A switching diffusion model for lifetime estimation in randomly varying environments

This article presents a switching diffusion model for estimating the useful lifetime of a component that operates in a randomly varying environment. The component's degradation process is unobservable; therefore, a signal of degradation is observed to estimate the environment parameters using a...

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Published inIIE transactions Vol. 46; no. 11; pp. 1227 - 1241
Main Authors Flory, John A., Kharoufeh, Jeffrey P., Gebraeel, Nagi Z.
Format Journal Article
LanguageEnglish
Published Norcross Taylor & Francis 02.11.2014
Taylor & Francis Ltd
Subjects
Approximation
Degradation-based reliability
Markov analysis
Monte Carlo simulation
Parameter estimation
random environment
Simulation
Stochastic models
Studies
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Abstract This article presents a switching diffusion model for estimating the useful lifetime of a component that operates in a randomly varying environment. The component's degradation process is unobservable; therefore, a signal of degradation is observed to estimate the environment parameters using a Markov chain Monte Carlo statistical procedure. These parameter estimates serve as key inputs to an analytical stochastic model that approximates the first passage time of the degradation process to a critical threshold. Several numerical examples involving simulated and real degradation data are presented to illustrate the quality of these approximations.
AbstractList This article presents a switching diffusion model for estimating the useful lifetime of a component that operates in a randomly varying environment. The component's degradation process is unobservable; therefore, a signal of degradation is observed to estimate the environment parameters using a Markov chain Monte Carlo statistical procedure. These parameter estimates serve as key inputs to an analytical stochastic model that approximates the first passage time of the degradation process to a critical threshold. Several numerical examples involving simulated and real degradation data are presented to illustrate the quality of these approximations.
Author Gebraeel, Nagi Z.
Kharoufeh, Jeffrey P.
Flory, John A.
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  fullname: Kharoufeh, Jeffrey P.
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  surname: Gebraeel
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  organization: H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology
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SubjectTerms Approximation
Degradation-based reliability
Markov analysis
Monte Carlo simulation
Parameter estimation
random environment
Simulation
Stochastic models
Studies
Title A switching diffusion model for lifetime estimation in randomly varying environments
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