Advances In Mathematical Modeling For Reliability
by Lesley Walls /
2008 / English / PDF
4.9 MB Download
Advances in Mathematical Modeling for Reliability discusses
fundamental issues on mathematical modeling in reliability theory
and its applications. Beginning with an extensive discussion of
graphical modeling and Bayesian networks, the focus shifts towards
repairable systems: a discussion about how sensitive availability
calculations parameter choices, and emulators provide the potential
to perform such calculations on complicated systems to a fair
degree of accuracy and in a computationally efficient manner.
Another issue that is addressed is how competing risks arise in
reliability and maintenance analysis through the ways in which data
is censored. Mixture failure rate modeling is also a point of
discussion, as well as the signature of systems, where the
properties of the system through the signature from the probability
distributions on the lifetime of the components are distinguished.
The last three topics of discussion are relations among aging and
stochastic dependence, theoretical advances in modeling, inference
and computation, and recent advances in recurrent event modeling
and inference.
Advances in Mathematical Modeling for Reliability discusses
fundamental issues on mathematical modeling in reliability theory
and its applications. Beginning with an extensive discussion of
graphical modeling and Bayesian networks, the focus shifts towards
repairable systems: a discussion about how sensitive availability
calculations parameter choices, and emulators provide the potential
to perform such calculations on complicated systems to a fair
degree of accuracy and in a computationally efficient manner.
Another issue that is addressed is how competing risks arise in
reliability and maintenance analysis through the ways in which data
is censored. Mixture failure rate modeling is also a point of
discussion, as well as the signature of systems, where the
properties of the system through the signature from the probability
distributions on the lifetime of the components are distinguished.
The last three topics of discussion are relations among aging and
stochastic dependence, theoretical advances in modeling, inference
and computation, and recent advances in recurrent event modeling
and inference.
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