Artificial Intelligence for Safety and Reliability Engineering
Methods, Applications, and Challenges
Buch in deiner Nähe kaufen
Beschreibung
This book is a comprehensive exploration of the latest theoretical research, technological advancements, and real-world applications of artificial intelligence (AI) for safety and reliability engineering.
Smart manufacturing relies on predictive maintenance (PdM) to ensure sustainable production systems, and the integration of AI has become increasingly prevalent in this field. This book serves as a valuable resource for researchers, practitioners, and decision-makers in manufacturing. By combining theoretical research, practical applications, and case studies, it equips readers with the necessary knowledge and tools to implement AI for safety and reliability engineering effectively in smart manufacturing contexts.
This book is a comprehensive exploration of the latest theoretical research, technological advancements, and real-world applications of artificial intelligence (AI) for safety and reliability engineering.
Smart manufacturing relies on predictive maintenance (PdM) to ensure sustainable production systems, and the integration of AI has become increasingly prevalent in this field. This book serves as a valuable resource for researchers, practitioners, and decision-makers in manufacturing. By combining theoretical research, practical applications, and case studies, it equips readers with the necessary knowledge and tools to implement AI for safety and reliability engineering effectively in smart manufacturing contexts.
Describes systematic artificial intelligence (AI) for safety and reliability engineering Offers insights on better-informed decision-making and more effective accident prevention in smart manufacturing Provides ready-to-use algorithms for readers and practitioners and contains case studies in every chapter
Autor*in
Kim Phuc Tran
Themen in »Artificial Intelligence for Safety and Reliability Engineering«
Machine Learning Reinforcement Learning Deep Learning Predictive Maintenance Safety and Reliability Engineering Remaining Useful Lifetime Prediction Smart Condition Monitoring Smart Manufacturing Industry 5.0