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149 articles for “AI-based process optimization”
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Greener 3D Printing: The Role of Artificial Intelligence in Sustainable Polymer and Composite Manufacturing
Abstract: The integration of sustainable materials with additive manufacturing (AM) technologies marks a significant step towards environmentally responsible production. Biodegradable polymers, recycled thermoplastics, and bio-based composites, when used in 3D printing, offer the potential to reduce the ecological footprint of manufacturing. However optimizing the interplay between material properties process parameters, and product performance remains a complex challenge. This review examines how artificial intelligence (AI) is being applied to address these challenges …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 288–300 Read article
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Innovative Approaches in Bioinspired and Biomimetic Membrane Technologies: Bridging Nature and Engineering
Abstract: Bioinspired and biomimetic membranes represent a ground breaking advancement in membrane technology, offering innovative solutions to critical global challenges in water purification, chemical separation, and energy conversion. These membranes leverage the exceptional transport properties of biological systems, particularly through the incorporation of aquaporin proteins, which facilitate rapid and selective water transport. This review synthesises recent developments in aquaporin-based membranes, highlighting their remarkable efficiency in desalination processes, where they serve as …
Published in International Journal of Membranes · Vol. 1, Issue 2, 2024 · pp. 53–60 Read article
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A Neuromorphic-Inspired, Low-Power VLSI Architecture for Edge AI in IoT Sensor Nodes
Abstract: As the proliferation of Internet of Things (IoT) devices continues to rise, there is an increasing demand for real-time, energy-efficient artificial intelligence (AI) processing directly at the network edge. Traditional edge AI accelerators, often based on deep learning models like convolutional neural networks (CNNs), struggle to meet the ultra-low-power requirements of battery-constrained IoT sensor nodes. In response to this challenge, this study introduces a neuromorphic-inspired, low-power very- large-scale integration (VLSI) …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 2, 2025 · pp. 41–47 Read article
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Parametric optimization of residual stress of TiO2 composite coating
Abstract: The primary objective was to develop a composite coating by utilizing the HVOF thermal spray technique and including TiO2. The substrate was covered with a high-quality composite layer utilizing the HVOF coating process. The TiO2-based powder and carbon powder were initially combined in the mixer for deposition. The composite powders were applied via an HVOF torch, namely the PT F4 model. The firearm frequently produces a high-speed flow of extremely …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 295–301 Read article
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Evolving Face of Quality in The World Robotics Process Automation (RPA)
Abstract: Robotics Process Automation (RPA) is a technology that automates repetitive and rule-based tasks using software robots or "bots." These bots mimic human interactions with digital systems and perform tasks like data entry, validation, report generation, and system integration. RPA leverages AI and ML to improve operational efficiency and can be applied across industries and functions. Implementing RPA offers benefits such as error reduction, productivity enhancement, and cost savings. RPA is …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 1, Issue 1, 2023 · pp. 1–9 Read article
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Advanced Digital Twin and AI Integration for Real-Time Optimization in Polymer Production
Abstract: The integration of Internet of Things (IoT) with Artificial Intelligence (AI) technologies opens up considerable avenues for reshaping polymer manufacturing by improving operational effectiveness, securing exceptional product standards, and advancing sustainability in the environment. This academic manuscript delineates an advanced framework that integrates IoT and AI with synergistic technologies, including blockchain, edge computing, and digital twin methodologies, to revolutionize polymer manufacturing processes. The proposed architecture utilizes IoT sensors for the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 81–89 Read article
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Optimizing RFID-Based Toll Gate System: A Novel Approach to Reducing Latency and Enhancing Traffic Flow
Abstract: This study presents a novel approach aimed at boosting the efficiency of Radio Frequency Identification (RFID) based toll gate systems. Traditional RFID-based toll gates function by reading the RFID data from the vehicle, fetching the corresponding user information from a centralized server, and subsequently deducting the toll amount from the user’s account. This process, while effective, inherently introduces a latency period. This latency, particularly during peak hours, can result in …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 3, 2024 · pp. 41–50 Read article
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Impact of Advanced Reinforcement Materials, Precise Plasticizer Utilization, and Thorough Processing Condition Optimization
Abstract: Material science is always changing, which has led to improvements in processing methods, plasticizers, and strengthening materials. These changes have led to new ideas in many fields. This abstract looks at how using advanced strengthening materials, exact plasticizer use, and thorough processing condition optimization can work together to make polymer-based materials perform better and have better qualities. When it comes to improving the dynamic qualities of plastics, reinforcement materials are …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 73–86 Read article
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AI-based Drug Discovery-Revolutionizing Pharmaceutical Research
Abstract: The traditional drug discovery process is often costly, time-consuming, and prone to high failure rates. The advent of Artificial Intelligence (AI) has revolutionized this field by significantly enhancing efficiency, reducing costs, and improving success rates. AI-driven approaches, including machine learning (ML), deep learning (DL), and natural language processing (NLP), have transformed key areas such as drug target identification, molecular screening, lead optimization, and clinical trial design. AI models can analyze …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 30–44 Read article
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Optimal Abrasive Jet Machining Parameters for Glass Fiber Reinforced Plastics
Abstract: Abrasive jet machining (AJM) is a best choice for processing of glass fiber reinforced plastics (GFRP). Inherent to the nonlinear behavior of performance characteristics during repeated experiments are inevitable variations, attributed to measurement errors and unknown influencing input variables. This study employs the Taguchi method with an orthogonal array to systematically identify optimal input variables through a limited number of experiments. The paper introduces a direct and reliable Taguchi-based multi-objective …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 247–255 Read article
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AI-Driven Pharmacogenomics and Precision Medicine: Future of Personalized Therapy
Abstract: Pharmacogenomics and artificial intelligence (AI) are emerging as important drivers of precision medicine, enabling healthcare systems to adopt individualized therapeutic approaches. Pharmacogenomics examines how genetic variations influence drug response, efficacy, metabolism, and toxicity, while AI provides advanced computational tools for analyzing complex genomic and clinical data. This review highlights the integration of AI-driven pharmacogenomics in personalized therapy and its potential to improve treatment outcomes. Machine learning, deep learning, natural language …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 1–12 Read article
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AI-Assisted Gain Scheduling for Real-Time Temperature Control in Chemical Reactors
Abstract: Temperature control in continuous stirred-tank reactors (CSTR) represents a critical challenge in chemical process industries due to inherent nonlinearities, time-varying dynamics, and parametric uncertainties. Conventional proportional-integral-derivative (PID) controllers with fixed gains often fail to maintain optimal performance across varying operating conditions, leading to temperature excursions that compromise product quality and safety. This paper presents a novel AI-assisted gain scheduling framework that integrates artificial neural networks (ANN) with adaptive PID control …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 24–33 Read article
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Artificial Intelligence and Machine Learning Applications in Optimizing Air Conditioning Systems
Abstract: The growing demand for air conditioning systems, especially in the wake of climate change and increasing global temperatures, has led to a significant increase in energy consumption. This, in turn, contributes to the growing concerns of environmental sustainability and operational costs. As a result, there is a pressing need for innovative solutions to optimize the performance and energy efficiency of air conditioning (AC) systems. Artificial Intelligence (AI) and Machine Learning …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 1, 2025 · pp. 38–43 Read article
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Emotions and Artificial Intelligence in Finance: Exploring the Relationship
Abstract: The integration of Artificial Intelligence (AI) into financial systems has profoundly transformed the industry, providing unprecedented efficiency, accuracy, and speed in decision-making processes. These technological advancements have streamlined operations, reduced human errors, and enabled more informed decision-making based on vast datasets analyzed in real-time. However, the role of emotions in finance remains a critical factor that cannot be ignored. Human emotions, such as fear, greed, and optimism, frequently drive market …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 15, Issue 1, 2025 · pp. 11–17 Read article
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Critical Review on Multifunctional Polymer Composites for Weight Reduction and AI Based Battery Thermal Management in Electric Vehicles
Abstract: The rapid growth of electric vehicles (EVs) has intensified the need for advanced materials and intelligent control systems capable of improving energy efficiency, driving range, thermal safety, and overall vehicle sustainability. This paper presents a critical review of multifunctional polymer composites and artificial intelligence-based battery thermal management systems (AI-BTMS) for next-generation EV applications. Polymer composites reinforced with carbon fibers, graphene, boron nitride, nanoclays, and carbon nanotubes offer significant advantages over …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 603–619 Read article
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Enhancing Interview Preparedness: Development of A Comprehensive AI-Driven Mock Interview System
Abstract: In the contemporary era of virtual interviews, the need for a comprehensive system to prepare users for online interviews is imperative. Mock interviews serve as invaluable tools for enhancing confidence and communication skills, ultimately improving performance. This paper introduces a groundbreaking AI-Driven Mock Interview System (MIS) fortified with cutting-edge Natural Language Processing (NLP) methodologies, specifically targeting syntax and semantic analysis. The MIS integrates a robust JSON-based question- answer repository spanning …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 2, 2024 · pp. 19–25 Read article
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Log Identification and Monitoring System Using Generative AI
Abstract: In contemporary software ecosystems, application and infrastructure logs play a vital role in ensuring system reliability, performance optimization, fault diagnosis, and security compliance. As applications become increasingly distributed and cloud native, the volume, velocity, and variety of generated log data have grown dramatically. This rapid expansion makes traditional manual log inspection inefficient, error-prone, and largely impractical. To address these challenges, this paper proposes an artificial intelligence (AI) driven log monitoring …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 08–16 Read article
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Design and Validation of an Artificial Intelligence-Driven Digital Twin for Real-Time Monitoring and Control in Polymer Composite Manufacturing
Abstract: Polymer Matrix Composites (PMCs) have become indispensable in high-performance sectors such as aerospace and automotive engineering, offering exceptional strength-to-weight ratios that outperform traditional metals in many demanding applications. However, the reliability of manufacturing PMCs via Vacuum-Assisted Resin Transfer Molding (VARTM) is frequently undermined by stochastic process variabilities. Unpredictable fluctuations in thermal history, preform permeability, resin rheology, and ambient conditions often lead to some defects; namely voids, dry spots, and incomplete …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 224–233 Read article
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Advancements in Humanoid Robot Locomotion: A Review of Control Strategies and Kinematic Models
Abstract: Humanoid robot locomotion has significantly improved over the past few decades, driven by improvements in control strategies and kinematic models. Researchers aim to develop robots that can walk, run, and navigate complex terrains with efficiency and stability. This review explores recent developments in humanoid locomotion, highlighting control strategies such as model predictive control, reinforcement learning, and central pattern generators. Additionally, it examines kinematic models, including inverted pendulum models and zero …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 1, 2025 · pp. 24–30 Read article
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An Adaptive Approach for Real-Time Embedded System Design, Analysis and Optimization
Abstract: Real-time embedded systems are critical components in various domains, such as automotive, aerospace, healthcare, and industrial automation. The design, analysis, and optimization of these systems are vital to ensure their reliable and efficient operation. In this paper, we propose an adaptive approach for real-time embedded systems that aims to address the challenges faced during the development process while maintaining high-quality results. Our approach leverages adaptive techniques to dynamically adjust the …
Published in International Journal of Solid State Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 8–14 Read article