Technical Library: soldering stick image (Page 1 of 2)

Stencil Printing Yield Improvements

Technical Library | 2014-06-05 16:44:07.0

Stencil printing capability is becoming more important as the range of component sizes assembled on a single board increases. Coupled with increased component density, solder paste sticking to the aperture sidewalls and bottom of the stencil can cause insufficient solder paste deposits and solder bridging. Yield improvement requires increased focus on stencil technology, printer capability, solder paste functionality and understencil cleaning.(...) The purpose of this research is to study the wipe sequence, wipe frequency and wipe solvent(s) and how these factors interact to provide solder paste printing yield improvement.

KYZEN Corporation

Deep Learning Based Defect Detection for Solder Joints on Industrial X-Ray Circuit Board Images

Technical Library | 2021-05-06 13:41:55.0

Quality control is of vital importance during electronics production. As the methods of producing electronic circuits improve, there is an increasing chance of solder defects during assembling the printed circuit board (PCB). Many technologies have been incorporated for inspecting failed soldering, such as X-ray imaging, optical imaging, and thermal imaging. With some advanced algorithms, the new technologies are expected to control the production quality based on the digital images. However, current algorithms sometimes are not accurate enough to meet the quality control. Specialists are needed to do a follow-up checking. For automated X-ray inspection, joint of interest on the X-ray image is located by region of interest (ROI) and inspected by some algorithms. Some incorrect ROIs deteriorate the inspection algorithm.

Southeast University (SEU)

Detection of PCB Soldering Defects using Template Based Image Processing Method

Technical Library | 2021-04-15 14:49:27.0

In this study, a predefined template-based image processing system is proposed to automatically detect of PCB soldering defects that negatively affect circuit operation. The proposed system consists of a scaled inspection structure, a camera, an image processing algorithm merged with Fuzzy and template guided inspection process. The prototype is produced using a plastic material, depending on the focal length of the camera and the PCB size. Image processing step comprises two steps. Firstly, solder joints are determined and boxed using Fuzzy C-means clustering algorithm.

Selcuk University

Void Detection in Large Solder Joints of Integrated Power Electronics

Technical Library | 2012-12-06 17:36:37.0

Inspection of integrated power electronics equals sophisticated test task. X-ray inspection based on 2D / 2.5D principles not utilizable. Full 3D inspection with adapted image capturing and reconstruction is necessary for test task.... First published in the 2012 IPC APEX EXPO technical conference proceedings.

GOEPEL Electronic

Method for Automated Nondestructive Analysis of Flip Chip Underfill

Technical Library | 2008-11-06 02:17:59.0

For many years Acoustic Micro Imaging (AMI) techniques have been utilized to evaluate the quality of the underfill used to support the solder bump interconnections of Flip Chip type devices. AMI has been established as one of the few techniques that can provide reliability and quality control data, but little has been done to automate the evaluation process for Flip Chip underfill until now.

Sonoscan, Inc.

Characterization of Solder Defects on Package on Packages with AXI Systems for Inspection Quality Improvement

Technical Library | 2016-05-30 22:24:00.0

As a part of series of studies on X-Ray inspection technology to quantify solder defects in BGA balls, we have conducted inspection of 3 level POP package by using a new AXI that capable of 3D-CT imaging. The new results are compared with the results of earlier AXI measurements. It is found that 3D measurements offer better defect inspection quality, lower false call and escapes.

Flex (Flextronics International)

New High-Speed 3D Surface Imaging Technology in Electronics Manufacturing Applications

Technical Library | 2020-03-26 14:55:29.0

This paper introduces line confocal technology that was recently developed to characterize 3D features of various surface and material types at sub-micron resolution. It enables automatic microtopographic 3D imaging of challenging objects that are difficult or impossible to scan with traditional methods, such as machine vision or laser triangulation.Examples of well-suited applications for line confocal technology include glossy, mirror-like, transparent and multi-layered surfaces made of metals (connector pins, conductor traces, solder bumps etc.), polymers (adhesives, enclosures, coatings, etc.), ceramics (components, substrates, etc.) and glass (display panels, etc.). Line confocal sensors operate at high speed and can be used to scan fast-moving surfaces in real-time as well as stationary product samples in the laboratory. The operational principle of the line confocal method and its strengths and limitations are discussed.Three metrology applications for the technology in electronics product manufacturing are examined: 1. 3D imaging of etched PCBs for micro-etched copper surface roughness and cross-sectional profile and width of etched traces/pads. 2. Thickness, width and surface roughness measurement of conductive ink features and substrates in printed electronics applications. 3. 3D imaging of adhesive dots and lines for shape, dimensions and volume in PCB and product assembly applications.

FocalSpec, Inc.

Avoiding the Solder Void

Technical Library | 2013-02-08 22:56:47.0

Solder voiding is present in the majority solder joints and is generally accepted when the voids are small and the total void content is minimal. X-ray methods are the predominate method for solder void analysis but this method can be quite subjective for non grid array components due to the two dimensional aspects of X-ray images and software limitations. A novel method of making a copper "sandwich" to simulate under lead and under component environs during reflow has been developed and is discussed in detail. This method has enabled quantitative solder paste void analysis for lead free and specialty paste development and process refinement. Profile and paste storage effects on voiding are discussed. Additionally an optimal design and material selection from a solder void standpoint for a heat spreader on a BCC (Bumpered Chip Carrier) has been developed and is discussed.

Heraeus

Stereo Vision Based Automated Solder Ball Height Detection

Technical Library | 2015-04-16 16:11:43.0

Solder ball height inspection is essential to the detection of potential connectivity issues in semi-conductor units. Current ball height inspection tools such as laser profiling, fringe projection and confocal microscopy are expensive, require complicated setup and are slow, which makes them difficult to use in a real-time manufacturing setting. Therefore, a reliable, in-line ball height measurement method is needed for inspecting units undergoing assembly. (...) In this paper, an automatic, stereo vision based, in-line ball height inspection method is presented. The proposed method includes an imaging setup together with a computer vision algorithm for reliable, in-line ball height measurement.

Intel Corporation

Enhanced X-Ray Inspection of Solder Joints in SMT Electronics Production using Convolutional Neural Networks

Technical Library | 2023-11-20 18:10:20.0

The electronics production is prone to a multitude of possible failures along the production process. Therefore, the manufacturing process of surface-mounted electronics devices (SMD) includes visual quality inspection processes for defect detection. The detection of certain error patterns like solder voids and head in pillow defects require radioscopic inspection. These high-end inspection machines, like the X-ray inspection, rely on static checking routines, programmed manually by the expert user of the machine, to verify the quality. The utilization of the implicit knowledge of domain expert(s), based on soldering guidelines, allows the evaluation of the quality. The distinctive dependence on the individual qualification significantly influences false call rates of the inbuilt computer vision routines. In this contribution, we present a novel framework for the automatic solder joint classification based on Convolutional Neural Networks (CNN), flexibly reclassifying insufficient X-ray inspection results. We utilize existing deep learning network architectures for a region of interest detection on 2D grayscale images. The comparison with product-related meta-data ensures the presence of relevant areas and results in a subsequent classification based on a CNN. Subsequent data augmentation ensures sufficient input features. The results indicate a significant reduction of the false call rate compared to commercial X-ray machines, combined with reduced product-related optimization iterations.

Siemens Process Industries and Drives

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