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Multivariate reliability modelling with empirical Bayes inference

Quigley, J.L. and Walls, L.A. (2007) Multivariate reliability modelling with empirical Bayes inference. In: ISSAT international conference on modeling of complex systems and environments, 2007-07-16 - 2007-07-18, Ho Chi Minh City, Vietnam. (Unpublished)

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    Abstract

    Recent developments in technology permit detailed descriptions of system performance to be collected and stored. Consequently, more data are available about the occurrence, or non-occurrence, of events across a range of classes through time. Typically this implies that reliability analysis has more information about the exposure history of a system within different classes of events. For highly reliable systems, there may be relatively few failure events. Thus there is a need to develop statistical inference to support reliability estimation when there is a low ratio of failures relative to event classes. In this paper we show how Empirical Bayes methods can be used to estimate a multivariate reliability function for a system by modelling the vector of times to realise each failure root cause.

    Item type: Conference or Workshop Item (Paper)
    ID code: 18157
    Keywords: reliability growth model, empirical Bayes, engineering design process, Management. Industrial Management, Management Science and Operations Research
    Subjects: Social Sciences > Industries. Land use. Labor > Management. Industrial Management
    Department: Strathclyde Business School > Management Science
    Related URLs:
    Depositing user: Strathprints Administrator
    Date Deposited: 11 May 2010 14:56
    Last modified: 04 Jul 2014 16:43
    URI: http://strathprints.strath.ac.uk/id/eprint/18157

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