Probabilistic Reliability Models
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Sprache:Englisch
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Produktdetails
Format
Kopierschutz
Ja
Family Sharing
Nein
Text-to-Speech
Nein
Erscheinungsdatum
07.08.2012
Verlag
Wiley-IEEE PressSeitenzahl
248 (Printausgabe)
Dateigröße
7404 KB
Auflage
1. Auflage
Sprache
Englisch
EAN
9781118370773
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.
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.
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