Artificial Intelligence and Industrial Applications: Smart Operation Management
Over dit e-boek
The 30 papers presented here were carefully reviewed and selected from 141 submissions by an international scientific committee. They address various aspects of artificial intelligence such as smart manufacturing, smart maintenance, smart supply chain management, supervised learning, unsupervised learning, reinforcement learning, graph-based and semi-supervised learning, neural networks, deep learning, planning and optimization, and other AI applications.
The book is intended for AI experts, offering them a valuable overview of the status quo and a global outlook for the future, with many new and innovative ideas and recent important developments in AI applications, both of a foundational and practical nature. It will also appeal to non-experts who are curious about this timely and important subject.
Over de auteur
Dr. Anass Cherrafi is an Assistant Professor at the Department of Industrial Engineering, ENSAM-Meknes, Moulay Ismail University UMI, Morocco. Holding a Ph.D. in Industrial Engineering, he has seven years of industry and teaching experience. He has published a number of articles in leading international journals and conference proceedings, and has been a Guest Editor for special issues of various international journals. His research interests include Industry 4.0, green manufacturing, Lean Six Sigma, integrated management systems and supply chain management.
Dr. Ibtissam El Hassani is a Professor of Industrial and Logistic Engineering at ENSAM-Meknes, Moulay Ismail University UMI, Morocco and Head of the Artificial Intelligence for Engineering Sciences (AIES) Research Team. She graduated as an Industrial Engineer before completing her Ph.D. in Computer Engineering & Systems Supervision at the Center for Doctoral Studies, Moulay Ismail University. Her research interests include applications of artificial intelligence in industrial engineering, especially in lean manufacturing, Six Sigma and continuous improvement, production systems, quality management systems, health and security at work, supply chain management and industrial risk management.
