Abstract: A method for automated generation of an extended fault tree structure adapted to a production installation or a specific installation is used within a system determining the effectiveness and analyzing causes of faults. Generation takes place using a data processor and stored programs for carrying out functions of a hypothesis verifier, a fault data classifier, and a hypothesis configurer, and also based upon a prescribed general hierarchical fault tree structure produced by accessing data of a data server with the verifier, from which it derives fault events according to execution requirements of the verification script and stores these fault events, possibly together with previously entered fault events, in a fault database. At prescribable time intervals, the classifier carries out classification of the fault events by accessing the database, maps them as weighted causes of faults onto the tree structure, and displays or outputs the tree structure so extended.

Abstract: A method and a system are described for determining the effectiveness of production installations, significant fault events that bring about deviations from a desired effectiveness and the causes of fault events. The production installation is connected to a data acquisition device, which is set up for continuous acquisition and ready-to-call-up storage of installation and production-related data. A service device is connected to the data acquisition device and has an input device for the input of additional installation and production-related descriptive data that cannot be called up from the data acquisition device. An online system part is set up for calling up installation and production-related data from the data acquisition device, calculating the effectiveness, detecting fault events, determining significant fault events by fault event evaluation, and determining in each case the causes of faults. An offline system part is provided and contains a number of generic fault models and assessment models.