Application of the cause–consequence diagram method to static systems

Abstract

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.

A Comparative Study of Risk Assessment Methods, MEHARI & CRAMM with a New Formal Model of Risk Assessment (FoMRA) in Information Systems

“…Most of elaborated quantitative, qualitative methods (graph-based, static and dynamic, relational and Markov) uses some or the majority of the assumptions of a standard model proposed by Parker [26,27,28,29,30]. These methods differ, however, in the approaches to the identification and classification of the assets, vulnerabilities and risks, the risk value assessment, the choice of countermeasures, etc.…”

Cause–consequence analysis of non-repairable phased missions

“…To deal with a common event failure the following algorithm is suggested, Andrews and Ridley [5,7]: 1. Extract the common event from the fault tree structures and place it in a new decision box preceding the first decision box that contains the common failure event (the new event is the occurrence of the common event: YES/NO).…”

“…The other dependency that can arise in the cause-consequence diagram is that the same component may be required to perform different functions which, if successfully accomplished, results in the components residing in different states at different times [5,7]. For example, initially a relay may be required to be closed and later in the sequence to be open.…”

“…As all consequence sequences are investigated, the method can assist in identifying system outcomes, which may not have been investigated at the design stage. Ridley and Andrews [5] notice that, for some types of system, the final cause-consequence diagram has an identical structure to that of the BDD. They noted however that the causeconsequence diagram was more concise due to the automatic extraction of common independent sub-modules.…”

Development of an algorithm for automated cause-consequence diagram construction

“…If a decision box is governed not by a component but by a sub-system then the probability of failure will be obtained via a fault tree [7]. These fault trees are produced automatically using fault tree construction methods developed previously [4,5].…”