Probabilistic Reliability Models

Practical Approaches to Reliability Theory in Cutting-EdgeApplications
Probabilistic Reliability Models helps readers understandand properly use statistical methods
and optimal resource allocation to solve engineeringproblems.
The author supplies engineers with a deeper understanding ofmathematical models while also
equipping mathematically oriented readers with a fundamentalknowledge of the engineeringrelated
applications at the center of model building. The book showcasesthe use of probability
theory and mathematical statistics to solve common, real-worldreliability problems. Following
an 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 systems
Detailed case studies illustrate the relevance of the discussedmethods to real-world technical
projects including software failure avalanches, gas pipelineswith underground storage, and
intercontinental ballistic missile (ICBM) control systems.Numerical examples and detailed
explanations accompany each topic, and exercises throughoutallow readers to test their
comprehension of the presented material.
Probabilistic Reliability Models is an excellent book forstatistics, engineering, and operations
research courses on applied probability at theupper-undergraduate and graduate levels. The
book is also a valuable reference for professionals andresearchers working in industry who
would like a mathematical review of reliability models and therelevant applications.