1st Edition
Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing
In this smart era, Data Analytics and Artificial Intelligence (AI) play an important role in Predictive Maintenance (PdM) within the manufacturing industry. This innovative approach aims to optimize maintenance strategies by predicting when equipment or machinery is likely to fail so that maintenance can be performed in time to prevent costly breakdowns. This book will contain up-to-date information on predictive maintenance and the latest advancements, trends, and tools required to reduce costs and save time for manufacturers and industries.
Data Analytics and Artificial Intelligence for Predictive Maintenance in 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 multi-disciplinary 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. Emphasizes is on scalability, making it suitable for both small and large manufacturing operations. Readers will learn how to adapt predictive maintenance strategies to different scales and industries.
The 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.
1. Introduction to Machine Learning Fundamentals. 2. AI Applications In Production. 3. Data Analytics and Artificial Intelligence for Predictive Maintenance in Manufacturing. 4. Scalability and Deployment of Emerging Technologies in Predictive Maintenance. 5. AI Models for Predictive Maintenance. 6. Role of Machine Learning and Deep Learning Models for Predictive Maintenance. 7. Data Analytics and AI for Predictive Maintenance in Pharmaceutical Manufacturing. 8. Real-Time Violence Detection in Video Streams: Exploit-ing ResNet-50 for Enhanced Accuracy. 9. The Analytics Advantage: Sculpting Tomorrow’s Decisions Today. 10. Using Ensemble Model to Reduce Downtime in Manufacturing Industry: An Advanced Diagnostic Framework for Early Failure Detection. 11. Use Cases of Digital Twin in Smart Manufacturing. 12. Data Analytics and Visualization in Smart Manufacturing using AI based Digital Twins. 13. Business Analytics, Business Intelligence, and Paradigm Shift in Organizational Structure: Perspective from Selected High-Performance Technology-Driven Businesses in Emerging Economy. 14. Applications of Human Computer Interaction, Explainable Artificial Intelligence and Conversational Artificial Intelligence in Real Life Sectors. 15. AI for Industry 4.0 with Real World’s problems. 16. Industry 4.0 in Manufacturing, Communication, Transportation, Healthcare. 17. Advancing IoT Anomaly Detection Through Dynamic Learning.
Biography
Amit Kumar Tyagi is working as an Assistant Professor, at the National Institute of Fashion Technology, India. Previously he has worked as Assistant Professor (Senior Grade 2), and Senior Researcher at Vellore Institute of Technology (VIT), India for the period of 2019-2022. He received his Ph.D. Degree (Full-Time) in 2018 from Pondicherry Central University, 605014, Puducherry, India. Dr. Tyagi has published over 100 papers in refereed high-impact journals, conferences, and books, and some of his articles have been awarded best paper awards. Also, he has filed more than 20 patents in the areas of Deep Learning, the Internet of Things, Cyber-Physical Systems, and Computer Vision and has edited more than 20 books. He has authored 3 Books and was the winner of the Faculty Research Award for 2020, 2021, and 2022. given by Vellore Institute of Technology, India. His current research focuses on Next Generation Machine Based Communications, Blockchain Technology, Smart and Secure Computing, and Privacy. He is a regular member of the ACM, IEEE, MIRLabs, Ramanujan Mathematical Society, Cryptology Research Society, Universal Scientific Education and Research Network, CSI, and ISTE.
Shrikant Tiwan received his Ph.D. from the Department of Computer Science, Indian Institute of Technology (Banaras Hindu University), Varanasi (India) in 2012 and M. Tech. in Computer Science and Technology from the University of Mysore (India) in 2009. Currently, he is working as an Associate Professor at the School of Computing Science and Engineering (SCSE), Galgotias University, India. He has authored and co-authored more than 50 national and international journal publications, book chapters, and conference articles. He has five patents filed to his credit and his research interests include machine learning, deep learning, computer vision, medical image analysis, pattern recognition, and biometrics. Dr. Tiwari is a FIETE and member of ACM, IET, CSI, ISTE, IAENG, SCIEI. He is also a guest editorial board member and a reviewer for many international journals of repute.
Gulshan Soni is an Associate Professor and Principal-In-Charge in the CSE department at MSE&IT, MATS University, Raipur, India. He holds a Ph.D. from Pondicherry University, India, along with a B.Tech. from NIT Raipur, India, and an M.E. from 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.
