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**Harvard**

Svensson, J. (2007) *Survival Estimation for Opportunistic Maintenance*. (Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie, nr: 2568).

** BibTeX **

@book{

Svensson2007,

author={Svensson, Johan},

title={Survival Estimation for Opportunistic Maintenance},

isbn={978-91-7291-887-942-6},

abstract={The problem of rational maintenance of aircraft engines is studied with
respect to the influence of random events.
Aircraft engines can be more economically maintained and resources can
be saved if the maintenance process is improved. The starting point is an optimization model suggesting what parts in
the engine that should be replaced at each maintenance time.
The input data is the age of the details in the engine.
Statistical models are developed that estimates the remaining life of the components in the engine. The models work with different kinds of data. The first data set only contains times between repairs and is modeled with a non-stationary renewal process and a non-homogeneous Poisson process. With our data the non-stationary renewal
process works better. Different repair stations affect the life
of the components, which the non-stationary renewal process manages to
model. This model also manages the aging component problem in an
effective way. However, in this case no aging is present other than
substantial degeneration after the first repair. The second dataset contains crack growth data. The remaining life is modeled with a empirical crack growth model. With data directly indicating the condition of the detail a more precise estimate of the reaming life can be made.
In order to get an interface with the optimization model the
distributions need to be discrete. Four methods to make discretizations are discussed and adapted to suit the model. The methods are compared and the choice concerning the number of points of support is discussed. Finally the consequence of using a narrow
scenario tree is commented upon.},

year={2007},

series={Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie, no: 2568},

keywords={non-stationary renewal process, non-homogeneous Poisson process, survival, optimal maintenance, discretization; points of support, crack growth },

}

** RefWorks **

RT Dissertation/Thesis

SR Electronic

ID 41560

A1 Svensson, Johan

T1 Survival Estimation for Opportunistic Maintenance

YR 2007

SN 978-91-7291-887-942-6

AB The problem of rational maintenance of aircraft engines is studied with
respect to the influence of random events.
Aircraft engines can be more economically maintained and resources can
be saved if the maintenance process is improved. The starting point is an optimization model suggesting what parts in
the engine that should be replaced at each maintenance time.
The input data is the age of the details in the engine.
Statistical models are developed that estimates the remaining life of the components in the engine. The models work with different kinds of data. The first data set only contains times between repairs and is modeled with a non-stationary renewal process and a non-homogeneous Poisson process. With our data the non-stationary renewal
process works better. Different repair stations affect the life
of the components, which the non-stationary renewal process manages to
model. This model also manages the aging component problem in an
effective way. However, in this case no aging is present other than
substantial degeneration after the first repair. The second dataset contains crack growth data. The remaining life is modeled with a empirical crack growth model. With data directly indicating the condition of the detail a more precise estimate of the reaming life can be made.
In order to get an interface with the optimization model the
distributions need to be discrete. Four methods to make discretizations are discussed and adapted to suit the model. The methods are compared and the choice concerning the number of points of support is discussed. Finally the consequence of using a narrow
scenario tree is commented upon.

T3 Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie, no: 2568

LA swe

LK http://www.math.chalmers.se/Stat/Research/Preprints/Doctoral/2007/4.pdf

OL 126