Discrete Event Model Structure Identification using Process Mining

Agnes Werner-Stark, Miklós Gerzson, and Katalin M. Hangos


discrete event systems, structure identification, process mining


A novel structure identification procedure for discrete event systems described by Petri nets are proposed in this paper for model-based diagnostic purposes that utilize the notions and tools of process mining. The identification of the structurally different discrete event system models describing a system in its normal and/or faulty modes was used for model-based isolation of the considered faulty modes. From the available process mining techniques that allow for the automatic construction of process models in Petri net form based on event logs, the genetic algorithm-based structure identification procedure has been found to be most capable of identifying the characteristic structural elements of the faulty models.The proposed procedures are illustrated on a simple example of an operated parking gate automaton with two faulty modes.

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