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192 articles for “Machining parameters”
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Predictive Maintenance Strategies for Safety-critical Mechanical Systems
Abstract: Ensuring the reliability and safety of industrial systems is essential, especially in high-risk sectors such as aerospace, manufacturing, and energy. Predictive maintenance (PdM) has become a crucial approach for minimizing operational failures and improving maintenance efficiency. This research introduces an advanced PdM framework that enhances industrial safety by integrating Internet of Things (IoT) technology, machine learning (ML), and big data analytics. By enabling real-time monitoring and predictive fault detection, this …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 1, 2025 · pp. 12–17 Read article
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From Differential Equations to Data Science: A Survey on Analytical Methods in Contemporary Problems
Abstract: The integration of differential equations and data science methods represents a dynamic and evolving approach to solving contemporary challenges across a wide range of disciplines, including engineering, physics, biology, economics, and finance. Differential equations have long served as fundamental tools for modeling continuous systems and processes, offering powerful insights into the behavior of natural and man-made phenomena. For example, they describe how heat diffuses through materials, how populations grow in …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 1–6 Read article
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Optimized Machine Learning Framework for Battery State Prediction in Smart Charging Systems
Abstract: Good estimation of battery states, including State-of-Charge (SoC), State-of-Health (SoH), and Remaining Useful Life (RUL), are important in managing energy wisely and controlling the adaptive charging. This work introduces a streamlined machine learning model based on the ability to use multi-dimensional sensor measurements in terms of voltage, current, temperature, and cycle number to forecast battery conditions with high accuracy. Decent preprocessing, such as noise elimination, feature scaling, and calculated features, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 11–23 Read article
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Optimization of EDM Machining Characteristics of Reinforced Aluminium Metal Matrix Composites by Taguchi
Abstract: Aluminium alloys metal matrix composites (AMMC) play a vital role in various industries, such as aerospace and automobiles. This study investigates the machining characteristics of AL8079 - based composites reinforced with 15 wt. % TiB₂ and 5 wt. % MoS₂ using Electrical Discharge Machining (EDM). The machining process was optimized using the L9 orthogonal array (OA) Taguchi - based design of experiments, and input parameters were considered at three levels, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 939–951 Read article
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Machine Learning Assisted Design and Analysis of Polymer Composite Materials for Sustainable Renewable Energy Systems
Abstract: Accurate prediction and optimization of polymer composite properties is of paramount importance in the design of these lightweight, durable, and sustainable materials within renewable energy technologies. This work will provide a holistic machine learning-assisted framework that unites materials informatics with domain-specific features and state-of-the-art ML methodologies in the prediction of the mechanical properties of polymer composites, such as tensile strength. This includes embedding several ensemble models, including Random Forest and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 391–402 Read article
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Use of Artificial Intelligence to Access and Ensure Safe Drinking Water Supply: A Review
Abstract: Ensuring access to safe drinking water is a critical public health challenge. Traditional water quality assessment methods are often labor-intensive and time-consuming. Artificial intelligence offers a promising alternative, providing rapid, accurate, and scalable solutions for monitoring and predicting water quality. This systematic review examines the application of AI. The review highlights various AI models, including artificial neural networks, support vector machines, decision trees, and ensemble methods, in predicting water quality …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 21–28 Read article
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Development and Performance Evaluation of a Multi-Purpose Power Tiller for Small-Scale Farming Applications
Abstract: This project outlines the development and testing of a multi-purpose power tiller tailored for small-scale farmers. Designed to reduce labor and enhance productivity, the machine integrates features for ploughing, seedbed preparation, and lightweight transportation. Key parameters including depth of tillage, working width, and fuel consumption were evaluated during field trials and benchmarked against manual operations. Results highlight its efficiency and potential for improving rural agricultural practices. Along with its primary …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 2, 2026 Read article
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Design and Implementation of the Double Fed Induction Generator in Sliding Mode
Abstract: These days, WECS is crucial to the production of electricity. Variable-speed wind turbines are the most often utilised type of wind turbine (DFIG). However, these machines are sensitive to voltage disturbances because their stator is directly connected to the grid. The oscillations produced in electromagnetic torque, active and reactive power during disturbances could damage the mechanical and electrical parts of the machine. Several control techniques are produced to control these …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 1, Issue 1, 2023 · pp. 11–22 Read article
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Photochemical Materials for Light-responsive Optical Switching: AI-optimized Design of Dynamic Visual Effects
Abstract: This paper presents an in-depth investigation into the design and behavior of photochemical materials that generate optical illusions and dynamic visual effects through light-induced molecular transformations. The study focuses on advanced photoresponsive compounds such as azobenzene and spiropyran derivatives, emphasizing their reversible optical transitions governed by photoisomerization, phase transitions, and photochromism in solid-state and polymeric matrices. Spectroscopic and kinetic analyses are employed to evaluate the influence of light wavelength, material …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 3, Issue 2, 2025 · pp. 13–27 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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Enhancing Cooling Efficiency in Dual Nozzle CO2-Based Vortex Tube Systems for Machining Titanium Alloys: Implications for Polymer and Composite Processing
Abstract: In machining of Titanium alloys, the cutting temperature plays a vital role that directly influences the performance and it is required to maintain as low as possible. In this study, a dual nozzle Vortex Tube Cooling System (VTCS) that supplies cool compressed CO2 gas is developed to reduce the cutting temperature in Ti-6Al-4V machining. The experiments were conducted at constant cutting and flow parameters during turning at different levels of …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 284–291 Read article
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Hybrid Quantum–Machine Learning Framework for Nonlinear Rheological Modeling of Polymer and Composite Materials
Abstract: In polymer and composite materials, a major challenge lies in predicting their nonlinear rheological response, owing to complex multiscale interactions that are not captured by traditional constitutive laws or conventional machine learning approaches. In this study, a hybrid Quantum Machine Learning (QML) model comprising Quantum Support Vector Machine (QSVM) and Quantum Neural Network (QNN) architectures is proposed for viscosity prediction without requiring any specific rheological equation. To train and test …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Biopolymer–Cement Hybrid Panels from Recycled Paper Mill Reject: Experimental Characterisation and Machine Learning Optimization
Abstract: The increased rate of the accumulation of industrial residues in the developing countries is a major cause of concern for the environment. The current study brings forth the use of industrial residues in the form of the production of eco-friendly building materials as a sustainable approach to their valorization. The valorization of recycled paper mill reject, a cellulose-based biopolymeric industrial residue, is being addressed in this study as a reinforcement …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 67–90 Read article
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Advanced Micromachining with Abrasive Jet Machining: Experimental Observations and Model Comparisons
Abstract: Abrasive Jet Machining (AJM), also known as Micro Blast Machining, is a non-traditional machining process that removes material through the erosive action of a high-velocity gas jet carrying fine abrasive particles. This process is particularly effective for machining intricate shapes in hard and brittle materials that are heat-sensitive and prone to chipping. Similar to sandblasting, AJM is widely utilized for tasks such as deburring, rough finishing, and micromachining, especially in …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 Read article
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Influence of EDM Process Parameters on MRR and TWR on Mild Steel and Cast Iron using Taguchi’s Method
Abstract: An alternative to conventional machining methods, Electrical Discharge Machining (EDM) uses electrical current for generating controlled sparks that erode surface of the material through thermal energy. Unlike traditional cutting processes, hard and electrically conductive materials with high precision can be machines very easily, which make it suitable for applications in tool and die manufacturing, aerospace, and automotive industries. Tool Wear Rate (TWR) and Material Removal Rate (MRR) for mild steel …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 614–627 Read article
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Review paper on concrete mix design optimization using machine learning based algorithm
Abstract: Concrete is an essential part of most construction works in civil engineering. The mix design of concrete is usually specified in terms of prescription or performance-based approach. One of the most important procedures is proportioning the concrete mix, which requires taking several safety precautions to get the proper amounts of elements like cement, aggregate, water, and admixtures. The current study offers a thorough analysis of the Artificial Neural Networks (ANN) …
Published in Journal of Polymer & Composites · Vol. 12, Issue 3, 2024 · pp. 311–320 Read article
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Analysis of Machine Learning in Metal Processing: A Novel Prospect
Abstract: Metal is processed by a wide range of procedures, from forming and casting to machining and riveting. Metal processing is a crucial part of modern manufacturing. The application of machine learning (ML) is driving a significant change in the sector, which has historically depended on empirical knowledge and trial-and-error techniques. Increased production, improved product quality, and resource optimization are expected outcomes of this action. This study aims to explore the …
Published in Journal of Materials & Metallurgical Engineering · Vol. 16, Issue 1, 2026 · pp. 40–51 Read article
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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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Sensors-Based Electric Machine Design for Industry
Abstract: The integration of advanced sensors is fundamentally changing the economics and reliability of electric machines. It moves design focus from minimizing material cost and adhering to conservative standards toward maximizing operational availability and energy efficiency. In the industry of tomorrow, the electric motor will not be a passive collection of coils and steel, but a self-diagnosing, self-optimizing, and perhaps even self-healing asset—a sentient motor—driven by its highly refined sixth sense, …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 1–10 Read article
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A Comparative Study of different Techniques to predict Maternal Morbidity and Mortality Model
Abstract: Artificial intelligence (AI) encompasses a range of techniques, including machine learning and deep learning, which are increasingly utilized in the healthcare sector for tasks such as disease diagnosis and drug discovery. To achieve accurate disease diagnosis through AI, it is essential to integrate data from multiple medical sources, including ultrasound imaging, magnetic resonance imaging (MRI), mammography, genomics, and computed tomography (CT) scans, among others. This article presents a comprehensive review …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 1, 2025 Read article