Demonstrates how to solve reliability problems using practical
applications of Bayesian models
This self-contained reference provides fundamental knowledge of Bayesian
reliability and utilizes numerous examples to show how Bayesian models
can solve real life reliability problems. It teaches engineers and
scientists exactly what Bayesian analysis is, what its benefits are, and
how they can apply the methods to solve their own problems. To help
readers get started quickly, the book presents many Bayesian models that
use JAGS and which require fewer than 10 lines of command. It also
offers a number of short R scripts consisting of simple functions to
help them become familiar with R coding.
Practical Applications of Bayesian Reliability starts by introducing
basic concepts of reliability engineering, including random variables,
discrete and continuous probability distributions, hazard function, and
censored data. Basic concepts of Bayesian statistics, models, reasons,
and theory are presented in the following chapter. Coverage of Bayesian
computation, Metropolis-Hastings algorithm, and Gibbs Sampling comes
next. The book then goes on to teach the concepts of design capability
and design for reliability; introduce Bayesian models for estimating
system reliability; discuss Bayesian Hierarchical Models and their
applications; present linear and logistic regression models in Bayesian
Perspective; and more.
- Provides a step-by-step approach for developing advanced reliability
models to solve complex problems, and does not require in-depth
understanding of statistical methodology
- Educates managers on the potential of Bayesian reliability models and
associated impact
- Introduces commonly used predictive reliability models and advanced
Bayesian models based on real life applications
- Includes practical guidelines to construct Bayesian reliability models
along with computer codes for all of the case studies
- JAGS and R codes are provided on an accompanying website to enable
practitioners to easily copy them and tailor them to their own
applications
Practical Applications of Bayesian Reliability is a helpful book for
industry practitioners such as reliability engineers, mechanical
engineers, electrical engineers, product engineers, system engineers,
and materials scientists whose work includes predicting design or
product performance.
