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49 articles for “Defect Prediction”
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An AI-Driven IoT Framework for Autonomous Quality Assurance in Optical Lens Manufacturing
Abstract: The evolution of high-precision optics—ranging from smartphone micro-lenses to high-end astronomical glass—demands unprecedented accuracy in manufacturing. Traditional inspection methods, reliant on manual sampling or static automated optical inspection (AOI), often fail to bridge the gap between high-speed production and the detection of microscopic surface aberrations. This paper introduces an integrated architecture combining the Internet of Things (IoT) and Deep Learning-based decision-making systems to revolutionize lens quality control. By deploying an …
Published in International Journal of Optical Innovations & Research · Vol. 4, Issue 1, 2026 · pp. 36–41 Read article
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Predictive and Degradation Analysis in the Life-Cycle of Monocrystalline and Multicrystalline Photovoltaic Modules using Electroluminescence Imaging & Monitoring Studies
Abstract: AbstractSolar Technology is the cynosure of all eyes in this global era. With major thrusts towards decarbonization, improving the overall efficiency of Solar Modules is the most coveted thing in this arena. The efficiency of a Solar panel ranges between 18-25 % when it is in good working condition. There are several causes of the efficiency decreasing further. A solar panel is susceptible to a lot of damages, ranging from …
Published in Journal of Semiconductor Devices and Circuits · Vol. 7, Issue 2, 2020 · pp. 23–27 Read article
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Reduction of Shrinkage-Porosity Defects in Sand Casting Using Finite Element Analysis: A Review
Abstract: Today production of casting is easy but market requirement is quality casting. Earlier casting is made with large no. of defects due to large no. of process parameter in casting process. Specially, to predict phase transformation is very critical. As the problem of automation in process, shortage of skill labour now a days; casting simulation requirement is high and it is identifies defects earlier without making actual casting. This process …
Published in Journal of Materials & Metallurgical Engineering · Vol. 6, Issue 1, 2016 · pp. 1–5 Read article
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Sand Casting Process Optimization via Design of Experiments: A Review
Abstract: Designing and optimizing of gating is an essential part of casting foundry as it contributes significantly to predict and minimize the flow turbulence resulting to casting defects like rough surface, sand inclusion, etc. An Optimization scheme for gating design parameters for casting was proposed with different past studies of the researches. Various designs were modeled and mould filling simulation rooted to minimize turbulence and macro defects are recommended in this …
Published in Trends in Machine design · Vol. 4, Issue 3, 2017 · pp. 1–4 Read article
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Fracture Toughness in Advanced Materials: A Comparative Review of Testing Methods and Standards
Abstract: Fracture toughness is a key material property used to assess a material's ability to resist crack propagation, which is vital for ensuring the reliability and durability of structures and components in high-performance applications. It is particularly important in advanced materials such as composites, ceramics, and high-strength alloys, which are increasingly used in demanding industries such as aerospace, automotive, and civil engineering. Fracture toughness testing helps determine the material's behavior under …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 1, 2025 · pp. 17–21 Read article
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An Efficient LoRa-Enabled Fault Detection Using Self-Powered IoT Device
Abstract: This study describes a revolutionary internet of things (IoT) solution for effective defect detection in a variety of applications. By utilizing an IoT device that generates energy from the surroundings, the suggested solution gets around the drawbacks of conventional battery-operated gadgets. The suggested approach makes use of a self-sustaining IoT gadget that can capture energy from the surroundings to get beyond the drawbacks of conventional battery-powered IoT devices. Longer functioning …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 1–13 Read article
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Conceptualization of An Intelligent Decision Framework for Control Factors and Weld Quality Prediction
Abstract: To improve the robot's welding quality, control welding precision, optimize welding parameters, realize continuous welding quality database optimization, and increase welding defect detection, a fuzzy neural network-based intelligent decision-making system must be built. This study demonstrates how fuzzy control theory and BP neural networks may be used to identify welding issues and enhance process variables. The experimental findings indicate that, with seam classification accuracy close to 90%, enhancing welding parameters …
Published in Journal of Polymer & Composites · Vol. 11, Issue 6, 2023 · pp. 10–19 Read article
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Heart Disease Evaluation Through Echocardiography Using CNN, ResetNet50, VGG16, and Image Processing
Abstract: Heart conditions stand out as primary contributors to untimely mortality among adults aged 30 and above, notably among those grappling with elevated cholesterol levels and diabetes. Detecting such ailments often necessitates the use of an echocardiogram, providing an intricate portrayal of the heart. However, precise analysis hinges on both the proper functioning of the echocardiogram apparatus and the proficiency of a skilled radiologist, a condition not always met. Manual scrutiny …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 2, 2024 · pp. 25–35 Read article
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Machine Learning Optimization for VARTM Carbon Polymer Laminates
Abstract: Vacuum-assisted resin transfer moulding (VARTM) is a key low-cost, out-of-autoclave process for manufacturing large-scale carbon-fibre reinforced polymer (CFRP) laminates crucial to aerospace wings, wind-turbine blades, marine hulls, and automotive structures. Unpredictable resin flow often leads to voids, dry spots, and race-tracking defects, resulting in 27.9% scrap rates and lengthy, costly trial-and-error design cycles. Although surrogate models provide rapid impregnation predictions for simple flat-plate geometries, vision-based monitoring is limited to idealized …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 229–245 Read article
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A Review on Digital Twin Technology in Robotics
Abstract: Digital Twin (DT) technology has emerged as a transformative concept in robotics and automation, enabling virtual representation of physical systems, real-time monitoring, and performance optimization. This review explores the foundations of Digital Twin, its integration in robotic systems, key enabling technologies, applications, current challenges, and future research directions. The paper concludes by highlighting how Digital Twin transforms design, control, prediction, and human-robot collaboration.Digital Twin technology is transforming the field of …
Published in International Journal of Manufacturing and Production Engineering · Vol. 4, Issue 1, 2026 · pp. 10–15 Read article
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Microvita as a Fermi-Boson Hybrid Quantum Excitation: A Statistical Pathway Toward Unified Physics, Chemistry, and Biological Organization
Abstract: This article reformulates Microvita as a hybrid quantum excitation that interpolates continuously between fermionic and bosonic statistical behavior. A generalized operator algebra, a dynamical statistical order parameter, and a Lorentz-covariant field equation are used to frame Microvita as an effective unification scheme rather than a mere philosophical construct. The formalism predicts renormalization-group flow between infrared fermionic and ultraviolet bosonic limits, while numerical profiles suggest vacuum-energy smoothing and topological-defect suppression in …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 17, Issue 1, 2026 · pp. 115–122 Read article
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A Study on the Use of AI and Sensors in Aerospace
Abstract: The synergistic combination of modern sensors including artificial intelligence (AI) has significantly changed the aeronautics industry's ongoing quest for increased safety, efficiency, and autonomy. The examination of the critical role these technologies play throughout the whole aerospace lifecycle from design and production to flight operations and maintenance is examined in this research. The eyes and ears of contemporary aircraft, sensors give an unparalleled amount and quality of real-time data about …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 25–34 Read article
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Artificial Intelligence for Polymer and Nanocomposite Materials: Performance Prediction, Manufacturing Optimization, and Future Perspectives
Abstract: The exceptional mechanical properties, design flexibility, and lightweight nature of polymer composite and nanocomposite materials make them indispensable in a wide range of applications, including aerospace, automotive, construction, biomedical, and energy sectors. The optimization of the strength, durability, and manufacturing efficiency of polymer composite and nanocomposite materials is highly challenging because their performance depends on matrix composition, reinforcement type, fiber or nanoparticle distribution, interfacial interactions, processing conditions, and environmental factors. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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ALADIN and its Protein Interactions with the Nucleoproteins: An Insilico Analysis
Abstract: The nuclear pore complex (NPCs) are big, protein complexes made up of multiple units that traverse the nuclear envelope (NE), establishing a discerning channel between the cytoplasm and nucleus for the nucleocytoplasmic transport. It has different roles in cellular processes, like cell-cycle progression, control of gene expression, and signal transduction. NPC is a vast and complex structure, compiled from almost 30 proteins, termed nucleoporins. Earlier studies have shown that each …
Published in Research and Reviews : Journal of Computational Biology · Vol. 7, Issue 1, 2018 · pp. 28–31 Read article
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Trends and Applications of Artificial Intelligence in Mechanical Engineering: A Review
Abstract: Artificial Intelligence (AI) has become a revolutionary force across various fields, including mechanical engineering, where it is redefining traditional approaches to design, manufacturing, maintenance, and overall system optimization. This review aims to provide a comprehensive introduction to AI and explore its diverse applications within the domain of mechanical engineering. The study begins with a foundational overview of AI, including key concepts such as machine learning, neural networks, deep learning, and …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 3, 2025 · pp. 30–35 Read article
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Digital Transformation of Urban Infrastructure with the Help of AI Guardians
Abstract: The construction industry continues to face challenges related to quality control, safety protocols, and meeting project deadlines. These issues often result in significant cost overruns and project delays. Traditional inspection and site management approaches rely heavily on manual work and individual judgment. As a result, human errors can easily occur, and these methods provide only limited snapshots of site conditions over time. This paper presents a comprehensive framework that uses …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 16–25 Read article
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Intelligent Failure Detection in Biomedical Composite Materials Using Machine Vision
Abstract: The biomedical composite materials are intelligent failure-detecting, which is necessary to ensure the reliability, safety, and durability of the current healthcare equipment. This paper describes a machine vision design, which incorporates convolutional neural networks, transformer models, and ensemble learning to correctly detect and localize material defects. The proposed system takes advantage of the capabilities of high-resolution imaging, advanced preprocessing software, and deep feature learning in the identification of the intricate …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Overview of Ionic Polarization: A Model Based Novel Approach
Abstract: This study presents a comprehensive analysis of ionic polarization through a novel model-based approach that integrates theoretical, computational, and experimental methodologies. Ionic polarization, which significantly influences the dielectric properties of materials, is examined through the lens of the Clausius-Mossotti equation and the Debye relaxation model, providing a theoretical framework for understanding the relationship between ionic displacement and dielectric behavior. To explore ionic displacement and polarization at the atomic level, advanced …
Published in International Journal of Cheminformatics · Vol. 2, Issue 2, 2024 · pp. 18–25 Read article
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Multi-Objective Optimization of Polymer-Based Functionally Graded Composites for Lightweight Structures
Abstract: Functionally graded composites (FGCs) improve lightweight structural performance by allowing material properties to change smoothly across a component. Polymer-based FGCs (P-FGCs), in particular, are gaining prominence in aerospace, automotive, and biomedical industries due to their excellent strength-to-weight ratio, tunability, and ease of processing. However, optimizing these materials for lightweight structural applications requires addressing conflicting design objectives, such as maximizing stiffness while minimizing weight or enhancing thermal resistance while maintaining manufacturability. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 961–973 Read article
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Modeling and Acoustic Analysis of Noise Vibration in Automotive Gearbox by Non-destructive Testing
Abstract: A gearbox is used for transferring power from the engine to the wheels. Predicting the vibration and noise radiation from a dynamic system like a gearbox gives designers an insight early in the design process. It was conducted experimental and modeling of vibration and noise for magnitude and pressure level variations in a Peugeot 206 automotive 5-speed gearbox. It was extract vibration data related to different periodic processing and then …
Published in Journal of Experimental & Applied Mechanics · Vol. 11, Issue 3, 2020 · pp. 54–63 Read article