Petri net discovery of discrete event processes by computing t-invariants

Abstract

In this paper the problem of discovering a Petri net (PN) from sampled events sequences representing the execution of industrial or business processes is addressed A method for building a 1-bounded PN from a single event sequence S composed of numerous execution traces is presented; it is based on determining causal and concurrency relations between tasks. A technique for computing the t-invariants of the PN from S is proposed; the obtained invariants allow determining the structure of a PN that executes S. The algorithms derived from the method have been implemented and tested on numerous examples of diverse complexity.