Process Mining: Auswahl und Anwendung eines Vorgehensmodells im Bereich der Intralogistik

Abstract

This master's thesis examines the application of process mining in intralogistics with the aim of presenting processes transparently, uncovering weaknesses and identifying optimization potential. The focus is on the analysis of existing process models and their practical implementation based on a real use case at the BMW Group in Steyr. Four central research questions are answered in the thesis. For this purpose, a combination of literature research, model comparison and empirical case study is applied. In the first step, eight process models for the introduction of process mining were analyzed and compared using a qualitative multi-criteria analysis. The Bross model proved to be particularly suitable, due to its iterative structure and consideration of intralogistics specifics such as real-time requirements and heterogeneous IT systems. A significant part of the work is dedicated to the challenges involved in the practical implementation of process mining. Data quality and complex data preparation represent key challenges. The interpretation of the analysis results also requires specialist knowledge as subject-specific peculiarities can lead to incorrect conclusions. The analysis of potential use cases shows that process mining can be used in a variety of ways in intralogistics, from warehouse and picking processes to applications in conveyor control. In the practical part, the focus was on the shipping process, in which more than 1.1 million movement data from engines were analyzed. The data was visualized and prepared in a dashboard using the Celonis tool. The insights gained from this, such as throughput times and process variants, were validated through expert interviews. The interviewees confirmed the informative value of the analyses and rated process mining as a valuable tool for strategic and operational process control. In summary, the work shows that process mining is an effective tool for the data-based analysis of intralogistics processes. The structured model approach, the high transparency of the analysis and the integration of operational expertise make it possible to identify weak points and introduce sustainable improvements. The case study also proves the practical suitability of the Bross model. However, it should be noted that the choice of process model should always be made in the context of the use case. Further research could aim to develop modular or adaptive model approaches for different logistics scenarios. Especially in complex logistics systems, process mining can make a contribution to building up process knowledge and subsequently to increasing efficiency and process quality.

Date of Award	2025
Original language	German (Austria)
Supervisor	Matthias Neubauer (Supervisor)