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 (Unpublished)
Full text not available in this repository. (Request a copy from the Strathclyde author)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 |
| 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 Oct 2012 17:33 |
| URI: | http://strathprints.strath.ac.uk/id/eprint/18157 |
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