Abstract
Rigorous analysis of the reliability of a dynamic system
calls for modelling of the dynamic behaviour of the
system and its interactions. However, traditional and the
most frequently used reliability analysis methods, such
as fault tree analysis, are static and have only limited
capability to represent dynamic systems. Therefore,
dynamic reliability analysis methods have been studied
since 1990s. Dynamic flowgraph methodology (DFM) is a
method for the reliability analysis of dynamic systems
containing feedback loops. A DFM model is a dynamic graph
representation of the analysed system. DFM has been most
often applied to different digital control systems. One
reason for this is that a DFM model can represent the
interactions between a control system and the controlled
process.
The main goal of DFM analysis is to identify prime
implicants, which are minimal combinations of events and
conditions that cause the analysed top event, for
example, system failure. This dissertation strengthens
the mathematical foundation of DFM by developing an
improved definition of a prime implicant. Risk importance
measures can be used to identify components and basic
events that are most important for the reliability of the
system. This dissertation develops new dynamic risk
importance measures as generalisations of two traditional
risk importance measures for the needs of DFM.
Unlike any other importance measure, the dynamic risk
importance measures utilise all the
information available in prime implicants of DFM. They
primarily measure the importances of different states of
components and variables of a DFM model. The computation
of the dynamic risk importance measures for failure
states of components provides significant additional
information compared to other importance values.This
dissertation also examines common cause failures (CCFs)
in dynamic reliability analysis. Taking CCFs into account
is important when modelling systems with redundancies.
The dissertation extends the DFM by presenting CCF models
that take failure times of components into account.
| Original language | English |
|---|---|
| Qualification | Doctor Degree |
| Awarding Institution |
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| Supervisors/Advisors |
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| Award date | 13 Oct 2017 |
| Place of Publication | Espoo |
| Publisher | |
| Print ISBNs | 978-952-60-7571-6, 978-951-38-8565-6 |
| Electronic ISBNs | 978-952-60-7570-9, 978-951-38-8564-9 |
| Publication status | Published - 2017 |
| MoE publication type | G5 Doctoral dissertation (article) |
Keywords
- reliability analysis
- dynamic system
- risk importance measure
- common cause failure
- prime implicant
- digital control system