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132 articles for “Machining parameters optimization”
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Exploring the Impact of Process Parameters on 3D Printing: A Comprehensive Review for Enhanced Product Quality
Abstract: Rapid developments in 3D printing technology have dramatically changed a wide range of industries, from consumer products and healthcare to automotive and aerospace. 3D printing is a process of manufacturing where material is deposited layer over layer which are previously deposited to provide the design shape to the desired products. This process has eliminated the numerous machining processes which were required to manufacture the products previously. The modification of process …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 975–996 Read article
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Optimization of Tensile and Flexural Properties of PETG Filament in FDM 3D Printing Using Response Surface Methodology
Abstract: Now a days manufacturing trend has been changed from subtractive to additive. In additive manufacturing (3D Printing), layer by layer deposition occurs and final product can be obtained. The main advantages of additive manufacturing is to obtain customized product, complex geometry product. This research investigates the optimization of tensile and flexural Strength of PETG filament in Fused Deposition Modeling (FDM) 3-d printing by using of Response Surface Methodology (RSM). Specimens …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 39–58 Read article
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Innovating Sustainably: The Role of Generative Design in Sustainable Technology Development
Abstract: As industries strive for sustainability, generative design has emerged as a transformative approach in engineering, offering solutions that minimize environmental impact while optimizing product performance. Based on established features, including material, size, weight, and performance standards, generative design generates an immense amount of design options using machine learning and artificial intelligent algorithms. Unlike traditional design, which relies on human intuition, generative design automates the exploration of solutions, ensuring material efficiency, …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 3, Issue 1, 2025 · pp. 39–45 Read article
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Effect of Drilling Process Parameters on Surface Roughness of LM6/B4C/Fly Ash Hybrid Composites
Abstract: This research seeks to assess the effect of process variables such as feed rate (FR), spindle speed (SS), drill material (DM) and reinforcement (R%) on surface roughness (SR) when drilling LM6/B4C/Fly ash hybrid composites. The stir casting process was used to fabricate the LM6/B4C/Flyash hybrid composites utilizing LM6 aluminum alloy as the matrix material and B4C/Fly ash as strengthening materials. Experiments were carried out using an L18 orthogonal array (OA) …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 898–906 Read article
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Mechanical Strength Prediction of Nano-Silica Concrete Composites Using Machine Learning Techniques
Abstract: Nano-silica, or nanosilica, refers to silicon dioxide nanoparticles, which are a kind of silica (SiO₂) with diameters that often fall below 100 nanometers. This nanomaterial has attracted considerable attention because of its distinctive characteristics and diverse array of uses, notably in augmenting the performance of materials such as concrete. The integration of nanoparticles with cementitious matrix in nano-silica concrete offers a viable approach to improving the mechanical characteristics and longevity …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 963–973 Read article
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Adaptive Routing Protocol to Optimize the Quality of Service of MANET Using Neural Network
Abstract: A MANET is a group of mobile nodes that create a temporary network without relying on centralized administration or standard supporting devices, often functioning as a conventional network. These dynamic environments present significant challenges for traditional routing and switching protocols, particularly in delivering Quality of Service (QoS) benchmarks such as bandwidth, latency, packet delivery ratio, and robustness. This study proposes an Adaptive Routing Protocol (ARP) leveraging Neural Network (NN) techniques …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 3, 2025 · pp. 01–09 Read article
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Wear Attribute of Aluminium Metal Matrix Composite Reinforced With MWCNT, Produced By FSP, On A Vertical Milling Machine
Abstract: The exceptional properties of Aluminium metal matrix composites (AMMCs) like good hardness, specific strength, enhanced wear rate made huge demand in the automobile and aerospace industries. The classical methods of manufacturing AMMCs leave problems at the interface of matrix and reinforcement segregation, like an agglomeration of reinforcements, wettability etc. To overcome this, an alternate, innovative method of fabricating aluminium matrix surface composites has been invented, which is termed friction stir …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 525–539 Read article
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Integrate AI and IoT to Develop Sustainable Polymer Structural Materials Processing Optimization: Enabled Monitoring Strategies for Performance and Lifecycle Assessment
Abstract: The need for long-lasting structural polymer materials that are both environmentally friendly and highly mechanically effective is driving demand for these materials as the industrial sector continues to grow. Optimizing processes, saving energy, detecting faults, and monitoring structures are all hindered by conventional polymer manufacture. This study suggests an AI-IoT system for environmentally friendly production of structural polymer materials to get around these problems. Tools for evaluating system performance and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 169–192 Read article
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ML Analysis of Factors Affecting Vaccination in Rural Children: A Machine Learning Approach
Abstract: Vaccination remains one of the most effective public health interventions for preventing childhood diseases, yet rural regions in India continue to experience uneven immunization coverage due to multiple socioeconomic and geographic barriers. This research applies machine learning techniques to identify and analyze the major determinants influencing childhood vaccination uptake in rural communities. The study utilizes survey-based demographic, socioeconomic, and healthcare-related parameters to build predictive models that classify children as vaccinated …
Published in International Journal of Vaccines · Vol. 3, Issue 2, 2026 Read article
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Prevention of Water Overflows and Leakages at MPCOE Campus
Abstract: Water is one of the fundamental necessities of human life, essential for a wide range of daily activities. People rely on water for drinking, cleaning, cooking, irrigation, and industrial processes. To meet these needs, water is often pumped from ground storage to overhead tanks. However, the use of non-automated switches to operate pumping machines can lead to significant issues, such as water overflow and unnecessary electricity consumption. The proposed system …
Published in Journal of Water Resource Engineering and Management · Vol. 12, Issue 1, 2025 · pp. 43–51 Read article
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Optimization of Pesticide Requirement Calculations for IoT-Operated Hexacopter Delivery Systems
Abstract: The integration of Internet of Things (IoT) technology into precision agriculture has transformed pesticide application strategies, enabling resource-efficient and environmentally sustainable practices. This study presents a computational methodology for optimizing pesticide requirements in an IoT-operated hexacopter system, designed for dynamic, data-driven pesticide delivery. Leveraging a fusion of real-time telemetric data from onboard LiDAR, multispectral imaging sensors, and environmental monitoring modules, the system employs predictive analytics and edge computing to calculate …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 08–14 Read article
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Transformer Health Monitoring System
Abstract: Rising demands for reliable and efficient power distribution in modern electric control grid increasingly call up for robust monitoring systems for critical substructure. Being a vital part of the power conduction system, transformer are subjected to mechanical, electrical, and environmental stresses, which, if not properly controlled, can cause failures. In this project, we propose a Transformer Health Monitoring System (THMS) using machine learning (ML) models and real-time monitoring method to …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 1–9 Read article
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AI for Cybersecurity: Deploying Machine Learning for Network Traffic Anomaly Detection
Abstract: The growing sophistication of cyberattacks and the growth of network traffic necessitate sophisticated anomaly detection methods. This study overviews the use of artificial intelligence (AI) and machine learning (ML) to counter these challenges, as noted in current studies. It analyses supervised learning (SVM, Decision Trees), unsupervised learning (K-means, DBSCAN), and deep learning (CNNs, RNNs, Auto-encoders) approaches, considering their strengths and weaknesses. The research integrates current developments in AI/ML-based network anomaly …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article
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Kinetics of Crystallization and Microstructural Evolution of Commercial Fluorophlogopite Machinable Glass- Ceramics in the System SrO∙4MgO∙Al2O3∙ 6SiO2∙2MgF2 with Varying in B2O3
Abstract: Glass materials based on fluorophlogopite stoichiometry with varying concentrations of B₂O₃ were synthesized using the melt-casting method, followed by heat treatment at different crystallization temperatures. The resulting glass and glass–ceramic samples were characterized using differential thermal analysis (DTA), scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier-transform infrared (FT-IR) spectroscopy. Kinetic analysis revealed that the activation energies required for the formation of glass–ceramics were 192.77 kJ mol⁻¹ and 210.47 kJ …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 12, Issue 3, 2025 · pp. 1–16 Read article
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IoT-Based Industrial Safety Management Systems
Abstract: The integration of the Internet of Things (IoT) in industrial safety management has transformed workplace safety by enabling real-time monitoring, predictive analytics, and automated hazard mitigation. IoT-Based Industrial Safety Management Systems utilize interconnected sensors, wearable devices, and intelligent analytics platforms to proactively detect and respond to potential risks in high-risk environments such as manufacturing, oil and gas, and construction. These systems continuously monitor critical safety parameters, including temperature, pressure, gas …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 1, 2025 · pp. 18–22 Read article
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Machine-Learning-Assisted Development of Polymer-Biochar Composite Adsorbents for the Removal of Heavy Metals from Gomti River Water
Abstract: Rapid urbanization, industrial discharge, and agricultural runoff pose a significant threat to freshwater sustainability and public health. Within these ecosystems, polymer pollutants—such as microplastics, nanoplastics, synthetic fibres, and additive residues—have emerged as persistent vectors capable of adsorbing and transporting toxic heavy metals. Because these polymeric contaminants dynamically interact with conventional aquatic parameters to alter pollutant mobility and ecological risk profiles, there is an urgent need to transition from passive environmental …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 72–95 Read article
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Experimental Validation and Implementation Framework for Optimized Methane Yield Prediction in Anaerobic Digestion
Abstract: The correct validation and realistic application of optimized anaerobic digestion (AD) models are essential steps in transferring biogas production systems to real-life. This paper outlines an experimental validation and deployment pipeline of an AI-optimized model of the methane yield prediction model based on the application of more advanced machine learning and Bayesian optimization methods. Others The validated surrogate-assisted optimization model was tested with controlled laboratory-scale AD experiments at optimized operating …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 25–32 Read article
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Quasar: Quantum-Accelerated Sustainable Anomaly Recognition in Climate Systems
Abstract: Accurate detection of climate anomalies is vital for disaster alleviation and policy making in a sustainable manner, but customary detection methods face the challenges of computational inefficiency and physical inconsistency. In this study, we propose a novel approach called Quantum-Optimized Fuzzy Physics-Informed Neural Networks (QFuzzy-PINNs), which integrates quantum computing, fuzzy logic, and physics-informed deep learning. As a first step, we employ quantum annealing for conventional optimization to adjust multiple Gaussian …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 18–27 Read article
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Influence of Nozzle Temperature, Nozzle Diameter, and Layer Height on Tensile and Hardness Characteristics of 3D Printed CF-PLA
Abstract: This research investigates the mechanical characterization of CF-PLA (Carbon Fiber-reinforced Polylactic Acid) composite material produced using Fused Deposition Modeling (FDM) technology. The study investigates the impact of different machine parameters, like nozzle temperature, nozzle diameter, and layer height, on the tensile property and hardness of CF-PLA specimens. A total of 27 samples were produced, each with different combinations of nozzle temperature (190°C, 200°C, and 210°C), nozzle diameter (0.4mm, 0.5mm, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 674–681 Read article
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Symmetry Breaking in Mathematical Models: Bifurcation, Chaos, and Pattern Formation
Abstract: Symmetry breaking serves as a central organizing principle in the understanding of nonlinear systems across physics, biology, chemistry, and engineering. When a system transitions from a symmetric state to an asymmetric configuration, it often signals the onset of new structures, dynamic behaviors, or even chaotic regimes. This review explores symmetry breaking from the theoretical and mathematical perspectives of bifurcation theory, chaos theory, and pattern formation. We discuss how small parameter …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 2, 2025 · pp. 25–30 Read article