Text Analysis on Green Supply Chain Practices of Electronic Companies DOI Creative Commons
Shilpa Balan, Sumali Conlon, Brian J. Reithel

et al.

International Journal of Decision Support System Technology, Journal Year: 2024, Volume and Issue: 16(1), P. 1 - 16

Published: Nov. 1, 2024

The electronics industry is one of the major regulated industries in United States that profoundly impacted by environmental issues. In this study, we use natural language processing (NLP) techniques to analyze reports from companies examine impact on their performance alignment with standards set U.S. Environmental Protection Agency (EPA). We applied collocation, semantic analysis and frequent pattern mining evaluate documented practices green supply chain management used firms industry. results our study indicate NLP can be publicly available highlight some best followed a electronic included are found focused energy efficiency implying likely more environmentally sustainable. tools present opportunities for investigating documenting regulatory compliance.

Language: Английский

Generative AI in AI-Based Digital Twins for Fault Diagnosis for Predictive Maintenance in Industry 4.0/5.0 DOI Creative Commons
Emilia Mikołajewska, Dariusz Mikołajewski, Tadeusz Mikołajczyk

et al.

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(6), P. 3166 - 3166

Published: March 14, 2025

Generative AI (GenAI) is revolutionizing digital twins (DTs) for fault diagnosis and predictive maintenance in Industry 4.0 5.0 by enabling real-time simulation, data augmentation, improved anomaly detection. DTs, virtual replicas of physical systems, already use generative models to simulate various failure scenarios rare events, improving system resilience prediction accuracy. They create synthetic datasets that improve training quality while addressing scarcity imbalance. The aim this paper was present the current state art perspectives using AI-based DTs 4.0/5.0. With GenAI, enable proactive minimize downtime, their latest implementations combine multimodal sensor generate more realistic actionable insights into performance. This provides operational profiles, identifying potential traditional methods may miss. New area include incorporation Explainable (XAI) increase transparency decision-making reliability key industries such as manufacturing, energy, healthcare. As emphasizes a human-centric approach, DT can seamlessly integrate with human operators support collaboration decision-making. implementation edge computing increases scalability capabilities smart factories industrial Internet Things (IoT) systems. Future advances federated learning ensure privacy exchange between enterprises diagnostics, evolution GenAI alongside ensuring long-term validity. However, challenges remain managing computational complexity, security, ethical issues during implementation.

Language: Английский

Citations

4
Review of Machine Learning applications in Additive Manufacturing DOI Creative Commons

Sirajudeen Inayathullah,

Raviteja Buddala

Results in Engineering, Journal Year: 2024, Volume and Issue: 25, P. 103676 - 103676

Published: Dec. 8, 2024

Language: Английский

Citations

16
Towards cyber-physical internet: A systematic review, fundamental model and future perspectives DOI Creative Commons
Hang Wu, Ming Li, Chenglin Yu

et al.

Transportation Research Part E Logistics and Transportation Review, Journal Year: 2025, Volume and Issue: 197, P. 104051 - 104051

Published: March 5, 2025

Language: Английский

Citations

1
Review of the 6G-Based Supply Chain Management within Industry 4.0/5.0 Paradigm DOI Open Access
Izabela Rojek, Małgorzata Jasiulewicz–Kaczmarek, Adrianna Piszcz

et al.

Electronics, Journal Year: 2024, Volume and Issue: 13(13), P. 2624 - 2624

Published: July 4, 2024

The pace of technological development, including smart factories within Industry 4.0/5.0, means that the vagaries supply chains observed previously cannot be repeated. automation and computerization chains, asset tracking, simulation, prediction disruption through artificial intelligence (AI) are becoming a matter course. In selected countries, this will facilitated by sixth-generation mobile networks planned for full deployment in 2030. 6G-based intelligent chain management 4.0/5.0 paradigm ensure not only greater fluidity supply, but also faster response to changes market availability or prices, allowing substitutes found taken into account production process its logistical provisioning. article outlines key research development trends area identifies priority directions, taking advantages opportunities offered Industrial Internet Things (IIoT) machine learning (ML). emergence 6G technology transform with unprecedented speed, connectivity, efficiency. This improve visibility, automation, collaboration while supporting sustainable safe operations. As result, companies able design, plan, operate their precision, flexibility, responsiveness, ultimately leading more robust agile ecosystem.

Language: Английский

Citations

8
Digital Twin Technology and Social Sustainability: Implications for the Construction Industry DOI Open Access
Hossein Omrany, Armin Mehdipour, Daniel Oteng

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(19), P. 8663 - 8663

Published: Oct. 7, 2024

To date, a plethora of research has been published investigating the value using Digital Twin (DT) technology in construction industry. However, contribution DT to promoting social sustainability industry largely unexplored. Therefore, current paper aims address this gap by exploring untapped potential advancing within end, comprehensive systematic literature review was conducted, which identified 298 relevant studies. These studies were subsequently analysed with respect their use supporting sustainability. The findings indicated that contributed 8 17 UN Sustainable Development Goals (SDGs), strong focus on SDG11 (77 publications), followed SDG3 and SDG9, 58 48 studies, respectively, focusing health well-being fostering resilient infrastructure innovation. Other contributions for SDG13 (30 studies), SDG7 (27 SDG12 (26 SDG4 (21 SDG6 (11 covering areas such as climate action, responsible consumption, affordable energy, quality education, clean water sanitation. This also proposes future directions further enhance include (i) enhancing inclusivity diversity, (ii) workforce safety well-being, (iii) training skill development, (iv) policy regulatory support, (v) cross-disciplinary collaboration.

Language: Английский

Citations

6
Text Analysis on Green Supply Chain Practices of Electronic Companies DOI Creative Commons
Shilpa Balan, Sumali Conlon, Brian J. Reithel

et al.

International Journal of Decision Support System Technology, Journal Year: 2024, Volume and Issue: 16(1), P. 1 - 16

Published: Nov. 1, 2024

The electronics industry is one of the major regulated industries in United States that profoundly impacted by environmental issues. In this study, we use natural language processing (NLP) techniques to analyze reports from companies examine impact on their performance alignment with standards set U.S. Environmental Protection Agency (EPA). We applied collocation, semantic analysis and frequent pattern mining evaluate documented practices green supply chain management used firms industry. results our study indicate NLP can be publicly available highlight some best followed a electronic included are found focused energy efficiency implying likely more environmentally sustainable. tools present opportunities for investigating documenting regulatory compliance.

Language: Английский

Citations

0