Potential Projects

Publication of the project topics

The project topics for the winter semester 2024/2025 will be available on this page from 1 October 2024. Please apply for the project by emailing the TM group contact person. The relevant contact information can be found in the respective project topics.


The application deadline by which you can then apply for the projects is 11 October 2024 until 11:59 pm.

Project 1

Project 1: Process Mining in Action: Optimizing Business Processes through Data-Driven Insights

Problem Statement:

In recent decades, companies' business processes have become increasingly complex. This development has been driven by a variety of factors, such as stricter regulatory requirements, changing customer needs and a changing technical and economic environment. In order to counteract this increasing complexity and at the same time ensure the efficiency of business processes, business process management (BPM) established itself as an independent specialist field back in the 1990s. BPM focuses on optimizing processes and adapting them to changing requirements.

As digitalization has progressed and new technical possibilities have emerged, process improvement has also evolved. Around ten years ago, the field of Process Mining emerged in this context. Process Mining forms a bridge between process science and data mining. It uses digital traces that arise in everyday business processes to make these processes transparent in a first step and to draw an accurate “as-is” picture of the actual processes. Based on this transparency, optimizations can be derived and implemented in the next step in order to further increase efficiency and eliminate potential bottlenecks or inefficiencies.

  • Dumas, Marlon; La Rosa, Marcello; Mendling, Jan; Reijers, Hajo A. (2018): Fundamentals of Business Process Management. Berlin, Heidelberg: Springer Berlin Heidelberg.
  • van der Aalst, Wil (2016): Process Mining. Berlin, Heidelberg: Springer Berlin Heidelberg.

Project Assignment:

As part of this bachelor's project, the participants are to independently carry out a case study in which they first implement the classic process of a process mining project. First, relevant data must be loaded into the Celonis process mining software. Various process mining dashboards are then to be created on this database to enable a detailed analysis of the current process. These dashboards serve as the basis for developing potential optimization measures for the existing process.

In addition to working out the optimization approaches, students must also develop and calculate a business case that illustrates the financial and operational benefits of the proposed measures. Finally, they have to present their results, including the optimization proposals and the business case, in a final presentation and make a convincing pitch.

It is intended to produce lessons learned throughout the project, with a focus on insights that can support the continuous improvement of teaching activities and contribute to the development of the Process Innovation and Automation Lab (PIA).

The Students will 

  • learn the basics and applications of process mining and deepen this knowledge by working on a real project.
  • acquire the ability to integrate and analyze data in order to identify process inefficiencies.
  • develop skills in creating business cases and presenting data-based optimization measures.
  • work together in groups to solve complex problems and successfully present project results.

Application: 

If you are interested in this project, form a group of 4-5 students and apply for this project with a short letter of motivation to Jannis.Nacke@icb.uni-due.de.