Published October 2007 | Version v1
Journal article

On system failure probability density function

  • 1. DIENCA, Universita' di Bologna, Lab. di Montecuccolino, Via dei Colli 16, 40136 Bologna (Italy)

Description

The assessment of the system unreliability is usually accomplished through well-known tools such as block diagram, fault tree, Monte Carlo and others. These methods imply the knowledge of the failure probability density function of each component 'k' (pdf pk). For this reason, possibly, the system failure probability density function (psys) has never been explicitly derived. The present paper fills this gap achieving an enlightening formulation which explicitly gives psys as the sum of (positive) terms representing the complete set of transitions leading the system from an operating to a failed configuration, due to the failure of 'a last' component. As a matter of fact, these are all the independent sequences leading the system to the failure. In our opinion, this formulation is important from both methodological and practical point of views. From the methodological one, a clear insight of the system-vs-components behaviors can be grasped and, in general, the explicit link between psys and pk seems to be a notable result. From a practical point of view, psys allows a rigorous derivation of Monte Carlo algorithms and suggests a systematic tool for investigating the system failure sequences

Additional details

Identifiers

DOI
10.1016/j.ress.2006.09.002;
PII
S0951-8320(06)00195-5;

Publishing Information

Journal Title
Reliability Engineering and System Safety
Journal Volume
92
Journal Issue
10
Journal Page Range
p. 1321-1327
ISSN
0951-8320
CODEN
RESSEP

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
38089602
Subject category
S42: ENGINEERING;
Descriptors DEI
ALGORITHMS; DIAGRAMS; FAILURES; FAULT TREE ANALYSIS; MONTE CARLO METHOD; PROBABILITY DENSITY FUNCTIONS
Descriptors DEC
CALCULATION METHODS; FUNCTIONS; INFORMATION; MATHEMATICAL LOGIC; SYSTEM FAILURE ANALYSIS; SYSTEMS ANALYSIS

Optional Information

Copyright
Copyright (c) 2006 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.