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Reliability Analysis and Modeling for Complex Systems is a crucial resource for engineers and technologists grappling with modern challenges. As technology advances and safety concerns mount, the complexity of systems like autonomous vehicles and critical infrastructure demands innovative reliability assessment methods. This book bridges theory and practice, offering practical solutions for professionals navigating the intricate world of reliability engineering. Through real-world case studies and interdisciplinary insights, it equips readers to address the multifaceted challenges of ensuring dependability in today's interconnected technological landscape.
List of contents
1. Introduction to Reliability Analysis for Complex Systems
2. Probabilistic Modeling Techniques for Complex Systems
3. Bayesian Methods in Reliability Analysis
4. Reliability Assessment of Cyber-Physical Systems
5. Human Factors in Complex System Reliability
6. Reliability-Centered Maintenance for Complex Systems
7. Failure Mode and Effects Analysis (FMEA) for Complex Systems
8. Measuring Complexity of Engineering Systems
9. Case Studies in Reliability Analysis of Complex Systems
10. Reliability of Renewable Energy Systems
11. Reliability in Healthcare Systems
12. Reliability of Autonomous Vehicles
13. Future Trends in Complex System Reliability
About the author
Seifedine Kadry is a Professor in the Department of Mathematics and Computer Science, at Norrof University College, in Norway. He has a Bachelor’s degree in 1999 from Lebanese University, MS degree in 2002 from Reims University (France) and EPFL (Lausanne), PhD in 2007 from Blaise Pascal University (France), HDR degree in 2017 from Rouen University. At present, his research focuses on data Science, education using technology, system prognostics, stochastic systems, and applied mathematics. He is an ABET program evaluator for computing, and ABET program evaluator for Engineering Tech. He is a Fellow of IET, Fellow of IETE, and Fellow of IACSIT. He is a distinguished speaker of IEEE Computer Society.
Dr. Shubham Mahajan is a distinguished academic and professional member of prestigious organizations such as IEEE, ACM, and IAENG. He earned his B.Tech. from Baba Ghulam Shah Badshah University, his M.Tech. from Chandigarh University, his Ph.D. from Shri Mata Vaishno Devi University in India, and his Postdoctoral degree in Applied Data Science at Noroff University College in Norway. Currently, he is working as an Assistant Professor at Amity University, Haryana, India.
Dr. Mahajan specializes in artificial intelligence, image processing and segmentation, data mining, and machine learning, holding eleven Indian patents along with one patent each from Australia and Germany.
