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On Bayesian System Reliability Analysis

Abstract

The view taken in this thesis is that reliability, the probability that a system will perform a required function for a stated period of time, depends on a person`s state of knowledge. Reliability changes as this state of knowledge changes, i.e. when new relevant information becomes available. Most existing models for system reliability prediction are developed in a classical framework of probability theory and they overlook some information that is always present. Probability is just an analytical tool to handle uncertainty, based on judgement and subjective opinions. It is argued that the Bayesian approach gives a much more comprehensive understanding of the foundations of probability than the so called frequentistic school. A new model for system reliability prediction is given in two papers. The model encloses the fact that component failures are dependent because of a shared operational environment. The suggested model also naturally permits learning from failure data of similar components in non identical environments. 85 refs.
Publication Date:
May 01, 1995
Product Type:
Thesis/Dissertation
Report Number:
LIU-TEK-LIC-95-22
Reference Number:
SCA: 220200; PA: AIX-26:077237; EDB-96:014647; NTS-96:008525; SN: 96001512704
Resource Relation:
Other Information: TH: Thesis (TeknL).; PBD: May 1995; Related Information: Linkoeping Studies in Science and Technology. Thesis, 490
Subject:
22 NUCLEAR REACTOR TECHNOLOGY; PROBABILISTIC ESTIMATION; FAILURES; INFORMATION NEEDS; RELIABILITY; STATISTICS
OSTI ID:
158000
Research Organizations:
Linkoeping Univ. (Sweden). Dept. of Mechanical Engineering
Country of Origin:
Sweden
Language:
English
Other Identifying Numbers:
Journal ID: ISSN 0280-7971; Other: ON: DE96606569; ISBN 91-7871-548-2; TRN: SE9500148077237
Availability:
INIS; OSTI as DE96606569
Submitting Site:
SWDN
Size:
92 p.
Announcement Date:

Citation Formats

Soerensen Ringi, M. On Bayesian System Reliability Analysis. Sweden: N. p., 1995. Web.
Soerensen Ringi, M. On Bayesian System Reliability Analysis. Sweden.
Soerensen Ringi, M. 1995. "On Bayesian System Reliability Analysis." Sweden.
@misc{etde_158000,
title = {On Bayesian System Reliability Analysis}
author = {Soerensen Ringi, M}
abstractNote = {The view taken in this thesis is that reliability, the probability that a system will perform a required function for a stated period of time, depends on a person`s state of knowledge. Reliability changes as this state of knowledge changes, i.e. when new relevant information becomes available. Most existing models for system reliability prediction are developed in a classical framework of probability theory and they overlook some information that is always present. Probability is just an analytical tool to handle uncertainty, based on judgement and subjective opinions. It is argued that the Bayesian approach gives a much more comprehensive understanding of the foundations of probability than the so called frequentistic school. A new model for system reliability prediction is given in two papers. The model encloses the fact that component failures are dependent because of a shared operational environment. The suggested model also naturally permits learning from failure data of similar components in non identical environments. 85 refs.}
place = {Sweden}
year = {1995}
month = {May}
}