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1
Petkov, Nikolay, and Malinka Ivanova. "Printed circuit board and printed circuit board assembly methods for testing and visual inspection: a review." Bulletin of Electrical Engineering and Informatics 13, no. 4 (August 1, 2024): 2566–85. http://dx.doi.org/10.11591/eei.v13i4.7601.
Повний текст джерелаАнотація:
Testing and visual inspection of printed circuit boards (PCBs) and printed circuit board assemblies (PCBAs) are important procedures in the manufacturing process of electronic modules and devices related to locating and identifying possible defects and failures. Earlier defects detection leads to decreasing expenses, time and used resources to produce high quality electronics. In this paper an exploration and analysis about the current research regarding methods for PCB and PCBA testing, techniques for defects detection and vusial inspection is performed. The impact of machine and deep learning for testing and visual inspection procedures is also investigated. The used methodology comprises bibliometric approach and content analysis of papers, indexed in scientific database Scopus, considering the queries: “PCB and testing” and “PCB and testing”, “printed circuit board assembly and testing” and “PCBA and testing”, “PCB defect detection” and “PCBA defect detection”, “PCB and visual inspection”, and “PCBA and visual inspection”. The findings are presented in the form of a framework, which summarizes the contemporary landscape of methods for PCBs and PCBAs testing and visual inspection.
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Hsia, Kuo-Hsien, and Jr-Hung Guo. "Estimation of the PCB Production Process Using a Neural Network." Proceedings of Engineering and Technology Innovation 15 (April 27, 2020): 01–07. http://dx.doi.org/10.46604/peti.2020.4265.
Повний текст джерелаАнотація:
Printed Circuit Boards (PCB) are an integral part of all electronic products, and the production process for printed circuit boards is quite complex. As the life cycle of electronic products becomes shorter and shorter, and the precision and signal bandwidth of electronic products become higher and higher, the manufacturing process of printed circuit boards is further complicated. Therefore, how to pre-evaluate the production difficulty before starting the production will effectively increase the efficiency and quality of printed circuit board production.
Gerber file is the most commonly used data format for the printed circuit board industry. This file contains most of the parameters required for the manufacture of printed circuit boards. Therefore, this study uses a neural network to evaluate new PCB products before they are produced through the production parameters that are more influential in the PCB manufacturing process. This makes it possible to evaluate the difficulty and the required production process before the new PCB product is produced. This will be very beneficial for the PCB production schedule, quality control, and cost.
3
Khan, Noor Mohmmed, Shubhangi Patil, Tushar Diggewadi, and Anand Gudnavar. "Cinch and Sterling Analog Circuits for Laboratory." International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering 6, no. 01 (June 25, 2017): 51–58. http://dx.doi.org/10.15662/ijareeie.2017.0601007.
Повний текст джерелаАнотація:
As we know that there is ever increasing demand for compact circuits and less complex wirings over the board, a technological boon evolved for such demand is Printed Circuit Board (PCB). A PCB will mechanically supports and electrically connects electronic components using conductive tracks, pads. These boards will have minimal chances for short circuits, components on the board are fixed; another advantage is creation of multiple boards using single design. Taking this technology forward to our everyday life, we implemented analog communication laboratory circuit, Schmitt trigger.
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Noor Yulita Dwi Setyaningsih, Moh Rizal, and Budi Cahyo Wibowo. "CNC Plotter Printed Circuit Board." Jurnal Media Elektrik 21, no. 2 (May 8, 2024): 116–22. http://dx.doi.org/10.59562/metrik.v21i2.2145.
Повний текст джерелаАнотація:
Prited Circuit Board is one part of the field of electronics that has many roles and benefits. This automatic PCB path manufacturing will provide many benefits to users that were previously still done manually. In this research, the PCB carving process will be operated using G-Code and GRBL controller to control the machine. The use of 3 stepper motors will provide a good carving composition in terms of x, y and Z axis movements, as well as the use of spindles for drill bit control that functions to carve PCB layouts. From the results, the PCB path manufacturing process is faster and has the accuracy of the specified design
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Lambture, Rahul. "Printed Circuit Board (PCB) Fault Detection." International Journal for Research in Applied Science and Engineering Technology 12, no. 6 (June 30, 2024): 542–48. http://dx.doi.org/10.22214/ijraset.2024.63142.
Повний текст джерелаАнотація:
Abstract: Nowadays many industries heavily depend on devices, those, with printed circuit boards (PCBs) to function properly. However issues like connections, damaged components or short circuits can cause malfunctions that result in downtime and financial losses. It is crucial to identify and resolve thesePCB faults to maintain the operation of electronic systems. On average businesses experience a 23% decrease in productivity due to PCB faults. One of the contributors to this problem is the lack of detection and resolution. To tackle this issue we propose an approach using machine learning techniques for PCB fault detection. Our solution harnesses the power of Web Machine Learning to implement a real time model for detecting PCB faults. By utilizing TensorFlow.js – a JavaScript library for training and deploying machine learning models in web browsers – we can provide instant feedback on the health of PCBs
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Wang, Qianyue. "A new frontier in electronics manufacturing: Optimized deep learning techniques for PCB image reconstruction." Applied and Computational Engineering 51, no. 1 (March 25, 2024): 267–73. http://dx.doi.org/10.54254/2755-2721/51/20241591.
Повний текст джерелаАнотація:
In the rapidly evolving electronics manufacturing sector, maintaining quality control and conducting failure analysis of Printed Circuit Boards (PCBs) are critical yet challenging tasks. This study presents a groundbreaking self-supervised learning framework to address existing gaps in the reconstruction of encoded or blurred Printed Circuit Board images. By leveraging a customized DeepLabV3+ architecture with depth-wise separable convolutions, our model is engineered to autonomously learn intrinsic Printed Circuit Board features, eliminating the need for manual data labeling. This not only alleviates computational burden but also ensures robust performance. Augmented by feature quantization and channel reduction techniques, our model stands out as both lightweight and resilient, making it highly adaptable for Printed Circuit board imaging. To validate the framework, a tailored dataset comprising raw and encoded Printed Circuit board images from diverse sources was assembled and further refined to match real-world industrial standards. Our model demonstrates unparalleled efficacy in Printed Circuit board image reconstruction, establishing a new benchmark for the field.
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Myers, Sharon A., Troy D. Cognata, and Hugh Gotts. "FTIR analysis of printed-circuit board residue." Proceedings, annual meeting, Electron Microscopy Society of America 54 (August 11, 1996): 264–65. http://dx.doi.org/10.1017/s0424820100163782.
Повний текст джерелаАнотація:
Logic boards were failing at Enhanced Mac Minus One (EMMO) test or Integrated Circuit Test (ICT) after printed circuit board (PCB) rework. The failure to boot was originally traced to a suspected bad microcontroller chip. Replacing this chip, or an oscillator tied to the microcontroller circuit, did not consistently solve the boot problem. With further testing, it was found the microcontroller circuit was very sensitive to resistance and was essentially shorted.A resistor in the microcontroller circuit was identified on the flip side of the PCB. Several areas on the board, including the resistor R161, were seen to have a slight white haze/ low gloss appearance on the surface of the PCB. To test if the residue was electrically conductive, five boards were selected whose sole failure was R161. The resistance of the individual resistors was measured with a digital multimeter (DMM). The resistor was then cleaned with isopropyl alcohol and a cotton swab. Each board was retested at ICT and the individual resistors measured again with a DMM. Cleaning the area surrounding the resistor with isopropyl alcohol, corrected the failure four of the times.
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Craven, Jeffery D., Ariel R. Oldag, and Robert N. Dean. "A Technique for Detecting Moisture Absorption in Printed Circuit Boards." Journal of Microelectronics and Electronic Packaging 17, no. 1 (January 1, 2020): 28–33. http://dx.doi.org/10.4071/imaps.1014123.
Повний текст джерелаАнотація:
Abstract Most circuit boards operate in environments that have the potential to be exposed to moisture, either in vapor or liquid form. Because low-cost circuit boards can readily absorb moisture, this can lead to performance issues, reliability issues, and even catastrophic failure. However, it is difficult to detect if moisture absorption has occurred before the circuit board suffers a complete failure. To alleviate this issue, a fringing field capacitor was implemented in printed circuit board (PCB) technology and used to detect the absorption of moisture in the circuit board through the accompanying increase in capacitance. Prototype sensors were fabricated and immersed for 42 d, demonstrating an increase in capacitance of between 14% and 29%. This sensor technology can easily be added to circuit board designs because they use the standard materials and fabrication processes used in commercial PCB construction.
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Umbetov, S. V., and S. P. Pronin. "COMPREHENSIVE METHOD FOR MONITORING PCB CORROSION PROCESS." Kontrol'. Diagnostika, no. 309 (March 2024): 50–57. http://dx.doi.org/10.14489/td.2024.03.pp.050-057.
Повний текст джерелаАнотація:
Experimental studies of corrosion penetration into printed circuit boards of laboratory samples are presented. Conditions similar to those ignited in contact with sea water were recreated and a series of experiments were carried out with each printed circuit board of the device. The results of laboratory studies of the relationship between corrosion of conductive tracks and their resistance according to the ratio of color components in a digital image of the corroded surface of a printed circuit board track are presented. The histogram of the distribution of pixels by color for photographs clearly shows that green will usually always predominate, since it is the main color of the PCB mask, but the corrosion itself is characterized by red. Measuring the resistance of the tracks during the experiment allows us to determine the effectiveness of protecting the mask on the printed circuit board from corrosion and assess the quality of the metallization process and application of the mask. In this case, we can say that there is a linear relationship between the variables, which corresponds to experimental data. A theoretical analysis of the factors influencing the change in the brightness of RGB components in the image of a corroded surface and the resistance of the conductive path has been carried out..
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Schmidt, H., M. Käß, R. Lichtinger, and M. Hülsebrock. "Model updating for the simulation of surface strains on printed circuit boards considering parameter uncertainty." Journal of Physics: Conference Series 2647, no. 21 (June 1, 2024): 212006. http://dx.doi.org/10.1088/1742-6596/2647/21/212006.
Повний текст джерелаАнотація:
Abstract The efficient and reliable design of power electronic components plays an important role in the development process of electrically driven vehicles. One key aspect is the reliability of solder joints on printed circuit boards (PCB) that greatly depends on the surface strain at the solder joint locations. It is therefore unavoidable to use precise simulations of surface strains to reliably estimate the solder joint lifetime. This work presents a procedure of model updating of a printed circuit board model that considers the variability of board behavior due to uncertainties in the material composition or the manufacturing process. Hierarchical Bayesian model updating is applied to incorporate this variability. The printed circuit board is seen as a multi-level model that is updated in two steps. Experimental data from system and component level are used to sequentially update the printed circuit board and the board mounting. The experimental data combine modal information and measured frequency response functions. The proposed procedure is applied to a test PCB and the updated model is validated with experimental surface strain data.
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Park, Pil-Ju, Bo-Sam Lee, and Kun-Mo Lee. "Life Cycle Assessment on Printed Circuit Board." Korean Journal of Life Cycle Assessment 2, no. 1 (August 2000): 61–68. http://dx.doi.org/10.62765/kjlca.2000.2.1.61.
Повний текст джерелаАнотація:
Life Cycle Assessment on Printed Circuit Board produced in C Electronics Co. was carried out. The system boundary encompasses raw material acquisition to the manufacturing of PCB(or cradle to gate). The product is FR4 PCB used for a component of HDD. FR is a mixture of glass fiber and epoxy resin. Generally site specific data were applied. However, database were used when it is hard to get site specific data. Impact assessment was carried out consecutively as classification, characterization, normalization and weighting. Considered Impact categories are ARD, GW, OD, POC, Acid, Eut, ET, HT. Sensitivity analysis is accomplished to find out how the variation of unreliable data affects the result of LCA. The PCB manufacturing was identified as the most contributing activity to all impact categories except OD. This is mainly due to the electricity consumed in the manufacturing phase. Even though the large amount of chemicals are used for PCB manufacturing in mass, environment impact of those chemicals is much less than they were consumed. The sensitivity of data method shows that the amount of electricity consumed in the PCB manufacturing is considerably sensitive to POC and GW. The sensitivity results of allocation method in the PCB manufacturing on the LCA indicate approximately 25% difference in all impact categories.
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Hietanen, Jarmo, and Nick Zacharov. "An integrated Printed Circuit Board (PCB) microphone." Journal of the Acoustical Society of America 107, no. 5 (May 2000): L25—L30. http://dx.doi.org/10.1121/1.428895.
Повний текст джерела
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Dong, Liangwei, and Yueli Hu. "Microfluidic networks embedded in a printed circuit board." Modern Physics Letters B 31, no. 19-21 (July 27, 2017): 1740017. http://dx.doi.org/10.1142/s0217984917400176.
Повний текст джерелаАнотація:
In order to improve the robustness of microfluidic networks in printed circuit board (PCB)-based microfluidic platforms, a new method was presented. A pattern in a PCB was formed using hollowed-out technology. Polydimethylsiloxane was partly filled in the hollowed-out fields after mounting an adhesive tape on the bottom of the PCB, and solidified in an oven. Then, microfluidic networks were built using soft lithography technology. Microfluidic transportation and dilution operations were demonstrated using the fabricated microfluidic platform. Results show that this method can embed microfluidic networks into a PCB, and microfluidic operations can be implemented in the microfluidic networks embedded into the PCB.
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Obe, C. T., S. E. Oti, C. U. Eya, D. B. N. Nnadi, and O. E. Nnadi. "A low-cost printed circuit board design technique and processes using ferric chloride solution." Nigerian Journal of Technology 39, no. 4 (March 24, 2021): 1223–31. http://dx.doi.org/10.4314/njt.v39i4.31.
Повний текст джерелаАнотація:
This paper presents a low-cost printed circuit board (PCB) design technique and processes using ferric chloride (𝑭𝒆𝑪𝒍𝟑) solution on a metal plate for a design topology. The PCB design makes a laboratory prototype easier by reducing the work piece size, eliminating the ambiguous connecting wires and breadboards circuit errors. This is done by manual etching of the designed metal plate via immersion in ferric chloride solutions for a given time interval 0-15mins. With easy steps, it is described on how to make a conventional single-sided printed circuit board with low-cost, time savings and reduced energy from debugging. The simulation and results of the printed circuit is designed and verified in the Multisim software version 14.0 and LeCroy WJ35Aoscilloscope respectively.
Keywords: Etching, Ferric Chloride, Insertion, Multisim, Metal Plate, Printed Circuit Board
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I., Ciocioi. "Electromagnetic interference in a multiconductor transmission system – MTL." Scientific Bulletin of Naval Academy XXII, no. 2 (December 15, 2019): 343–51. http://dx.doi.org/10.21279/1454-864x-19-i2-041.
Повний текст джерелаАнотація:
In electrical and electronic practice, many connection and transmission elements (cables) are used as a multi-conductor transmission lines (MTL). The electromagnetic fields existing in the environment of these multiconductor transmission lines and can generate different types of coupling phenomena, causing EMC problems by the appearance of the unwanted EMI, disturbing the correct function and altering the information. Electromagnetic coupling between the circuits/cables of a circuit (also known as crosstalk) can also occur between the signal and power paths of an assembly made on printed circuit boards, PCB (printed board circuit), so it is important that when designing such an electrical / electronic circuit, these aspects should be taken into account.
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Sharma, M. Dinesh, Kowshick K, Mokesh Prabhu S, Nitin Kumar S, and Pandiya Raj C. "PRINTED CIRCUIT BOARD DEFECT DETECTION USING MACHINE LEARNING." International Journal of Technical Research & Science 9, Spl (June 25, 2024): 27–35. http://dx.doi.org/10.30780/specialissue-iset-2024/040.
Повний текст джерелаАнотація:
As technology advances, printed circuit boards (PCBs) add more components and change their layout. One of the most important quality control procedures is PCB surface inspection, as small defects in signal traces can cause major damage to the system. Due to the disadvantages of manual scanning, great efforts have been made to automate scanning using high-resolution CCD or CMOS sensors. In traditional machine vision approaches, it is always difficult to determine pass/fail criteria based on small failure examples. the development of improved sensor technology. To solve this problem, we propose an advanced PCB inspection solution based on a jump-related convolutional autoencoder. A deep autoencoder model is trained to separate imperfect original images from defective ones. The location of defects is determined by comparing the decoded image with the input image. In the first production, we scaled the correct representation to improve the performance of training samples through a small and unbalanced database. The printed circuit board (PCB), which is the basic structure for electronic devices, is very important to the electronics industry. PCB quality and reliability must be ensured, but manual inspection methods are often labor-intensive and error-prone. This study presents a new machine learning (ML) method for PCB fault detection. To automatically detect defects, we use advanced ML models such as Convolutional Neural Networks (CNNs) on a large database of PCB images marked for defects. To provide reliable and accurate detection results, our research focuses on data preparation, feature extraction, model selection, and robust validation. The results show that ML-based PCB defect detection is effective, which enables better quality control. electronics manufacturing industry. The performance of our system has been carefully evaluated, showing good accuracy and efficiency in detecting defects using precise validation methods. This research is an important step towards automating PCB inspection, improving the reliability of electronic products, and reducing production costs. It also laid the groundwork for advances in quality control and defect prevention in electronics manufacturing. Added ML-based PCB defects These findings are expected to revolutionize quality assurance procedures as the electronics industry evolves and open the door to more efficient, error-free, and costeffective electronics manufacturing.
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Melnyk, Roman, and Andrii Shpek. "Defects Detection in PCB Images by Scanning Procedure, Flood-filling and Mathematical Comparison." WSEAS TRANSACTIONS ON CIRCUITS AND SYSTEMS 22 (December 31, 2023): 206–17. http://dx.doi.org/10.37394/23201.2023.22.23.
Повний текст джерелаАнотація:
The basis of the approach is a scanning procedure with the movement of windows on the printed circuit board to detect defects of various types. Mathematical image comparison, pixel distribution histograms, padding algorithms, statistical calculations, and histogram deviation measurements are applied to the small parts of the PCB image in a small window area. The paper considers K-mean clustering of pixel intensities to simplify the printed circuit board image, separation of elements on the printed circuit board image by filling with colors, determination of defect intensity, and subtraction formulas.
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Tang, S. C., S. Y. Hui, and H. S. H. Chung. "Characterization of coreless printed circuit board (PCB) transformers." IEEE Transactions on Power Electronics 15, no. 6 (November 2000): 1275–82. http://dx.doi.org/10.1109/63.892842.
Повний текст джерела
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Han, Tae Uk, Seungdo Kim, Young-min Kim, Byeonga Hwang, U. Bayasgalan, and Jeong-Yeon Lee. "Pyrolysis Reaction Characteristics of Waste Paper Laminated Phenolic-Printed Circuit Board (p-PCB)." Journal of Korea Society of Waste Management 32, no. 2 (March 30, 2015): 161–69. http://dx.doi.org/10.9786/kswm.2015.32.2.161.
Повний текст джерела
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Melnyk, Roman, and Vitalii Vorobii. "PCB Image Defects Detection by Artificial Neural Networks and Resistance Analysis." WSEAS TRANSACTIONS ON CIRCUITS AND SYSTEMS 23 (May 23, 2024): 70–83. http://dx.doi.org/10.37394/23201.2024.23.7.
Повний текст джерелаАнотація:
The approach contains the sequence of algorithms and formulas for image processing. They are single-layer neural networks, thinning, clustering, mathematical image comparison, and measurements of the trace length and width. All these procedures solve the task of selection and separation of the main objects in the printed circuit board: contacts, traces, and defects. The calculated features connect the conductance resistance of traces with the characteristics of defects. Imposing a tolerance on the distributed or concentrated changes of resistance it is possible to mark the defective and suspicious printed circuit boards.
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Yang, Jun, and Jing Liu. "Direct printing and assembly of FM radio at the user end via liquid metal printer." Circuit World 40, no. 4 (October 28, 2014): 134–40. http://dx.doi.org/10.1108/cw-07-2014-0029.
Повний текст джерелаАнотація:
Purpose – This paper aims to demonstrate the practicability of the liquid metal printer, developed in the authors’ laboratory, in the direct manufacture and assembly of circuit boards at the end customer side using GaIn24.5 alloy as printing ink at room temperature. Design/methodology/approach – A practical procedure for printing a real designed frequency modulation (FM) radio circuit on flexible and transparent substrate using liquid metal printer was established. Necessary electronic components are then assembled on this circuit board. To enhance the mechanical stability of the FM radio circuit board, we further package the circuit board using room temperature vulcanizing silicone rubber. Finally, an efficient way to recycle the liquid metal ink and electronic components is presented at the end of circuit board’s life cycle. Findings – Methods of designing the circuit patterns that are applicable to liquid metal printer are similar to the conventional printed circuit board (PCB) designing strategies. The procedure of applying liquid metal printer for printing the circuits is entirely automatic, cost-effective and highly time-saving, which allows the user to print out desired device in a moment. Through appropriate packaging, the FM radio circuit board can be flexibly used. These PCBs own many outstanding merits including easy modification and stretchability. Nearly all liquid metal ink and components can be recycled. Originality/value – The present end-customer-oriented liquid metal printing opens the way for large-scale personal electronics manufacture which is expected to initiate many emerging applications in education, design, industry, entertainment and more maker targets.
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Paul, Shubhra Deb, and Swarup Bhunia. "SILVerIn: Systematic Integrity Verification of Printed Circuit Board Using JTAG Infrastructure." ACM Journal on Emerging Technologies in Computing Systems 17, no. 3 (June 25, 2021): 1–28. http://dx.doi.org/10.1145/3460232.
Повний текст джерелаАнотація:
A printed circuit board (PCB) provides necessary mechanical support to an electronic system and acts as a platform for connecting electronic components. Counterfeiting and in-field tampering of PCBs have become significant security concerns in the semiconductor industry as a result of increasing untrusted entities in the supply chain. These counterfeit components may result in performance degradation, profit reduction, and reputation risk for the manufacturers. While Integrated Circuit (IC) level authentication using physical unclonable functions (PUFs) has been widely investigated, countermeasures at the PCB level are scarce. These approaches either suffer from significant overhead issues, or opportunistic counterfeiters can breach them like clockwork. Besides, they cannot be extended to system-level (both chip and PCB together), and their applications are also limited to a specific purpose (i.e., either counterfeiting or tampering). In this article, we introduce SILVerIn , a novel systematic approach to verify the authenticity of all chips used in a PCB as well as the board for combating attacks such as counterfeiting, cloning, and in-field malicious modifications. We develop this approach by utilizing the existing boundary scan architecture (BSA) of modern ICs and PCBs. As a result, its implementation comes at a negligible (∼0.5%) hardware overhead. SILVerIn is integrated into a PCB design during the manufacturing phase. We implement our technique on a custom hardware platform consisting of an FPGA and a microcontroller. We incorporate the industry-standard JTAG (Joint Test Action Group) interface to transmit test data into the BSA and perform hands-on measurement of supply current at both chip and PCB levels on 20 boards. We reconstruct these current values to digital signatures that exhibit high uniqueness, robustness, and randomness features. Our approach manifests strong reproducibility of signatures at different supply voltage levels, even with a low-resolution measurement setup. SILVerIn also demonstrates a high resilience against machine learning-based modeling attacks, with an average prediction accuracy of ∼51%. Finally, we conduct intentional alteration experiments by replacing the on-board FPGA to replicate the scenario of PCB tampering, and the results indicate successful detection of in-field modifications in a PCB.
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Kong, Lingzhe. "Research on the application of deep learning algorithms to PCB defect detection." Applied and Computational Engineering 43, no. 1 (February 26, 2024): 44–48. http://dx.doi.org/10.54254/2755-2721/43/20230805.
Повний текст джерелаАнотація:
In today's electronics industry, Printed Circuit Boards play a crucial role in providing the layout for circuit components and conductive traces in nearly all electronic devices. The quality of components soldered onto Printed Circuit Boards directly impacts product performance. To ensure the performance of electronic devices, Printed Circuit Boards defect detection based on deep learning algorithms has become a pivotal technology in the defect inspection process within the electronics industry. However, the application of deep learning algorithms in this context faces several challenges. These challenges include difficulties in acquiring Printed Circuit Boards defect datasets, limited generalization capability in Printed Circuit Boards defect detection, and slow and low-quality Printed Circuit Boards image stitching processes. To enhance researchers' understanding of deep learning-based Printed Circuit Boards defect detection, this paper analyzes the challenges associated with deep learning in the Printed Circuit Boards defect detection process and proposes several viable solutions. In conclusion, this paper provides insights into the future of deep learning-based Printed Circuit Boards defect detection.
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Zainul Muttaqin, Ahnaf, Ibrahim Nawawi, and Johan Pamungkas. "Implementasi Machine Learning pada Deteksi Kecacatan Printed Circuit Board." Voteteknika (Vocational Teknik Elektronika dan Informatika) 12, no. 1 (March 1, 2024): 44. http://dx.doi.org/10.24036/voteteknika.v12i1.127224.
Повний текст джерелаАнотація:
Kualitas suatu rangkaian elektronik sangat bergantung pada kualitas Printed Circuit Board (PCB) untuk mendukung proses berjalannya semua komponen. Meskipun dapat menggunakan inspeksi manual terhadap kecacatan pada PCB, namun metode tersebut memiliki keterbatasan terhadap ketelitian dan waktu. Oleh karena itu, penelitian ini dilakukan untuk mengimplementasikan Machine Learning dalam deteksi kecacatan pada PCB. Dalam pengaplikasiannya, penelitian ini menggunakan algoritma deteksi objek YOLOv5 (You Look Only Once versi 5), yang merupakan pengembangan dari convolutional neural network. Fokus penelitian ini adalah membangun sistem yang dapat mengidentifikasi kecacatan pada PCB menggunakan algoritma YOLOv5. Dataset yang digunakan terdiri dari 600 gambar, dengan 480 data latih dan 120 data uji. Jenis kecacatan PCB yang diidentifikasi meliputi open circuit, missing hole, mouse bite, short, spur, dan spurious copper. Hasil penelitian menunjukkan bahwa penggunaan YOLOv5m menghasilkan nilai mean Average Precision (mAP) sebesar 95,3%. Selain itu, dalam pengujian dengan 120 data uji, model berhasil mencapai akurasi sebesar 93,83%, presisi 98,13%, recall 95,43%, dan error 6,17%. Selain itu peningkatan spesifikasi hardware juga berpengaruh dalam kecepatan deteksi objek kecacatan pada PCB.Kata kunci : PCB, kecacatan, Machine Learning, convolutional neural network, YOLOv5 The quality of an electronic circuit depends significantly on the quality of the Printed Circuit Board (PCB) supporting its operation. While manual inspection of defects on PCBs has been carried out, this method has limitations in terms of precision and time. Therefore, this research aims to implement Machine Learning in detecting defects on PCBs. In its application, this study utilizes the YOLOv5 (You Look Only Once version 5) object detection algorithm, which is an advancement of the convolutional neural network. The focus of this research is to build a system capable of identifying defects on PCBs using the YOLOv5 algorithm. The dataset used consists of 600 images, with 480 training data and 120 test data. Types of PCB defects identified include open circuit, missing hole, mouse bite, short, spur, and spurious copper. The research results indicate that using YOLOv5m yields a mean Average Precision (mAP) value of 95.3%. Additionally, in testing with 120 test data, the model achieved an accuracy of 93.81%, precision of 98.13%, recall of 95.43%, and an error rate of 6.17%. Furthermore, the improvement of hardware specifications also influences the speed of object detection for defects on PCBs.Keywords: PCB, defect, Machine Learning, convolutional neural network, YOLOv5
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Nassajfar, Mohammad Naji, Ivan Deviatkin, Ville Leminen, and Mika Horttanainen. "Alternative Materials for Printed Circuit Board Production: An Environmental Perspective." Sustainability 13, no. 21 (November 3, 2021): 12126. http://dx.doi.org/10.3390/su132112126.
Повний текст джерелаАнотація:
This article investigates the potential environmental impacts of four-layer printed circuit board (PCB) production from cradle to grave. The study starts with a lifecycle assessment of conventional PCB production. Then, the alternative materials of polyethylene terephthalate (PET), polylactic acid (PLA)/glass fiber composite and paper are investigated for the substrate. A conventional PCB adopts copper as the conductive material and requires an etching process. The environmental impacts of changing the conductive deposition method to an additive method by printing silver nanoparticles is studied. In a conventional PCB, electricity generation contributes 41% of the global warming potential (GWP) and 38% of the abiotic resource depletion (ADP), in the fossil category. By applying an additive manufacturing method, the GWP of PCB manufacturing can be reduced to 14% of that of the conventional method. A sensitivity analysis of silver recycling illustrates that a 40% higher silver recycling rate would decrease the GWP of silver material by about 48–60%. Uncertainty in the energy consumption of PCB production would alter the environmental impacts; however, even with the most conservative energy consumption in a conventional PCB production method, the environmental impacts of the additive method are about five times lower than those of conventional PCB production.
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Huang, Xin, Zhi Shun Chen, Cheng Yong Wang, Li Juan Zheng, and Yue Xian Song. "Measurement of Micro-Drill Breakage during PCB Drilling." Materials Science Forum 836-837 (January 2016): 592–99. http://dx.doi.org/10.4028/www.scientific.net/msf.836-837.592.
Повний текст джерелаАнотація:
Due to the weak rigidity of micro-drills and impulse effects, the micro-drill breakage is a common problem in printed circuit board micro-drilling. Traditional micro-drill breakage detection methods and principles, including vacuum-type, laser-type, and contact-type detection, were reviewed in this paper. The comparison of three detection methods showed that the contact-type detection can more satisfy the performance of CNC drilling machine. Three effective contact-detection circuits, including no transformer and rectifier circuit pulse-type, active-type, and trigger-type detection circuit, were introduced. And as a conclusion, differences of these detection methods were compared. Based on the characteristic of three effective micro-drill breakage contact detection circuits, the development trends and designs of innovative detection circuit were proposed to meet the challenges in micro-drill breakage measurement during PCB drilling.
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Wileman, Andrew, Suresh Perinpanayagam, and Sohaib Aslam. "Physics of Failure (PoF) Based Lifetime Prediction of Power Electronics at the Printed Circuit Board Level." Applied Sciences 11, no. 6 (March 17, 2021): 2679. http://dx.doi.org/10.3390/app11062679.
Повний текст джерелаАнотація:
This paper presents the use of physics of failure (PoF) methodology to infer fast and accurate lifetime predictions for power electronics at the printed circuit board (PCB) level in early design stages. It is shown that the ability to accurately model silicon–metal layers, semiconductor packaging, printed circuit boards (PCBs), and assemblies allows, for instance, the prediction of solder fatigue failure due to thermal, mechanical, and manufacturing conditions. The technique allows a life-cycle prognosis of the PCB, taking into account the environmental stresses it will encounter during the period of operation. Primarily, it involves converting an electronic computer aided design (eCAD) circuit layout into computational fluid dynamic (CFD) and finite element analysis (FEA) models with accurate geometries. From this, stressors, such as thermal cycling, mechanical shock, natural frequency, and harmonic and random vibrations, are applied to understand PCB degradation, and semiconductor and capacitor wear, and accordingly provide a method for high-fidelity power PCB modelling, which can be subsequently used to facilitate virtual testing and digital twinning for aircraft systems and sub-systems.
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Tang, Hong Qun, Cheng Yong Wang, Bing Wang, F. Su, Ping Ma, and Yue Xian Song. "Module Partition and Application for Printed Circuit Board High Speed Drilling Machine." Advanced Materials Research 188 (March 2011): 104–9. http://dx.doi.org/10.4028/www.scientific.net/amr.188.104.
Повний текст джерелаАнотація:
The target of this paper is to design a high speed drilling machine suitable for printed circuit board with micro-hole of 0.1 mm diameter, which has drilling force measuring function and rapid change spindle function. Therefore, in this paper, the main principles of module partition for drilling machine were analyzed. Module partition was conducted for high speed drilling machine of Printed Circuit Board (PCB), as well as using modular components combine PCB high speed drilling machine. Then, performance testing and simulation of dynamic modeling were carried out on the modular PCB high speed drilling machine. The results show that the modular PCB high speed drilling machine has good performance, enough stiffness, better stability and meeting the design requirements. The modular partition laid the foundation for further study on the module creation and reconfiguration of PCB drilling machine.
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Weller, S. D. T., I. P. Jones, Ian M. Fox, and Terry Hirst. "High Reliability Pb-Free Printed Circuit Board Assembly." Key Engineering Materials 450 (November 2010): 9–12. http://dx.doi.org/10.4028/www.scientific.net/kem.450.9.
Повний текст джерелаАнотація:
The solderability and reliability of SnAgCu and SnAgCuSbBiNi lead-free solders were assessed against SnPbAg solder on a range of PCB finishes. A novel solderability test has been developed to assess the solder system’s ability to realign when a deliberately inaccurate solder stencil printing process was applied. This has shown to be an excellent way to compare PCB finishes and solders, as well as define process parameters. Electroless Nickel Immersion Gold (ENIG) finish proved to give the best solderability and the optimum process parameters were also found. SnPbAg solder has shown superior thermal cycling performance compared to SnAgCu.
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Oyebola, Blessed Olalekan, and E. Eze Blessing. "Simulation and Implementation of Microcontroller Based Printed Circuit Board Ready Circuits for Technical Training and Demonstration." Asian Journal of Engineering and Applied Technology 7, no. 1 (May 5, 2018): 29–36. http://dx.doi.org/10.51983/ajeat-2018.7.1.981.
Повний текст джерелаАнотація:
The paper presents designed and constructed microcontroller based PCB ready on five automation circuits as an attempt to aid technical education on microcontroller circuits’ simulation in Computer Engineering Technology. The designs were of three stages that include circuit design and simulation by using Proteus software, printed circuit board (PCB) production using manual techniques and construction of five selected circuits (Seven Segment to Display Number 0-9, seven Segment Counter to Count 0-99, Matrix Led to Display A-Z, Digital Thermometer and Motion Sensor to Switch 10 Points of Loads) for purpose of training. The microcontroller programing were done in Mikro C programming platform. The presented hand-on circuits have proved to be instructive to trainees.
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Wardani, Gatut Ari, Rokiy Alfanaar, and Sri Juari Santosa. "Pelarutan Selektif Tembaga dari Limbah Printed Circuit Board dengan Hidrogen Peroksida." ALCHEMY Jurnal Penelitian Kimia 14, no. 1 (February 15, 2018): 51. http://dx.doi.org/10.20961/alchemy.14.1.11168.51-59.
Повний текст джерелаАнотація:
<p>Pelarutan selektif tembaga dari limbah <em>printed circuit board</em> (PCB) telah berhasil dilakukan. Logam tembaga yang terkandung di dalam papan PCB dapat dipisahkan menggunakan campuran hidrogen peroksida dan asam sulfat dengan variasi perbandingan volume 0 : 1, 1 : 1, 2 : 1, 3 : 1, 4 : 1, dan 5 : 1. Pemisahan optimal dilakukan dengan sistem perendaman selama 3 hari dengan campuran H<sub>2</sub>O<sub>2</sub>/H<sub>2</sub>SO<sub>4</sub> = 3 : 1 (v/v). Jumlah tembaga yang terkandung di dalam papan PCB dianalisis menggunakan <em>X-ray fluorescense</em>. Tembaga yang terkandung di dalam PCB sebesar 57,7%. Pelarutan selektif dapat menurunkan kadar tembaga sehingga tembaga yang masih tersisa adalah sebesar 7,7 x 10<sup>-4 </sup>%. Penurunan kadar tembaga yang terkandung di dalam PCB mencapai 99,999%. Analisis spektrometri serapan atom dilakukan untuk mengetahui jumlah tembaga yang terlarut yaitu sebesar 25,415 mg/kg PCB.</p><p><strong>Leaching of Copper from Printed Circuit Board Waste with Hydrogen Peroxide</strong><strong>. </strong>Leaching of copper from printed circuit board (PCB) waste has been successfully performed. The copper metal contained in the PCB can be separated using a mixture of hydrogen peroxide and sulfuric acid with a variation of volume ratio is 0 : 1, 1 : 1, 2 : 1, 3 : 1, 4 : 1, and 5 : 1. Optimal separation is carried out by the immersion system for 3 days using H<sub>2</sub>O<sub>2</sub>/H<sub>2</sub>SO<sub>4</sub> = 3:1 (v/v). The amount of copper contained in the PCB was analyzed using X-ray fluorescence. The copper contained in the printed circuit board is 57.7%. The leaching process can decrease the copper content so that the remaining copper is 7.7 x 10<sup>-4</sup>%. The decrease of copper content contained in PCB reaches 99.999%. Analysis of atomic absorption spectrometry was conducted to determine the amount of dissolved copper that is 25.415 mg/kg PCB.</p>
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Jenu, Mohd Zarar Mohd, Ahmed M. Sayegh, and Syarfa Zahirah Sapuan. "Maximum Radiated Emissions of Printed Circuit Board Using Analytical Methods." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 6 (December 1, 2019): 2919. http://dx.doi.org/10.11591/ijece.v7i6.8658.
Повний текст джерелаАнотація:
<span>The rapid progress of technology has imposed significant challenges on Printed Circuit Boards (PCB) designers. Once of those challenges is to satisfy the electromagnetic compatibility (EMC) compliance requirements. For that reason, EMC compliance must be considered earlier at the design stage for time and cost savings. Conventionally, full wave simulation is employed to check whether the designed PCB meets EMC standards or not. However, this method is not a suitable option since it requires intensive computational time and thus increasing the unit cost. This paper describes novel analytical models for estimating the radiated emissions (RE) of PCB. These models can be used to help the circuit designer to modify their circuit based on the maximum allowable RE comparing to the relevant EMC-RE standard limit. Although there are many RE sources on PCB, this paper focuses on the significant source of RE on PCB; namely PCB-traces. The trace geometry, termination impedance, dielectric type, etc. can be specified based on the maximum allowable emissions. The proposed models were verified by comparing the results of the proposed models with both simulation and experimental results. Good agreements were obtained between the analytically computed results and simulation/measurement results with accuracy of ±3dB.</span>
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Jenu, Mohd Zarar Mohd, Ahmed M. Sayegh, and Syarfa Zahirah Sapuan. "Maximum Radiated Emissions of Printed Circuit Board Using Analytical Methods." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 6 (December 1, 2017): 2919. http://dx.doi.org/10.11591/ijece.v7i6.pp2919-2928.
Повний текст джерелаАнотація:
<span>The rapid progress of technology has imposed significant challenges on Printed Circuit Boards (PCB) designers. Once of those challenges is to satisfy the electromagnetic compatibility (EMC) compliance requirements. For that reason, EMC compliance must be considered earlier at the design stage for time and cost savings. Conventionally, full wave simulation is employed to check whether the designed PCB meets EMC standards or not. However, this method is not a suitable option since it requires intensive computational time and thus increasing the unit cost. This paper describes novel analytical models for estimating the radiated emissions (RE) of PCB. These models can be used to help the circuit designer to modify their circuit based on the maximum allowable RE comparing to the relevant EMC-RE standard limit. Although there are many RE sources on PCB, this paper focuses on the significant source of RE on PCB; namely PCB-traces. The trace geometry, termination impedance, dielectric type, etc. can be specified based on the maximum allowable emissions. The proposed models were verified by comparing the results of the proposed models with both simulation and experimental results. Good agreements were obtained between the analytically computed results and simulation/measurement results with accuracy of ±3dB.</span>
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Xu, Fei, Chuan Ri Li, Tong Min Jiang, and Long Tao Liu. "Vibration Modeling and Sensitivity Analysis of Printed Circuit Board." Applied Mechanics and Materials 226-228 (November 2012): 345–50. http://dx.doi.org/10.4028/www.scientific.net/amm.226-228.345.
Повний текст джерелаАнотація:
Various failures in electronic systems, particularly in the connections between the printed circuit board (PCB) and components, are due to mechanical shock and vibration. The vibration characteristic of a plug-in PCB in an airborne electronic case (AEC) was studied first by finite element modeling (FEM) and experimental techniques. The coupling method and torsional spring elements were used in FEM to better simulate the PCB’s realistic boundary condition. A reasonable correlation between simulation and test results was obtained. Since the fundamental frequency is one of the most important dynamic characteristics of PCB, the orthogonal design and variance analysis, as well as FEM method, were discussed subsequently to investigate the effects of different factors. Analysis results demonstrate a good correlation with current studies. Finally, a general design guideline was presented to maximize the PCB’s fundamental frequency.
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Martin, Mitchell, and Jim Plusquellic. "NotchPUF: Printed Circuit Board PUF Based on Microstrip Notch Filter." Cryptography 4, no. 2 (April 4, 2020): 11. http://dx.doi.org/10.3390/cryptography4020011.
Повний текст джерелаАнотація:
Physical Unclonable Functions (PUFs) are primitives that are designed to leverage naturally occurring variations to produce a random bitstring. Current PUF designs are typically implemented in silicon or utilize variations found in commercial off-the-shelf (COTS) parts. Because of this, existing designs are insufficient for the authentication of Printed Circuit Boards (PCBs). In this paper, we propose a novel PUF design that leverages board variations in a manufactured PCB to generate unique and stable IDs for each PCB. In particular, a single copper trace is used as a source of randomness for bitstring generation. The trace connects three notch filter structures in series, each of which is designed to reject specific but separate frequencies. The bitstrings generated using data measured from a set of PCBs are analyzed using statistical tests to illustrate that high levels of uniqueness and randomness are achievable.
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Zheng, Yali, Da Meng, and Libing Bai. "PCB Network Analysis for Circuit Partitioning." Applied Sciences 12, no. 16 (August 17, 2022): 8200. http://dx.doi.org/10.3390/app12168200.
Повний текст джерелаАнотація:
The complexity of automatic placement and routing is proportional to the scale of the circuit. Through netlist partition algorithms, printed circuit board (PCB) circuits are divided into different submodules, and the problem scale is effectively reduced in order to obtain the optimal automatic layout and routing. In this paper, we analyze net attributes and potential patterns in netlists through visualization, and propose a heuristic PCB netlist partition approach based on net attributes and potential patterns which we discover from netlists. Our partition approach takes the netlist as input, and module partition set as output. Firstly, the modules are prepartitioned using net attributes. Further, the special patterns in circuits are discovered, and the scattered resistors, capacitors, and other components caused by prepartitioning would be allocated to initial modules by three rules—classifying, matching, and force strategy. Our method is evaluated on 11 PCB netlists which are built manually. Experimental results show that our proposed netlist partition approach significantly outperforms the state of the art on all evaluation indices, which can achieve 80–96% partition accuracy.
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A., Salunke Purva, Sherkar Shubhangi N., and Arya C.S.. "PCB (Printed Circuit Board) Fault Detection Using Machine Learning." International Journal of Computer Science and Mobile Computing 10, no. 2 (February 23, 2021): 54–56. http://dx.doi.org/10.47760/ijcsmc.2021.v10i02.008.
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Frick, M., R. Eidher, and R. Weigel. "Coupling path influence on the conducted emission measurement results by the EMC semiconductor test board." Advances in Radio Science 9 (August 1, 2011): 303–8. http://dx.doi.org/10.5194/ars-9-303-2011.
Повний текст джерелаАнотація:
Abstract. The fact of reduced development time in the automotive sector requires a change in the electromagnetic compatibility (EMC) validation of electronic components. To increase the development time of automotive components, e.g. sensors or electronic control units (ECUs), it is mandatory to verify the EMC behavior of the integrated circuit (IC) itself in an early development stage simultaneous to the development process of the entire ECU into which it is embedded. The conducted IC EMC tests emission as well as immunity is realized with a specific test printed circuit board (PCB) which is built according to the guidelines of the Bosch, Infineon, Siemens VDO Specification (BISS, 2007). The measurement results of these EMC tests are affected by the test PCB itself. To deduce the application requirements of the component from the application circuit of the test PCB it is necessary to consider this influence by the printed circuit board. The text at hand gives an overview on how far the emission results are adulterated by the used test PCB. The presented method also grants a validation of the disturbance voltage directly at the IC pin considering the application circuit.
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Saif, Ullah, Zai Lin Guan, Zong Dong He, Cong He, and Cao Jun. "Modeling of Order Oriented Planning for Printed Circuit Board Assembly Line." Applied Mechanics and Materials 789-790 (September 2015): 1245–51. http://dx.doi.org/10.4028/www.scientific.net/amm.789-790.1245.
Повний текст джерелаАнотація:
Printed circuit board (PCB) assembly planning problem has been given lot of attention to efficiently manage the orders of different PCB products. However, little effort has been paid to describe its comprehensive model which can demonstrate all the planning problems collectively considering in the surface mount technology (SMT) lines. A mixed integer model for PCB assembly line which includes the integration of different levels of the planning problems and considered component allocation problem (line balancing), PCB model sequencing problem (mixed model sequencing problem), feeder arrangement problem and component placement sequencing problem on different SMT machines collectively. Current research is significant to solve different planning problems of the PCB assembly line simultaneously to get the overall global solution of the problem in future.
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Ibrahim, Zuwairie, Ismail Ibrahim, Kamal Khalil, Sophan Wahyudi Nawawi, Muhammad Arif Abdul Rahim, Zulfakar Aspar, and Wan Khairunizam Wan Ahmad. "Noise Elimination for Image Subtraction in Printed Circuit Board Defect Detection Algorithm." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 10, no. 2 (August 5, 2013): 1317–29. http://dx.doi.org/10.24297/ijct.v10i2.7000.
Повний текст джерелаАнотація:
Image subtraction operation has been frequently used for automated visual inspection of printed circuit board (PCB) defects. Even though the image subtraction operation able to detect all defects occurred on PCB, some unwanted noise could be detected as well. Hence, before the image subtraction operation can be applied to real images of PCB, image registration operation should be done to align a defective PCB image against a template PCB image. This study shows how the image registration operation is incorporated with a thresholding algorithm to eliminate unwanted noise. The results show that all defects occurred on real images of PCB can be correctly detected without interfere by any unwanted noise.
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Pan, Pengfei, Yi Han, Hexin Lv, Guoyong Dai, and Zhiyong Jin. "MGPM Methods for Rectangular Single-Size Printed Circuit Board Orthogonal Packing Problems." Mathematical Problems in Engineering 2022 (October 12, 2022): 1–17. http://dx.doi.org/10.1155/2022/2224820.
Повний текст джерелаАнотація:
Printed circuit board (PCB) orthogonal packing problems derive from the massive circuit board production process in the electronic industry. In the early stage, it mainly relied on human experiences to make decisions on how to make the most of each sheet while meeting customers’ orders. Up till now, researchers in enterprises and academic circles are still trying to explore effective mathematical models and feasible optimization methods. In most cases, what PCB companies generally face is the orthogonal layout decision, which considers positioning each rectangle PCB piece (PCB-P) on a rectangle sheet board (panel) in an ideal way so that each panel has the minimal remains with the most PCB-Ps. In this paper, multi-round gradual packing methods (MGPMs) are proposed based on the idea of combinatorial optimization and dynamic programming. MGPMs include the depth priority-based method (MGPM-DP) and breadth priority-based branch-and-prune method (MGPM-BC). The former has the advantage of finding better solutions, while the latter has the advantage of consuming short computational time. Through extensive computational tests on real data from a PCB production enterprise in China, both MGPM-DP and MGPM-BC have achieved noticeable and satisfactory results compared with the simplex method, dynamic programming method, and a widely used industrial software (Yuanbo) in China.
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Yunardi, Riky Tri, Moh Zakky Zulfiar, Rr Wanda Auruma Putri, and Deny Arifianto. "Design and Implementation of Solder Paste Dispenser Based on Linear Drive System." JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) 3, no. 2 (November 13, 2019): 338. http://dx.doi.org/10.21070/jeee-u.v3i2.2637.
Повний текст джерелаАнотація:
In the technology to create prototypes for electronic hardware is usually constructed using surface mount device printed circuit board (SMD PCB). In this paper introduces the design and implementation of low-cost electrical solder paste dispenser that supports the PCB solder process. The design consists of a nozzle and linear drive systems based on stepper motors operating with electric power to push the plunger down to drop the solder paste on the board. To test the performance of solder paste that has been designed verified by experiment. Solder paste dispenser design was tested using SMD resistor with the solder pads of different sizes for R0603, R0805, and R1206 on PCB. The results showed that the design of the prototype was able to put the pasta in various field pads between 0.54 mm2, 0.91 mm2 and 1.44 mm2 for standard solder pads with an error in the 2% - 5%. Based on the results, the device has been shown to potentially be used to attach electronic components to printed circuit boards.
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Shi, Pei, Yuyang Zhang, Yunqin Cao, Jiadong Sun, Deji Chen, and Liang Kuang. "DVCW-YOLO for Printed Circuit Board Surface Defect Detection." Applied Sciences 15, no. 1 (December 31, 2024): 327. https://doi.org/10.3390/app15010327.
Повний текст джерелаАнотація:
The accurate and efficient detection of printed circuit board (PCB) surface defects is crucial to the electronic information manufacturing industry. However, current approaches to PCB defect detection face challenges, including large model sizes and difficulties in balancing detection accuracy with speed. To address these challenges, this paper proposes a novel PCB surface defect detection algorithm, named DVCW-YOLO. First, all standard convolutions in the backbone and neck networks of YOLOv8n are replaced with lightweight DWConv convolutions. In addition, a self-designed C2fCBAM module is introduced to the backbone network for extracting features. Next, within the neck structure, the C2f module is substituted with the more lightweight VOVGSCSP module, thereby reducing model redundancy, simplifying model complexity, and enhancing detection speed. By enhancing prominent features and suppressing less important ones, this modification allows the model to better focus on key regions, thereby improving feature representation capabilities. Finally, the WIoU loss function is implemented to replace the traditional CIoU function in YOLOv8n. This adjustment addresses issues related to low generalization and poor detection performance for small objects or complex backgrounds, while also mitigating the impact of low-quality or extreme samples on model accuracy. Experimental results demonstrate that the DVCW-YOLO model achieves a mean average precision (mAP) of 99.3% and a detection speed of 43.3 frames per second (FPS), which represent improvements of 4% and 4.08%, respectively, over the YOLOv8n model. These results confirm that the proposed model meets the real-time PCB defect detection requirements of small and medium-sized enterprises.
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Zhang, Kai. "Using deep learning to automatic inspection system of printed circuit board in manufacturing industry under the internet of things." Computer Science and Information Systems, no. 00 (2023): 20. http://dx.doi.org/10.2298/csis220718020z.
Повний текст джерелаАнотація:
Industry 4.0 is currently the goal of many factories, promoting manufacturing factories and sustainable operation. Automated Optical Inspection (AOI) is a part of automation. Products in the production line are usually inspected visually by operators. Due to human fatigue and inconsistent standards, product inspections still have defects. In this study, the sample component assembly printed circuit board (PCB), PCB provided by the company was tested for surface components. The types of defects on the surface of the PCB include missing parts, multiple parts, and wrong parts. At present, the company is still using visual inspection by operators, the PCB surface components are more complex. In order to reduce labor costs and save the development time required for different printed circuit boards. In the proposed method, we use digital image processing, positioning correction algorithm, and deep learning YOLO for identification, and use 450 images and 10500 components of the PCB samples. The result and contribution of this paper shows the total image recognition rate is 92% and the total component recognition rate reaches 99%, and they are effective. It could use on PCB for different light, different color backplanes, and different material numbers, and the detection compatibility reaches 98%.
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Chen, Kun-Nan. "Optimal Support Locations for a Printed Circuit Board Loaded With Heavy Components." Journal of Electronic Packaging 128, no. 4 (February 15, 2006): 449–55. http://dx.doi.org/10.1115/1.2353281.
Повний текст джерелаАнотація:
In the design of printed circuit boards (PCBs), it is preferable to increase their fundamental frequency so as to reduce the effects of the dynamic loading on them. The dynamic characteristics of a PCB carrying various electronic components and modules are most significantly affected by the geometrical and material properties of the bare board and by the boundary conditions supporting the loaded PCB. In this research, a PCB carrying a heavy CPU cooling fan and supported by six fastening screws is investigated by the modal testing and analyzed by the finite element method. After the finite element model of the PCB is verified by the experimental results, the locations of the six supporting screws are optimized to achieve a maximum fundamental frequency for the loaded PCB. The position of each fastening screw can be determined by two design variables, i.e., x and y coordinates. Two cases are studied: the symmetric case (six design parameters) with the symmetric constraint on the support locations imposed, and the asymmetric case (12 design parameters) without the constraint imposed. Finally, verification experiments are performed on the two PCBs supported by screws located at the optimal positions. Although relatively large differences between the calculated, optimized fundamental frequencies and the experimental values are observed, the experiments confirm a very significant improvement in frequency for both cases.
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Chhetri, Shivaji Pandit, Santosh Bhat, Pradeep Timalsina, and Bipin Thapa Magar. "Detection of Missing Component in PCB Using YOLO." International Journal on Engineering Technology 1, no. 1 (December 21, 2023): 62–71. http://dx.doi.org/10.3126/injet.v1i1.60902.
Повний текст джерелаАнотація:
The detection of missing components in printed circuit boards (PCBs) is a critical task in the electronics manufacturing industry. The current practice of manual inspection is time-consuming and prone to human error, which can result in faulty products and increased costs. In this paper, we propose a solution that uses the YOLO (You Only Look Once) object detection algorithm to automatically detect missing electronic components in PCBs. Electronic components detection model is trained using YOLOv3 architecture. Dataset is prepared using high quality printed circuit board images and manual labeling in Label Studio. The model is trained on a dataset of 16 different electronic components commonly found in PCBs including Electrolytic Capacitor, QFP, Toroidal core Inductor, Crystal Oscillator etc. Prepared model recognizes these electronic components with an average map score of 65.8%with IoU 50% and 42.6% with IoU 95%. The results show that the proposed solution can detect the missing components.
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Zheng, L. J., Cheng Yong Wang, Yue Xian Song, L. P. Yang, Y. P. Qu, Ping Ma, and L. Y. Fu. "A Review on Drilling Printed Circuit Boards." Advanced Materials Research 188 (March 2011): 441–49. http://dx.doi.org/10.4028/www.scientific.net/amr.188.441.
Повний текст джерелаАнотація:
Drilling is a particularly complicated machining process, and it becomes much more complicated when the workpiece is printed circuit boards (PCBs). PCB is composite materials with anisotropy. Even a small defect in PCB may cause great losses. Both the drilling process and PCB structure design have been researched by many scholars. But the investigations into the drilling processes of PCB are not systematic. The present review article address the report about tool materials and geometrics, cutting force, cutting temperature, radial run-out and damages occurring in drilling processes. And as a conclusion, some of these critical issues are proposed to meet the challenges in analysis and optimization for PCB drilling.
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Tan, Cher-Ming, Hsiao-Hi Chen, Jing-Ping Wu, Vivek Sangwan, Kun-Yen Tsai, and Wen-Chun Huang. "Root Cause Analysis of a Printed Circuit Board (PCB) Failure in a Public Transport Communication System." Applied Sciences 12, no. 2 (January 10, 2022): 640. http://dx.doi.org/10.3390/app12020640.
Повний текст джерелаАнотація:
A printed circuit board (PCB) is an essential element for practical circuit applications and its failure can inflict large financial costs and even safety concerns, especially if the PCB failure occurs prematurely and unexpectedly. Understanding the failure modes and even the failure mechanisms of a PCB failure are not sufficient to ensure the same failure will not occur again in subsequent operations with different batches of PCBs. The identification of the root cause is crucial to prevent the reoccurrence of the same failure. In this work, a step-by-step approach from customer returned and inventory reproduced boards to the root cause identification is described for an actual industry case where the failure is a PCB burn-out. The failure mechanism is found to be a conductive anodic filament (CAF) even though the PCB is CAF-resistant. The root cause is due to PCB de-penalization. A reliability verification to assure the effectiveness of the corrective action according to the identified root cause is shown to complete the case study. This work shows that a CAF-resistant PCB does not necessarily guarantee no CAF and PCB processes can render its CAF resistance ineffective.
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Wang, Lance. "System I/O Optimization with SoC, SiP, PCB Co-Design." International Symposium on Microelectronics 2019, no. 1 (October 1, 2019): 000013–18. http://dx.doi.org/10.4071/2380-4505-2019.1.000013.
Повний текст джерелаАнотація:
Abstract The increasing complexity of system on chips (SoCs) combined with a new generation of designs that combine multiple chips in a single package is creating new challenges in the design of packages, printed circuit boards (PCBs) and integrated circuits (ICs). The process typically involves three independent design processes – chip, package and PCB – carried out with point tools whose interface requires time-consuming manual processes that are error-prone and limit the potential for reuse. This challenge is being addressed by a new integrated 3D chip/package/board co-design environment that makes it possible to holistically optimize the package, board and IC design to a greater degree than was possible in the past by considering the system-level impact of each design decision. The new co-design approach enables designers to optimize routability via pin assignment and I/O placement to achieve minimum layer counts between chip, package and board. The end result is higher performance.
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Shamkhalichenar, Hamed, Collin J. Bueche, and Jin-Woo Choi. "Printed Circuit Board (PCB) Technology for Electrochemical Sensors and Sensing Platforms." Biosensors 10, no. 11 (October 30, 2020): 159. http://dx.doi.org/10.3390/bios10110159.
Повний текст джерелаАнотація:
The development of various biosensors has revolutionized the healthcare industry by providing rapid and reliable detection capability. Printed circuit board (PCB) technology has a well-established industry widely available around the world. In addition to electronics, this technology has been utilized to fabricate electrical parts, including electrodes for different biological and chemical sensors. High reproducibility achieved through long-lasting standard processes and low-cost resulting from an abundance of competitive manufacturing services makes this fabrication method a prime candidate for patterning electrodes and electrical parts of biosensors. The adoption of this approach in the fabrication of sensing platforms facilitates the integration of electronics and microfluidics with biosensors. In this review paper, the underlying principles and advances of printed board circuit technology are discussed. In addition, an overview of recent advancements in the development of PCB-based biosensors is provided. Finally, the challenges and outlook of PCB-based sensors are elaborated.