A printed circuit board (PCB) functions as a substrate essential for interconnecting and securing electronic components. Its widespread integration is evident in modern electronic devices, spanning computers, cell phones, televisions, digital cameras, and diverse apparatus. Ensuring product quality mandates meticulous defect inspection, a task exacerbated by the heightened precision of contemporary circuit boards, intensifying the challenge of defect detection. Conventional algorithms, hampered by inefficiency and limited accuracy, fall short of usage benchmarks. In contrast, PCB defect detection algorithms rooted in deep learning hold promise for achieving heightened accuracy and efficiency, bolstered by their adeptness at discerning novel defect types. This review presents a comprehensive analysis of machine vision-based PCB defect detection algorithms, traversing the realms of machine learning and deep learning. It commences by contextualizing and elucidating the significance of such algorithms, followed by an extensive exploration of their evolution within the machine vision framework, encompassing classification, comparison, and analysis of algorithmic principles, strengths, and weaknesses. Moreover, the introduction of widely used PCB defect detection datasets and assessment indices enhances the evaluation of algorithmic performance. Currently, the detection accuracy can exceed 95% at an Intersection over Union (IoU) of 0.5. Lastly, potential future research directions are identified to address the existing issues in the current algorithm. These directions include utilizing Transformers as a foundational framework for creating new algorithms and employing techniques like Generative Adversarial Networks (GANs) and reinforcement learning to enhance PCB defect detection performance.

A Comprehensive Review of Deep Learning-based PCB Defect Detection

Cavitation refers to the phenomenon of generating bubbles in water or other liquids. The collapse of cavitation bubbles will have a strong impact on the surrounding materials. Therefore, people have developed the technology of using cavitation bubbles to conduct the surface processing of materials. Laser induced cavitation is one of the multiple methods to generate cavitation bubbles. Laser induced cavitation has the advantages of strong controllability, good spherical symmetry, no mechanical deformation and precise positioning, so it is widely used in many fields, such as medical, aerospace, etc. In surface processing, cavitation bubble induced by laser in water or other liquids impacts the sample surface and causes it to strengthen or deform. In this paper, the current research status of laser induced cavitation surface processing is reviewed. The principle of laser cavitation surface processing and the model proposed by predecessors are summarized. It is considered that laser cavitation surface processing affects the mechanical properties of sample through three procedures: plasma impact, cavitation bubble collapse impact and water-jet impact. The influences of machining parameters on the impact process and impact effect are discussed and analyzed, especially the dynamic change of cavitation bubbles and the mechanical properties of sample surface. The effects of laser cavitation surface processing on micro-structure, surface morphology, hardness and strength are described. At last, the development of laser cavitation technology is summarized and prospected. As a mean to improve the mechanical properties and change the morphology of components, laser cavitation surface processing has a great development potential and a good development prospect in many fields. 

Progress in applications of laser induced cavitation on surface processing

In recent years, infrared thermographic (IRT) technology has experienced notable advancements and found widespread applications in various fields, such as renewable industry, electronic industry, construction, aviation, and healthcare. IRT technology is used for defect detection due to its non-contact, efficient, and high-resolution methods, which enhance product quality and reliability. This review offers an overview of active IRT principles. It comprehensively examines four categories based on the type of heat sources employed: pulsed thermography (PT), lock-in thermography (LT), ultrasonically stimulated vibration thermography (UVT), and eddy current thermography (ECT). Furthermore, the review explores the application of IRT imaging in the renewable energy sector, with a specific focus on the photovoltaic (PV) industry. The integration of IRT imaging and deep learning techniques presents an efficient and highly accurate solution for detecting defects in PV panels, playing a critical role in monitoring and maintaining PV energy systems. In addition, the application of infrared thermal imaging technology in electronic industry is reviewed. In the development and manufacturing of electronic products, IRT imaging is used to assess the performance and thermal characteristics of circuit boards. It aids in detecting potential material and manufacturing defects, ensuring product quality. Furthermore, the research discusses algorithmic detection for PV panels, the excitation sources used in electronic industry inspections, and infrared wavelengths. Finally, the review analyzes the advantages and challenges of IRT imaging concerning excitation sources, the PV industry, the electronics industry, and artificial intelligence (AI). It provides insights into critical issues requiring attention in future research endeavors.

Progress in Active Infrared Imaging for Defect Detection in the Renewable and Electronic Industries

Nanosecond pulsed laser processing is an efficient method of processing carbon fiber reinforced plastic(CFRP), which is widely used in the manufacturing field of aviation, medical, and auto industries. The anisotropic heat transfer of carbon fiber is a key factor degrading the surface integrity of laser processing CFRP. So it is urgent to explore the significant mechanism of anisotropic heat transfer of laser interacting with CFRP. A novel numerical model considering anisotropic heat transfer was established to analyze heat transfer and thermal damage of CFRP laser machining. By comparison of simulation and experiments, the average error of ablation depth and width ranges from 4.71% to 15.09%, so the model could precisely simulate the CFRP laser machining. It demonstrates that the heat conductivity along the axial carbon fiber is higher than that along the radial, resulting in an elliptical ablation morphology. And when the laser scanning direction is parallel to the direction of the carbon fiber, deeper and narrower microgrooves can be obtained. In addition, laser processing at the edge of the CFRP plate causes serious heat accumulation, leading to severe thermal damage. The simulation and experiments were conducted to explore the effect of parameters including laser energy, scanning speed, and scanning space on the depth and width of laser ablation. A deeper micro-channel with a smooth machined surface and small thermal damage was obtained when laser energy E = 0.275 mJ, scanning speed v = 630 mm/s, and scanning space h = 21 μm. 

Study on anisotropic heat transfer and thermal damage in nanosecond pulsed laser processing of CFRP

Due to the brittleness of silicon, the use of a diamond wire to cut silicon wafers is a critical stage in solar cell manufacturing. In order to improve the production yield of the cutting process, it is necessary to have a thorough understanding of the phenomena relating to the cutting parameters. This research reviews and summarizes the technology for the precision machining of monocrystalline silicon using diamond wire sawing (DWS). Firstly, mathematical models, molecular dynamics (MD), the finite element method (FEM), and other methods used for studying the principle of DWS are compared. Secondly, the equipment used for DWS is reviewed, the influences of the direction and magnitude of the cutting force on the material removal rate (MRR) are analyzed, and the improvement of silicon wafer surface quality through optimizing process parameters is summarized. Thirdly, the principles and processing performances of three assisted machining methods, namely ultrasonic vibration-assisted DWS (UV-DWS), electrical discharge vibration-assisted DWS (ED-DWS), and electrochemical-assisted DWS (EC-DWS), are reviewed separately. Finally, the prospects for the precision machining of monocrystalline silicon using DWS are provided, highlighting its significant potential for future development and improvement.

Recent Advances in Precision Diamond Wire Sawing Monocrystalline Silicon

Carbon fiber reinforced plastic (CFRP) is widely applied to aviation, medical, and motorbike industry fields, thanks to its excellent performances of mechanical properties and corrosion resistance. Nanosecond pulsed laser is an efficient method for machining microchannels and holes in CFRP plates. The anisotropic heat transfer of CFRP leads to a complex mechanism of laser machining under different scanning directions (0°, 30°, 45°, 60°, 90°). A numerical model considering heterogeneity and anisotropy of nanosecond laser processing CFRP was established by COMSOL Multiphysics. By comparison of simulation and experiments under different scanning directions, the deviation of microchannel width between simulation and experimental ranges from 5.01% to 16.99%. The ablation mechanism of laser processing CFRP under different scanning directions was investigated. It demonstrates that the width of the heat affected zone (HAZ) and ablation increases with the scanning angle increasing, while decreasing with the scanning speed increasing. In addition, when compared to the scanning direction of 90°, the processing efficiency increases by 55.36%, while the width of the HAZ decreases by 55.01% when compared to the scanning direction of 0°. An optimal laser scanning speed of 630 mm/s is used to obtain the open hole with minimal HAZ and thermal damage. 

Investigation on heat transfer and ablation mechanism of CFRP by different laser scanning directions

Structures with multiple deformation paths provide a promising platform for robotics and reprogrammable mechanical and thermal deformation materials. Reconfigurations with a multi-path can fulfill many tasks (e.g., walking and grasping) and possess multiple properties (e.g., targeted Poisson’s ratio and thermal expansion coefficient). Here, we proposed a new ring-like kirigami structure and theoretically and experimentally found that for a basic unit, there are four discrete deformation patterns and a continuous shearing deformation pattern; thus, there are a large number of discrete deformation patterns for a multi-unit combination with geometrical compatibility coupled with a shearing deformation mode. Moreover, targeted Poisson’s ratios (either + or -) in the x- and y-directions can be realized by inversely designing the geometrical parameters for a certain deformation path. Additionally, we showed the capability of constructing 2D and 3D cellular structures in various patterns with the proposed ring-like units. The multiple deformation modes demonstrated here open up avenues to design new reprogrammable materials and robots across various scales.

Continuous and Discrete Deformation Modes of Mechanical Metamaterials With Ring-Like Unit Cells

Precisely regulating thermal deformation behavior of wire electrical discharge machining thin-wall fin via pulsed laser-induced shockwave

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Shichuan Wei

Author Tools

Chat about Author