Data Mining in MRO
Publication - February 2019
Data mining seems to be a promising way to tackle the problem of unpredictability in MRO organizations. The Amsterdam University of Applied Sciences therefore cooperated with the aviation industry for a two-year applied research project exploring the possibilities of data mining in this area.
Research and Findings
Researchers studied more than 25 cases at eight different MRO enterprises, applying a CRISP-DM methodology as a structural guideline throughout the project. They explored, prepared, and combined MRO data, flight data, and external data, and used statistical and machine learning methods to visualize, analyze, and predict maintenance. They also used the individual case studies to make predictions about the duration and costs of planned maintenance tasks, turnaround time, and useful life of parts.
Challenges presented by the case studies included time-consuming data preparation, access restrictions to external data sources, and the still-limited data science skills in companies. Recommendations were made in terms of ways to implement data mining—and ways to overcome the related challenges—in MRO.
Overall, the research project has delivered promising proofs of concept and pilot implementations.
Authors
- Maurice Pelt
- Konstantinos Stamoulis
- Asteris Apostolidis
- Robert J. de Boer
- Maaik Borst
- JJonno Broodbakker
- R. Jansen
- Lorance Helwani
- Roberto Felix Felix Patron
- Konstantinos Stamoulis
- Jonno Broodbakker
- Ruud Jansen
- Roberto Felix Patron
Aviation Engineering research group
The aviation industry must become smarter and more sustainable. The Aviation Engineering research group is ensuring the sector has all the knowledge and insights it needs to transition to, and develop, more-efficient en more-environmentally friendly engineering and operational practices.