A Process Model Repair Approach by Constructing Choice Structures via Logic Petri Nets

Abstract

Models of business processes can be discovered and improved by process mining techniques according to event logs generated by enterprise information systems. With the changing of business processes, some new activities that have choice relations with original activities appear in event logs, while the original model cannot replay them. Thus, a new process mining technique named model repair is developed. However, existing model repair methods cannot accurately find the positions where to add these new activities. This paper proposes a new model repair method based on logic Petri nets, which can add new activities as choice branches to the original model. First, two order sets for an event log and an original model are constructed by redefining order relations. Then the deviations related to new activities are collected. Next, the model is repaired by adding new activities as choice branches or constructing new choice structures. The correctness and effectiveness of the proposed method is illustrated by some case studies and experiments. The precision and simplicity of the repaired model is improved by our method comparing with other methods.

Keywords

• Logic petri net
• process mining
• model repair
• order relations
• choice structures