Process Mining of Programmable Logic Controllers: Input/Output Event Logs
For automation engineers, this provides a way to model undocumented PLC logic, though the approach is demonstrated only on simulated data.
The paper presents a method to reverse-engineer unknown PLC programs from input/output event logs using process mining, demonstrating applicability on three simulated scenarios.
This paper presents an approach to model an unknown Ladder Logic based Programmable Logic Controller (PLC) program consisting of Boolean logic and counters using Process Mining techniques. First, we tap the inputs and outputs of a PLC to create a data flow log. Second, we propose a method to translate the obtained data flow log to an event log suitable for Process Mining. In a third step, we propose a hybrid Petri net (PN) and neural network approach to approximate the logic of the actual underlying PLC program. We demonstrate the applicability of our proposed approach on a case study with three simulated scenarios.