Technical Library | 2023-09-15 11:17:10.0
Ensure the integrity of your components with our SMT Offline X-Ray System. Detect hidden defects and improve the quality of your PCBAs with precise X-ray inspection technology.
Technical Library | 2023-09-15 10:00:02.0
Experience top-tier quality inspection with our DIP Inverted Camera Online PCBA AOI solution. Ensure flawless PCB assemblies and detect defects with precision using advanced technology. Improve efficiency and minimize production issues with this cutting-edge automated optical inspection system.
Technical Library | 2023-09-15 10:05:59.0
Elevate your electronics manufacturing with SMT Online AOI. Achieve real-time quality control, defect detection, and production efficiency optimization with our advanced automated optical inspection system. Improve your production process and ensure top-notch quality with SMT Online AOI technology.
Technical Library | 2023-09-15 09:58:06.0
Elevate your electronics production with our PCBA Coating Online SMT AOI solution. Achieve precision coating and comprehensive quality assurance in one integrated system. Boost efficiency and reduce defects with cutting-edge automated optical inspection technology.
Technical Library | 2023-09-15 10:03:54.0
Achieve thorough quality control with our DIP On-line Dual Side PCBA AOI system. Detect defects on both sides of PCBAs in real-time, ensuring impeccable quality and production efficiency. Elevate your electronic manufacturing process today.
Technical Library | 2020-08-27 01:15:10.0
Automobile surface defects like scratches or dents occur during the process of manufacturing and cross-border transportation. This will affect consumers' first impression and the service life of the car itself. In most worldwide automobile industries, the inspection process is mainly performed by human vision, which is unstable and insufficient. The combination of artificial intelligence and the automobile industry shows promise nowadays. However, it is a challenge to inspect such defects in a computer system because of imbalanced illumination, specular highlight reflection, various reflection modes and limited defect features. This paper presents the design and implementation of a novel automatic inspection system (AIS) for automobile surface defects which are the located in or close to style lines, edges and handles. The system consists of image acquisition and image processing devices, operating in a closed environment and noncontact way with four LED light sources. Specifically, we use five plane-array Charge Coupled Device (CCD) cameras to collect images of the five sides of the automobile synchronously. Then the AIS extracts candidate defect regions from the vehicle body image by a multi-scale Hessian matrix fusion method. Finally, candidate defect regions are classified into pseudo-defects, dents and scratches by feature extraction (shape, size, statistics and divergence features) and a support vector machine algorithm. Experimental results demonstrate that automatic inspection system can effectively reduce false detection of pseudo-defects produced by image noise and achieve accuracies of 95.6% in dent defects and 97.1% in scratch defects, which is suitable for customs inspection of imported vehicles.
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.
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 | 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 | 2013-08-08 15:23:11.0
In this project Machine Vision PCB Inspection System is applied at the first step of manufacturing, i.e., the making of bare PCB. We first compare a PCB standard image with a PCB image, using a simple subtraction algorithm that can highlight the main problem-regions. We have also seen the effect of noise in a PCB image that at what level this method is suitable to detect the faulty image. Our focus is to detect defects on printed circuit boards & to see the effect of noise. Typical defects that can be detected are over etchings (opens), under-etchings (shorts), holes etc...
Our Company handle AOI (Auto Optical Inspection) and SPI (Solder Paste Inspection) Machines.
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