Walls, L.A. (1996) A graphical approach to identification of dependent failures. Journal of the Royal Statistical Society. Series D, The Statistician, 45 (2). pp. 185-196. ISSN 0039-0526Full text not available in this repository. (Request a copy from the Strathclyde author)
Field data provide a rich source of information about the dependent failures whose omission from existing models can result in underestimation of the reliability of repairable systems, A graphical technique has been developed to highlight these events. This involves comparing the observed number of failures with the expected pattern under a null model of no common cause dependence, a non-homogeneous Poisson process with Weibull rate function. The derivation of the graph is outlined and its use as a screening tool is illustrated by applications to field data. The dependent failures identified are described and their engineering implications are discussed. The statistical power of the technique is evaluated for a range of alternative models of dependence, including simple shock models.
|Keywords:||common cause failures, dependent failures, exploratory data analysis, non-homogeneous Poisson process, reliability, repairable systems, Statistics, Statistics and Probability|
|Subjects:||Social Sciences > Statistics|
|Department:||Strathclyde Business School > Management Science|
|Depositing user:||Strathprints Administrator|
|Date Deposited:||04 May 2010 09:27|
|Last modified:||04 May 2016 14:00|