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192 articles for “Machining parameters”
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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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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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Quantitative Image-Based Assessment of Degradation Patterns in Polymer-Based Medical Implants
Abstract: Polymer-based medical devices are widely used in clinical practice, where long-term material degradation can compromise performance and patient safety. Traditional polymer degradation studies predominantly rely on laboratory-based experiments, which often fail to capture real-world operational and usage conditions. In this study, a multimodal, data-driven framework is proposed for the quantitative assessment of degradation patterns in polymer-based medical devices using publicly available clinical failure data. Structured operational parameters, including cumulative usage …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1510–1518 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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Intelligent Aquaculture System for Fish Disease Detection Using Machine Learning
Abstract: Aquaculture is one of the key factors for global food security, but fish diseases bring about heavy economic losses and jeopardize sustainability. One of the most important aspects of global food security is aquaculture, but fish infections endanger sustainability and cause significant financial losses. Early diagnosis is not possible since traditional disease detection techniques are laborious and necessitate expert intervention. To effectively detect fish infections, this study suggests an Intelligent …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 2, 2025 · pp. 30–37 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
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Evaluating UX Design Factors Affecting Efficiency of Composite Material Design and Analysis Platforms
Abstract: Within engineering software platforms that involve the design, simulation and characterization of composite materials, user experience (UX) design has become a key determinant for efficient use. This research aims to quantify how user experience design parameters relate to productivity in composite engineering workflows by analyzing the relationship between usability, learnability, accessibility, complexity of the UI, navigation efficiency and users engineering results satisfaction. Computational techniques in python were used in the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 341–366 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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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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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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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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ML-Based Predictive Modeling of Mechanical Properties in 3D-Printed Polymer Composites for IoT Applications
Abstract: This study aims to develop an interpretable and high-accuracy machine learning framework for predicting the mechanical properties of 3D-printed fiber-reinforced polymer composites, with a focus on structure–property correlations relevant to polymer processing and functional performance. Composite specimens based on PLA and ABS matrices were fabricated using FDM with varying weight fractions (5–20 wt%) of carbon and glass fibers. Standardized mechanical testing (ASTM D638, D256, D790) was performed to evaluate tensile …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 61–78 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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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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Investigation of Robotic Transverse Twin-Wire GMAW for Large-Scale Wire-Arc Additive Manufacturing Applications
Abstract: Bulk metal additive manufacturing using wire-arc processes has gained significant attention for fabricating large-scale engineering components due to their high deposition rate and material efficiency. In this study, the feasibility and performance of robotic transverse twin-wire gas metal arc welding (GMAW) for bulk wire-arc additive manufacturing (WAAM) is systematically assessed. The research focuses on understanding arc stability, weld bead characteristics, and process–product relationships under high-deposition conditions. Welding current signals from …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 4, Issue 1, 2026 · pp. 36–50 Read article
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Lightweight Models for Per-PC Energy Consumption Forecasting: Comparative Study with ML and DL Approaches
Abstract: We have collected primary data from automated logging of parameters like CPU utilization, estimated power, active or idle state, user logging activity, and the type of day. Additionally, survey data showed user awareness, energy-saving behaviour, and PC usage patterns. The data is pre-processed and merged by applying processes such as data cleaning, normalization, and feature extraction, i.e., determining the peak active timings and downtime. Developed lightweight prediction models based on …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 17, Issue 1, 2026 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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Mechanical Testing Under Tensile-load
Abstract: Mechanical testing is a technique used to establish a material's mechanical qualities by examining its strength, toughness, hardness, and other characteristics. Specimens produced of various materials whose qualities need to be examined are used to verify this property. In which a static load is applied and a dynamic load is applied, and the test is completed. Understating loads in mechanical testing is the topic of this research article. Any manufacturing …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 1, 2025 · pp. 1–10 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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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