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132 articles for “Machining parameters optimization”
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Cognitive AI-Based Quality Control and Operational Optimization of Polymer Composites for Healthcare Applications
Abstract: The use of polymer composite materials in healthcare is on the rise because of their adjustable mechanical characteristics, biocompatibility and structural flexibility. Yet, it is difficult to ensure stable quality of such composites due to process-related defects, heterogeneity of the material and the lack of real-time adaptive control. The proposed study suggests the use of cognitive AI-based framework of quality control and optimization of operation of polymer composite systems which …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 571–591 Read article
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Energy-Efficient Design Strategies for Sustainable Machine Tool Development
Abstract: The design of energy-efficient machine tools is essential for promoting sustainable manufacturing, as it addresses the significant energy consumption and carbon emissions generated by these tools in industrial settings. This study investigates innovative design approaches that enhance energy efficiency, with a focus on lightweight materials, improved drive systems, smart control frameworks, and methods for recovering energy. Implementing lighter structural materials allows machine tools to operate with less force, which in …
Published in Trends in Machine design · Vol. 12, Issue 3, 2025 · pp. 30–34 Read article
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Database-Driven Energy Management in Electric Vehicles
Abstract: With the growing concern over environmental pollution, there is an increasing demand for sustainable and eco-friendly technologies. Among these, electric vehicles (EVs) have emerged as a promising alternative to conventional fossil-fuel-based transportation. However, as EV adoption accelerates, efficient energy management becomes critical to enhance vehicle performance, extend battery life, and ensure overall system reliability. This research presents a Database-Driven Energy Management System (DBEMS) that leverages real-time data from EV components …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 19–24 Read article
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Multi-directional Wind Turbine System Optimisation and Mathematical Modelling for India’s Sustainable Wind Energy Development
Abstract: The global trend towards green energy usage is expanding. Wind power is clean and sustainable and may compete with fossil fuels in the electricity market. This project's manufacturing cost must match fossil fuels or other energy sources to be competitive. The main investment in wind generation is in machinery and infrastructure. Wind power becomes competitive by lowering energy costs through turbine design, building, and operation. Understanding wind turbine activity over …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 1, Issue 1, 2023 · pp. 32–42 Read article
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An effort for maximizing the material removal rate during the wire cutting of difficult to machine Inconel X750 using electric discharge machining process
Abstract: The growing demand for harder materials with exceptional hardness poses a significant challenge for industries as achieving precise machining becomes increasingly tricky. The Inconel family of materials, renowned for their hardness, has been extensively studied. However, with the continuous introduction of new materials, the scope of research remains vast. In this context, Inconel X750, a corrosion and oxidation resistance, nickel-chromium-based alloy with excellent hardness, has gained attention. Despite its significance, …
Published in Journal of Polymer & Composites · Vol. 11, Issue 12, 2023 · pp. 1–17 Read article
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Wear and Tribological Characteristics of Novel Metal Matrix Composites
Abstract: The development of advanced metal matrix composites (MMCs) with enhanced tribological performance has become increasingly important due to the premature failure of critical engineering components operating under severe wear conditions in automotive, aerospace, marine, defense, and power generation systems. Conventional composites such as Copper–Alumina and Aluminium–Silicon Carbide have demonstrated improved mechanical and wear characteristics; however, their widespread application is often limited by issues including particle agglomeration, non-uniform reinforcement distribution, porosity …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1326–1346 Read article
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Parametric Study of Fused Deposition Modelling Process During Fabrication of Acrylonitrile Butadiene Styrene (ABS) Based Injection Molding Die
Abstract: The purpose of this study is to dictate an optimum process parameter during the fabrication of additively manufactured acrylonitrile butadiene styrene (ABS) based injection mold using fused deposition modelling methodology based additive manufacturing process and to assess the quality of the infection mold by analyzing the surface roughness of the injection mold, and the time taken in the manufacturing of the mold. The ABS PRO+ filament is used in manufacturing …
Published in Journal of Polymer & Composites · Vol. 10, Issue 1, 2022 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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Machine Learning Based Optimization of Polymer Structure Property Relationships in Composite Material Systems
Abstract: In modern engineering applications, polymer-based composite materials have garnered a lot of attention because of their lightweight nature, high strength-to-weight ratio, and changing physical features. In order to maximize the relationships between polymer structure and properties in composite materials, this study suggests a strategy based on reinforcement learning (RL). The research utilized the Polymer Composite Properties Dataset, which contains 12,700 records associated with polymer matrices, reinforcement fillers, interfacial bonding characteristics, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 242–255 Read article
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Thermal Performance Analysis and Optimization of Pin-Fin Heat Sink Using CFD, Taguchi Method, and Machine Learning
Abstract: Efficient thermal management is essential for improving the performance and reliability of modern engineering systems and electronic devices. This study presents the design, simulation, and optimization of a pin-fin heat sink using SolidWorks for three-dimensional modeling and ANSYS for thermal and computational fluid dynamics (CFD) analysis. Four different pin-fin geometries, namely square, pentagon, octagon, and circular fins, are considered to evaluate their thermal performance under varying operating conditions. Aluminum is …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Machine Learning Framework for Optimizing Polymer–Metal Oxide Composites as Charge Selective Layers in Perovskite Solar Cells
Abstract: To achieve high-performance and stability of perovskite solar cells (PSCs), it was important to incorporate innovative interfacial materials to tune the balanced charge extraction, low recombination, and enhanced operational lifespan. On this note, polymer composites with metal oxides have been proposed as promising candidates as charge selective layers (CSLs), whereby they present a rare combination of tunable energy levels, improved film forming abilities, and better interface engineering capabilities. In this …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 1073–1098 Read article
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Microstructural Characterisation and Analysis of Mechanical Behaviour of Hybrid AA 7075/7178 Fabricated Using Die Casting Technique
Abstract: AA are being increasingly used in the field of structural engineering owing to their desirable mechanical properties coupled with their recyclable and sustainable nature, thus contributing significantly towards reduction of carbon footprints and development of circular economy. Till date numerous research projects have been prompted to investigate the structural performance of aluminium alloy structures and develop alternatives with enhanced performance parameters. AA 7xxx (Al-Zn-Mg-Cu) are being widely used in variety …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 441–451 Read article
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AI-Driven Prediction of Mechanical and Thermal Properties in Polymer-Based Functionally Graded Composites
Abstract: The proposed architecture of the current paper is an artificial intelligence (AI)-driven model of forecasting mechanical and thermal aspects of polymer-based functionally-graded composites (FGCs). Traditional micromechanical and finite element models, which are practical in homogeneous composites, might not be able to account in nonlinear interaction that is caused by compositional gradient. To overcome the challenge, machine learning (ML) models like artificial neural network (ANN), support vectors regression (SVR), and gradient-boosted …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 70–89 Read article
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Process Parameter Optimization of Magnesium Alloy Material Welded by Friction Stir Welding Using UTM and Taghuchi Approach
Abstract: Welding is a fabrication process where materials are fused together which may similar or dissimilar according to requirement. Welding is a systematic approach where dissimilar and similar materials are welded with an application of heat. Friction stir welding (FSW) is a welding method where metals are converting to a molten phase and with a desirable application of pressure leads to metal joining. FSW is a metal joining process used in …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 381–392 Read article
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Diabetes Risk Prediction from Survey Data Using Machine Learning Algorithms
Abstract: Diabetes mellitus represents one of the most significant global health challenges, affecting millions worldwide and leading to severe complications if left undiagnosed or poorly managed. Early detection and risk assessment are crucial for preventing the progression of this chronic condition. This research presents a comprehensive machine learning approach for predicting diabetes risk using survey-based health parameters. The study implements and compares four prominent classification algorithms: Logistic Regression, K-Nearest Neighbors (KNN), …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Money Laundering Transaction with Machine Learning
Abstract: This study discusses the use of machine learning algorithms to discover firms that are prone to money laundering. The purpose of this research is to develop, describe, and test a machine learning model for determining which bank transactions should be physically scrutinized for money laundering activities. To train a supervised machine learning model, three categories of historical data are required: legitimate "normal" transactions, transactions flagged as suspicious by the bank's …
Published in Current Trends in Information Technology · Vol. 14, Issue 2, 2024 · pp. 1–15 Read article
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Optimization of Production Processes to Minimize Waste and Improve Efficiency in Automobile Servicing Plant Using Lean Six Sigma
Abstract: This study focuses on optimizing production processes within an automobile servicing plant to minimize waste and enhance efficiency through the application of lean six sigma (LSS) methodologies. Utilizing a case study approach, the research addresses real-time challenges related to productivity and waste reduction. Data collection involves assessing machine functionality metrics, material and labor flow at various stages of the servicing process. The optimization strategy integrates lean tools including value stream …
Published in International Journal of Manufacturing and Production Engineering · Vol. 2, Issue 2, 2024 · pp. 47–63 Read article
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Taguchi Method: A New Approach for Evaluating and Optimizing Parameters of TIG Welding
Abstract: The construction and industrial sectors must improve the quality of their welds. An experimental plate fabricated of SS304L was to be tungsten inert gas (TIG) welded in this experiment, and an effort was made to enhance the mechanical properties. The Taguchi L9 orthogonal array was used to organize the experiment, and the mechanism of advancement was used to simulate the performance. The tensile strength of the welded junction rises in …
Published in Journal of Polymer & Composites · Vol. 11, Issue 2, 2023 · pp. 121–129 Read article
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A Comprehensive Study of Sensor and Camera Fusion for Real-Time Parking Space Detection
Abstract: Due to the rapid growth in urban vehicle density, there have been major problems in the effective management of parking space, which has caused congestion, more traveling time, wastage of fuel, and environmental pollution. Conventional parking systems are very ineffective, as they are based on manual surveillance and cannot provide drivers with much real-time information. To overcome these challenges, the present paper explores the design, development, and operation of a …
Published in Trends in Transport Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 1–16 Read article
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Green AI-Enabled Opto-Electronic Communication Systems for Carbon-Neutral Digital Networks
Abstract: The rapid expansion of digital communication infrastructure, driven by cloud computing, Internet of Things (IoT), 6G networks, and artificial intelligence applications, has significantly increased the energy consumption and carbon footprint of modern communication systems. Conventional optical communication networks often rely on static resource allocation and energy-intensive signal processing mechanisms, resulting in inefficient utilization of network resources and elevated operational costs. This study proposes a Green Artificial Intelligence (Green AI)-Enabled Opto-Electronic …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 2, 2026 Read article