AI-powered AOI Solutions Reduce False Calls and Escapes LEARN WHY MORE THAN ONE IN THREE AOI MACHINES INSTALLED IS FROM KOH YOUNG AI-powered True 3D AOI Solutions from Koh Young help manufacturers achieve zero-defect Production. The portfolio of A
The MVP approach to 3D AOI utilizes the combination of both 2D and 3D AOI technologies bringing the advantages of high speed and superior defect coverage for complex defects. MVP’s advanced software tools are the key to taking advantage of each of th
Electronics Forum | Fri Sep 20 14:23:50 EDT 2002 | larryk
PizzaFred, Scott mentioned lots of good ideas. Take one of your boards to each vendor and see what it takes to program the board how long it takes for it to become online. I've found some that are easy to program, but require 40 or more assemblies to
Electronics Forum | Thu Sep 19 21:46:01 EDT 2002 | scottefiske
In the past year I was responsible for developing and leading a Team focused on AOI, Evaluation, Justification, and with a full ROI required, supporting a HMLV manufacturing environment. If you have in these economic times the additional resources t
Used SMT Equipment | AOI / Automated Optical Inspection
- 8 CAMERAS(5 MEGA PIXEL CAMERA) • High performance inspection for 01005 components • New 5.0 megapixel CMOS color cameras • 17 micron camera resolution • Dual-core dual-processor computer • Line-speed inspection for demanding cell phone and
Used SMT Equipment | AOI / Automated Optical Inspection
2022 VisionPro Merlin AOI System: Demo Machine For Sale The VisionPro Merlin AOI solution offered by ASC International provides manufactures with a solid platform to validate the overall variables associated with component placement. State of the a
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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.
500,000 components per hour Maximum Board Size: 22” x 20” (560mm x 510mm) Clearance: 2” (50mm) top and bottom Minimum Component Size: 0201; 01005 with high magnification option
Equipped with a "Clear Vision Capturing System", the RV-1 is capable high-speed and high-precision inspection. The RV-1 captures super clear images using a large sized ring light and coaxial light and enables easy operation by using a newly develope
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MVP AOI Machine Vision Products - MVP Ni ce package deal consisting of (4) MVP 1820 Ultra and (2) Inspection Repair Stations