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Real-Time Data-Driven Maintenance Logistics: A Public-Private Collaboration

Authors Willem van Jaarsveld , Alp Akçay , Laurens Bliek , Paulo da Costa , Mathijs de Weerdt , Rik Eshuis , Stella Kapodistria , Uzay Kaymak , Verus Pronk, Geert-Jan van Houtum , Peter Verleijsdonk , Sicco Verwer , Simon Voorberg , Yingqian Zhang

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ACM Subject Classification
  • General and reference → Surveys and overviews
Keywords
  • Data
  • Maintenance
  • Logistics
  • Optimization
  • Research
  • Project

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Abstract

The project "Real-time data-driven maintenance logistics" was initiated with the purpose of bringing innovations in data-driven decision making to maintenance logistics, by bringing problem owners in the form of three innovative companies together with researchers at two leading knowledge institutions. This paper reviews innovations in three related areas: How the innovations were inspired by practice, how they materialized, and how the results impact practice.

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Willem van Jaarsveld, Alp Akçay, Laurens Bliek, Paulo da Costa, Mathijs de Weerdt, Rik Eshuis, Stella Kapodistria, Uzay Kaymak, Verus Pronk, Geert-Jan van Houtum, Peter Verleijsdonk, Sicco Verwer, Simon Voorberg, and Yingqian Zhang. Real-Time Data-Driven Maintenance Logistics: A Public-Private Collaboration. In Commit2Data. Open Access Series in Informatics (OASIcs), Volume 124, pp. 5:1-5:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) https://doi.org/10.4230/OASIcs.Commit2Data.5

Author Details

Willem van Jaarsveld
  • Department of Industrial Engineering and Innovation Sciences, Eindhoven University of, Technology, The Netherlands
Alp Akçay
  • Department of Industrial Engineering and Innovation Sciences, Eindhoven University of, Technology, The Netherlands
Laurens Bliek
  • Department of Industrial Engineering and Innovation Sciences, Eindhoven University of, Technology, The Netherlands
Paulo da Costa
  • Etsy Inc., Dublin, Ireland
Mathijs de Weerdt
  • Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of , Technology, The Netherlands
Rik Eshuis
  • Department of Industrial Engineering and Innovation Sciences, Eindhoven University of , Technology, The Netherlands
Stella Kapodistria
  • Department of Mathematics and Computer, Science, Eindhoven University of Technology, The Netherlands
Uzay Kaymak
  • Jheronimus Academy of Data Science, Eindhoven University of Technology, The Netherlands
Verus Pronk
  • Philips Research Laboratories, Eindhoven, The Netherlands
Geert-Jan van Houtum
  • Department of Industrial Engineering and Innovation Sciences, Eindhoven University of, Technology, The Netherlands
Peter Verleijsdonk
  • Department of Mathematics and Computer, Science, Eindhoven University of Technology, The Netherlands
Sicco Verwer
  • Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of , Technology, The Netherlands
Simon Voorberg
  • Department of Information Systems Supply Chain Management and Decision Analysis, NEOMA Business School, Rouen, France
Yingqian Zhang
  • Department of Industrial Engineering and Innovation Sciences, Eindhoven University of , Technology, The Netherlands

Funding

This work was supported by the "Netherlands Organisation for Scientific Research" (NWO). Project: NWO Big data - Real Time ICT for Logistics. Number: 628.009.012.

Acknowledgements

We want to thank all the involved private partners who have contributed to this project.

References

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