A graphical approach to identification of dependent failures

L.A. Walls

Research output: Contribution to journal › Article

1 Citation (Scopus)

Abstract

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.
LanguageEnglish
Pages185-196
Number of pages11
JournalJournal of the Royal Statistical Society. Series D, The Statistician
Volume45
Issue number2
Publication statusPublished - 1996

Fingerprint

Dependent
Shock Model
Non-homogeneous Poisson Process
Repairable System
Statistical Power
Rate Function
Weibull
Screening
Null
Model
Engineering
Alternatives
Graph in graph theory
Range of data
Graphics

Keywords

  • common cause failures
  • dependent failures
  • exploratory data analysis
  • non-homogeneous Poisson process
  • reliability
  • repairable systems

Cite this

Walls, L.A. / A graphical approach to identification of dependent failures. In: Journal of the Royal Statistical Society. Series D, The Statistician. 1996 ; Vol. 45, No. 2. pp. 185-196.
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Walls, LA 1996, 'A graphical approach to identification of dependent failures' Journal of the Royal Statistical Society. Series D, The Statistician, vol. 45, no. 2, pp. 185-196.

A graphical approach to identification of dependent failures. / Walls, L.A.

In: Journal of the Royal Statistical Society. Series D, The Statistician, Vol. 45, No. 2, 1996, p. 185-196.

Research output: Contribution to journal › Article

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T1 - A graphical approach to identification of dependent failures

AU - Walls, L.A.

PY - 1996

Y1 - 1996

N2 - 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.

AB - 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.

KW - common cause failures

KW - dependent failures

KW - exploratory data analysis

KW - non-homogeneous Poisson process

KW - reliability

KW - repairable systems

UR - http://www.jstor.org/stable/2988407

M3 - Article

VL - 45

SP - 185

EP - 196

JO - Journal of the Royal Statistical Society. Series D, The Statistician

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JF - Journal of the Royal Statistical Society. Series D, The Statistician

SN - 0039-0526

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ER -

Walls LA. A graphical approach to identification of dependent failures. Journal of the Royal Statistical Society. Series D, The Statistician. 1996;45(2):185-196.

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