Artificial Intelligence in Tribology

1. Auflage 2026
ISBN: 978-1-041-03528-2
Verlag: Taylor & Francis Ltd

Buch, Englisch, 352 Seiten, Format (B × H): 156 mm x 234 mm

Reihe: Advances in Surface Engineering and Tribology

Artificial Intelligence in Tribology presents the use of machine learning AI, neural networks, and optimization algorithms in studying friction, wear, and lubrication. It explores the selection of materials, modeling of the tribo-system, prediction of tribological behavior, and assessment and optimization of performance across numerous systems.

Addressing tribological problems from macroscale to nanoparticles, the book discusses AI-driven methods to improve productivity, detect disasters, and support sustainable engineering. Case studies from various industries – such as automotive, aerospace, renewable energy, and marine engineering – highlight the transformative impact of AI in real-world scenarios.

This book will interest researchers and graduate students studying AI integration and advances in surface engineering, tribology, and materials science.

Zielgruppe

Academic, Postgraduate, and Undergraduate Advanced

Autoren/Hrsg.

Vasudev, Hitesh

Singh, Jashanpreet

Fachgebiete

• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Technologie der Oberflächenbeschichtung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Maschinenbau Tribologie
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Technische Mechanik | Werkstoffkunde
• Naturwissenschaften Physik Mechanik Energie

Inhaltsverzeichnis

1. Introduction to Tribology and Artificial Intelligence. 2. AI Foundations for Tribology. 3. Machine Learning for Predictive Modelling in Tribology. 4. AI-Driven Surface Engineering. 5. Optimization Techniques for Lubrication Design. 6. Tribological and Wear Analysis Using Neural Networks. 7. Applications of AI-Tribology in Aerospace and Renewable Energy. 8. Sustainability through Artificial Intelligence in Tribology. 9. Artificial Intelligence-based Emerging Tools and Techniques in Tribology. 10. Case Study on Artificial Intelligence in Automotive Tribology. 11. Case Study on Artificial Intelligence in Biomedical Tribology. 12. AI-Driven Predictive Maintenance and Wear Prediction in Tribology: Industrial Case Studies and Applications. 13. Artificial Intelligence in Marine Tribology: Applications, Challenges, and Future Directions. 14. Challenges and Future Directions in AI and Tribology.

Über Autor(innen)

Dr. Jashanpreet Singh is an Assistant Professor at Chandigarh University, Mohali, India. In 2019, he obtained his PhD degree from Thapar Institute of Engineering and Technology, Patiala, India. He has several years of both teaching and industry experience. His area of research includes tribology-solid particle erosion, power plant engineering, ash conveying, thermal spray coatings, CFD simulation, composites, and materials characterization. Dr. Singh has authored over hundred research publications indexed in SCOPUS database. He has authored and edited 5 books with CRC Press. He serves as a reviewer for various journals, and he is a member of AICTSD, IAENG, and NITTSD.

Dr. Hitesh Vasudev is a Professor in the School of Mechanical Engineering at Lovely Professional University, Phagwara, Punjab, India. He earned his Ph.D. degree in 2018 from Guru Nanak Dev Engineering College, Ludhiana, India. His primary research interests are surface engineering, with particular emphasis on thermal spray technologies; development of nanostructured, multimodal, and high-entropy alloy coatings for high-temperature oxidation and corrosion resistance; thermal barrier coatings (TBCs); and microwave processing of materials. Dr. Vasudev has made significant scholarly contributions to the field of thermal spray coatings through numerous publications in reputed international journals.