Thesis-2007-Sun.pdf (9.88 MB)
System dependency modelling
thesis
posted on 2018-09-18, 08:43 authored by Huiling SunIt is common for modern engineering systems to feature dependency relationships between its
components. The existence of these dependencies render the fault tree analysis (FTA) and its
efficient implementation, the Binary Decision Diagram (BDD) approach, inappropriate in
predicting the system failure probability. Whilst the Markov method provides an alternative
means of analysis of systems of this nature, it is susceptible to state space explosion problems
for large, or even moderate sized systems.
Within this thesis, a process is proposed to improve the applicability of the Markov analysis.
With this process, the smallest independent sections (modules) which contain each
dependency type are identified in a fault tree and analysed by the most efficient method. Thus,
BDD and the Markov analysis are applied in a combined way to improve the analysis
efficiency. The BDD method is applied to modules which contain no dependency, and the
Markov analysis applied to modules in which dependencies exist.
Different types of dependency which can arise in an engineering system assessment are
identified. Algorithms for establishing a Markov model have also been developed for each
type of dependency.
Three types of system are investigated in this thesis in the context of dependency modelling:
the continuously-operating system, the active-on-demand system and the phased-mission
system. Different quantification techniques have been developed for each type of system to
obtain the system failure probability and other useful predictive measures.
Investigation is also carried out into the use of BDD in assessing non-repairable systems
involving dependencies. General processes have been established to enable the quantification.
History
School
- Science
Department
- Mathematical Sciences
Publisher
© Huiling SunPublisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Publication date
2007Notes
A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy at Loughborough University.Language
- en