Smart Materials and Manufacturing Technologies for Sustainable Development (eng)

This book offers a comprehensive exploration of " Smart Materials and Manufacturing Technologies for Sustainable Development “delves into the dynamic intersection of innovative materials, intelligent manufacturing, and sustainable practices, presenting a vital resource for researchers, engineers, and professionals seeking to shape a greener and more advanced future.

Covering a wide range of topics, the book delves into the latest advancements in materials processing, with a particular focus on cutting-edge technologies such as advanced manufacturing, nanotechnology, and materials. The book addresses the pressing need for sustainable manufacturing practices, unveiling eco-friendly approaches that reduce environmental impact without compromising performance. Chapters dedicated to artificial intelligence and machine learning illuminate how these game-changing technologies facilitate manufacturing, materials characterization, and process optimization.

By integrating IoT, Industry 4.0, robotics, and automation, this book highlights the growing synergy between intelligent manufacturing and sustainable materials, paving the way for increased efficiency and productivity. It examines the importance of advanced materials characterization techniques, empowering researchers to gain deeper insights into materials' properties, behaviour, and potential applications.

With its multidisciplinary approach, this book appeals to a diverse audience, including materials scientists, manufacturing engineers, environmentalists, policymakers, and students eager to contribute to a more sustainable and technologically advanced society.

Dr Vijeesh Vijayan is a highly proficient professional in the field of Materials Engineering and Welding Metallurgy, with a remarkable track record of achievements. With a Ph.D. in Metallurgical and Materials Engineering from NITK, Surathkal and 12+ years of research experience, Dr Vijeesh has established himself as an expert in their field of additive manufacturing, welding, and casting. He worked as a post-doctoral in Dong-Eui University Busan, South Korea for a span of one year from December 2016. To his credit he has had opportunity to work on several industry sponsored projects.  He has published more than 50 papers in renowned peer-reviewed journals, conducted groundbreaking research, and made valuable contributions to topics such as cooling curve analysis, heat treatment of aluminium alloys, and material characterization.
In addition to his academic accomplishments, Dr Vijeesh has excelled in securing and managing research projects, receiving sponsored projects from government as well as private sectors. He has been honoured with prestigious awards, including William Spraragen Memorial Award for year 2021 from American Welding Society (AWS).  

Dr. Rashmi P Shetty is an accomplished and dedicated academician in the field of Mechanical Engineering. With a passion for research and teaching, she has made significant contributions to the study of wind power prediction, optimization, and modelling. Dr. Shetty currently holds the position of Assistant Professor in the Department of Mechanical Engineering at NMAM Institute of Technology, Nitte, situated in Udupi, Karnataka, India.
Driven by her curiosity to explore cutting-edge research areas, Dr. Shetty embarked on a Ph.D. at NITK, Surathkal, focusing on Artificial Neural Network (ANN) modelling and optimization of power output from horizontal axis wind turbines. In 2019, she successfully defended her thesis, becoming a Ph.D. holder in her chosen field.
Throughout her academic journey, Dr. Rashmi P Shetty has demonstrated exceptional research capabilities and a flair for publishing her findings in reputable journals and international conferences. Her research papers cover diverse topics, such as wind power prediction, feature selection, parameter optimization, and artificial intelligence applications in wind energy and other engineering domains. Her contributions have been recognized with several awards, including the prestigious gold medal during her M.Tech studies and best paper awards for her outstanding research publications.
Besides her academic achievements, Dr. Rashmi P Shetty has held an editorial role as a Guest Editor for Elsevier Materials Today Proceedings, showcasing her proficiency in her field and her commitment to contributing to the academic community. Dr. Shetty's dedication to research, teaching, and mentoring aspiring engineers has earned her respect and recognition among her peers and students alike. With her expertise and passion for renewable energy and artificial intelligence applications, she continues to be an influential figure in the realm of Mechanical Engineering and contributes significantly to the advancement of the field.

Dr. Srinivasa Pai P. is currently working as Professor & Head in the Dept.of Mechanical Engg. at NMAMIT, Nitte, Karnataka.  He obtained his B.E. in Industrial & Production Engg., from NMAMIT, Nitte in 1993 and M.Tech in Maintenance Engg., from SJCE, Mysore in 1996. He obtained his Ph.D in Mechanical Engg., from Mysore University in 2004. He has 25 years of teaching and research experience. He has 210 papers in various National and International Journals and Conferences. He went to Utah State University, Utah, USA as a Post-Doctoral Research Scholar in Metal Machining for a period of 1 year during 2009–10. He is a life Member of several professional societies. He has won the following awards: Indian Society for Technical Education (ISTE) – SGSITS National Award: for The Research Work done by Young Teachers (Below 35) of Engineering Colleges for the year 2005 and Air India BOLT (Broad Outlook – Learner Teacher) Award for the District of Udupi for the year 2006.  He won the Appreciation Certificate for guiding the II Best M. Tech Thesis in Mechanical Engineering during 2012. He won the “Best Researcher Award”, instituted by NMAMIT, Nitte in 2013.  Some of his areas of interest are high speed machining, surface integrity studies, difficult to machine materials, condition monitoring, artificial neural networks, signal processing, optimization techniques and engineering education.