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oapen-20.500.12657-394812020-07-21T10:12:00Z Data Mining in MRO Pelt, Maurice Apostolidis, Asteris de Boer, Robert J. Borst, Maaik Broodbakker, Jonno Jansen, Ruud Helwani, Lorance Patron, Roberto Stamoulis, Konstantinos data mining U bic Book Industry Communication::U Computing & information technology 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 2020-06-09T10:19:12Z 2020-06-09T10:19:12Z 2019 book http://library.oapen.org/handle/20.500.12657/39481 eng application/pdf Attribution-NonCommercial-NoDerivatives 4.0 International data-mining-in-mro---publication-auas-2019.pdf https://www.amsterdamuas.com/car-technology/shared-content/projects/projects-general/data-mining-in-mro.html Amsterdam University of Applied Sciences c3051bc5-324a-4e1b-aa48-b1f6b58fe5a1 da087c60-8432-4f58-b2dd-747fc1a60025 Dutch Research Council (NWO) 53 Nederlandse Organisatie voor Wetenschappelijk Onderzoek Netherlands Organisation for Scientific Research open access
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OAPEN
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English
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description |
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
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data-mining-in-mro---publication-auas-2019.pdf
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data-mining-in-mro---publication-auas-2019.pdf
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data-mining-in-mro---publication-auas-2019.pdf
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title_full |
data-mining-in-mro---publication-auas-2019.pdf
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title_fullStr |
data-mining-in-mro---publication-auas-2019.pdf
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data-mining-in-mro---publication-auas-2019.pdf
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data-mining-in-mro---publication-auas-2019.pdf
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publisher |
Amsterdam University of Applied Sciences
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publishDate |
2020
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url |
https://www.amsterdamuas.com/car-technology/shared-content/projects/projects-general/data-mining-in-mro.html
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1771297514267344896
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