Optimizing Virtual Commissioning of a Robotic System using Process Mining and Footprints Conformance Checking

Abstract

In the aircraft manufacturing industry, the process plans created for tasks such as automated drilling and riveting are lengthy and require prior testing and validation using Virtual Commissioning (VC), which can be time-consuming. The introduction of a new process plan requires the complete plan to be tested and validated again, exacerbating the challenge of testing and validating several plans or sequences in advance using VC. This research paper proposes using process mining and footprints conformance checking to reduce VC time for robotic systems. By integrating these techniques, differences in process plans can be detected, and only the new sequences or changes from an old to a new process plan need to be tested, significantly reducing the time needed to perform VC. This research implies that the developed approach can improve the efficiency of VC and ultimately enhance the performance of automated manufacturing systems.