TY  - BOOK
AU  - Pelt, Maurice
AU  - Apostolidis, Asteris
AU  - de Boer, Robert J.
AU  - Borst, Maaik
AU  - Broodbakker, Jonno
AU  - Jansen, Ruud
AU  - Helwani, Lorance
AU  - Patron, Roberto
AU  - Stamoulis, Konstantinos
AB  - 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. 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, analyse 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
KW  - data mining
L1  - https://library.oapen.org/bitstream/id/083fcbfb-ac19-4e2e-9ca4-a632c5f23d02/data-mining-in-mro---publication-auas-2019.pdf
LA  - English
LK  - http://library.oapen.org/handle/20.500.12657/39481
PB  - Amsterdam University of Applied Sciences
PY  - 2019
TI  - Data Mining in MRO : Centre for Applied Research Technology
ER  - 
