Search
192 articles for “Machining parameters”
-
Machine Learning Approach to Predict the Performability and Emissions of Diesel Engine Fueled with Doped Biodiesel Blend
Abstract: Enhancing the performability and emission characteristics of diesel engines has been a difficult task in light of growing concerns about global warming and other negative effects, as diesel accounts for 70% of global energy demand. In this study, engine performance and exhaust emissions for various fuel blends were thoroughly evaluated using machine learning techniques to predict engine emission and performance behavior. We focused on biodiesel blend and nanoparticle additive concentration …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 1–12 Read article
-
Structure–Property Modeling of Cement-Based Multi-Component Composites Using Ensemble Machine Learning and Explainable Feature Attribution
Abstract: Accurate prediction of compressive strength is central to structure–property optimization, quality control, and sustainability-driven design in cement-based composite materials. Cementitious systems represent heterogeneous multi-phase composites composed of reactive binder matrices and dispersed aggregate phases, whose macroscopic mechanical performance emerges from complex nonlinear interactions among constituents and curing-dependent microstructural evolution. This study develops a data-driven structure–property modeling framework to quantify the nonlinear dependence of compressive strength on multi-component composite composition and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 112–131 Read article
-
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
-
ML-Driven Optimization Framework for the Analysis, Design, and Development of Efficient Wireless Power Transfer Systems for EV Charging
Abstract: The fast uptake of electric vehicles (EVs) has heightened the necessity of effective, dependable and convenient charging systems. The Wireless Power Transfer (WPT) systems can be taken as a potential solution as they allow charging cells without contact, without any risks, and without any overcrowding; the efficiency of the system is strongly influenced by the alignment of coils, the fluctuations of air-gaps, the conditions of the loads, and geometrical arrangements …
Published in International Journal of Manufacturing and Production Engineering · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
-
Machine Learning Techniques for Predicting Industries Based on Region
Abstract: In recent years, there has been a growing interest and emphasis on agricultural land preparation and its implementation among researchers, primarily due to various factors. These factors include an increased focus within the research community, a rising demand for agricultural land, and the significance of assessing soil health for ensuring robust crop production. Picture request is one such philosophy for soil and land prosperity examination. It is a staggering measure …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 1, 2023 · pp. 1–8 Read article
-
Performance Analysis of Deep CNN Architectures
Abstract: A Convolutional Neural Network (CNN) is an artificial neural network renowned for its remarkable ability to handle large image datasets effectively, particularly excelling in tasks such as image recognition and classification. The fundamental structure of a CNN relies on mathematical convolution operations, comprising essential components such as convolutional layers, activation functions, pooling layers, and fully connected layers. These components work synergistically to extract and learn hierarchical features from input data, …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
-
Application-Driven Rule-Based Framework for Lubrication Failure Modes in Industrial Systems
Abstract: Modern lubricants increasingly rely on polymer-based composites, integrating synthetic base oils, polymer thickeners and solid additives like MoS₂ and PTFE for high-performance applications. These formulations not only enhance thermal and mechanical stability but also enable low-friction operation across diverse industrial conditions. Lubrication-related failures represent a critical cause of unplanned downtime and reduced reliability in industrial machinery. This paper presents an application-driven, rule-based framework designed to assess and mitigate lubrication failure …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 522–531 Read article
-
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
-
Heat Transfer by Arc Welding for A Similar Material Joint
Abstract: Electric arc welding (EAW) is a traditional fabrication process used in wider domestic, commercial and industrial application. Welding is a joining of two materials with the application of heat at the molecular level with the application of heat and pressure. Many materials used for welding application for different joining process. Maraging steel is special steel used for production of different air-craft components. Maraging material is used for heavy tools, producing …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 2, 2025 · pp. 1–13 Read article
-
Jowar Millet Crop Monitoring and Analysis Robot (JMAR): A Smart Solution for Plant and Soil Health in Jowar Millet Farming
Abstract: Farmers cultivating jowar millet (Sorghum) face significant challenges in maintaining crop health and optimizing yield due to the limitations of traditional plant disease detection and soil health assessment methods. Visual inspection and indigenous knowledge are labour-intensive, time-consuming, and often inaccurate, while soil monitoring requires specialized equipment that is not always affordable or accessible. These issues hinder timely intervention and can lead to crop losses and soil degradation. To address these …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 2, 2025 · pp. 8–18 Read article
-
Graphene Based Electronic Skin for Wearable Health Monitoring and Human– review on Machine Interaction, Materials, Structures and AI Integration
Abstract: Graphene-based electronic skin (e-skin) has emerged as a transformative technology for next-generation wearable health monitoring and advanced human–machine interaction (HMI). Owing to its outstanding electrical conductivity, mechanical flexibility, atomic-scale thickness, and biocompatibility, graphene enables the fabrication of ultrathin, conformal, and multifunctional sensors capable of mimicking the sensory functions of natural human skin. Over the past decade, research in this domain has progressed rapidly across four interconnected fronts: material synthesis and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
AI Approaches in Gait and Posture Analysis: A Review
Abstract: This review synthesizes current research on the application of artificial intelligence (AI) in gait and posture analysis, focusing on methodologies, algorithms, and clinical applications. It examines the use of machine learning (ML) and deep learning (DL) techniques to extract relevant features from sensorderived data, offering objective, and automated assessments that surpass traditional methods. A systematic literature review was conducted, analyzing studies that utilized AI for gait and posture analysis with …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 1–3 Read article
-
Experimental Investigation of Boron Carbide Reinforced Al-Mg-Si Alloy Nano Composites by the Stir Casting Method Using Machine Learning Algorithm
Abstract: For the purpose of this experiment, Al-Mg-Si alloys were manufactured with the use of the stir casting process with a metal mold. The alloys had different weight percentages of nano boron carbide, which ranged from 0 to 4% by weight. The intervals between the percentages were 0.5. Following that, the microstructural and mechanical parameters of the as-cast alloy and the nano composites were compared and contrasted according to ASTM Standards …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1766–1779 Read article
-
Feature Extraction and Analysis of Bearing Faults: A Review
Abstract: One of the most important steps in identifying bearing problems is feature extraction. In order to provide a more meaningful dataset, it entails locating and extracting pertinent features from raw bearing vibration signals. Tasks involving categorization and prediction can then make use of these attributes. In many practical applications, such as monitoring rotating machinery or electronic components, the raw signals collected (e.g., vibration, current, temperature) are often complex, high-dimensional, and …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 20–28 Read article
-
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
-
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
-
Optimization of Process Parameter in 3D Printing to Minimize Wear Loss and increase Tensile Strength
Abstract: Additive Manufacturing (AM) and especially Fused Deposition Modeling (FDM) has emerged as a very versatile process of manufacturing polymer components with complex and highly-integrated geometries. Polylactic Acid (PLA) is a favorite of the many thermoplastic FDM materials because of its biodegradability, easy processing and predictable mechanical properties. The study aimed at maximizing critical parameters in FDM process in order to reduce wear loss and also increase tensile strength of PLA …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 849–858 Read article
-
Neurodevelopmental Effects of Cell Tower Radiation in Children: A Longitudinal Study
Abstract: This study investigates the impact of radiation exposure from cell phone towers on the neurodevelopmental outcomes of children aged 0–5 years. A prospective cohort approach was employed to assess key developmental parameters, including Gross Motor Skills, Fine Motor Skills, and sleep disorders. Given the increasing presence of wireless communication infrastructure, understanding its potential effects on early childhood development is crucial for public health.To analyze the collected data, advanced machine learning …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 2, 2025 Read article
-
AI-Driven Optimization of Biopolymer Composite Formulations Using IoT Data Streams
Abstract: Biodegradable polymer composites have emerged as a sustainable alternative to petroleum-based materials in packaging, biomedical, and structural applications. However, traditional formulation techniques for reinforced polymer composites often lack precision and fail to adapt to real-time variations during processing, resulting in suboptimal material performance. This research proposes a real-time AI-IoT-enabled framework to optimize biopolymer composite formulations. The goal is to intelligently tune composite properties such as mechanical strength, moisture resistance, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 85–100 Read article
-
Thermal Interaction Analysis Between Flexible Magnetic Abrasive Brush and Aluminium Alloy During Single-Pole MAF
Abstract: Magnetic Abrasive Finishing (MAF) is a precision surface‐finishing approach that employs magnetic abrasive particles (MAPs) within a managed magnetic field to eliminate micro-level material and enhance surface condition. In the finishing process, the friction created between the workpiece and the flexible magnetic abrasive brush (FMAB) leads to heat accumulation, which may badly affect the surface integrity. This study focuses on investigating the temperature distribution at the FMAB–workpiece interface to decrease …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1906–1918 Read article