TY  - BOOK
AU  - Tran,Kim Phuc
ED  - SpringerLink (Online service)
TI  - Artificial Intelligence for Safety and Reliability Engineering: Methods, Applications, and Challenges 
T2  - Springer Series in Reliability Engineering,
SN  - 9783031714955
AV  - T55.4-60.8 
U1  - 670 23
PY  - 2024///
CY  - Cham
PB  - Springer Nature Switzerland, Imprint: Springer
KW  - Industrial engineering
KW  - Production engineering
KW  - Artificial intelligence
KW  - Production management
KW  - Industrial and Production Engineering
KW  - Artificial Intelligence
KW  - Production
N1  - Introduction to Artificial Intelligence for Safety and Reliability Engineering -- Artificial Intelligence for Safety and Reliability Engineering in Industry 5.0 Methods, Applications and Challenges -- System Reliability Inference for Common Cause Failure Model in Contexts of Missing Information -- Predictive maintenance enabled by a Light Weight Federated Learning in Smart Manufacturing: Remaining Useful Lifetime Prediction -- Explainable Trustworthy and Transparent Artificial Intelligence for Reliability Engineering and Safety Applications -- Inverse Reinforcement Learning for Predictive Maintenance -- Reliability and Risk Assessment with Explainable Artificial Intelligence -- An Anomaly Detection Framework for Safety and Reliability Engineering -- Wearable Technology for Workplace Safety with Embedded Artificial Intelligence -- Safety and Reliability of Artificial Intelligence systems -- Physics-informed machine learning for reliability and systems safety applications
N2  - 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.
UR  - http://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-3-031-71495-5
ER  -