Industry News | 2002-01-25 07:28:11.0
This year�s SMT Vision Award for Best New Product in the category for pick and place went to MYDATA automation, for its revolutionary Agilis feeder. The SMT Vision Award is a sought-after distinction and is well recognized in the surface mount industry.
Industry News | 2017-02-14 19:47:02.0
Seica will be exhibiting at the Apex show held in San Diego this year showing our expanding lines of test and assembly equipment. The automated Pilot4DV8 will be showcased fully automated in a batch line environment. The automated solution will demonstrate a magazine and conveyance solution that will allow customers to load different board part numbers for automated testing.
Industry News | 2013-06-10 12:32:44.0
Nordson DAGE, a division of Nordson Corporation (NASDAQ: NDSN) is pleased to announce that its newly developed camera assist automation system will be exhibited in Booth 5971 at the SEMICON West exhibition scheduled to take place on 9-11th July 2013 in San Francisco, Calif.
Industry News | 2007-05-30 17:19:09.0
Billerica, MA � May 24, 2007. Orbotech, Inc., the North American subsidiary of Orbotech Ltd., today announced jointly with Endicott Interconnect Technologies, Inc. (EI) that the advanced electronic interconnect supplier has placed a major multi-million dollar order for Orbotech laser direct imaging (LDI) and automated optical inspection (AOI) equipment for use in production at its facility in Endicott, NY, USA.
Industry News | 2019-07-09 19:48:53.0
Semicon West is being held at the Moscone Center from July 9 – 11 in San Francisco, California. A leading provider of Flying Probe technology, Seica’s newest line of testers brings with it key advances and features required in the semiconductor market.
Technical Library | 2021-04-15 14:39:41.0
Inspection of printed circuit board (PCB) has been a crucial process in the electronic manufacturing industry to guarantee product quality & reliability, cut manufacturing cost and to increase production. The PCB inspection involves detection of defects in the PCB and classification of those defects in order to identify the roots of defects. In this paper, all 14 types of defects are detected and are classified in all possible classes ...
Technical Library | 2022-06-27 16:50:26.0
Electronics industry is one of the fastest evolving, innovative, and most competitive industries. In order to meet the high consumption demands on electronics components, quality standards of the products must be well-maintained. Automatic optical inspection (AOI) is one of the non-destructive techniques used in quality inspection of various products. This technique is considered robust and can replace human inspectors who are subjected to dull and fatigue in performing inspection tasks. A fully automated optical inspection system consists of hardware and software setups. Hardware setup include image sensor and illumination settings and is responsible to acquire the digital image, while the software part implements an inspection algorithm to extract the features of the acquired images and classify them into defected and non-defected based on the user requirements. A sorting mechanism can be used to separate the defective products from the good ones. This article provides a comprehensive review of the various AOI systems used in electronics, micro-electronics, and opto-electronics industries. In this review the defects of the commonly inspected electronic components, such as semiconductor wafers, flat panel displays, printed circuit boards and light emitting diodes, are first explained. Hardware setups used in acquiring images are then discussed in terms of the camera and lighting source selection and configuration. The inspection algorithms used for detecting the defects in the electronic components are discussed in terms of the preprocessing, feature extraction and classification tools used for this purpose. Recent articles that used deep learning algorithms are also reviewed. The article concludes by highlighting the current trends and possible future research directions.
Technical Library | 2021-11-22 20:32:10.0
The aim of this work is to define a procedure to develop diagnostic systems for Printed Circuit Boards, based on Automated Optical Inspection with low cost and easy adaptability to different features. A complete system to detect mounting defects in the circuits is presented in this paper. A low cost image acquisition system with high accuracy has been designed to fit this application. Afterward, the resulting images are processed using the Wavelet Transform and Neural Networks, for low computational cost and acceptable precision. The wavelet space represents a compact support for efficient feature extraction with the localization property. The proposed solution is demonstrated on several defects in different kind of circuits.
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.
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.
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