Estimating Lifetime Distributions in a Random Environment

We consider the problem of estimating the lifetime distribution of a component whose degradation is driven by an exogenous environment process. The environment is assumed to be unobservable; therefore, its order and transition rates must be inferred from a sequence of degradation observations. We pr...

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Published inIISE Annual Conference. Proceedings p. 1
Main Authors Flory, John A, Kharoufeh, Jeffrey P
Format Journal Article
LanguageEnglish
Published Norcross Institute of Industrial and Systems Engineers (IISE) 01.01.2011
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Abstract We consider the problem of estimating the lifetime distribution of a component whose degradation is driven by an exogenous environment process. The environment is assumed to be unobservable; therefore, its order and transition rates must be inferred from a sequence of degradation observations. We present and assess the effectiveness of a HiddenMarkovModel (HMM) approach to estimate the governing environment and the component's lifetime distribution. [PUBLICATION ABSTRACT]
AbstractList We consider the problem of estimating the lifetime distribution of a component whose degradation is driven by an exogenous environment process. The environment is assumed to be unobservable; therefore, its order and transition rates must be inferred from a sequence of degradation observations. We present and assess the effectiveness of a HiddenMarkovModel (HMM) approach to estimate the governing environment and the component's lifetime distribution. [PUBLICATION ABSTRACT]
Author Kharoufeh, Jeffrey P
Flory, John A
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Snippet We consider the problem of estimating the lifetime distribution of a component whose degradation is driven by an exogenous environment process. The environment...
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SubjectTerms Markov analysis
Randomized algorithms
Reliability engineering
Stochastic models
Studies
Title Estimating Lifetime Distributions in a Random Environment
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