Springer eBooks, Год журнала: 2024, Номер unknown, С. 1 - 16
Опубликована: Дек. 11, 2024
Applied Sciences, Год журнала: 2025, Номер 15(4), С. 2068 - 2068
Опубликована: Фев. 16, 2025
The transition from Industry 4.0 to 5.0 raises concerns about integrating advanced quality control measures by replacing humans. biggest challenge of this is infrastructure compatibility. This paper proposes a remote collaboration solution via the Internet Things (IoT) infrastructure. study identifies challenges in implementing such strategies and highlights importance AI–human collaboration, aligning with concepts. research integrates data multiple visual sensors (cameras) devices into an IoT framework create monitoring system. system’s application focuses on ensuring cast standards. proposed artificial AI method provides compatibility for entire Nonconformity Indicator Algorithm (NIA) was designed defect detection. NIA, developed using Azure Custom Vision Service, identified classified manufactured product defects based image analysis Accuracy 98.18%, Precision 98.44%, Recall 96.56%, F1-Score 97.50%. Furthermore, IoT-based system that employs real-time sensor fusion techniques manufacturing environments. devices, including like ESP32-CAM, within powered Hub Service. enables facilitating communication Event Grid Trigger integrated Function through Hub.
Язык: Английский
Процитировано
2
Future Internet, Год журнала: 2025, Номер 17(3), С. 118 - 118
Опубликована: Март 6, 2025
The evolution of smart cities is intrinsically linked to advancements in computing paradigms that support real-time data processing, intelligent decision-making, and efficient resource utilization. Edge cloud have emerged as fundamental pillars enable scalable, distributed, latency-aware services urban environments. Cloud provides extensive computational capabilities centralized storage, whereas edge ensures localized processing mitigate network congestion latency. This survey presents an in-depth analysis the integration cities, highlighting architectural frameworks, enabling technologies, application domains, key research challenges. study examines allocation strategies, analytics, security considerations, emphasizing synergies trade-offs between paradigms. present also notes future directions address critical challenges, paving way for sustainable development.
Язык: Английский
Процитировано
0
Current Opinion in Environmental Science & Health, Год журнала: 2025, Номер unknown, С. 100609 - 100609
Опубликована: Март 1, 2025
Язык: Английский
Процитировано
0
Sustainability, Год журнала: 2025, Номер 17(6), С. 2783 - 2783
Опубликована: Март 20, 2025
Leading industries have implemented various strategic initiatives to enhance the resilience and sustainability of their logistics support systems in response series unforeseen disruptions that significantly impacted supply chains (SCs) incurred substantial costs over past few decades. It is essential assess whether incorporating additive manufacturing (AM) technologies into processes—either as a complementary solution or conjunction with existing strategies—can effectively reduce vulnerabilities modern, complex SCs. AM enable use business models distributed manufacturing, opposed centralized potential create significant change traditional SCs by bringing parts products closer customer. The raw materials necessary for production lower than methods. While this provides cost benefit current structure, there are still challenges, such testing final adjustments printing parameters. shorter delivery times compared methods while also reducing distribution costs. This not only enhances service levels, but lowers inventory across all stages SC. Additionally, can help businesses comply increasingly stringent environmental regulations introduced recent Both AM-based processes it smaller ecological footprints making more sustainable alternative.
Язык: Английский
Процитировано
0
Zeitschrift für wirtschaftlichen Fabrikbetrieb, Год журнала: 2025, Номер 120(s1), С. 17 - 24
Опубликована: Март 20, 2025
Abstract The integration of Generative AI (GenAI) and Agentic Architecture offers potential for scalability, automation, improved decision-making in engineering manufacturing. These technologies contribute to efficiency process optimization but face challenges such as data fragmentation interoperability. This paper examines the role addressing these issues, presenting scalable solutions, practical use cases, strategic considerations sustainable AI-driven innovation industrial applications.
Язык: Английский
Процитировано
0
Економіка та суспільство, Год журнала: 2025, Номер 72
Опубликована: Фев. 24, 2025
У статті обґрунтовано вплив сучасних технологій на ефективність діяльності машинобудівних підприємств України. Здійснено аналіз стану машинобудівної галузі, виявлено ключові тенденції, виклики та перспективи її розвитку в умовах економічної нестабільності воєнних викликів. Досліджено рівень впровадження автоматизації, цифрових двійників, штучного інтелекту, Інтернету речей, робототехніки, 3D-друку ERP-систем, які сприяють підвищенню продуктивності, зниженню витрат покращенню фінансових показників підприємств. Виявлено основні бар’єри цифрової трансформації, включаючи недостатнє фінансування, складнощі інтеграції сучасного обладнання дефіцит кваліфікованих кадрів. Окреслено економічних факторів розвиток галузі. Узагальнено технологічного оновлення підприємств, визначено напрями підвищення їх конкурентоспроможності через інноваційних рішень, залучення інвестицій розширення державно-приватного партнерства.
Процитировано
0
Machines, Год журнала: 2025, Номер 13(2), С. 81 - 81
Опубликована: Янв. 23, 2025
Tribology plays a critical role in machining technologies. Friction is an essential factor processes such as composite material and bonding. This short review highlights the recent advancements controlling leveraging tribological phenomena machining. For instance, high-precision increasingly relying on situ observation real-time measurement of tools, test specimens, equipment for effective process control. Modern engineering materials often incorporate functional metastable states, composites dissimilar materials, rather than conventional stable-phase materials. In these cases, effects during can impede precision. On other hand, friction additive manufacturing demonstrates constructive application tribology. Traditionally, understanding mitigating have involved developing physical chemical models individual factors using simulations to inform decisions. However, accurately predicting system behavior has remained challenging due complex interactions between machine components variations initial operational (or deteriorated) states. Recent innovations introduced data-driven approaches that predict without need detailed models. By integrating advanced monitoring technologies learning, methods enable predictions within controllable parameters live data. shift opens new possibilities achieving more precise adaptive
Язык: Английский
Процитировано
0
Springer proceedings in earth and environmental sciences, Год журнала: 2025, Номер unknown, С. 226 - 237
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0
Journal of Manufacturing Processes, Год журнала: 2025, Номер 144, С. 1 - 53
Опубликована: Апрель 15, 2025
Язык: Английский
Процитировано
0
Nuclear Engineering and Design, Год журнала: 2024, Номер 431, С. 113719 - 113719
Опубликована: Ноя. 19, 2024
Язык: Английский
Процитировано
2