Estimation of System Reliability Using a Semiparametric Model

Leon Li Wu; Timothy Kaleva Teravainen; Gail E. Kaiser; Roger N. Anderson; Albert G. Boulanger; Cynthia Rudin

Estimation of System Reliability Using a Semiparametric Model
Wu, Leon Li
Teravainen, Timothy Kaleva
Kaiser, Gail E.
Anderson, Roger N.
Boulanger, Albert G.
Rudin, Cynthia
Technical reports
Computer Science
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Columbia University Computer Science Technical Reports
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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.
Computer science
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Suggested Citation:
Leon Li Wu, Timothy Kaleva Teravainen, Gail E. Kaiser, Roger N. Anderson, Albert G. Boulanger, Cynthia Rudin, 2011, Estimation of System Reliability Using a Semiparametric Model, Columbia University Academic Commons, http://hdl.handle.net/10022/AC:P:10670.

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