UTILIZING MACHINE LEARNING TO ASSESS DATA COLLECTION METHODS IN MANUFACTURING AND MECHANICAL ENGINEERING

Academic journal on science, technology, engineering & mathematics education., Journal Year: 2024, Volume and Issue: 4(2), P. 14 - 25

Published: June 13, 2024

This study explores the significant impact of machine learning (ML) on data collection methods within manufacturing and mechanical engineering sectors, emphasizing its superiority over traditional techniques. By analyzing from 20 case studies 15 industry reports, research highlights how ML models such as neural networks support vector machines enhance accuracy, efficiency, reliability. The findings reveal that ML-based excel in handling large datasets, automating processes, reducing human error, thereby improving quality operational performance. Applications predictive maintenance control demonstrate substantial reductions equipment downtime defect detection errors, alongside streamlined workflows cost savings. Additionally, shows can optimize process parameters identify bottlenecks more effectively, leading to enhanced overall efficiency industrial operations. These results underscore transformative potential optimizing practices, marking a advancement operations paving way for innovative efficient practices across sector.

Language: Английский

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A REVIEW OF BLOCKCHAIN TECHNOLOGY'S IMPACT ON MODERN SUPPLY CHAIN MANAGEMENT IN THE AUTOMOTIVE INDUSTRY

Deleted Journal, Journal Year: 2024, Volume and Issue: 3(3), P. 13 - 27

Published: June 4, 2024

Blockchain technology has emerged as a transformative force in various industries, including supply chain management within the automotive sector. This review examines impact of blockchain on by analyzing 183 articles, focusing its ability to enhance transparency, traceability, and efficiency. By providing decentralized immutable ledger, ensures real-time tracking parts components, thereby reducing risk counterfeit products ensuring compliance with regulatory standards. The automation transactions through smart contracts streamlines processes, reduces need for intermediaries, leads substantial cost savings faster delivery times. However, implementation also presents challenges such scalability, interoperability existing systems, high costs, concerns. Addressing these future research pilot projects is essential unlocking full potential revolutionizing industry. synthesizes current literature provide comprehensive understanding both benefits associated implementation, highlighting necessary steps successful adoption.

Language: Английский

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ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING ENHANCE ROBOT DECISION-MAKING ADAPTABILITY AND LEARNING CAPABILITIES ACROSS VARIOUS DOMAINS

Deleted Journal, Journal Year: 2024, Volume and Issue: 1(3), P. 14 - 27

Published: June 3, 2024

This study examines the transformative role of artificial intelligence (AI) and machine learning (ML) in enhancing robot decision-making, adaptability, capabilities. By integrating AI ML algorithms, robots are evolving from pre-programmed tools into intelligent collaborators capable operating effectively complex dynamic environments. article provides a comprehensive overview robotics, exploring their fundamental principles, diverse applications across industries, associated challenges. Through case-study-based approach, analyzes real-world implementations AI-powered manufacturing, healthcare, logistics, industrial inspection, demonstrating significant impact on efficiency, productivity, safety. The findings highlight potential to revolutionize various sectors, while emphasizing need for ongoing research responsible development address ethical considerations ensure safe beneficial integration society.

Language: Английский

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THE INTEGRATION OF INDUSTRY 4.0 AND LEAN TECHNOLOGIES IN MANUFACTURING INDUSTRIES: A SYSTEMATIC LITERATURE REVIEW

Deleted Journal, Journal Year: 2024, Volume and Issue: 1(3), P. 14 - 25

Published: June 4, 2024

This systematic literature review examines the integration of Industry 4.0 and Lean technologies in manufacturing, a topic growing importance as industries seek to enhance efficiency competitiveness. By analyzing 156 peer-reviewed journal articles, conference papers, industry reports published between 2010 2023, this identifies vital themes, benefits, challenges, gaps literature. 4.0, characterized by IoT, big data analytics, artificial intelligence (AI), machine learning (ML), offers significant potential for improving real-time collection, process automation, advanced analytics. When integrated with manufacturing principles, which focus on waste reduction continuous improvement, these can lead more efficient operations, better quality control, faster response times. However, also highlights several including high initial costs, need skilled workforce, complexity integrating new existing systems. Despite numerous case studies best practices demonstrate successful implementation approaches, providing valuable insights future research practical applications. concludes recommendations addressing identified leveraging synergies achieve operational excellence manufacturing.

Language: Английский

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POWER SYSTEM STABILITY CONSIDERING THE INFLUENCE OF DISTRIBUTED ENERGY RESOURCES ON DISTRIBUTION NETWORKS

Academic journal on science, technology, engineering & mathematics education., Journal Year: 2024, Volume and Issue: 4(2), P. 1 - 13

Published: June 13, 2024

The increasing penetration of distributed energy resources (DERs) into power systems has transformed the landscape distribution, bringing both opportunities and significant challenges. This study examines impact DER integration on system stability, focusing voltage frequency transient stability. A comprehensive review 50 high-quality studies from peer-reviewed journals reputable conference proceedings was conducted, utilizing advanced modeling, simulation, empirical analysis methods. findings reveal that intermittent nature renewable DERs, such as solar wind, leads to fluctuations, necessitating control strategies maintain Additionally, displacement traditional synchronous generators by inverter-based DERs reduces inertia, posing severe stability challenges require innovative solutions like synthetic inertia fast response mechanisms. Transient issues are also exacerbated integration, highlighting need for inverter controls enhanced fault ride-through capabilities. Energy storage (ESS) identified crucial buffering variability providing essential services regulation support. However, high costs scalability remain barriers widespread ESS adoption. underscores importance supportive regulatory policy frameworks in facilitating seamless while maintaining grid Effective policies promote smart technologies DER-friendly regulations ensuring a stable, resilient, sustainable grid. research contributes deeper understanding complex dynamics introduced offers insights developing robust address modern systems.

Language: Английский

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Nanofiber Drug Delivery Systems: Recent Advances in Nanofabrication and Their Role in Targeted Therapy in Cancer, Neurodegenerative, and Cardiovascular Diseases

Polymers for Advanced Technologies, Journal Year: 2025, Volume and Issue: 36(5)

Published: May 1, 2025

ABSTRACT Nanofiber‐based drug delivery systems show strong potential due to their high surface area‐to‐volume ratio and adjustable structure. Recent studies demonstrated loading efficiencies exceeding 85%, with sustained release kinetics up 96 h. In cancer models, nanofiber‐based carriers improved accumulation at tumor sites by 3–4 fold compared conventional formulations, enhancing therapeutic efficacy minimizing systemic toxicity. This review outlines methods for precise nanofiber shape function control through electrospinning solution blow spinning techniques. advancements in technology have proven promising biomedical applications where they are utilized tissue engineering, neurodegenerative disease management, wound healing, targeted therapy. Nanofibers as an optimal system that improves cellular restoration, together controlled deep penetration capabilities. The recent development of dual‐drug systems, stimuli‐responsive nanofibers, scaffolds composed nanofibers smart materials has expanded usage precision medicine. Research now demonstrates facilitate remodeling functions along angiogenesis promotion, inflammatory response stability improvement. also focuses on the patents a system. addition, this presents new approaches overcome these challenges based interdisciplinary cooperation, AI‐driven design such sophisticated bioinformatics tools. review, advances prospects realizing revolution field improving healthcare outcomes presented detailed overview.

Language: Английский

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DEVELOPING AN EXTRUDER MACHINE OPERATING SYSTEM THROUGH PLC PROGRAMMING WITH HMI DESIGN TO ENHANCE MACHINE OUTPUT AND OVERALL EQUIPMENT EFFECTIVENESS (OEE)

Deleted Journal, Journal Year: 2024, Volume and Issue: 1(3), P. 1 - 13

Published: June 2, 2024

Designing a state-of-the-art PLC-based extrusion machine with user-friendly HMI ensures seamless operation, enhancing Overall Equipment Effectiveness (OEE). This project focuses on automating an system advanced technologies for optimized functionality and reliability. The architecture includes sophisticated components to boost productivity product quality. Key aspects involve orderly control synchronization of the extruder motor, feeder lubrication pump, vacuum pump consistent performance precise temperate profile. A significant innovation is centralized blower temperature profile analysis control, replacing individual controllers enhance thermal management efficiency ensure uniform distribution. high-low alarm alerts operators deviations, maintaining process stability. Real-time data current (Amps) frequency (Hz) displayed from inverter monitoring diagnostics. also features downline controlling capabilities efficient downstream processes. Collectively, these innovations create robust, efficient, that enhances OEE

Language: Английский

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Academic journal on science, technology, engineering & mathematics education., Journal Year: 2024, Volume and Issue: 4(2)

Published: June 13, 2024

This study explores the significant impact of machine learning (ML) on data collection methods within manufacturing and mechanical engineering sectors, emphasizing its superiority over traditional techniques. By analyzing from 20 case studies 15 industry reports, research highlights how ML models such as neural networks support vector machines enhance accuracy, efficiency, reliability. The findings reveal that ML-based excel in handling large datasets, automating processes, reducing human error, thereby improving quality operational performance. Applications predictive maintenance control demonstrate substantial reductions equipment downtime defect detection errors, alongside streamlined workflows cost savings. Additionally, shows can optimize process parameters identify bottlenecks more effectively, leading to enhanced overall efficiency industrial operations. These results underscore transformative potential optimizing practices, marking a advancement operations paving way for innovative efficient practices across sector.  

Language: Английский

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None

Deleted Journal, Journal Year: 2024, Volume and Issue: 1(3)

Published: June 2, 2024

Designing a state-of-the-art PLC-based extrusion machine with user-friendly HMI ensures seamless operation, enhancing Overall Equipment Effectiveness (OEE). This project focuses on automating an system advanced technologies for optimized functionality and reliability. The architecture includes sophisticated components to boost productivity product quality. Key aspects involve orderly control synchronization of the extruder motor, feeder lubrication pump, vacuum pump consistent performance precise temperate profile. A significant innovation is centralized blower temperature profile analysis control, replacing individual controllers enhance thermal management efficiency ensure uniform distribution. high-low alarm alerts operators deviations, maintaining process stability. Real-time data current (Amps) frequency (Hz) displayed from inverter monitoring diagnostics. also features downline controlling capabilities efficient downstream processes. Collectively, these innovations create robust, efficient, that enhances OEE  

Language: Английский

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