Focusing on shocks modeling, burn-in and heterogeneous populations,
Stochastic Modeling for Reliability naturally combines these three
topics in the unified stochastic framework and presents numerous
practical examples that illustrate recent theoretical findings of the
authors.
The populations of manufactured items in industry are usually
heterogeneous. However, the conventional reliability analysis is
performed under the implicit assumption of homogeneity, which can result
in distortion of the corresponding reliability indices and various
misconceptions. Stochastic Modeling for Reliability fills this gap and
presents the basics and further developments of reliability theory for
heterogeneous populations. Specifically, the authors consider burn-in as
a method of elimination of 'weak' items from heterogeneous populations.
The real life objects are operating in a changing environment. One of
the ways to model an impact of this environment is via the external
shocks occurring in accordance with some stochastic point processes. The
basic theory for Poisson shock processes is developed and also shocks as
a method of burn-in and of the environmental stress screening for
manufactured items are considered.
Stochastic Modeling for Reliability introduces and explores the
concept of burn-in in heterogeneous populations and its recent
development, providing a sound reference for reliability engineers,
applied mathematicians, product managers and manufacturers alike.