Technical Library: x axis error (Page 1 of 2)

Staking/Epoxy Adhesive Dispensing for Aerospace

Technical Library | 2023-08-16 18:48:50.0

One of our aerospace customers was looking to automate a few manual operations and asked for suggestions. This customer specializes in assemblies for inflight connectivity for commercial airlines and low orbit satellites. The dispensing process included the application of bonding to the sides of large and small components (4-axis) and the ability to cope with the changing viscosity during processing. The material used was EC-2216 B/A Two Part Epoxy and the largest board size was 12"x10"

GPD Global

Justifying AOI and Automated X-Ray

Technical Library | 2013-07-02 16:44:31.0

AOI and AXI systems can address multiple tasks in various locations of the manufacturing process and have become the leading technologies in the quest to identify defects and improve process yields.

Nordson YESTECH

Head in Pillow X-ray Inspection at Flextronics

Technical Library | 2014-12-18 17:22:34.0

Manufacturing technology faces challenges with new packages/process when confronting the need for high yields. Identifying product defects associated with the manufacturing process is a critical part of electronics manufacturing. In this project, we focus on how to use AXI to identify BGA Head-in-Pillow (HIP), which is challenging for AXI testing. Our goal is to help us understand the capabilities of current AXI machines.

Flex (Flextronics International)

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)

AOI-AXI Duo Improves Product Yield

Technical Library | 2009-08-26 19:32:32.0

Automated optical inspection (AOI) and automated X-ray inspection (AXI) have been around for some time in various configurations and both have played a role in improving the quality of circuit boards. While some companies opt for one technology over the other, each form of inspection contributes its own unique benefit to the manufacturing process.

Nordson YESTECH

MEMS Products PCB Design, Mounting, and Handling Guidelines - ICM-40xxx, ICM-42xxx, ICM-43xxx, and ICM-45xxx

Technical Library | 2023-10-09 16:10:02.0

This document provides high-level PCB design, sensor mounting, and handling guidelines for TDK IMU devices, which incorporate a combination of gyroscopes and accelerometers. Each sensor has specific requirements to ensure the highest performance in a finished product. For a layout assessment of your design, including placement and estimated temperature disturbances, please contact TDK. The TDK IMU devices discussed in this document (ICM-40607x, ICM-40608, ICM-42xxx, ICM-43xxx, and ICM-45xxx products) consist of 3-axis MEMS gyroscopes and 3-axis MEMS accelerometers.

TDK - Lambda Americas

Jetting Strategies for mBGAs a question of give and take...

Technical Library | 2015-04-02 20:12:58.0

The demands on volume delivery and positioning accuracy for solder paste deposits are increasing as the size and complexity of circuits continue to develop in the electronics industry. According to the iNEMI 2013 placement accuracy for these kinds of components will reach 6 sigma placement accuracy in X and Y of 30 um by 2023.This study attempts to understand the dependencies on piezo actuation pulse profile on jetting deposit quality, especially focused on positioning, satellites and shape. The correlation of deposit diameter and positioning deviation as a function of piezo actuation profile shows that positioning error for deposits increase almost monotonically with decreasing droplet volume irrespective of the piezo-actuation profile. The trends for shape and satellite levels are not as clear and demand further study.

Mycronic AB

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

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

A Machine Vision Based Automatic Optical Inspection System for Measuring Drilling Quality of Printed Circuit Boards

Technical Library | 2024-04-29 21:39:52.0

In this paper, we develop and put into practice an Automatic Optical Inspection (AOI) system based on machine vision to check the holes on a printed circuit board (PCB). We incorporate the hardware and software. For the hardware part, we combine a PC, the three-axis positioning system, a lighting device and CCD cameras. For the software part, we utilize image registration, image segmentation, drill numbering, drill contrast, and defect displays to achieve this system. Results indicated that an accuracy of 5µm could be achieved in errors of the PCB holes allowing comparisons to be made. This is significant in inspecting the missing, the multi-hole and the incorrect location of the holes. However, previous work only focusses on one or other feature of the holes. Our research is able to assess multiple features: missing holes, incorrectly located holes and excessive holes. Equally, our results could be displayed as a bar chart and target plot. This has not been achieved before. These displays help users analyze the causes of errors and immediately correct the problems. Additionally, this AOI system is valuable for checking a large number of holes and finding out the defective ones on a PCB. Meanwhile, we apply a 0.1mm image resolution which is better than others used in industry. We set a detecting standard based on 2mm diameter of circles to diagnose the quality of the holes within 10 seconds.

National Cheng Kung University

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