Buch, Englisch, 160 Seiten, Format (B × H): 156 mm x 234 mm
Solutions for Surface Engineering
Buch, Englisch, 160 Seiten, Format (B × H): 156 mm x 234 mm
Reihe: Advances in Surface Engineering and Tribology
ISBN: 978-1-041-24289-5
Verlag: Taylor & Francis Ltd
Tribology for Industry 4.0: Solutions for Surface Engineering explores how data analytics, AI, IoT, and smart sensors can be combined to maximize tribological performance in modern industrial systems. It further examines the use of ML and big data analytics to enhance wear management, friction control, and surface engineering efficiency.
Covering adaptive coatings, smart lubrication systems, and predictive maintenance techniques, the book explains how they dynamically respond to operating conditions, minimizing downtime and maximizing efficiency. It emphasizes eco-friendly tribology techniques to help industries comply with environmental regulations and lessen their carbon footprint, such as cutting energy use, improving lubrication, and implementing sustainable materials. Real-world examples and case studies are included to demonstrate successful implementation in manufacturing, automotive, aerospace and energy sectors.
Researchers and graduate students studying surface engineering, lubrication, and wear management will benefit from this book.
Zielgruppe
Postgraduate
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Technologie der Oberflächenbeschichtung
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
- Technische Wissenschaften Maschinenbau | Werkstoffkunde Maschinenbau Tribologie
Weitere Infos & Material
1. Introduction to Tribology 4.0 and Surface Engineering in the Smart Manufacturing Era. 2. Transforming Tribological Systems through Digital Technologies, Digital Twins, and Innovations. 3. Advanced Smart Coatings and Innovative Surface Treatment Technologies. 4. Optimizing Maintenance Strategies in Tribology Using Predictive Technologies and Real-World Implementations. 5. Enhancing Tribological Performance with Artificial Intelligence and Machine Learning Techniques. 6. Applications of Tribological Principles in Additive Manufacturing Technologies. 7. Leveraging Data Analytics and System Optimization in Tribological Processes. 8. Addressing Challenges and Exploring Opportunities in Implementing a Smart Tribology System. 9. Case Studies and Practical Real-World Examples in Smart Tribology. 10. Emerging Future Trends and Innovations in Tribology for the Age of Industry 4.0, and Future Outlook on Industry 5.0.




