Artificial Intelligence and Machine Learning

Pioneering the Next Generation of Mechanical Engineering
1. Auflage 2026
ISBN: 978-1-041-06634-7
Verlag: Taylor & Francis Ltd

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

Artificial Intelligence and Machine Learning in Mechanical Engineering explores the transformative impact of these technologies across critical domains, including design optimization, process optimization, additive manufacturing, material science, metrology, and smart materials.

Readers will discover how AI-driven tools enable engineers to create complex, lightweight structures through enhanced simulation and optimization techniques, while machine learning algorithms improve quality control and in-process monitoring in manufacturing environments. The book explores the application of these technologies in predicting material properties, accelerating the discovery of novel materials with superior mechanical performance, and facilitating the creation of intricate 3D-printed geometries. Additionally, it demonstrates how AI/ML integration supports the development of intelligent materials and structures, streamlines manufacturing processes, and enables data-driven decision-making that enhances efficiency, sustainability, and innovation across the mechanical engineering landscape.

This book is designed to support researchers, engineers, scholars, technical experts, and specialists in understanding and leveraging the integration of AI/ML within the field of mechanical engineering.

Zielgruppe

Postgraduate and Professional Practice & Development

Autoren/Hrsg.

Jani, S.P.

Rajan, B. Muthu Chozha

P S, Shijin Kumar

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik Fertigungstechnik
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Maschinenbau
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

Part 1: AI & ML Application in Materials and Smart Manufacturing
1. AI and ML Innovations in Mechanical Engineering for Future Sustainability
2. Smart Engineering: AI and ML for Advanced Mechanical Design Optimization
3. Smart Materials and AI: Shaping the Future of Mechanical Engineering
4. AI/ML-optimization in Tribology Applications
5. Prediction of Processes in Machinability Study
6. Surface Morphology Studies and Crack Prediction using Deep Learning
7. Prediction of Process Parameters in 3D Printed Material
Part 2: AI/ML Transformations in Mechanical Engineering
8. Integrating AI and ML in Mechanical Engineering for Modern Advancements
9. Energy Storage Design
10. AI & ML Usages in Future Manufacturing Industries

11. AI & ML in Industries automation techniques
12. Battery Management System for EVs
13. Quality Control Approaches using AI & ML

Über Autor(innen)

S. P. Jani, PhD, is an Associate Professor in the Department of Mechanical Engineering at Marri Laxman Reddy Institute of Technology and Management, Hyderabad, India, where he has served as an educator and researcher since 2012. He completed his doctorate on the machinability of hybrid fiber/epoxy composites using abrasive water jet machining at Anna University, Chennai, Tamil Nadu, India, where he also earned his undergraduate and postgraduate degrees. His research interests encompass additive manufacturing, advanced manufacturing, machinability studies, and machining of natural fiber composites. Dr. Jani served as Editor of Materials Science and Engineering for the International Conference on Challenges in Mechanical Engineering (2021), has authored more than 50 papers in reputed international journals, and serves as a reviewer for more than 20 international journals.

B. Muthu Chozha Rajan, PhD, is a Professor in the Department of Mechanical Engineering and Sethu Research and Innovation Centre at Sethu Institute of Technology, Virudhunagar, Tamil Nadu, India, where he has served as an educator and researcher since 2008. He completed his doctorate on carbon fiber reinforced aluminum laminates, and his research interests include additive manufacturing, natural fiber composites, and AI/ML applications in composite materials. With over 16 years of teaching experience, Dr. Rajan has significantly advanced research and education in mechanical engineering, earning recognition through prestigious awards including the Young Scientist Award. He has authored more than 20 papers in reputed international journals and serves as a reviewer for more than 10 international journals.

P. S. Shijin Kumar, PhD, is an Associate Professor in the Department of Electronics and Communication Engineering at A.R.J College of Engineering and Technology, Mannargudi, India, bringing more than 15 years of teaching experience and 1 year of industrial experience to his role as educator and researcher. He completed his doctorate in Electronics and Communication Engineering from Noorul Islam University in 2018, earned his M.E. in Communication Systems from Anna University in 2009, and obtained his B.Tech degree in Electronics and Communication Engineering from the University of Kerala, India in 2006. His research interests include image processing, embedded systems, data science, and deep learning. Dr. Kumar has authored more than 15 papers in reputed international journals and conference proceedings and is a life member of ISTE.