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212 articles for “Sustainable machining”
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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
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Energy-Efficient Design Strategies for Sustainable Machine Tool Development
Abstract: The design of energy-efficient machine tools is essential for promoting sustainable manufacturing, as it addresses the significant energy consumption and carbon emissions generated by these tools in industrial settings. This study investigates innovative design approaches that enhance energy efficiency, with a focus on lightweight materials, improved drive systems, smart control frameworks, and methods for recovering energy. Implementing lighter structural materials allows machine tools to operate with less force, which in …
Published in Trends in Machine design · Vol. 12, Issue 3, 2025 · pp. 30–34 Read article
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Optimization of Sustainable Electrochemical Machining Parameters for Polymer based Materials Using AHP Integrated TOPSIS Method
Abstract: The current paper describes the use of the AHP-TOPSIS method to optimize process parameters in sustainable electrochemical machining of polymer composites. Combine lightweight polymer matrices with reinforcing particles or fibers such as TiB₂, SiC, or Al₂O₃, offering high strength-to-weight ratio, corrosion resistance, and design flexibility, making them ideal for aerospace and automotive applications. Non-conductive and heterogeneous nature poses challenges during electrochemical machining, as it affects current distribution and material removal …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1048–1059 Read article
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Enhancing Cooling Efficiency in Dual Nozzle CO2-Based Vortex Tube Systems for Machining Titanium Alloys: Implications for Polymer and Composite Processing
Abstract: In machining of Titanium alloys, the cutting temperature plays a vital role that directly influences the performance and it is required to maintain as low as possible. In this study, a dual nozzle Vortex Tube Cooling System (VTCS) that supplies cool compressed CO2 gas is developed to reduce the cutting temperature in Ti-6Al-4V machining. The experiments were conducted at constant cutting and flow parameters during turning at different levels of …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 284–291 Read article
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Designing a Sustainable Pedal-Powered Washing Machine for Rural Areas
Abstract: The ingenuity can be found in its simple construction, sparse use of pricey components, extremely low upkeep and repair costs, accessibility to all segments of society, and lack of environmental impact. According to the environmental issue, it is essential to use energy in alternative ways in order to conserve it. The PPWM additionally conserves time, water in a container and power while being reasonably priced. The leg-powered washing machine (PPWM) …
Published in International Journal of Manufacturing and Production Engineering · Vol. 1, Issue 1, 2023 · pp. 20–25 Read article
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Integrating Digital Twins, Smart Materials, and Human Machine Collaboration for Sustainable Smart Manufacturing: Smart CNC & Industry 4.0 Applications
Abstract: The rapid evolution of Industry 4.0 and the emerging transition toward Industry 5.0 have been catalyzed by the convergence of intelligent digital technologies such as digital twins, cyber–physical systems (CPS), artificial intelligence (AI), the Internet of Things (IoT), and human-in-the-loop (HITL) frameworks. These technologies have transformed traditional manufacturing into adaptive, data-centric ecosystems capable of real-time optimization and predictive decision-making. In recent years, the fusion of computer numerical control (CNC) machines, …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 2, 2025 · pp. 1–8 Read article
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Forecasting of Crushing Strength of Sustainable Concrete by Employing Deep and Random Forest Machine Learning
Abstract: Sustainable concrete is one of the milestone of the concrete industry. This concrete fulfills the requirements of concrete manufacturing industry such as strengthen, Durability, environment friendly and many of other. With this properties of concrete, sustainable concrete is an ideal substitute for ordinary concrete in the concrete industry. In the 21th century Machine learning is a tool which is use to employ the characteristics of sustainable concrete by using deep …
Published in Journal of Polymer & Composites · Vol. 12, Issue 7, 2024 · pp. 41–46 Read article
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AI and Big Data for Optimized Water Resource Management in Arid Regions
Abstract: Water scarcity in arid regions is an escalating global challenge, driven by climate change, population growth, and increasing demands from urban, industrial, and agricultural sectors. Effective water resource management (WRM) is crucial for sustaining livelihoods, economic stability, and infrastructure resilience. Emerging technologies such as artificial intelligence (AI), machine learning (ML), and big data offer innovative solutions for optimizing water use, enhancing efficiency, and improving sustainability in water-scarce environments. This paper …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 1–5 Read article
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Smart City Solutions for Waste Management and Pollution Control
Abstract: Recent trends in the role of artificial intelligence, IoT, and other smart technologies have a critical role toward addressing urban environmental challenges related to air quality and waste management in the context of a smart city. This changes the scope of managing air quality as, with the integration of IoT sensors, big data, and AI, they are able to predict pollution levels through real time monitoring and analysis. These technologies …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 1, 2025 · pp. 11–22 Read article
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Atmospheric Remote Sensing: Bridging Technology and Environmental Challenges
Abstract: The rapid advancements in remote sensing technologies have revolutionized the field of atmospheric studies, offering unprecedented capabilities for detailed observation, analysis, and understanding of the Earth's atmosphere. These technological innovations have proven to be instrumental in tackling critical environmental challenges, providing scientists and researchers with the tools needed to monitor and analyze atmospheric phenomena with greater precision and depth.This article delves into the historical development, current state, and diverse applications …
Published in International Journal of Atmosphere · Vol. 2, Issue 1, 2025 · pp. 14–19 Read article
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Quasar: Quantum-Accelerated Sustainable Anomaly Recognition in Climate Systems
Abstract: Accurate detection of climate anomalies is vital for disaster alleviation and policy making in a sustainable manner, but customary detection methods face the challenges of computational inefficiency and physical inconsistency. In this study, we propose a novel approach called Quantum-Optimized Fuzzy Physics-Informed Neural Networks (QFuzzy-PINNs), which integrates quantum computing, fuzzy logic, and physics-informed deep learning. As a first step, we employ quantum annealing for conventional optimization to adjust multiple Gaussian …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 18–27 Read article
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Strategic Optimization of CNC Machining in Production Systems: A Managerial Review of Methods, Metrics, and Industry 4.0 Integration
Abstract: Computer numerical control (CNC) machining has significantly influenced modern production systems by enabling higher efficiency, quality, and sustainability. As industrial operations strive for leaner production and strategic competitiveness, optimization of machining parameters—including cutting speed, feed rate, depth of cut, and tool path strategies—has emerged as a cornerstone of production planning. This review evaluates the optimization methodologies developed from 2015 to 2025, spanning traditional mathematical models to artificial intelligence (AI)-driven metaheuristic …
Published in Journal of Production Research & Management · Vol. 15, Issue 2, 2025 · pp. 25–30 Read article
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Enhanced Sustainable Concrete Mix Design Using LLMs and Advanced Machine Learning Techniques
Abstract: Large Language Models (LLMs) are emerging as transformative tools in materials science, offering human-like reasoning, zero-shot problem solving, and the ability to integrate fuzzy laboratory knowledge with structured data. This study extends and reinterprets the original systematic benchmark for using LLMs in sustainable concrete design, particularly for Alkali-Activated Concrete (AAC). We introduce an enhanced, multi-model framework combining LLM-based inverse design, Random Forest regression, Gaussian Process Regression (GPR), and a lightweight …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Industry 6.0: Building a Sustainable Future
Abstract: The next stage of industrialization, known as Industry 6.0, is centered on developing intelligent, fully integrated manufacturing systems that require little human involvement. India is in a perfect position to become a major player in the sector 6.0 ecosystem, thanks to its robust technological infrastructure, fast expanding economy, and large talent pool. It blends big data, cloud computing energy, human-robot interaction, artificial intelligence, and quantum computing. The main aim of …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 25–32 Read article
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A Detailed Survey of Machine Learning Applications, Methods, and Future Prospects in Agriculture
Abstract: Agriculture is undergoing a digital transformation driven by machine learning (ML) and artificial intelligence. The integration of ML techniques with data from sensors, drones, satellites, and IoT devices has enabled precision agriculture, early disease detection, optimized resource use, and improved yield prediction. This paper presents a comprehensive review of machine learning applications in modern agriculture, covering key areas such as crop monitoring, soil analysis, irrigation scheduling, pest, and disease detection, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 39–45 Read article
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Fertilizer Prediction Using Machine Learning
Abstract: Fertilizer prediction is a critical aspect of modern agriculture, aimed at optimizing resource utilization while maximizing crop yields. In recent years, machine learning (ML) techniques have emerged as powerful tools for addressing this challenge by leveraging data-driven approaches to predict the optimal type and quantity of fertilizer required for different crops and soil conditions. This research paper provides a comprehensive review of the existing literature and methodologies employed in fertilizer …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 2, 2024 · pp. 26–35 Read article
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Hybrid Machining Processes in Advanced Manufacturing: A Review of Mechanisms and Industrial Applications
Abstract: Hybrid machining processes (HMPs) have gained considerable attention in recent years as an effective approach to address the growing complexity and performance demands of modern manufacturing systems. These processes combine two or more machining techniques—such as mechanical, thermal, chemical, or electrical methods—into a single setup, enabling enhanced productivity, precision, and adaptability, particularly for hard-to-machine materials like ceramics, composites, and superalloys. The integration of distinct energy sources results in synergistic effects …
Published in Journal of Production Research & Management · Vol. 15, Issue 2, 2025 · pp. 19–24 Read article
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A Data-Driven Analysis of Machine Learning Classification Models for Reliable Crop Yield Prediction
Abstract: The adoption of ML technologies in agriculture is reshaping farming practices, empowering producers to make informed, data-oriented decisions that improve yields, sustainability, and long-term resilience. In mango cultivation, ML analyzes data from weather, soil, and pests to optimize irrigation, fertilization, and pest control. Predictive analytics help forecast ideal farming practices, minimizing resource wastage and improving yield. Real-time monitoring and image-based disease detection allow timely interventions to maintain plant health and …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 1, 2026 · pp. 12–17 Read article
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Biohybrid Machines: Integrating Organic Systems with Robotics for Enhanced Mobility and Function
Abstract: Biohybrid machines are an innovative frontier at the intersection of biological systems and robotics. This research field explores the integration of living organisms with machines, combining the advantageous characteristics of both synthetic materials and biological components. Through the integration of organic cells, tissues, and even entire organisms with robotics, biohybrid machines possess unique capabilities such as self-healing, adaptability, and energy efficiency, making them more suitable for tasks that require flexibility …
Published in Trends in Machine design · Vol. 12, Issue 1, 2025 · pp. 30–37 Read article
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AI and IoT in Sustainable Agriculture: A Review
Abstract: Artificial Intelligence (AI) and Internet of Things (IoT) integration have transformed the world of sustainable agriculture, presenting new ways of resource optimization, increasing crop yields, and making environmental sustainability more accessible. The current literature review analyzes the applications of AI and IoT in three significant agricultural systems: aquaponics, hydroponics, and poultry farming. By critically analyzing recent studies, this paper emphasizes how deep learning- enabled computer vision techniques allow for the …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 2, 2025 · pp. 32–45 Read article