Synopses & Reviews
Synopsis
Since the publication of the Second Edition of this popular textbook, new standards have changed the focus of reliability engineering, which introduced new concepts and terminology. Consequently, the Third Edition of System Reliability Theory: Models, Statistical Methods, and Applications has been thoroughly rewritten and updated to meet current standards. With an updated practical focus, incorporation of industry feedback, and many new examples based on real-world industry problems and data, this book begins with an introduction on reliability engineering and is followed by coverage on failures and failure analysis. The authors address failure models and qualitative system analysis and present new coverage on state space models. In addition, a new chapter on component reliability and availability is followed by a chapter on systems of independent components. Component importance is covered followed by a chapter on dependent failures, which now includes a discussion on causes of common cause failures, explicit versus implicit modeling, and the Beta-factor model. The authors also discuss counting processes and Markov Processes. In addition, the authors provide new sections on: maintenance assessment and optimization; advanced models failure rates; human errors; software bugs; CCFs (ICED + method in IEC 61508); generic failure rate databases; FRACAS data; application-specific data; frequency of dangerous failures (PFH); and reliability prediction. The book is supplemented with a companion website, which contains an Instructor Solutions Manual, lecture slides, reliability data sources, sample exam questions, and a terminology review.
Synopsis
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.