The technique of fault tree analysis is commonly used to assess the probability of
failure of industrial systems. During the analysis of the fault tree the component
failures are assumed to occur independently. When this condition is not satisfied
alternative approaches such as the Markov method can be used. Constructing the
Markov representation of a system is not such as intuitive process for engineers as
fault tree construction since the state-transition diagram does not readily document the
failure logic. In addition to this the size of the Markov diagram increases rapidly as
the number of components in the system increases.
This thesis presents the development of a new model which uses a combination of
conventional fault tree methods with those of Markov methods to solve systems
containing sequential or standby failures. New gates were developed in order to
incorporate the dependent failures on the fault tree structure. The new assessment
method was shown to efficiently solve these systems. With theses extended fault tree
capabilities in place the technique was embedded within an optimisation framework to
obtain the best system performance for systems containing standby failures.
Sequential failures can be represented on a fault tree by using the Priority-And gate,
however they can also be represented on a Cause-Consequence diagram. As with the
fault tree analysis method, the Cause-Consequence Diagram method documents the
failure logic of the system. In addition to this the Cause-Consequence Diagram
produces the exact failure probability in a very efficient calculation procedure and has
significant implications in terms of efficiency for static systems. Construction and
analysis rules were devised for a cause-consequence diagram and used on systems
containing independent and dependent failures.
A Doctoral Thesis. Submitted in partial fulfillment of the requirements for the award of Doctor of Philosophy of Loughborough University.