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...
Technical Library | 2012-11-29 14:23:58.0
1000 units per day) production environment presents challenging technical, logistic and cost obstacles that are usually more complex than those encountered at the inspection (automated optical inspection) and the manufacturing process test step (in-circuit test).
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 20:39:44.0
Quality control is a key activity performed by manufacturing companies to verify product conformance to the requirements and specifications. Standardized quality control ensures that all the products are evaluated under the same criteria. The decreased cost of sensors and connectivity enabled an increasing digitalization of manufacturing and provided greater data availability. Such data availability has spurred the development of artificial intelligence models, which allow higher degrees of automation and reduced bias when inspecting the products. Furthermore, the increased speed of inspection reduces overall costs and time required for defect inspection. In this research, we compare five streaming machine learning algorithms applied to visual defect inspection with real world data provided by Philips Consumer Lifestyle BV. Furthermore, we compare them in a streaming active learning context, which reduces the data labeling effort in a real-world context. Our results show that active learning reduces the data labeling effort by almost 15% on average for the worst case, while keeping an acceptable classification performance. The use of machine learning models for automated visual inspection are expected to speed up the quality inspection up to 40%.
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.
Technical Library | 2019-05-23 21:56:56.0
Automatic on-line shoe sole spraying system: automatic shoe sole spraying system, simple and convenient operation, using 3D vision positioning system. Automatic recognition and automatic generation of spraying trajectory. Robot non-contact spraying gun is used to complete the process of shoe sole spraying with maturity, stability, high speed and high precision along the predetermined trajectory. The automatic generation of spraying trajectory is the realization of shoe sole spraying technology. Shoe sole spraying characteristics: 1.Positioning System: 3D Visual Positioning 2.Components: Intelligent Robot, Laser Scanner, Industrial Computer, Gum Spraying System, Conveyor Belt, Electrical Control System, etc. 3.Spraying time: slightly different according to shoe size and spraying time Fully automatic sole spraying advantages: 1. Simple application: suitable for soles of different specifications, models and sizes 2. Faster speed: 6-8 seconds to complete sole scanning and spraying, superior to similar products at home and abroad. 3. Quality stability: gum spraying trajectory is scheduled, gum dosage is fixed, gum spraying quality is greatly improved. 4. High cost performance: the same performance, the price is only 1/3 of the same type of equipment of European brand. 5. Reduce wear and tear: glue is fully utilized and not wasted, reducing human contact with glue. Intelligent operation advantage manual only need general operation can be automated workshop, mechanical arm automatic spraying glue, accurate spraying, reduce glue waste. Environmental protection effect of long-term close contact with glue seriously affects human health and mechanical work, glue does not directly contact, do not harm the human body. Fully automatic spraying, shoe sole adhesion process for automatic spraying machine, will not cause great challenges! With the deepening of personalized shoemaking, higher requirements have been put forward for the spraying technology in shoemaking process. The method of creating spraying trajectory must be adapted to shoes of different sizes and styles. The automatic generation of spraying trajectory is one of the key technologies to realize the automation of shoe sole spraying process. The method of off-line programming and real-time generation of spraying trajectory for robots based on the three-dimensional CAD model of sole and the data of sole. A new method of generating spray trajectory by scanning the sole of shoe upper with linear structured light sensor is presented. The feasibility of the method is verified by industrial robots. Aiming at the need of generating shoe sole spray rubber trajectory based on line structured light, the format standard of IGES file of three-dimensional model of shoe sole was tested. The shoe sole contour line and the shoe sole surface were extracted, and then the offset curve of the shoe sole contour line on the shoe sole surface was calculated to obtain the spray rubber trajectory. Three-dimensional profilometer is to use structured light to obtain sole information, effectively improve the automatic shoemaking spraying process, which will help to improve the efficiency of shoemaking, improve the quality of footwear products, and promote the development of personalized shoemaking.
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Industrial Sensor Vision International specializes in advanced camera technology of high resolution fast speed cameras for automation, AOI, 2-D/3-D, SPI inspection and wafer inspection.
3 Morse Road 2A
Oxford, CT USA
Phone: +1 203 592 8723
