System Reliability Theory: Models, Statistical Methods, and Applications, Third Edition (Wiley Series in Probability and Statistics) - Hardcover

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MARVIN RAUSAND is Professor Emeritus in the department of Mechanical and Industrial Engineering at the Norwegian University of Science and Technology (NTNU), Norway, and author of Risk Assessment: Theory, Methods, and Applications and Reliability of Safety-Critical Systems: Theory and Applications, both published by Wiley.

ANNE BARROS, PHD, is Professor in reliability and maintenance engineering at Ecole CentraleSupélec, University of Paris-Saclay, France. Her research focus is on degradation modeling, prognostics, condition based and predictive maintenance. She got a PHD then a professorship position at University of Technology of Troyes, France (2003 – 2014) and spent five years as a full-time professor at NTNU, Norway (2014 – 2019). She is currently heading a research group and holds an industrial chair at CentraleSupélec with the ambition to provide reliability assessment and maintenance modeling methods for systems of systems.

The late ARNLJOT HØYLAND, PHD, was a Professor in the Department of Mathematical Sciences at the Norwegian University of Science and Technology.

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Handbook and reference for industrial statisticians and system reliability engineers

System Reliability Theory: Models, Statistical Methods, and Applications, Third Edition presents an updated and revised look at system reliability theory, modeling, and analytical methods. The new edition is based on feedback to the second edition from numerous students, professors, researchers, and industries around the world. New sections and chapters are added together with new real-world industry examples, and standards and problems are revised and updated.

System Reliability Theory covers a broad and deep array of system reliability topics, including:

• In depth discussion of failures and failure modes
• The main system reliability assessment methods
• Common-cause failure modeling
• Deterioration modeling
• Maintenance modeling and assessment using Python code
• Bayesian probability and methods
• Life data analysis using R

Perfect for undergraduate and graduate students taking courses in reliability engineering, this book also serves as a reference and resource for practicing statisticians and engineers.

Throughout, the book has a practical focus, incorporating industry feedback and real-world industry problems and examples.