the side joint lengths, based on the correlation value to reduce deviation between the first data and the second data. Later, the updated algorithm is used as a dimensional metrology in the first measurement machine for detecting the defect in the solder joints.