Buch, Englisch, 180 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 431 g
Challenges, Improvements, and Case Studies
Buch, Englisch, 180 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 431 g
Reihe: Intelligent Manufacturing and Industrial Engineering
ISBN: 978-1-032-47839-5
Verlag: CRC Press
Technology Innovation Pillars for Industry 4.0: Challenges, Improvements, and Case Studies discusses the latest innovations in the application of technologies to Industry 4.0 and the nine pillars and how they relate, support, and bridge the gap between the digital and physical worlds we now live in.
This book discusses each of the nine pillars and the roles they play in the rapid transformation of the design and operation, and offers applications and case studies supporting Industry 4.0 technologies. It presents the supply chain organizational activities utilizing cyber- physical systems architectures and talks about the advantages of intelligent manufacturing and the ability to proactively detect and respond to events, to improve quality and yield, reduce downtime, and lead to better overall equipment effectiveness among other advantages in smart factory operations.
This reference book provides a great resource for undergraduate and graduate students, industrial and manufacturing engineers, and engineers of related disciplines along with business professionals, explaining what the nine pillars are and how they relate to Industry 4.0 and smart factories.
Zielgruppe
Professional Reference and Undergraduate Advanced
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Technik Allgemein Industrial Engineering
- Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik Fertigungstechnik
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken
Weitere Infos & Material
1. Role of Artificial Intelligence in Telecommunication Systems: A Healthcare Perspective. 2. An Intelligent System Utilizing Bipolar Fuzzy Logic for Ensuring Semantic Interoperability and Privacy Preservation in Healthcare Systems. 3. Graph Optimizations in Neural Networks by ONNX Model. 7.Convolutional Neural Network Architecture for Accurate Plant Classification. 5. Big Data Visualizing with Augmented and Virtual Reality: Challenges and Research Agenda. 6. Mathematical Model for Service-Selection Optimization and Scheduling in Cloud Manufacturing Using Sub-Task Scheduling With Fuzzy Inference Rule. 7. Social Media Initiatives through IoT to Link the Bridge between Industrial Demands with Higher Education Millennial Students through Experience Learning. 8. Analyzing Consumer Product Feedback Dynamics with Confidence Intervals. 9. Amplifying the Effectiveness of a Learning Management System: Exploring the Impact of NEP-Compliant Curriculum Changes on Higher Education Institutions. 10. The Future of Immersive Experience: Exploring Metaverse Application Development Technologies and Tools.