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Empirical Bayes methodology for estimating equipment failure rates with application to power generation plants

Hutchison, Kenneth and Quigley, John and Raza, M. and Walls, L.A. (2008) Empirical Bayes methodology for estimating equipment failure rates with application to power generation plants. In: IEEE International Conference on Industrial Engineering and Engineering Management, 2008. International Conference on Industrial Engineering and Engineering Management IEEM, 1-3 . IEEE, pp. 1359-1364. ISBN 978-1-4244-2629-4

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Abstract

Many reliability databases pool event data for equipment across different plants. Pooling may occur both within and between organizations with the intention of sharing data across common items within similar operating environments to provide better estimates of reliability and availability. Frequentist estimation methods can be poor when few, or no, events occur even when equipment operate for long periods. An alternative approach based upon empirical Bayes estimation is proposed. The new method is applied to failure data analysis in power generation plants and found to provide credible insights. A statistical comparison between the proposed and frequentist methods shows that empirical Bayes is capable of generating more accurate estimates.

Item type: Book Section
ID code: 28136
Keywords: Bayes methods, data analysis, estimation theory, failure analysis, power apparatus, power engineering computing, power generation faults, power plants, Management. Industrial Management, Electrical engineering. Electronics Nuclear engineering
Subjects: Social Sciences > Industries. Land use. Labor > Management. Industrial Management
Technology > Electrical engineering. Electronics Nuclear engineering
Department: Strathclyde Business School > Management Science
Related URLs:
    Depositing user: Mrs Caroline Sisi
    Date Deposited: 14 Oct 2010 15:03
    Last modified: 12 Mar 2012 11:20
    URI: http://strathprints.strath.ac.uk/id/eprint/28136

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