Process Mining Quick-Scan

Automated Operational Process Improvement (AOPI)

The main aim of the AOPI project is to develop technology making it possible to support automated process improvement in a data-driven manner. We envision an interactive tool that supports and integrates multiple process mining disciplines such as process discovery, conformance checking and enhancement. For example, by highlighting deviations on the currently discovered mode, the user is able to (possibly manually) change the model to better describe reality.

Process Mining for Python (pm4py)

The Process Mining group of Fraunhofer FIT plays an active and leading role of the process mining for python (pm4py) python library. The pm4py library comprises of a vast array of process mining algorithms supporting all the aspects of process mining, i.e. process discovery, conformance checking and process enhancement. The library allows both researchers and industry professionals to more efficiently adopt process mining techniques in their analyses, and, allows for quick adoption with other data science algorithms and tools.