arrow
Return

Predictive inference for system reliability after common-cause component failures

delete2015-03-01
delete36
delete
OA
AI
F
Frank P. A. Coolen *
T
Tahani Coolen‐Maturi
DOI:10.1016/j.ress.2014.11.005delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
This paper presents nonparametric predictive inference for system reliability following common-cause failures of components. It is assumed that a single failure event may lead to simultaneous failure of multiple components. Data consist of frequencies of such events involving particular numbers of components. These data are used to predict the number of components that will fail at the next failure event. The effect of failure of one or more components on the system reliability is taken into account through the system's survival signature. The predictive performance of the approach, in which uncertainty is quantified using lower and upper probabilities, is analysed with the use of ROC curves. While this approach is presented for a basic scenario of a system consisting of only a single type of components and without consideration of failure behaviour over time, it provides many opportunities for more general modelling and inference, these are briefly discussed together with the related research challenges. (C) 2014 Elsevier Ltd. All rights reserved.
Keywords:
Common-cause failures
Lower and upper probabilities
Nonparametric predictive inference
ROC curves
Survival signature
System reliability
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

R
Reliability Engineering and System Safety
IF:
11
Papers:
9.0K
Citations:
4.2W

Organization

D
Durham University
Scholars:
1.3W
Papers: 1.5W
Citations: 2.1W
Cited Papers

Cited Papers

COX‐2 inhibitors selectively block prostacyclin synthesis in endotoxin exposed vascular smooth muscle cells
err2004-02-20
err0
PREAI
errStefan Schildknecht; Markus Bachschmid; Achim Baumann; Volker Ullrich
errShare
errSave
errShare
errSave
Bayesian Inference for Reliability of Systems and Networks Using the Survival Signature
err2014-06-11
err68
errOAAI
errAslett, Louis J. M.; Coolen, Frank P. A.; Wilson, Simon P.
errShare
errSave
errShare
errSave
Electrocardiographic T Wave Abnormalities and the Risk of Sudden Cardiac Death: The Finnish Perspective
err2015-09-22
err0
errOAAI
errJani T. Tikkanen; Tuomas Kenttä; Kimmo Porthan; Heikki V. Huikuri; M. Juhani Junttila
errShare
errSave
researcher View more