Опубликована: Ноя. 26, 2024
Язык: Английский
Benchmarking An International Journal, Год журнала: 2025, Номер unknown
Опубликована: Янв. 23, 2025
Purpose Industries have been the most significant contributor to carbon emissions since beginning of Industrial Revolution. The transition Industry 5.0 (I5.0) marks a pivotal moment in industrial revolution, which aims reconcile productivity with environmental responsibility. As concerns about decline quality increase and demand for sustainable methods intensifies, experts recognize shift toward I5.0 as crucial turning point. Design/methodology/approach This review study explores convergence green technological advancements evolving landscape I5.0, thereby presenting roadmap neutrality. Through an extensive analysis literature spanning from 2012 2024, sourced Scopus database, research unravels transformative potential innovations, artificial intelligence, supply chain management metaverse. Findings findings underscore urgent imperative integrating technologies into fabric highlighting opportunities challenges inherent this endeavor. Furthermore, provides insights tailored policymakers, regulators, researchers stakeholders, fostering informed decision-making carbon-neutral future. Originality/value serves call action, urging collective efforts harness innovation betterment industry environment.
Язык: Английский
Процитировано
3
IEEE Access, Год журнала: 2024, Номер 12, С. 116162 - 116201
Опубликована: Янв. 1, 2024
Industry 5.0 is an evolving concept that aims to enhance the way modern factories operate by seeking long-term growth, production efficiency and well-being of industrial workers. Human-centricity, sustainability resilience are three pillars 5.0, which developed on 4.0 enabling technologies. One most compelling technologies help implement communications architecture proposed blockchain, can provide trustworthy, secured decentralized information different domains. This article provides analysis transition between paradigms. Moreover, it examines benefits challenges arise when using blockchain develop applications analyzes design factors should be considered developing this type applications. Furthermore, presents a thorough review relevant blockchain-based for pillars. Therefore, main goal comprehensive detailed guide future developers allows determining how might benefit next generation human-centric, sustainable, resilient
Язык: Английский
Процитировано
9
Flexible Services and Manufacturing Journal, Год журнала: 2024, Номер unknown
Опубликована: Ноя. 30, 2024
Abstract Industry 5.0 (I5.0) marks a transformative shift toward integrating advanced technologies with human-centric design to foster innovation, resilient manufacturing, and sustainability. This study aims examine the evolution collaborative dynamics of I5.0 research through bibliometric analysis 942 journal articles from Scopus database. Our findings reveal significant increase in research, particularly post-2020, yet highlight fragmented collaboration networks noticeable gap between institutions developed developing countries. Key thematic areas identified include human-robot collaboration, data management security, AI-driven sustainable practices. These insights suggest that more integrated approach is essential for advancing I5.0, calling strengthened global collaborations balanced emphasis on both technological elements fully realize its potential driving industrial provides first comprehensive offering valuable researchers practitioners.
Язык: Английский
Процитировано
9
Advances in business strategy and competitive advantage book series, Год журнала: 2025, Номер unknown, С. 35 - 68
Опубликована: Янв. 31, 2025
The incorporation of Artificial Intelligence (AI) within Industry 5.0 significantly enhances resilience among small businesses. This chapter explores how AI transforms resilience, sustainability, and customer engagement strategies. With Small businesses can analyze large datasets to identify risks, optimize operations, deliver personalized experiences that align with consumer expectations. AI's ability process data efficiently allows anticipate market changes navigate uncertainties. Additionally, adopting fosters a culture encouraging employees embrace change. also supports sustainable practices by optimizing resource use reducing waste. Customer improves through AI-driven personalization, allowing tailor products services individual preferences. concludes recommendations for businesses: invest in employee training collaboration, ensure leadership commitment, prioritize foster adaptability thrive today's 5.0.
Язык: Английский
Процитировано
1
Frontiers in Nutrition, Год журнала: 2025, Номер 12
Опубликована: Март 13, 2025
This study aims to explore the transformative role of Artificial Intelligence (AI) in food manufacturing by optimizing production, reducing waste, and enhancing sustainability. review follows a literature approach, synthesizing findings from peer-reviewed studies published between 2019 2024. A structured methodology was employed, including database searches inclusion/exclusion criteria assess AI applications manufacturing. By leveraging predictive analytics, real-time monitoring, computer vision, streamlines workflows, minimizes environmental footprints, ensures product consistency. The examines AI-driven solutions for waste reduction through data-driven modeling circular economy practices, aligning industry with global sustainability goals. Additionally, it identifies key barriers adoption—including infrastructure limitations, ethical concerns, economic constraints—and proposes strategies overcoming them. highlight necessity cross-sector collaboration among stakeholders, policymakers, technology developers fully harness AI's potential building resilient sustainable ecosystem.
Язык: Английский
Процитировано
1
Sustainability, Год журнала: 2024, Номер 16(13), С. 5317 - 5317
Опубликована: Июнь 21, 2024
This paper addresses a pragmatic and well-articulated qualitative methodology for the identification, prioritization, consultation of stakeholder groups higher education institution as key element organization in context digital transformation Industry 5.0. First, identification phase required technological surveillance competitive intelligence, which allowed defining organization’s stakeholders their characteristics. Then, prioritization was performed to determine that potentially will have greatest impact on achieving institution’s strategic objectives targets Sustainable Development Goals prioritized by institution, those who be most affected (positively or negatively) HEI activities. Finally, different methods tools were used consulting internal external stakeholders, according type relationship with each group, understanding perceptions issues such gender equity, mental health, regenerative economy, diversity training. The results are then presented terms organizational context, where concept group defined dynamics selected HEI; include students, employees, academic research sector, public business social community, archdiocese diocese, alumni, donors, benefactors. approach enabled became priority university’s actions towards future. Although is mainly qualitative, can represent high degree subjectivity, exercise provides organizations inputs decision making aligned needs expectations. Using help experience structural changes reflected improved alignment, understanding, satisfaction stakeholders’ expectations needs, enhancement reputation, risk conflict mitigation, consolidation long-term healthy trustworthy relationships, Society 5.0, human-centered solutions expected.
Язык: Английский
Процитировано
5
Future Internet, Год журнала: 2024, Номер 16(9), С. 345 - 345
Опубликована: Сен. 21, 2024
This paper explores the role that 5G, WiFi 7, and Time-Sensitive Networking (TSN) play in driving smart manufacturing as a fundamental part of Industry 4.0 vision. It provides an in-depth analysis each technology’s application industrial communications, with focus on TSN its key elements enable reliable secure communication networks. In addition, this includes comparative study these technologies, analyzing them based several use cases, supported secondary applications, industry adoption, current market trends. concludes by highlighting challenges future directions for adopting technologies networks emphasizes their importance realizing vision within context manufacturing.
Язык: Английский
Процитировано
5
Journal of Cleaner Production, Год журнала: 2024, Номер 468, С. 142983 - 142983
Опубликована: Авг. 1, 2024
Язык: Английский
Процитировано
4
Energies, Год журнала: 2025, Номер 18(9), С. 2345 - 2345
Опубликована: Май 3, 2025
Industry 5.0 transforms industrial ecosystems via artificial intelligence (AI), human–machine collaboration, and sustainability-focused innovations. This systematic literature review examines 5.0′s role in energy transition through digital transformation, sustainable supply chains, efficiency strategies. Key findings highlight AI-driven smart grids, blockchain-enabled transactions, twin simulations as enablers of low-carbon, adaptive operations. uniquely integrates technological, managerial, policy perspectives, providing actionable insights for policymakers industry leaders. enhances innovative management, renewable integration, flexible distribution, strengthening resilience sustainability. It fosters environmental responsibility, social impact, circular economy principles, laying the foundation a low-carbon accelerating global transition.
Язык: Английский
Процитировано
0
Sustainability, Год журнала: 2025, Номер 17(3), С. 827 - 827
Опубликована: Янв. 21, 2025
Addressing resource scarcity and climate change necessitates a transition to sustainable consumption circular economy models, fostering environmental, social, economic resilience. This study introduces deep learning-based ensemble framework optimize initial public offering (IPO) performance prediction while extending its application processes, such as recovery waste reduction. The incorporates advanced techniques, including hyperparameter optimization, dynamic metric adaptation (DMA), the synthetic minority oversampling technique (SMOTE), address challenges class imbalance, risk-adjusted enhancement, robust forecasting. Experimental results demonstrate high predictive performance, achieving an accuracy of 76%, precision 83%, recall 75%, AUC 0.9038. Among methods, Bagging achieved highest (0.90), outperforming XGBoost (0.88) random forest (0.75). Cross-validation confirmed framework’s reliability with median 0.85 across ten folds. When applied scenarios, model effectively predicted sustainability metrics, R² values 0.76 for both reduction low mean absolute error (MAE = 0.11). These highlight potential align financial forecasting environmental objectives. underscores transformative learning in addressing challenges, demonstrating how AI-driven models can integrate goals. By enabling IPO predictions enhancing outcomes, proposed aligns Industry 5.0’s vision human-centric, data-driven, industrial innovation, contributing resilient growth long-term stewardship.
Язык: Английский
Процитировано
0