Journal of Open Innovation Technology Market and Complexity, Год журнала: 2025, Номер 11(2), С. 100545 - 100545
Опубликована: Май 2, 2025
Язык: Английский
Sci, Год журнала: 2024, Номер 6(4), С. 60 - 60
Опубликована: Окт. 3, 2024
This study explores the evolution and impact of research on challenges opportunities in implementation artificial intelligence (AI) manufacturing between 2019 August 2024. By addressing growing integration AI technologies sector, seeks to provide a comprehensive view how applications are transforming production processes, improving efficiency, opening new business opportunities. A bibliometric analysis was conducted, examining global scientific production, influential authors, key sources, thematic trends. Data were collected from Scopus, detailed review publications carried out identify knowledge gaps unresolved questions. The results reveal steady increase related manufacturing, with strong focus automation, predictive maintenance, supply chain optimization. also highlights dominance certain institutions authors driving this field research. Despite progress, significant remain, particularly regarding scalability solutions ethical considerations. findings suggest that while holds considerable potential for industry, more interdisciplinary is needed address existing maximize its benefits.
Язык: Английский
Процитировано
9
Measurement, Год журнала: 2025, Номер unknown, С. 117191 - 117191
Опубликована: Март 1, 2025
Язык: Английский
Процитировано
1
Advanced Engineering Informatics, Год журнала: 2024, Номер 63, С. 102972 - 102972
Опубликована: Дек. 2, 2024
Язык: Английский
Процитировано
6
Advanced Engineering Informatics, Год журнала: 2025, Номер 65, С. 103102 - 103102
Опубликована: Янв. 9, 2025
Язык: Английский
Процитировано
0
International Journal on Interactive Design and Manufacturing (IJIDeM), Год журнала: 2025, Номер unknown
Опубликована: Янв. 16, 2025
Язык: Английский
Процитировано
0
Communications in computer and information science, Год журнала: 2025, Номер unknown, С. 372 - 398
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0
Sensors, Год журнала: 2025, Номер 25(5), С. 1288 - 1288
Опубликована: Фев. 20, 2025
Artificial intelligence (AI) has become a revolutionary tool in the automotive sector, specifically quality management and issue identification. This article presents systematic review of AI implementations whose target is to enhance production processes within Industry 4.0 5.0. The main methods analyzed are deep learning, artificial neural networks, principal component analysis, which improve defect detection, process automation, predictive maintenance. manuscript emphasizes AI’s role live auto part tracking, decreasing dependance on manual inspections, boosting zero-defect manufacturing strategies. findings indicate that control tools, like convolutional networks for computer vision considerably strengthen fault identification precision while reducing material scrap. Furthermore, allows proactive maintenance by predicting machine defects before they happen. study points out importance incorporating solutions actual ensure consistent adaptation 5.0 requirements. Future investigations should prioritize transparent approaches, cyber-physical system consolidation, enhancement sustainable production. In general terms, changing assurance industry, improving efficiency, consistency, long-term results.
Язык: Английский
Процитировано
0
Опубликована: Март 5, 2025
Small and medium enterprises (SMEs) form the backbone of many economies, yet they often struggle to remain competitive innovative under resource constraints. Rapid advances in artificial intelligence (AI) offer fresh possibilities for SMEs transform their operations, discover untapped market segments, foster resilient business models. AI tools can enhance decision-making reduce operational inefficiencies, from automating repetitive processes generating predictive insights. At same time, ethical considerations data privacy concerns underscore importance implementing responsibly. By embracing cross-sector collaboration, developing robust training programs, advocating supportive policy frameworks, harness AI’s immense potential without compromising social values or organizational integrity. This paper highlights both opportunities challenges poses, proposing actionable strategies that enable drive sustainable, inclusive growth.
Язык: Английский
Процитировано
0
Advances in business information systems and analytics book series, Год журнала: 2025, Номер unknown, С. 225 - 284
Опубликована: Фев. 14, 2025
The construction industry is undergoing a fundamental transformation with the introduction of advanced digital technologies such as twins (DT), artificial intelligence (AI) and optimization. These increase operational efficiency, improve maintenance, promote sustainability. DT enable real-time monitoring optimization projects, while AI analyzes large data sets for predictive maintenance resource Optimization algorithms support efficient planning, scheduling cost reduction. Despite benefits, challenges cybersecurity management remain. This chapter explores synergy between these technologies, their benefits successful implementation in provides recommendations future research.
Язык: Английский
Процитировано
0
Array, Год журнала: 2025, Номер unknown, С. 100393 - 100393
Опубликована: Март 1, 2025
Язык: Английский
Процитировано
0