The measure of effect in an expert system for automatic generation of fault trees

The authors introduce the measure of effect, which reflects both the probability of the cause factor and its effect on the event in the context of an expert system for automatic generation of fault trees. Its properties and applications are investigated and several theorems are proven. Using this measure it is possible to delete those events which have a minor effect on the resultant events in real cases and make the fault trees generated in the first stage simpler and more practical. An example illustrates the use of the measure of effect in the inference procedure