Technical Library | 2023-07-22 02:26:05.0
Patch offset; Uneven patches throughout the substrate (each substrate is offset in a different way); Only part of the substrate is offset; Only certain components are offset; The patch Angle is offset; Component absorption error; Laser identification (component identification) error; Nozzle loading and unloading error; Mark (BOC mark, IC mark) identification error; Image recognition error (KE-2060 only); Analysis of the main reasons for throwing material. More information about KINGSUN please Contact US at jenny@ksunsmt.com or visit www.ksunsmt.com
Technical Library | 2023-11-25 07:46:13.0
In the dynamic realm of Surface Mount Technology (SMT), where efficiency and precision are paramount, I.C.T, a renowned SMT equipment manufacturer, proudly unveils its latest innovation – the I.C.T-910 Automatic IC Programming System. Crafted to cater to the intricate demands of SMD chip programming, this cutting-edge device vows to redefine your programming experience and elevate production capabilities. Programming system.png The Power of IC Programming System: As a beacon of excellence in IC Programming Systems, the I.C.T-910 seamlessly integrates advanced technology with user-friendly features. This system empowers manufacturers in the SMT industry, offering versatility in programming needs by accommodating a wide range of SMD chips. Precision Programming: The I.C.T-910 boasts unparalleled precision in programming SMD chips, ensuring accuracy in every generated code. In the SMT industry, where even the slightest error can lead to setbacks, this precision is indispensable. Efficiency Redefined: Accelerate your production timelines with the I.C.T-910's efficient programming capabilities. Engineered to optimize workflows, this system ensures rapid programming without compromising quality, recognizing that time is money in the SMT industry. User-Friendly Interface: Navigating the complexities of IC programming is simplified with the I.C.T-910's intuitive user interface. Operators, even without extensive programming expertise, can harness the system's power, minimizing the learning curve and maximizing productivity. Compatibility and Adaptability: The I.C.T-910 breaks free from limitations, supporting a wide array of SMD chip models. It is a versatile solution for diverse programming requirements, allowing you to stay ahead of technological advancements. Why Choose I.C.T-910 IC Programming System? 8 sets of 32-64sit burners Nozzle: 4pcs Camera: 2pcs (Component camera + Marking camera) UPH: 2000-3000PCS/H Package type: PLCC, JLCC, SOIC, QFP, TQFP, PQFP, VQFP, TSOP, SOP, TSOPII, PSOP, TSSOP, SON, EBGA, FBGA, VFBGA, BGA, CSP, SCSP, and so on. Compatibility: Adapters provided based on customer products. Simple operation interface: Modular and layered interface with pictures and texts for easy operation. System upgrade: Free software upgrade service. Reliability: Trust in the I.C.T-910, a programming system that prioritizes reliability. Rigorous testing ensures consistent and dependable performance, reducing the risk of programming errors and downtime. Elevate Your Competitiveness: Incorporate the I.C.T-910 into your production line to elevate competitiveness in the market. Stay ahead with a programming system designed to meet the demands of the fast-paced SMT industry. Embrace the Future with I.C.T-910: In a landscape where precision, efficiency, and adaptability are non-negotiable, the I.C.T-910 Automatic IC Programming System emerges as the game-changer for SMT manufacturers. Revolutionize your programming processes, enhance productivity, and future-proof your operations with the I.C.T-910. Choose I.C.T-910 and stay ahead in the SMT industry, ushering in the next era of IC programming excellence.
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.
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 | 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 | 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.
Technical Library | 2019-10-17 08:44:01.0
There has been an increase in sealing and encapsulation applications mainly in the field of autonomous driving. Safety and assistance systems already make driving safer and more comfortable today. With increasing progress even more electronic systems will be added. The smooth functioning of computers, sensors, cameras, etc. - and thus our safety as road users - also depends on optimally applied potting media. These can be applied economically, quickly and with high quality in individual applications and are now mastered. With the changing mobility concepts, however, the prerequisites in manufacturing are changing. The requirements are often not fixed at the outset, but only develop during the course of the project. The aim here is to generate a flexible standard that enables attractive pricing and short delivery times. However, we are prepared for these developments: with our modular system consisting of scalable system modules. From this, individual processes can be taken and combined according to requirements. Our new LiquiPrep systems have recently become part of this modular system. They represent a further development of the proven A310 product family and enable reliable processing and conveying of self-levelling media. In addition to a significantly more intuitive operation, the LiquiPrep systems also offer higher performance thanks to a new, patented membrane pump and an optimized agitator. Image: Optimally applied sealants and casting materials form the basis for high quality and smooth functioning of the components.
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