## Probabilistic Reliability Models
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.
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. |

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### Contents

Recoverable Systems Markov Models | |

Recoverable Systems Heuristic Models | |

Time Redundancy | |

Aging Units and Systems of Aging Units | |

TwoPole Networks | |

Performance Effectiveness | |

System Survivability | |

Multistate Systems | |

Main Distributions Related to Reliability | |

Laplace Transformation | |