Platform for data-driven logistics

Small and medium-sized enterprises have limited in-house expertise, resources and tools to develop data-driven applications. Therefore, an industry platform was developed for the collective research and development of data-driven applications for the logistics industry. The industrial research project focused on developing inspiring use cases to raise the awareness of data-driven logistics and stimulate adoption.

Methodology

The design science research methodology was utilized to design, develop, test, and implement an industry platform for data-driven logistics. The data platform is based on the Open Trip Model (OTM) for real-time data exchange and to standardize algorithms in reusable data-driven applications. The industry platform was tested in collaboration with Emons in a pilot study for smart tendering and project for dynamic refuelling.

Results

In order to stimulate data use, an industry platform was designed and a supporting learning community was established. The industry platform has been realized in three iterations and provides:

1. a web-based user interface,
2. APIs for real-time data exchange using the OTM,
3. OTM compliant database,
4. developer toolbox to create data-driven applications, and
5. a scalable infrastructure to run and monitor applications.

The learning community supported the development and adoption of data-driven applications with practical design tools, educational materials, and an evaluation framework.

Authors and downloads

This research is performed by Sebastian Piest, Martijn Gemmink , Bjorn Goossens , Maria Iacob and Marten J. van Sinderen .

Poster

• Platform for data-driven logistics

Publications

• Piest, J. P. S. (2022). An Industry Platform for Data-driven Logistics in Small and Medium-sized Enterprises. [EngD Thesis, University of Twente]. University of Twente. https://doi.org/10.3990/1.9789036553650
• Piest, J. P. S., Iacob, M. E., van Sinderen, M. J., Gemmink, M., & Goossens, B. (2021). A Reinforcement Learning Platform for Small and Medium-sized Enterprises in Logistics. In 2021 IEEE 25th International Enterprise Distributed Object Computing Workshop (EDOCW) (pp. 289-298). (IEEE International Enterprise Distributed Object Computing Workshop (EDOCW); Vol. 2021). IEEE. https://doi.org/10.1109/EDOCW52865.2021.00060

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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 "Reinforcement LeArning Platform voor Logistieke MKBs (ReAL)" and supported by the Topsector Logistiek and NWO (Dutch Research Council).

For more information (in Dutch) check the:

• Project page ICCOS
• Project page ReAL