Process mining in logistics

Real-time event data from board computers is a rich source for process mining. However, event data originates from heterogenous sources, which lead to data quality and interoperability issues. This experimental research project aimed to assess if the Open Trip Model (OTM) can solve these issues and be used for the development of standardized process mining applications.

Methodology

First, an informal conceptual mapping study was conducted to assess the feasibility of the OTM for process mining. Next, experimental research has been conducted to assess the use of the OTM to create an event log for process mining. Then, case study research was conducted using real-life datasets. Lastly, the platform for data-driven logistics was utilized to develop reusable and standardized process mining applications.

Results

The experimental research successfully demonstrated the feasibility of the OTM for process mining. More specific, the mapping study showed how the minimal requirements for creating an event log can be satisfied. The case study illustrated the current problems. The platform demonstrated how these problems can (partly) be solved. Furthermore, the research showed the potential of standardized process mining with four generalizable use cases, including process performance measurement, bottleneck detection, waiting time analysis, and compliance with EU driving and resting regulations. Additionally, a set of standard KPIs were developed based on the OTM.

Authors and downloads

This research is performed by Jennifer Cutinha , Thom Baas , Bhinawa Putra Raja , Rob Bemthuis , Faiza A. Bukhsh and Sebastian Piest.

Poster

Process mining in logistics

Theses and articles

• Cutina, Jennifer (2020) Assessing the use of process mining techniques to monitor the work process of commercial drivers. https://essay.utwente.nl/82235/
• Baas, T. (2022) Creating standardized process mining applications based on the open trip model. https://essay.utwente.nl/92066/
• Putra Raja, Bhinawa (2023) Visualizing Transport Key Performance Using the Open Trip Model Data Messaging Format. https://essay.utwente.nl/94012/
• Piest, J.P.S., Cutinha, J.A., Bemthuis, R.H., and Bukhsh, F.A. (2021). Evaluating the Use of the Open Trip Model for Process Mining: An Informal Conceptual Mapping Study in Logistics. http://dx.doi.org/10.5220/0010477702900296
• Piest, J.P.S., Bemthuis, R.H., Cutinha, J.A., Arachchige, J.J. , & Bukhsh, F.A. (2023). A Method for Bottleneck Detection, Prediction, and Recommendation Using Process Mining Techniques. https://doi.org/10.1007/978-3-031-36840-0_7

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This research was conducted as part of the TKI DINALOG projects "Industry 4.0 driven Supply Chain Coordination for Small and Medium-sized Enterprises (ICCOS)" and supported by the Topsector Logistiek . For more information (in Dutch) check the: Project page ICCOS.