Abstract
Temporal aspects of multilevel flow modelling (MFM) are important for reasoning about causes and consequences. In particular real time reasoning about sensor data are dependent on proper temporal ordering of events in order to cope with plant dynamics. The purpose of the present paper is to contribute to the further development of the temporal aspects of MFM by explaining how time stamps associated to the measured signals can be used to enhance the causality analysis and infer the possible causes of a sequence of alarms.
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