Real-Time Data-Driven Maintenance Logistics

A Public-Private Collaboration

Conference Paper (2024)
Author(s)

Willem van Jaarsveld (Eindhoven University of Technology)

Laurens Bliek (Eindhoven University of Technology, TU Delft - Electrical Engineering, Mathematics and Computer Science)

Mathijs de Weerdt (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Stella Kapodistria (Eindhoven University of Technology)

Verus Pronk (Philips Research)

Peter Verleijsdonk (Eindhoven University of Technology)

Simon Voorberg (NEOMA Business School)

Sicco Verwer (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Yingqian Zhang (TU Delft - Electrical Engineering, Mathematics and Computer Science, Eindhoven University of Technology)

undefined More Authors (External organisation)

Research Group
Algorithmics
DOI related publication
https://doi.org/10.4230/OASIcs.Commit2Data.5 Final published version
More Info
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Publication Year
2024
Language
English
Research Group
Algorithmics
Article number
5
ISBN (electronic)
9783959773515
Downloads counter
293
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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.