Probabilistic Reliability Models

<p><b>Practical Approaches to Reliability Theory in Cutting-Edge Applications</b></p> <p><i>Probabilistic Reliability Models</i> helps readers understand and properly use statistical methods</p> <p>and optimal resource allocation to solve engineering problems.</p> <p>The author supplies engineers with a deeper understanding of mathematical models while also</p> <p>equipping mathematically oriented readers with a fundamental knowledge of the engineeringrelated</p> <p>applications at the center of model building. The book showcases the use of probability</p> <p>theory and mathematical statistics to solve common, real-world reliability problems. Following</p> <p>an introduction to the topic, subsequent chapters explore key systems and models including:</p> <p>• Unrecoverable objects and recoverable systems</p> <p>• Methods of direct enumeration</p> <p>• Markov models and heuristic models</p> <p>• Performance effectiveness</p> <p>• Time redundancy</p> <p>• System survivability</p> <p>• Aging units and their related systems</p> <p>• Multistate systems</p> <p>Detailed case studies illustrate the relevance of the discussed methods to real-world technical</p> <p>projects including software failure avalanches, gas pipelines with underground storage, and</p> <p>intercontinental ballistic missile (ICBM) control systems. Numerical examples and detailed</p> <p>explanations accompany each topic, and exercises throughout allow readers to test their</p> <p>comprehension of the presented material.</p> <p><i>Probabilistic Reliability Models</i> is an excellent book for statistics, engineering, and operations</p> <p>research courses on applied probability at the upper-undergraduate and graduate levels. The</p> <p>book is also a valuable reference for professionals and researchers working in industry who</p> <p>would like a mathematical review of reliability models and the relevant applications.</p>