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

Practical Approaches to Reliability Theory in Cutting-EdgeApplicationsProbabilistic Reliability Models helps readers understandand properly use statistical methodsand optimal resource allocation to solve engineeringproblems.The author supplies engineers with a deeper understanding ofmathematical models while alsoequipping mathematically oriented readers with a fundamentalknowledge of the engineeringrelatedapplications at the center of model building. The book showcasesthe use of probabilitytheory and mathematical statistics to solve common, real-worldreliability problems. Followingan introduction to the topic, subsequent chapters explore keysystems and models including:* Unrecoverable objects and recoverable systems* Methods of direct enumeration* Markov models and heuristic models* Performance effectiveness* Time redundancy* System survivability* Aging units and their related systems* Multistate systemsDetailed case studies illustrate the relevance of the discussedmethods to real-world technicalprojects including software failure avalanches, gas pipelineswith underground storage, andintercontinental ballistic missile (ICBM) control systems.Numerical examples and detailedexplanations accompany each topic, and exercises throughoutallow readers to test theircomprehension of the presented material.Probabilistic Reliability Models is an excellent book forstatistics, engineering, and operationsresearch courses on applied probability at theupper-undergraduate and graduate levels. Thebook is also a valuable reference for professionals andresearchers working in industry whowould like a mathematical review of reliability models and therelevant applications.