| Issue |
MATEC Web Conf.
Volume 304, 2019
9th EASN International Conference on “Innovation in Aviation & Space”
|
|
|---|---|---|
| Article Number | 04005 | |
| Number of page(s) | 8 | |
| Section | Systems | |
| DOI | https://doi.org/10.1051/matecconf/201930404005 | |
| Published online | 17 December 2019 | |
Data analytics case studies in the maintenance, repair and overhaul (MRO) industry
1
Aviation Academy, Faculty of Technology, Amsterdam University of Applied Sciences (AUAS)
Amsterdam,
Netherlands
2
KLM Royal Dutch Airlines,
Netherlands
Data analytics seems a promising approach to address the problem of unpredictability in MRO organizations. The Amsterdam University of Applied Sciences in cooperation with the aviation industry has initiated a two-year applied research project to explore the possibilities of data mining. More than 25 cases have been studied at eight different MRO enterprises. The CRISP-DM methodology is applied to have a structural guideline throughout the project. The data within MROs were explored and prepared. Individual case studies conducted with statistical and machine learning methods, were successfully to predict among others, the duration of planned maintenance tasks as well as the optimal maintenance intervals, the probability of the occurrence of findings during maintenance tasks.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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