Search
516 articles for “drying optimization”
-
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
-
Enhancing Energy Efficiency in Air Handling Units Through AI Driven Optimization
Abstract: This research explores the implementation of artificial intelligence (AI) in enhancing the energy efficiency of Air Handling Units (AHUs) in manufacturing facilities. The study proposes a comprehensive solution architecture that incorporates temperature and humidity sensors within AHUs, utilizing RS485 for data communication. The collected data undergoes exploratory analysis, which informs the training of a decision tree algorithm, chosen for its accuracy and compatibility with edge gateways. The algorithm's predictions enable …
Published in International Journal of Industrial and Product Design Engineering · Vol. 2, Issue 2, 2024 · pp. 19–28 Read article
-
TOPSIS-Driven Optimization of FFF Process Parameters for Mechanical Strength Enhancement
Abstract: In this study, the application of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method for optimizing Fused Filament Fabrication (FFF) process parameters to enhance the tensile and flexural strength of Polylactic Acid (PLA) material-based 3D printed components is explored. This investigation delves into the intricate relationship between key parameters, such as layer height, print speed, infill density, print temperature, and nozzle diameter, and their impact …
Published in Journal of Polymer & Composites · Vol. 11, Issue 12, 2023 · pp. 246–255 Read article
-
Digital Twin-Driven Optimization of Dynamic Covalent Polymer Networks under Real-Time IoT Monitoring
Abstract: The dynamic covalent polymer networks (DCPNs) has the highest allurement because of the reversibility of all of the chemicals and repetitive. The process of convalescence is delayed, the sense of source betrayal and acting relations is too strong. This transport to our material situation is an ever-refrigerated digital twin in this painting which was developed through repetition produced by constant synchronism sensors of the IoT that is constantly refined by …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 137–157 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
-
Hydrolysis-Driven Optimization of Hydroxypropyl Maize Starch for Improved Micro-Pellet Binding and Quick Solubility of Spirulina-Based Micro-Pellets
Abstract: Acid hydrolysis is a well-established approach for modifying the physicochemical properties of polysaccharides & macromolecules including hydroxypropyl Maize starch (HPMS). In this study, the effect of varying concentrations of hydrochloric acid on the partial hydrolytic degradation of HPMS (Lycoat RS-780) was investigated at 85°C for 4 h, yielding polymers of different molecular weights. The Acid-mediated degradation effects on polymer characteristics were systematically assessed using capillary viscometry and gel permeation chromatography …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 17, Issue 3, 2026 Read article
-
Optimization Of Solar Drying Parameters for Turmeric and Papaya Leaves: Effects on Nutritional and Bioactive Compound Retention
Abstract: This study focuses on the optimization of solar drying parameters for turmeric and papaya leaves, based on their impact on retention of nutritional and bioactive compounds. One of the most crucial postharvest procedures is solar drying as it decreases the moisture content in plant materials, thereby increasing shelf life and preserving quality. This study considers traditional methods as open sun drying (OSD) and advanced solar dry techniques, including Hybrid Indirect …
Published in International Journal of Electrical Power and Machine Systems · Vol. 3, Issue 1, 2025 · pp. 29–37 Read article
-
Artificial Neural Network Modelling to Optimize Micro-Drilling Parameters of ECDM of Developed Novel Zn/(Ag+Fe)-MMC
Abstract: Several engineering fields have increased their use of metal matrix composites (MMCs) in the past few years. Due to the increase in composites, the demand for accurate machining has also become important. Specifically, pertaining to biomaterial applications, accuracy factor with desired surface finish is critical. While the near-net shape manufacturing process has advanced, MMCs frequently require post-mould machining to achieve surface quality, and dimensional tolerances. In the present study, a …
Published in Journal of Polymer & Composites · Vol. 11, Issue 1, 2023 · pp. 01–13 Read article
-
Drilling Parameters Optimization in LM6/B4C/Fly ash Hybrid Composites by Taguchi Technique
Abstract: Aluminium matrix composites (AMCs) are challenging to machine due to its abrasive characteristics. Because of the broad adoption of MMCs, it is vital to create sufficient equipment to facilitate efficient manufacturing. The current study utilizes signal-to-noise ratio (S/N) analysis to determine the ideal machining parameters for drilling AMC’s. The goal with this study is to investigate the effect of feed rate (FR), drill type (D), speed (SS), reinforcing material R …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 890–897 Read article
-
Intelligent Optimization of Drilling Parameters in Polymer Composites using Machine Learning and Metaheuristic Techniques
Abstract: The study tests different ways to use ML and metaheuristic algorithms to determine the best drilling parameters for polymer matrix composites. The research uses a composite matrix made from 55.25% vinyl ester, 44.0% Nickel–Phosphorous coated glass fiber and 0.75% Al₂O₃ nanowires which are tested for tensile strength (64.57 MPa), flexural strength (85.86 MPa) and impact strength (71.79 kJ/m²). By applying a Taguchi orthogonal array, it is observed that a slower …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1795–1810 Read article
-
Artificial Intelligence and Edge Computing in Oil and Gas: Applications, Architectures, and Operational Realities
Abstract: Artificial intelligence has arrived in oil and gas, and unlike some previous waves of digital enthusiasm in the sector, this one is sticking. Saudi Aramco analyses approximately 10 billion data point every day and reported USD 4 billion in technology-driven operational gains in 2024. ExxonMobil uses AI to increase shale well output by more than 5 percent. Shell has deployed machine learning across more than 10,000 assets using C3.ai to …
Published in Journal of Petroleum Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 01–06 Read article
-
Strategies for Efficient Integration of Distributed Energy Resources into Microgrid Systems
Abstract: With the growing integration of Distributed Energy Resources into modern power systems, the global energy landscape is changing. Some of the DERs are solar photovoltaic (PV), wind turbines, battery storage systems, combined heat and power (CHP) units, and electric vehicles (EVs). Some of the advantages include lower transmission losses, better energy efficiency, and more resilience to grid failures. However, the far-reaching integration of DERs carries with it considerable technical, economic, …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 51–56 Read article
-
AI-Driven Topology Optimization of Woven Fiber-Reinforced Composite Chassis Structures for Electric Vehicles Under Crash Loading
Abstract: The structural design of an electric vehicle (EV) chassis represents a unique engineering challenge to achieve minimal weight while meeting occupants' safety requirements during high-energy crash conditions without compromise to the battery housing's integrity or the geometrical constraints of the electric powertrain package. In this paper, a single framework is proposed to integrate physics-based artificial intelligence (AI) surrogate models using PINNs, CNN-accelerated topology optimization, and FEA to design woven fiber-reinforced …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 72–89 Read article
-
Development of Lightweight Chassis and Efficient Drivetrain for Formula Student Applications
Abstract: The chassis and drivetrain of a Formula Student vehicle are designed, analyzed, and optimized in this research study with an emphasis on manufacturability, performance, and safety. The project emphasizes the use of advanced engineering tools such as SolidWorks for computer-aided design (CAD) and ANSYS for structural analysis to evaluate the chassis under various dynamic conditions. The primary objective is to ensure that the driver remains safe inside the cockpit while …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 1–17 Read article
-
Improving Black Cotton Soil with Sodium Hydroxide and Fly Ash: An Assessment of Optimum Moisture Content, Dry Density, and California Bearing Ratio
Abstract: This study investigates the stabilization of Black Cotton Soil (BCS), an expansive clayey soil primarily composed of montmorillonite minerals, using sodium hydroxide (NaOH) and fly ash. Due to its high plasticity and significant volume changes with moisture, BCS is challenging for construction purposes. Adding NaOH and fly ash can potentially improve the soil's moisture tolerance, compressibility, and reduce its plasticity, making it more suitable for structural applications. The research evaluates …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 192–201 Read article
-
Electronic Resources of University Libraries: AI-Driven Management and Optimization
Abstract: In order to maximize accessibility, utilization, and efficiency, university libraries’ growing reliance on electronic resources (ER) has prompted the creation of sophisticated management techniques. The difficulty of handling enormous volumes of data has increased as educational institutions move from conventional physical collections to massive digital repositories. A key instrument in revolutionizing library operations, artificial intelligence (AI) offers creative ways to improve retrieval methods, manage digital resources more effectively, and customize …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 3, 2025 · pp. 8–15 Read article
-
Multi-Objective Optimization of Carbon-Glass Fiber Polymer Drilling Process Based on Fuzzy Grey Entropy Weighing Method
Abstract: In recent years, the machining characteristics of hybrid fiber polymer composites have garnered significant research attention due to their growing industrial applications. This study specifically focuses on the drilling of hybrid carbon-glass fiber reinforced (CGFR) epoxy composites, fabricated using the hand layup technique. The key machining characteristics evaluated in this drilling process include surface roughness and circularity error. The influence of critical drilling process parameters, such as spindle speed, drill …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 100–112 Read article
-
Optimizing Parameters for Dry Sliding Wear Control in Stir-Cast AA7050/SiC Composites
Abstract: Using a pin-on-disc tribometer, this study examined the dry sliding wear behavior of AA7050/SiC composites. The production of this metal matrix composite was achieved through the stir-casting process, which involved an initial step of melting the AA7050 alloy, followed by the careful introduction of silicon carbide (SiC) particles, stirring to achieve uniform dispersion, and finally, casting the molten mixture. Wear rate (WR) was determined by three operational parameters: SiC reinforcement …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1624–1635 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
-
An Innovative Approach to Find the Optimum Lubricant for Diverse Applications Based on Scikit-Learn Library Using Python
Abstract: This paper presents an innovative approach for finding the optimum lubricant using the Scikit-learn library in Python. The proposed approach uses a linear regression model to analyze a dataset of lubricant properties and performance, specifically the viscosity, wear, and friction. The model is trained on the dataset to predict the wear and friction for a given viscosity, which can be used to identify the optimum lubricant. By analyzing a dataset …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 25–35 Read article