
Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing
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Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing provides an extensive and in-depth exploration of the intersection of data analytics, artificial intelligence, and predictive maintenance in the manufacturing industry and covers fundamental concepts, advanced techniques, case studies, and practical applications. Using a multidisciplinary approach, this book recognizes that predictive maintenance in manufacturing requires collaboration among engineers, data scientists, and business professionals and includes case studies from various manufacturing sectors showcasing successful applications of predictive maintenance. The real-world examples explain the useful benefits and ROI achieved by organizations. The emphasis is on scalability, making it suitable for both small and large manufacturing operations, and readers will learn how to adapt predictive maintenance strategies to different scales and industries. This book presents resources and references to keep readers updated on the latest advancements, tools, and trends, ensuring continuous learning.
Serving as a reference guide, this book focuses on the latest advancements, trends, and tools relevant to predictive maintenance and can also serve as an educational resource for students studying manufacturing, data science, or related fields.
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Shrikant Tiwari, PhD, is an Associate Professor in the Department of Computer Science and Engineering (CSE), School of Computing Science and Engineering (SCSE) at Galgotias University, Greater Noida, Uttar Pradesh, India. Dr. Tiwari also is a Senior Member of IEEE. He earned a PhD in computer science and engineering at the Indian Institute of Technology (Banaras Hindu University), Varanasi, India, in 2012 and an MTech in computer science and technology at the University of Mysore, India, in 2009. He has authored or co-authored more than 75 national and international journal publications, book chapters, and conference articles. He has five patents filed to his credit. His research interests include machine learning, deep learning, computer vision, medical image analysis, pattern recognition, and biometrics. Dr. Tiwari is a member of ACM, IET, FIETE, CSI, ISTE, IAENG, and SCIEI. He is also a guest editorial board member and a reviewer for many international journals of repute.
Gulshan Soni, PhD, is an Associate Professor and Principal in Charge in the Computer Science Engineering Department at the School of Engineering and Information Technology, Mahaveer Academy of Technology and Science University (MATS University), Raipur, India. He earned a PhD at Pondicherry University, India, along with a BTech at the National Institute of Technology (NIT), Raipur, India, and an ME at the National Institute of Technical Teachers Training and Research (NITTTR), Chandigarh, India. His research interests include wireless sensor networks, wireless body area networks, MAC protocols, and routing protocols, as well as distributed computing. Dr. Soni has published extensively in reputable journals and presented at national and international conferences. With over eight years of teaching experience, he brings valuable expertise to both government and private academic institutions in India.
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