Search
116 articles for “machining stability”
-
Review and analysis of the Programmable Tungsten Inert Gas Welding Machine
Abstract: The purpose of this study is to examine metal inert gas (MIG) and tungsten inert gas (TIG) welding processes. This study focuses on welding defects with various kinds of AISI- 1020 mild steel welding joints when using metal inert gas (MIG) and tungsten inert gas (TIG). The impact of different process variables on mild steel welding was looked into. In this study, the main process parameters were changed, and destructive …
Published in International Journal of Manufacturing and Production Engineering · Vol. 4, Issue 2, 2026 Read article
-
Development of 3D Printing Filaments from Industrial Waste Plastics
Abstract: The global plastic waste crisis has prompted innovative approaches to sustainable material reuse, particularly in additive manufacturing. Simultaneously, the accumulation of plastic waste presents significant environmental concerns. Recycling plastic into filament supports eco-friendly innovation and brings us closer to a circular economy where materials are reused instead of thrown away. This study investigates the development of 3D printing filaments from industrial waste plastics, including polypropylene (PP), acrylonitrile butadiene styrene (ABS), …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 1, 2025 · pp. 12–17 Read article
-
Integrated Computational and Bio-catalytic Transformations: DFT-Guided Mechanistic Insights, Machine Learning, and Nano-biocatalyst Engineering for Sustainable Catalysis
Abstract: Computational catalysis has emerged as a transformative scientific discipline that integrates quantum chemistry, molecular modeling, machine learning, and density functional theory (DFT) to understand catalytic mechanisms and design highly efficient catalytic systems for sustainable industrial applications. The increasing global demand for environmentally responsible chemical manufacturing has accelerated research on advanced catalytic materials including transition metal catalysts, metal–organic frameworks (MOFs), homogeneous catalysts, heterogeneous systems, and bimetallic catalysts involving nickel and iron. …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 2, 2026 · pp. 36–44 Read article
-
Adaptive Neuro-Fuzzy Inference System (ANFIS) Control for Total Harmonic Distortions Reduction of Multi-Pulse STATCOM
Abstract: In this paper proposed ANFIS System is adapted for controllable mitigation of Total harmonic distortions of STATCOM with Multiple pulse technology. Integrated power electronics device, Gate Turn Off (GTO) is used in switching mode with Voltage source convertor during application of distinct load conditions. The proportional and integrated Controller is replaced by a smart fuzzy logic controller that offers great support for harmonic mitigation by redefining the electrical magnitudes of …
Published in Journal of Mechatronics and Automation · Vol. 9, Issue 2, 2022 · pp. 17–31` Read article
-
Intelligent Automated Guided Vehicle (AGV) System for Optimized Material Handling
Abstract: This project is the development of an Automated Guided Vehicle (AGV) system that has been developed to handle materials in the high-accuracy, reliability, and efficiency in industrial settings. The AGV is a combination of a blend of advanced technologies including sensor fusion, real-time path planning, and AI-based navigation to allow smooth and intelligent operation with minimal human intervention. The vehicle is able to efficiently identify, and evade obstacles by using …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
-
Soft Computing Based Prediction of Deviator Stress of Waste Plastic Reinforced Sand
Abstract: In the recent past, the soft computing techniques have received a significant attention for solution of the geotechnical stability problems. Following the trend, the present study tries to explore the use of different soft computing techniques such as random forest regression, support vector machines (SVM) RBF kernel, SVM poly kernel and M5P model tree for the prediction of deviator stress of sand reinforced with waste plastic strips. The deviator stress …
Published in Journal of Geotechnical Engineering · Vol. 6, Issue 3, 2019 · pp. 1–7 Read article
-
Intelligent Automated Guided Vehicle (AGV) System for Optimized Material Handling
Abstract: This project is the development of an Automated Guided Vehicle (AGV) system that has been developed to handle materials in the high-accuracy, reliability, and efficiency in industrial settings. The AGV is a combination of a blend of advanced technologies including sensor fusion, real-time path planning, and AI-based navigation to allow smooth and intelligent operation with minimal human intervention. The vehicle is able to efficiently identify, and evade obstacles by using …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 1–7 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
-
Integrative Structural-Functional Genomics of Fc and Fab: Precision Models for Monoclonal Antibody Stability and Anti-Aggregation Engineering
Abstract: Monoclonal antibodies (mAbs) represent the cornerstone of biotherapeutics, yet aggregation propensity compromises up to 50% of candidates during development, driven by Fab hypervariability and Fc vulnerabilities.(1,2) This review integrates functional genomics from OAS (4B+ sequences)(5) and structural databases (SAbDab: 10K+ structures)(6) with machine learning models achieving R=0.97 for SAP prediction.(11) We dissect biophysical mechanisms, benchmark predictive tools (DeepSP, ESM2), and engineering strategies (YTE, FW mutations) that enhance Tm by 5-10°C …
Published in International Journal of Molecular Biotechnological Research · Vol. 4, Issue 1, 2026 Read article
-
Carbon capture using polymer based membranes: A green solution to climate change
Abstract: Growing concerns over greenhouse gas emissions have intensified the search for efficient and eco-friendly carbon capture technologies. This study explores the potential of innovative polymer-based membranes as a sustainable approach to controlling CO2 emissions. The paper outlines the fundamental mechanisms of gas transport in membranes, reviews recent advancements in polymer material design, and examines various membrane configurations suited for industrial applications. Special attention is given to newly developed high-performance polymers …
Published in International Journal of Membranes · Vol. 2, Issue 2, 2025 · pp. 13–18 Read article
-
Machine Learning-Assisted Design and Optimization of Lightweight Polymer Composites for IoT-Enabled Automotive Applications
Abstract: This study aims to develop an integrated machine learning and optimization framework for the intelligent design of lightweight polymer composites suited for IoT-enabled automotive applications. The goal is to enhance material performance while satisfying multiple design constraints such as mechanical strength, thermal stability, and process compatibility. A curated dataset of polymer composite formulations was used to train a Random Forest Regression (RFR) model capable of predicting tensile strength, thermal conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 12–27 Read article
-
Damping Power System Oscillations using Fuzzy based Power System Stabilizer with Seven and Nine Linguistic Variables
Abstract: Low-frequency oscillations are created in a power system due to insufficient damping. Low-frequency oscillations in a power system can be damped using conventional power system stabilizer (CPSS) or fuzzy-based power system stabilizer (FLPSS). The performance of FLPSS is significantly affected by the number of linguistic variables used in designing FLPSS. In this paper, FLPSS is designed to damp the low frequency oscillations in a power system. The novelty of the …
Published in Trends in Electrical Engineering · Vol. 4, Issue 3, 2014 · pp. 35–40 Read article
-
Federated Learning for Energy Management in Next Generation Smart Cities
Abstract: Federated learning has emerged as a promising approach for addressing the challenges of energy management in next-generation smart cities. This decentralized approach to machine learning allows collaborative model training among distributed data sources, while safeguarding data privacy and security. In this study, we explore the application of federated learning techniques to optimize energy consumption, enhance grid stability, and promote sustainability in smart city environments. By aggregating data from diverse sources …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 1, 2024 · pp. 19–27 Read article
-
Self-Healing Structural Polymer Composites Incorporating Bio-Inspired Nanofillers
Abstract: Self-healing polymer composites become an attractive family of intelligent materials that are capable of autonomously repairing damage, which will enhance their durability, reliability and service life in extreme engineering applications. The materials are based on the principles of nature, using the nanofillers that are derived from biological systems to improve mechanical properties and self-healing capabilities by utilizing hierarchical structures and multifunctional interface interactions. The recent developments on the formulation of …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
Drug Discovery and Design: Focus on computational approaches used in the discovery and design of new drugs
Abstract: Computational approaches have revolutionized the field of drug discovery and design, offering efficient and cost-effective strategies for identifying and developing new therapeutics. This review article explores the application of computational methods in drug discovery, with a focus on virtual screening techniques, molecular docking, molecular dynamics simulations, and quantitative structure-activity relationship (QSAR) models. Virtual screening plays a crucial role in narrowing down large chemical libraries by utilizing ligand-based and structure-based approaches. …
Published in Research and Reviews : Journal of Computational Biology · Vol. 12, Issue 1, 2023 · pp. 26–30 Read article
-
A Threshold-Weighted Mathematical Fusion Model for Epidemic Outbreak Prediction Using SEIR Residual Dynamics and Cloud-Based Machine Learning
Abstract: Accurate prediction of epidemic outbreaks is critical for effective public health management, resource planning, early warning generation, and timely intervention by municipal authorities. Traditional compartmental models such as Susceptible–Exposed–Infectious–Recovered (SEIR) offer valuable epidemiological insights and mathematical interpretability; however, they may not adequately capture the complex nonlinear relationships present in real-world urban health systems. Conversely, data-driven machine learning techniques can identify hidden patterns in large datasets but often lack epidemiological structure …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 12–19 Read article
-
Interfacial and Tribo-Mechanical Performance of a TiO₂–Castor Oil Polymeric Nanofluid During Sustainable Machining of AISI 316L Stainless Steel Under MQL Conditions
Abstract: This research examines the tribo-mechanical performance and interfacial film characteristics of a TiO₂-reinforced castor-oil polymeric nanofluid during the turning of AISI 316L stainless steel under minimum-quantity lubrication (MQL). A Taguchi L9 orthogonal array was utilized to assess the synergistic effects of cutting speed, depth of cut, and coolant composition on surface integrity, while machining experiments were performed under dry, conventional, and TiO₂-nanofluid lubrication techniques. ANOVA and multiple-regression modeling were used …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 901–914 Read article
-
Investigations On Use of Poly(3,4-Ethylenedioxythiophene): Poly (Styrene Sulfonic Acid) (PEDOT: PSS) Conductive Polymers for Design of Improved EEG Based Brain Computer Interface for Seizure Control and Analysis
Abstract: This research explores the application of Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonic acid) (PEDOT:PSS) conductive polymers in the design of an enhanced Electroencephalography (EEG)-based Brain-Computer Interface (BCI) for seizure control and analysis. PEDOT: PSS, known for its high conductivity, flexibility, and biocompatibility, is employed to improve the efficiency and sensitivity of EEG electrodes, addressing challenges such as signal noise, skin-electrode impedance, and user comfort. The study evaluates the material’s properties, including its electrical conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 223–241 Read article
-
Microstructural Design and Functional Properties of Polycrystalline Materials
Abstract: Polycrystalline materials, composed of an aggregate of crystallites or grains, are foundational to modern engineering applications due to their versatile functional properties. The microstructural design—encompassing grain size, shape, orientation, phase distribution, and grain boundary characteristics—plays a pivotal role in determining mechanical, thermal, electrical, and magnetic behavior. This abstract explores the intricate relationship between microstructure and functionality, emphasizing how tailored processing techniques such as thermomechanical treatments, sintering, and additive manufacturing can …
Published in International Journal of Crystalline Materials · Vol. 2, Issue 2, 2025 · pp. 16–20 Read article
-
AI-Driven Multi-Objective Optimization of Conductive Polymer Composites for High-Performance Flexible Electronics
Abstract: The development of conductive polymer composites (CPCs) is critical for advancing flexible and wearable electronic technologies. However, the conventional trial-and-error approach to material formulation is time-consuming and often inefficient due to the high-dimensional nature of the design space. This study introduces a novel AI-driven framework that integrates machine learning (ML) with multi-objective optimization to accelerate the discovery of high-performance CPCs. A dataset of 1,000 experimentally reported formulations was compiled, capturing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 734–745 Read article