This book provides a comprehensive guide to using data-driven methods in reliability and safety engineering for industrial systems. It explores how modern technologies like data analytics, machine learning, and artificial intelligence can enhance decision-making, predict failures, and improve system resilience.

In an era of increasingly complex industrial systems, traditional methods often fail to address reliability and safety challenges. This book highlights how integrating data-driven techniques can optimize system performance, reduce risks, and enhance safety outcomes. Key topics include predictive maintenance, risk assessment, AI integration, and the challenges of implementing these technologies in real-world environments. Case studies across industries like energy and manufacturing illustrate the practical applications of these methods.

This book is aimed at professionals in reliability engineering, safety, risk management, and industrial systems, as well as researchers and students seeking to understand the role of data-driven methods in modern engineering practices.

Presents a guide to using data-driven methods in reliability and safety engineering for industrial systems Includes case studies across industries like energy and manufacturing that illustrate the practical applications Serves as a reference for researchers and professionals in reliability engineering, safety, and industrial systems

Autorentext

Dr. He Li obtained his Ph.D. degrees from the University of Electronic Science and Technology of China, China (2021), and the University of Lisbon, Portugal (2025), and has been a researcher at Liverpool John Moores University, UK (2024-). He is a fellow of the International Society of Engineering Asset Management (ISEAM Fellow), a technical committee member of the European Safety and Reliability Association (Marine Engineering, ESRA Fellow), and an editor/associate editor/guest editor/editorial board member for more than 10 Journals. He has been selected as a Marie Curie fellow and recognized as a World's Top 2% Scientist (2024, 2025). Dr. Li has a selection of publications, e.g., monographs and journal/conference papers with several highly cited/hot papers and best paper awards. His research focuses on the reliability and maintainability of marine energy systems.

Professor Ke Feng is a full professor at Xi’an Jiaotong University, China. He is a Marie Curie fellow, a World's Top 2% Scientist, and received a Ph.D. degree from the University of New South Wales, Australia. He worked at the University of British Columbia and the National University of Singapore in 2022 and 2023, respectively. His main research interests include digital twins, vibration analysis, structural health monitoring, dynamics, tribology, signal processing, and machine learning. He is recognized as the emerging leader (2023) by the Measurement Science and Technology journal. He has been the associate editor and guest editor of several journals, including IEEE Transactions on Industrial Informatics, Information Fusion, Mechanical Systems and Signal Processing, IEEE Transactions on Industrial Cyber-Physical Systems, etc.

Professor Mohammad Yazdi is an assistant professor at Macquarie University, Australia. He earned a dual Ph.D. degree from Memorial University of Newfoundland, Canada, and Macquarie University, Australia. His research interests and professional background converge at the nexus of system safety, risk assessment, resilience, process integrity, and asset management, especially concerning renewable and non-renewable energy infrastructure. With an impressive track record of leading large-scale energy projects and technology-rich initiatives, Mohammad offers invaluable support to asset operators, developers, and maintainers and has been recognized as a World's Top 2% Scientist for many years.

Professor Hong-Zhong Huang is a full professor and director of the Center for System Reliability and Safety, at the University of Electronic Science and Technology of China. He has held visiting appointments at several universities in the USA, Canada, and Asia. He received a Ph.D. degree in reliability engineering from Shanghai Jiaotong University, China. He has published more than 200 journal papers and 5 books in the fields of reliability engineering, optimization design, fuzzy sets theory, and product development. His main research interests include reliability design, optimization design, condition monitoring, fault diagnosis, and life prediction.

Inhalt

Reliability analysis of aircraft grooved joints based on response surface methodology.- Comprehensive evaluation techniques of basic reliability based on data fusion of similar products.- Mission reliability comprehensive evaluation technique based on multi-stage information.- Preliminary exploration of exemption methods for single-fault criteria in nuclear power plants.- Accuracy lifetime prediction methodology for RV reducer.- Derating design of control circuits based on harpness simulation.- Ak-Sysc: A kriging-based approach for multi-failure-mode structural system reliability analysis.- Risk-informed intelligent design optimization for nuclear power plants using probabilistic safety analysis.- Research on fault data-driven quality risk assessment method for aviation equipment.- A preliminary summary of failure mode and effects analysis of digital control systems.- Research on the reliability assurance system in the product development process.- An architectural design for the reliability and safety of battery management system.- 13. Research on reliability classification technology of high-temperature gas-cooled reactor.- Maintenance optimisation for K-out-of-N: G system using deep reinforcement learning.- Investigation on quantitative evaluation technology for system integrated support.- Goal-oriented reliability program framework for space science and application payloads.- Study on the effectiveness evaluation of cross-flooding hatches in damage stability design of large passenger vessels.- Calculation and analysis of fatigue life damage of diesel engine crankshaft.- Exploratory research on optimizing equipment support supply chain based on boundaryless organization theory.- Research on high-efficiency milling process and machining parameter optimization of aircraft wing rib components.- Espac-based linear array microtremor tomography method and its application in goaf detection.- A study on fault prediction of simulated die press machine based on machine learning.- Digital twin-driven condition monitoring for servo valves.- Yolo-Mvcp: A lightweight fault diagnosis method of rolling bearing based on STFT time-frequency graph and mobilevit network pruning.- Design of system-level self-health energy management of manned spacecraft.- A Pinn-Cnn hybrid architecture for vibration-based damage detection in airship envelopes.- Coupling simulation analysis of high temperature heater under multiple physical fields.- Statistical process control for robust genetic evaluation software: Monitoring accuracy, stability, and efficiency in blup and genomic selection models.- From phenomena to mechanisms: A timespacematter multidimensional analysis of aerospace electronic failures.- Research on the health monitoring technology of preload for complex aerospace equipment fastening devices.- Probabilistic life estimation framework for mechanical component.- Uncertainty propagation in bridge construction carbon emission quantification.- Gas turbine rotor systematic upgrading technology research and engineering application.- A storage life assessment method for missile based on critical component inspection date.- Research on internal stress damage detection strategies for optical components.- Study of properties of high Zn content aluminium alloys for thin wall deep cavity casting.- Nanoindentation-based finite element characterization method for 25cr2ni2mov rotor steel welded joints.…