Machine Intelligence in Mechanical Engineering (Woodhead Publishing Reviews: Mechanical Engineering Series) - Softcover

Über die Autorinnen und Autoren

K. Palanikumar is a professor and principal at Sri Sai Ram Institute of Technology, Chennai, India. He has more than 25 years of experience in teaching and research. He received a “National Best Researcher Award” from ISTE and published more than 100 papers in SCI Journals.

Elango Natarajan is a chartered mechanical engineer (CEng.), who specialized in mechanical engineering design, CAE, optimization, and soft robotics. He has worked for engineering colleges/universities for over 20 years in various academic positions.

Dr. S. Ramesh is an Assistant Professor (SS) in the Department of Mechatronics Engineering, Rajalakshmi Engineering College, Thandalam, Chennai. He has completed his Ph.D. degree in Embedded Systems/ Machine Learning from VIT University, Chennai in 2020, an M. Tech. Degree in Embedded Systems from SRM University, Chennai, Tamilnadu, India in 2011, B.E. Degree from National Engineering College, Kovilpatti, Tamilnadu, India in 2008. In addition to this, he is currently doing Post Doctoral Research in Malaysia. He has over 13 years of Teaching and Research Experience at various Universities and Engineering Colleges around India.

Prof. (Dr.) J. Paulo Davim is a Full Professor at the University of Aveiro, Portugal, with over 35 years of experience in Mechanical, Materials, and Industrial Engineering. He holds multiple distinguished academic titles, including a PhD in Mechanical Engineering and a DSc from London Metropolitan University. He has published over 300 books and 600 articles, with more than 36,500 citations. He is ranked among the world's top 2% scientists by Stanford University and holds leadership positions in numerous international journals, conferences, and research projects.

Von der hinteren Coverseite

Machine Intelligence in Mechanical Engineering explains the latest applications of machine intelligence and data-driven decision-making in mechanical engineering industries. Machine Intelligence is currently a key topic in industrial automation, enabling machines to solve complex engineering tasks and driving efficiencies in the smart production line. Smart preventative maintenance systems can prevent machine downtime, smart monitoring and control can produce more effective workflows with less human intervention. By providing introductory theory, trouble-shooting case studies, detailed algorithms and implementation instructions this interdisciplinary book will help readers to explore additional applications in their own fields. Those with a mechanical background will learn the important tasks related to preprocessing of datasets, feature extraction, verification and validation of machine learning models which unlock these new methods.