Estimation of system reliability using a semiparametric model
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Rudin_Estimation of system.pdf
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471.91 KB
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Author(s)
Wu, Leon
Teravainen, Timothy
Kaiser, Gail
Anderson, Roger
Boulanger, Albert
Rudin, Cynthia
Date Issued
July 2011
Journal
EnergyTech, 2011 IEEE
Publisher
Institute of Electrical and Electronics Engineers
Citation
Wu, Leon et al. “Estimation of System Reliability Using a Semiparametric Model.” EnergyTech, 2011 IEEE, 25-26 May 2011, Case Western Reserve University, IEEE, 2011. 1–6. Web.
Version
Author's final manuscript
Abstract
An important problem in reliability engineering is to predict the failure rate, that is, the frequency with which an engineered system or component fails. This paper presents a new method of estimating failure rate using a semiparametric model with Gaussian process smoothing. The method is able to provide accurate estimation based on historical data and it does not make strong a priori assumptions of failure rate pattern (e.g., constant or monotonic). Our experiments of applying this method in power system failure data compared with other models show its efficacy and accuracy. This method can be used in estimating reliability for many other systems, such as software systems or components.
MIT Department
Sloan School of Management
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/EnergyTech.2011.5948537
