Technology Innovation Pillars for Industry 4.0 by Elngar, Ahmed A.; Thillaiarasu, N.; Saravanan, T.;

Challenges, Improvements, and Case Studies

Sorozatcím: Intelligent Manufacturing and Industrial Engineering;

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A termék adatai:

Kiadás sorszáma 1
Kiadó CRC Press
Megjelenés dátuma 2024. július 31.

ISBN 9781032478395
Kötéstípus Keménykötés
Terjedelem180 oldal
Méret 234x156 mm
Súly 453 g
Nyelv angol
Illusztrációk 111 Illustrations, black & white; 31 Halftones, black & white; 80 Line drawings, black & white; 18 Tables, black & white

Kategóriák

Rövid leírás:

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 live in.

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Hosszú leírás:

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.

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Tartalomjegyzék:

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.

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