Titlebook: Artificial Intelligence for Safety and Reliability Engineering; Methods, Application Kim Phuc Tran Book 2024 The Editor(s) (if applicable)

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Introduction to Artificial Intelligence for Safety and Reliability Engineering, stage for detailed discussions in subsequent chapters. AI can deliver novel and more accurate insights compared to traditional methods in the field of Safety and Reliability Engineering. Additionally, this book addresses the importance of ensuring the safety and reliability of AI systems, which are

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Physics-Informed Machine Learning for Industrial Reliability and Safety Engineering: A Review and Penhance the reliability and safety of complex industrial systems. Traditional methods in reliability engineering often rely on physics-based models, which, despite their robustness, face limitations when dealing with highly complex systems involving multiple interacting scales and incomplete knowled

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,Anomaly Detection for?Catalyzing Operational Excellence in?Complex Manufacturing Processes: A Surveted technologies such as the Industrial Internet of Things (IIoT), artificial intelligence (AI), and machine learning. This transformation has spawned smarter, more efficient production environments that, while advantageous, have led to the emergence of complex anomalies and deviations that traditio

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,Enhancing Trustworthiness in?AI-Based Prognostics: A Comprehensive Review of?Explainable AI for?PHMcoming a key component in their maintenance and operation. While artificial intelligence (AI) has become a powerful tool for PHM, the opaque nature of AI methods might present hurdles in their deployment for real-world PHM applications, as the lack of transparency in how these methods process and in

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