In the last 30 years various mathematical models have been used to identify the effect of component failures on the performance of a system. The most frequently used technique for system reliability assessment is Fault Tree Analysis (FTA) and a large proportion of its popularity can be attributed to the fact that it provides a very good documentation of the way that the system failure logic was developed. Exact quantification of the fault tree, however, can be problematic for very large systems and in such situations approximations can be used. Alternatively an exact result can be obtained via the conversion of the fault tree into a binary decision diagram. The binary decision diagram, however, loses all failure logic documentation during the conversion process. This paper outlines the use of the Cause-Consequence Diagram method as a tool for system risk and reliability analysis. As with the fault tree analysis method, the Cause-Consequence Diagram 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. The Cause-Consequence Diagram technique has been applied to a static system and shown to yield the same result as those produced by the solution of the equivalent fault tree and binary decision diagram. On the basis of this, general rules have been devised for the correct construction of the Cause-Consequence Diagram given a static system. The use of the cause-consequence method in this manner has significant implications in terms of efficiency of the reliability analysis and can be shown to have benefits for static systems.

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The technique of fault tree analysis is commonly used to assess the probability of failure of industrial systems. The fault tree represents the failure logic of the system in an inverted tree structure and has the advantage that it provides very good documentation of the way that the failure logic was developed. During the analysis of a fault tree the component failures or basic events are assumed to occur independently. When this condition is not satisfied, as in the case of standby systems for example, alternative approaches such as Markov methods can be used. Constructing the state transition diagram required for a Markov model is not such an intuitive process for engineers as fault tree construction, since state transition diagrams do not readily document the failure logic process. This paper introduces a new gate into the fault tree diagram, which enables the reliability analyst to incorporate standby dependencies. The analysis of the fault tree is then performed by identifying the sections of the fault tree which conform to the usual requirements of independence and those which do not. Using a combination of conventional fault tree analysis methods with Markov methods, the analysis of the tree is performed by computer code in a manner that is transparent to the analyst. A similar approach has been developed for the analysis of systems with sequential failures represented by a PRIORITY AND gate on the fault tree diagram. With these extended fault tree capabilities in place, the technique has been embedded within an optimization framework to get the best system performance for systems where failures are dependent. Copyright © 1999 John Wiley & Sons, Ltd.