Solder Joint Inspection Using Pseudo Cross-Sectional Tomography
Solution Overview
Problem
Conventional inspection methods require significant operator effort to determine the joint state between a substrate and solder from tomographic images, increasing inspection time and complexity.
Innovation Solution
An inspection apparatus that performs image analysis on cross-sectional images and creates pseudo cross-sectional images to estimate the joint state of solder between a substrate and an electronic component, simplifying the inspection process by automating the evaluation of solder joint quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If tomographic images are used to inspect solder joints, then the inspection accuracy is improved, but the inspection time and operator effort increase
Solution Approach 1:
The inspection process is segmented into two distinct phases: (1) acquiring tomographic images at multiple angles to reconstruct three-dimensional solder joint shapes, and (2) using automated image analysis algorithms to evaluate joint quality. This segmentation allows the complex inspection task to be divided between advanced imaging technology and automated processing, reducing operator time investment while maintaining high accuracy through systematic multi-angle data collection and algorithmic evaluation
Solution Approach 2:
The patent replaces manual operator analysis of tomographic images with automated image analysis algorithms. The system uses computer vision and pattern recognition techniques to automatically evaluate solder joint quality from the reconstructed three-dimensional images, substituting human visual inspection and judgment with automated computational analysis. This substitution dramatically reduces inspection time and operator effort while maintaining or improving measurement precision through consistent, objective algorithmic evaluation
2Measurement precision
If manual analysis of tomographic images is performed, then detailed inspection is possible, but inspection complexity increases
Solution Approach 1:
The inspection system performs self-service through automated image analysis algorithms that independently evaluate solder joint quality without requiring operator intervention. The algorithms automatically process the tomographic images, reconstruct three-dimensional joint shapes, and determine pass/fail criteria based on predefined standards. This self-service capability reduces inspection complexity by eliminating the need for operators to manually analyze complex tomographic data, while still providing detailed inspection results through systematic automated evaluation
3Ease of operation
If conventional visual inspection is used, then the inspection process is simple, but the ability to observe solder state is insufficient
Solution Approach 1:
The patent transitions from two-dimensional conventional visual inspection to three-dimensional tomographic imaging. By acquiring images at multiple angles and reconstructing three-dimensional solder joint shapes, the system adds a spatial dimension to the inspection process. This dimensional enhancement enables operators to view solder joints from any cross-section, providing comprehensive three-dimensional information while maintaining ease of operation through standardized imaging and automated analysis protocols
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 apparatus enables efficient and simplified inspection of solder joints, reducing manual effort and increasing inspection speed while maintaining accurate assessment of joint quality.
Implementation Method 1
a technique is presented, in which the three-dimensional shape of the solder in a joint portion is reconstructed into an image based on transmission images of the solder obtained by radiating X-rays onto a substrate from multiple different directions
Data Source
AI summary
A substrate surface detection unit performs image analysis of cross-sectional images of an object to be inspected including a substrate and an electronic component and specifies a surface image on which the surface of the substrate is photographed. A pseudo cross-sectional image creation unit specifies a region of the solder for joining the substrate and the electronic component, the solder being photographed on the cross-sectional images, and creates a pseudo cross-sectional image in which an imaged region is made to have a thickness in a pseudo manner by piling up the cross-sectional images on which the solder is photographed. An inspection unit estimates whether the joint state of the solder is good or bad by performing image analysis on the region of the solder photographed on the surface image and the pseudo cross-sectional image.