Nowadays, companies and their processes have to be adapted ever more quickly and flexibly. Process mining methods can create transparency and a better understanding of processes. Process mining makes it possible to identify, analyze and improve business processes based on data.

Up to now, process mining research has primarily focused on structured processes. Unstructured and knowledge-intensive processes such as product development or order processing in plant and mechanical engineering have received little attention to date. Many processes in individual and small batch production are not repeated frequently enough and are subject to customer and product-specific variants, meaning that the data volumes generated are comparatively small. Additional data must therefore be integrated into process mining and taken into account when interpreting the results.

The aim of the 'BPM-I4.0' project is the holistic development, implementation and evaluation of process mining methods for the analysis and prescriptive control of industrial core processes. To this end, methods and tools for the use of process mining in industry are to be developed. These methods consist of innovative procedures, concepts and algorithms that are to be prototypically designed, implemented, evaluated, processed and generalized in the product development and order processing processes of participating companies. The results achieved should enable the participating companies to significantly improve the quality of their core processes by analyzing their process data and to proactively control process execution in order to maintain and expand their competitiveness in the medium and long term.