Search
116 articles for “machining stability”
-
Finite Element, Experimental, and Machine Learning-Based Optimization of Machining Stability for Polymer Composite Material Processing
Abstract: The machining of polymer composite materials, particularly fibre-reinforced polymer-matrix composites, requires stable spindle-tool performance to avoid delamination, fibre pull-out, matrix cracking, thermal softening, poor surface integrity, and premature tool wear. In line with the scope of the Journal of Polymer & Composites, this study presents an integrated finite element, experimental, and machine learning framework for improving machining stability during end-milling of composite material systems. The spindle-tool assembly is modelled using …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
Optimization of Machining Parameters of EN-27 Material Using Wire Electric Discharge Machining (WEDM)
Abstract: The optimization of Wire Electrical Discharge Machining (WEDM) parameters for EN-27 alloy steel, a high-strength material widely utilized in mechanical and structural applications, is the subject of this study's methodical analysis. Due to its hardness and poor machinability by conventional methods, WEDM is preferred for achieving precise dimensional accuracy and surface integrity. The primary objective of this work is to enhance machining performance by identifying optimal process parameters influencing Material …
Published in Journal of Production Research & Management · Vol. 16, Issue 1, 2026 · pp. 32–36 Read article
-
Periodic Turing Machines
Abstract: AbstractIt is proved that in comparison with Turing machines, inductive Turing machines represent the next step in the development of computer science providing better models for contemporary computers and computer networks. In particular, it is proved that simple inductive Turing machines can solve the Halting Problem for Turing machines, while inductive Turing machines of higher orders can generate and decide the whole arithmetical hierarchy. It means that inductive Turing machines …
Published in Journal of Computer Technology & Applications · Vol. 5, Issue 3, 2014 · pp. 6–18 Read article
-
Enhancing Chatter Resistance in Deep Hole Boring Through Modified Tool Design: A Study on Impact of Length-To-Diameter (L/D) Ratio
Abstract: Deep hole boring is a specialized machining process crucial for creating precise bores with high length-to-diameter (L/D) ratios, particularly vital in aerospace, automotive, and oil and gas industries. The L/D ratio is pivotal for stability and performance. Chatter, a detrimental vibration phenomenon, is a significant concern in deep hole boring, influenced by the L/D ratio. Higher L/D ratios increase chatter, leading to poor surface finish and reduced tool life. Longer …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 2, Issue 2, 2024 · pp. 24–33 Read article
-
A Review on Optimization of Surface Roughness during Dry Turning Operation of AISI 1045 Steel
Abstract: It is a well-known fact that manufacturing industries are repeatedly challenged for attaining higher productivity and high-quality products in order to stay competitive. The preferred shape, size and finished ferrous and non-ferrous materials are usually produced through turning with the help of cutting tools that moved past the work piece in a machine tool. From the various cutting processes, turning process is one of the most important and most applied …
Published in Journal of Automobile Engineering and Applications · Vol. 4, Issue 3, 2017 · pp. 31–38 Read article
-
Process Variable Optimization and Experimental Review of Aero-engine Blade using ECM
Abstract: AbstractProcess of blade in (EMC) can be effected by numerous factors, e.g., shape of blade, electrolytic liquid field and anodic dissolution, ECM parameters may result in affections on blade accuracy. Some aero-engine blade as research object, five main process parameters, voltage, machining gap, feed rate, temperature of working fluid and pressure variation of electrolyte inlet/outlet, are evaluated and optimized as per BP neural network Method. From 3125 possible operating parameter …
Published in Recent Trends in Sensor Research & Technology · Vol. 5, Issue 3, 2018 · pp. 27–32 Read article
-
A PWM Based Series Compensator for Power System Performance Enhancement
Abstract: Enhancement of power system stability through a relatively new FACTS device named pulse width modulated series compensator (PWMSC) in the transmission line has been investigated in this article. The three-phase PWMSC is realized with a simple pulse width modulated (PWM) AC link converter consisting of four force-commutated switches and a three-phase diode bridge. The PWMSC is modeled as a continuously controllable series capacitive reactance in the transmission line of a …
Published in Journal of Power Electronics and Power Systems · Vol. 6, Issue 1, 2016 · pp. 12–25 Read article
-
Entomo-Analytics: Insect Behavioral Intelligence for Climate-Smart Environmental Monitoring Systems
Abstract: Rapid environmental change driven by climate variability, urbanization, and ecological degradation has intensified the need for innovative monitoring systems capable of providing real-time ecological intelligence. Traditional environmental monitoring methods often rely on satellite imaging and stationary sensors, which may lack fine-scale biological sensitivity. In contrast, insects—due to their abundance, ecological diversity, and rapid responsiveness to environmental shifts—offer a powerful yet underutilized source of bio-sensing data. This paper introduces the concept …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 17–26 Read article
-
Regression and ANN Models in Predicting Tool Wear
Abstract: A modern machining system must be able to detect tool wear while milling in order to maintain the product's surface quality. The vibration signatures produced by a single point cutting tool during machining have been found to be good predictors of the tool's health. The current study used Artificial Neural Networks to forecast tool life by analysing vibration signatures when turning EN9 and EN24 steel alloys (ANN). Tool wear prediction …
Published in Journal of Production Research & Management · Vol. 12, Issue 1, 2022 · pp. 14–18 Read article
-
Transfer Learning in Deep Learning Models for Medical Imaging: Utilizing Pretrained Models to Improve Performance in Medical Image Analysis
Abstract: Transfer learning is now a trending technique in deep learning, especially in medical imaging. This technique solves landmark problems by utilizing the pre-trained models, including the limited availability of the annotated medical data and the time-consuming computational costs of training deep learning models from scratch. The generalizability of deep models could increase diagnostic precision for specific medical tasks, require fewer samples to train, and take less time to train due …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 67–85 Read article
-
The Convergence of AI and Composites - A Review Anchored in Patent Trends
Abstract: The integration of artificial intelligence (AI) and machine learning (ML) techniques is revolutionizing the design, analysis, and optimization of polymer (PC/FRP), metal (MC), and ceramic matrix composites (CC). Techniques such as artificial neural networks (ANN), deep learning (DL), genetic algorithms (GA), and physics-informed machine learning (PIML) are employed to enhance property estimation, process optimization, and predictive modeling. These AI-driven frameworks enable virtual testing, application-specific material design, and real-time decision-making, while …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 182–198 Read article
-
A Comprehensive Investigation of Bagging-Based Ensemble Methods for Improving Machine Learning Model Robustness
Abstract: Machine learning models such as Decision Trees, Logistic Regression, and K-Nearest Neighbors are widely used for classification tasks due to their simplicity and interpretability. However, these models often suffer from high variance, overfitting, and poor generalization when applied to real-world datasets, particularly those that are small, noisy, or imbalanced, as commonly encountered in healthcare, finance, and cybersecurity applications. To address these limitations, this research proposes a Bagging (Bootstrap Aggregating)-based ensemble …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 24–34 Read article
-
Failed Component Image Acquisition Quality Optimization for Machine Vision System
Abstract: AbstractWith the rapid development of the global semiconductor industry, electronic products are required to have new ideas, diversified functions, and thinness and shortness. The ball grid array (BGA) packaging technique arranges solder balls in a matrix mode on the bottom of the component substrate, so as to increase the functional density. The dye stain test is extensively used for array component failure analysis; however, the operation takes time and extends …
Published in Current Trends in Signal Processing · Vol. 10, Issue 2, 2020 · pp. 17–25 Read article
-
Fortifying the Blockchain Fortress: A Machine Learning Paradigm for Enhanced Security
Abstract: Blockchain technology has emerged as a revolutionary tool in the digital landscape, enabling secure and transparent transactions across a decentralized network. Despite its robust security features, blockchain systems remain vulnerable to anomalies and malicious activities. The detection of these anomalies using machine learning has become essential for protecting blockchain networks and ensuring their integrity. This project delves into the application of machine learning techniques to detect abnormal patterns within blockchain …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 33–40 Read article
-
State Space Modeling and Robust Wind Power Generation System
Abstract: AbstractAs producing power from renewable energy is increasing, facing new problems emerging from this phenomenon is becoming a good challenge for power system engineers. One of these problems is the dynamic and transient stability of such systems when they are connected to a power network. In this paper, a variable speed cage machine wind generation system is considered as the case study. The concept of power system stabilizer, which has …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 8, Issue 2, 2017 · pp. 24–39 Read article
-
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
-
Aerodynamic Optimization of UAV Wings Using Machine Learning
Abstract: Unmanned Aerial Vehicles (UAVs) are increasingly deployed across defense, transportation, agriculture, and environmental monitoring, demanding improved aerodynamic efficiency to enhance endurance, stability, and payload capacity. Traditional aerodynamic optimization approaches, relying on computational fluid dynamics (CFD) simulations and wind tunnel experiments, are often time-consuming and computationally expensive. This study proposes a machine learning (ML)-driven framework for the aerodynamic optimization of UAV wing geometries, aiming to significantly reduce design cycles while improving …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 1–7 Read article
-
Wireless Biosensing Polymer Composites for Smart Healthcare Devices
Abstract: The wireless biosensing polymer composites have been found as one of the possible solutions in developing flexible, real-time and intelligent healthcare monitoring systems. Biomimic polymer matrices coupled with conductive nanomaterials can be used to design an understanding of physiological signals (strain, pressure, and temperature) that are highly sensitive and adaptable sensors. The attachment of these sensors to wireless communication systems, such as the Bluetooth Low Energy and Wi-Fi, eases the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 14, 2026 Read article
-
Personality and Behavior Identification Based on Handwriting Analysis
Abstract: Graphing is the process of identifying, evaluating, and understanding a person's personality traits through handwritten patterns. The accuracy of handwriting analysis depends on the skill of the analyst, it is expensive and prone to errors. The proposed approach is therefore focused on building a system that can predict personality traits with the help of machine learning without human intervention. In this project, 657 authors' handwritten samples were taken as datasets. …
Published in Journal of Communication Engineering & Systems · Vol. 12, Issue 1, 2022 · pp. 42–54 Read article
-
Enhance Thermal and Conductive Properties through Graph Neural Network-Based Machine Learning-Driven Advanced Polymer Material Design
Abstract: Advanced polymer materials are widely used in modern engineering and manufacturing because of their lightweight nature, flexibility, durability, and adaptability to different applications. However, designing polymer materials with enhanced thermal and electrical properties remains a challenging task. The performance of polymers is influenced by a complex combination of molecular structures, filler materials, processing parameters, and nanoscale interactions. Conventional optimization methods often require extensive experimental trials and computational resources, making it …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 386–407 Read article