Search
839 articles for “Processing optimization”
-
Recent Trends in Rotary Kiln and Refractory Material Patterns in Cement Production: A Review Approach
Abstract: The manufacturing of cement and other industrial operations depend heavily on rotary kilns, which use refractory materials to endure high temperatures and challenging chemical conditions. With an emphasis on their effects on durability and operating efficiency, this study looks at the most recent developments in rotary kiln technology and refractory material choices. Various rotary kiln designs, typical refractory material patterns, and the difficulties posed by kiln failures are all covered. …
Published in Journal of Experimental & Applied Mechanics · Vol. 16, Issue 2, 2025 · pp. 27–34 Read article
-
Optimized Design and Control of Oil Exploitation Strategies: An Assisted Approach
Abstract: Because there are so many factors and scenarios to consider, optimizing oil exploitation tactics requires complicated decision-making. Conventional approaches frequently concentrate on particular elements of the design infrastructure, which restricts their capacity to fully handle the process. In order to maximize a set of oil exploitation variables in a hierarchical fashion, this research proposes a novel assisted optimization technique that combines mathematical algorithms with engineering analysis. By grouping variables into …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 29–34 Read article
-
A Sustainable and Green Prototyping Framework for Low-carbon and Resource-efficient Virtual Product Development
Abstract: The increasing emphasis on sustainable manufacturing has intensified the need for environmentally responsible design and development methodologies for polymer and polymer-composite materials, where material selection, processing routes, and waste generation play a critical role in overall environmental impact. This paper presents a Sustainable and Green Prototyping (SGP) framework that integrates Virtual Prototyping (VP), Life Cycle Assessment (LCA), and multi-objective optimization to systematically reduce carbon footprint, energy consumption, and material waste …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 459–471 Read article
-
Parametric Study of Laser Drilling Process Using Multi Variable Regression Analysis
Abstract: The laser drilling process is an advanced manufacturing technique extensively employed for intricate and high-value components in aerospace, automotive, and electronics industries. Laser drilling technology offers opportunities to meet the contemporary demands of industries using a broad spectrum of engineering materials. However, this process encounters several engineering challenges such as thermal damage, dimensional inaccuracies, and the formation of a recast layer in the drilled components. This study focuses on examining …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1000–1015 Read article
-
Parametric Optimization of Biocompatible Ti6AL4V Alloy on Selective Laser Melting for Enhanced Structural Support and Reduced Stress Shielding
Abstract: The Selective Laser Melting technique is widely employed in the production of complexly shaped end products for a range of industries, including biomedical, aerospace, automotive, and defence. SLM is a complicated manufacturing process since a lot of factors influence the characteristics of the items that are printed using it. The SLM printing of fully dense parts is becoming more and more popular for various high-end applications. Because of their biocompatibility …
Published in Journal of Polymer & Composites · Vol. 12, Issue 6, 2024 · pp. 143–156 Read article
-
Exploring the Impact of Process Parameters on 3D Printing: A Comprehensive Review for Enhanced Product Quality
Abstract: Rapid developments in 3D printing technology have dramatically changed a wide range of industries, from consumer products and healthcare to automotive and aerospace. 3D printing is a process of manufacturing where material is deposited layer over layer which are previously deposited to provide the design shape to the desired products. This process has eliminated the numerous machining processes which were required to manufacture the products previously. The modification of process …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 975–996 Read article
-
Green and Edge-Aware Computing: Rethinking Cloud Infrastructure for Sustainability
Abstract: Cloud computing has transformed the way organizations access and manage information technology resources, providing flexible, scalable, and cost-efficient services that support today’s data-driven world. Despite these advantages, the rapid expansion of large-scale cloud infrastructures has resulted in rising energy consumption, significant heat generation, and a growing environmental footprint. This research focuses on advancing green cloud computing by examining methods that reduce power usage while maintaining high performance. Key strategies include …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 17–24 Read article
-
Optimizing DevOps Pipelines with Maven: Advanced Build Automation Techniques
Abstract: As modern software development continues to evolve, DevOps has become a fundamental methodology for integrating development and operations teams to enhance collaboration, reduce software delivery time, and improve overall product quality. Automating builds is a crucial aspect of any DevOps pipeline, as it helps maintain consistency and dependability throughout the different phases of the development process. Maven, a robust build automation tool commonly used in Java projects, is instrumental in …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 06–11 Read article
-
Thermodynamic Analysis and Slow Pyrolysis Product Characterization are Used to Assess Rice Straw for Bio-char Production
Abstract: This work explores the viability of using slow pyrolysis to produce bio-char using rice straw as a feedstock. The objective is to characterize the resulting bio char and analyse the thermodynamic processes involved in its formation. Rice straw, an abundant agricultural residue, was subjected to slow pyrolysis under controlled conditions. The produced bio char was characterized using various analytical techniques, including scanning electron microscopy, elemental analysis, and surface area measurements. …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 13, Issue 2, 2024 · pp. 26–29 Read article
-
Advancements in K-Means Clustering: Boosting Algorithm Performance through Innovations
Abstract: K-Means clustering is a widely used unsupervised learning algorithm for partitioning a dataset into distinct clusters. Despite its popularity and simplicity, K-Means has several limitations, such as sensitivity to initial centroids, convergence to local minima, and inefficiency with large datasets. This paper reviews recent advancements aimed at addressing these challenges and enhancing the performance of the K-Means algorithm. Innovations include improved initialization methods, such as K-Means++, which significantly reduce the …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 30–37 Read article
-
Design and Optimization of Heat Dissipation Systems for Electric Vehicle Battery Packs: A Study on Advanced Cooling Techniques
Abstract: In order to guarantee battery safety, performance, and longevity, the increasing popularity of electric vehicles (EVs) has increased the demand for efficient heat management systems. With an emphasis on cutting-edge cooling methods, this study explores the design and optimization of heat dissipation systems for EV battery packs. The study compares cutting-edge techniques like phase change materials, micro channel heat sinks, and thermoelectric cooling systems with more conventional cooling techniques like …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 1–10 Read article
-
Empowering Vehicle: The Impact of Deep and Reinforcement Learning in IoV
Abstract: Deep learning and reinforcement learning represent two pivotal pillars within the realm of artificial intelligence and machine learning, bearing transformative potential in the domain of the Internet of Vehicles (IoV). This abstract explores the multifaceted applications of these cutting-edge techniques within the IoV framework. Deep learning, exemplified by convolution neural networks (CNNs) and recurrent neural networks (RNNs), empowers IoV systems with the prowess to discern complex patterns in sensory data. …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 2, 2025 · pp. 1–12 Read article
-
Effect of Welding Factors on Nugget Size of Polymer-Metal Composite Sheets Using Computational Methods
Abstract: Resistance spot welding (RSW) is a vital technique for joining materials in industries like automotive and aerospace. This study extends the application of RSW to polymer-metal composite sheets by developing 2D axisymmetric, thermo-electro-mechanical coupled model in ANSYS. The focus is on analyzing the temperature distribution, nugget formation, and parameter optimization in hybrid composite sheets, emphasizing the unique challenges posed by polymers' thermal and electrical properties. These properties differ significantly from …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 612–623 Read article
-
AI-Driven Framework for Accelerating Polymer Nanocomposite Commercialization in Computational Materials Engineering
Abstract: The remarkable mechanical strength increased functional qualities, lightweight structure, and thermal stability of polymer nanocomposites have prompted modern materials research to prioritize their rapid commercialization. Advanced materials can be created by adding nanoscale fillers such as carbon nanotubes, graphene, silica, and metal oxides to polymer matrices. These materials have applications in biomedical engineering, aerospace, electronics, packaging, and automobile manufacture. Research and development of polymer nanocomposites has traditionally relied on costly …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1–19 Read article
-
AI-Driven Inverse Design of Functionally Graded Bio-Nanocomposites for Sustainable High-Barrier Packaging
Abstract: Multilayer plastic packaging realizes high barrier performance through laminated heterogeneous structures, but the heterogeneous structure has severe end-of-life challenges caused by the interfacial incompatibility of materials and the poor recyclability. This study proposes the inverse design of functionally graded PLA-nanoclay composite films by reinforcement learning as a monolithic alternative to traditional multilayer systems. Twin-screw extrusion is designed as a continuous control Markov decision process, and proximal policy optimization (PPO) is …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1547–1564 Read article
-
Advances in Pipe Flow Systems, Turbulence, and Combustion Processes in Fluid Mechanics
Abstract: Fluid mechanics plays a critical role in the design and optimization of engineering systems involving fluid transport, energy conversion, and thermal processes. This review presents recent advances in pipe flow systems, turbulence behavior, and combustion processes, highlighting their interdependence in modern applications. Pipe flow systems are essential in industries such as water distribution, oil and gas transport, and chemical processing, where flow characteristics are influenced by factors such as pressure, …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 1, 2026 · pp. 1–7 Read article
-
Application of Convolutional Neural Networks in Design of Efficient Pipe Flow System
Abstract: Convolutional Neural Networks exhibit remarkable capabilities in flow pattern recognition, pressure drop prediction, leak detection, and system optimization through their ability to process complex spatial and temporal data patterns. The study examines CNN architectures specifically adapted for fluid dynamics applications, including data preprocessing techniques, feature extraction methods, and performance optimization strategies. Key applications include real-time flow monitoring, predictive maintenance, design parameter optimization, and anomaly detection in pipe networks. Comparative analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 1–9 Read article
-
Bridging Brain-Inspired Learning and Quantum Reasoning for Future AGI Systems
Abstract: This research paper presents a novel neuromorphic–quantum hybrid computing framework envisioned to advance intelligent systems toward artificial general intelligence. The architecture integrates brain-inspired spiking networks for adaptive, energy-efficient learning with quantum processors for non-classical optimization and reasoning. A shared synaptic–quantum memory layer enables dual information representation, while neuromorphic adaptive controllers provide real-time stabilization of noisy quantum circuits. While quantum processors offer features like superposition- enabled exploration and entanglement-based correlations that …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 Read article
-
Challenges and Opportunities in the Catalytic Conversion of CO₂ to Value-Added Chemicals
Abstract: The catalytic conversion of CO2 into value-added chemicals presents a promising strategy for tackling the dual challenges of greenhouse gas emissions and the sustainable production of chemicals. This process transforms CO2, a major contributor to climate change, into useful products such as methanol, formic acid, and hydrocarbons. Such an approach not only helps mitigate CO2 levels in the atmosphere but also generates economically valuable products, thereby supporting both environmental and …
Published in Journal of Catalyst & Catalysis · Vol. 11, Issue 2, 2024 · pp. 30–35 Read article
-
Leveraging Deep Learning for Accurate Weed Identification
Abstract: Weed control is very important for all types of agricultural businesses. The project here revolves around the application of computer vision techniques and, more concretely, deep learning techniques, for the effective recognition and classification of weeds. The EfficientNetB4 architecture is an appropriate backbone as its scalability and performance optimization is adequate. The modifier used is Adam optimization algorithm which will serve as a pre- processor for the model. Weeds at …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 90–99 Read article