Technical Library: guide of x ray inspection (Page 1 of 1)

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

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)

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

How to Identify Faulty Components on a PCB: A Quick Guide

Technical Library | 2024-11-22 06:29:45.0

This article discusses the critical importance of identifying faulty components in Printed Circuit Boards (PCBs). It outlines common signs of defective components--such as physical damage, electrical failures, and overheating--while also exploring detection techniques like visual inspection, multimeter testing, thermal imaging, and X-ray analysis. Emphasizing the significance of choosing a reliable PCB manufacturing partner, the article highlights how proactive detection can ensure greater reliability and longevity in electronic devices. For businesses seeking comprehensive PCB solutions, the article encourages engaging with specialized manufacturers to optimize their PCB projects and enhance product quality.

PCB Power Market

Comparing Costs and ROI of AOI and AXI

Technical Library | 2013-08-07 21:52:15.0

PCB architectures have continued their steep trend toward greater complexities and higher component densities. For quality control managers and test technicians, the consequence is significant. Their ability to electrically test these products is compounded with each new generation. Probe access to high density boards loaded with micro BGAs using a conventional in-circuit (bed-of-nails) test system is greatly reduced. The challenges and complexity of creating a comprehensive functional test program have all but assured that functional test will not fill the widening gap. This explains why sales of automated-optical and automated X-ray inspection (AOI and AXI) equipment have dramatically risen...

Teradyne

Common Process Defect Identification of QFN Packages

Technical Library | 2019-07-23 22:33:47.0

The Quad Flat Pack No Leads (QFN) style of leadless packaging [also known as a Land Grid Array (LGA)] is rapidly increasing in us e for wireless, automotive, telecom and many other areas becaus e of its low cost, low stand-off height and excellent thermal and electri cal properties. With the implementation of any new package type, there is always a learning curve for its use in design and processing as well as for the Process and Quality Engineers who have to get to grips with the challenges that these packages bring. Therefore, this paper will provide examples of the common process defects that can be seen with QFNs /LGAs when using optical and x-ray inspection as part of manufacturing quality control. Results of trials conducted on four PCB finishes and using vapour phase and convection reflow will be discussed.

Nordson DAGE

Benefits of Manual X-Ray Inspection for Medium-Sized EMS and OEM suppliers

Technical Library | 2023-11-20 17:42:33.0

Zero-defect strategies and increased demands on the production of assemblies are making quality assurance in electronics production increasingly important. Continous miniaturization of components, ever higher packing densities and the associated hard-to-view assembly areas, as well as the increased use of components such as BGAs, QFNs and QFPs, pose a considerable challenge when it comes to high-precision quality control.

Viscom AG

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guide of x ray inspection searches for Companies, Equipment, Machines, Suppliers & Information

INSPECTION TECH
INSPECTION TECH

Our Company handle AOI (Auto Optical Inspection) and SPI (Solder Paste Inspection) Machines.

Equipment Dealer / Broker / Auctions

Hwaseong-si, Gyeonggi-do, Korea
Hwaseong-si, South Korea

Phone: +82-1029254936