Data Mining in MRO
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. Res...
שמור ב:
| Main Authors: | , , , , , , , , |
|---|---|
| פורמט: | Online |
| שפה: | אנגלית |
| יצא לאור: |
Amsterdam University of Applied Sciences
2021
|
| נושאים: | |
| גישה מקוונת: | OCN: 1253405383 |
| תגים: |
אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!
|
| _version_ | 1869514789801164800 |
|---|---|
| author | Pelt, Maurice Apostolidis, Asteris de Boer, Robert J. Borst, Maaik Broodbakker, Jonno Jansen, Ruud Helwani, Lorance Patron, Roberto Stamoulis, Konstantinos |
| author_browse | Apostolidis, Asteris Borst, Maaik Broodbakker, Jonno Helwani, Lorance Jansen, Ruud Patron, Roberto Pelt, Maurice Stamoulis, Konstantinos de Boer, Robert J. |
| author_facet | Pelt, Maurice Apostolidis, Asteris de Boer, Robert J. Borst, Maaik Broodbakker, Jonno Jansen, Ruud Helwani, Lorance Patron, Roberto Stamoulis, Konstantinos |
| author_sort | Pelt, Maurice |
| collection | Directory of Open Access Books |
| 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 |
| format | Online |
| id | doab-20.500.12854ir-33071 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | Amsterdam University of Applied Sciences |
| publisherStr | Amsterdam University of Applied Sciences |
| record_format | ojs |
| spelling | doab-20.500.12854ir-330712025-03-11T20:41:58Z 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 thema EDItEUR::U Computing and 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 2021-02-10T14:04:43Z 2021-02-10T14:04:43Z 2020-06-09T10:19:12Z 2019 book OCN: 1253405383 http://library.oapen.org/handle/20.500.12657/39481 https://directory.doabooks.org/handle/20.500.12854/33071 eng open access image/jpeg image/jpeg image/jpeg Attribution-NonCommercial-NoDerivatives 4.0 International Attribution-NonCommercial-NoDerivatives 4.0 International Attribution-NonCommercial-NoDerivatives 4.0 International https://library.oapen.org/bitstream/20.500.12657/39481/1/data-mining-in-mro---publication-auas-2019.pdf https://library.oapen.org/bitstream/20.500.12657/39481/1/data-mining-in-mro---publication-auas-2019.pdf https://library.oapen.org/bitstream/20.500.12657/39481/1/data-mining-in-mro---publication-auas-2019.pdf Amsterdam University of Applied Sciences e0a6503c-7ce4-4889-8213-7eef270ca402 Nederlandse Organisatie voor Wetenschappelijk Onderzoek da087c60-8432-4f58-b2dd-747fc1a60025 Dutch Research Council (NWO) 53 open access |
| spellingShingle | data mining thema EDItEUR::U Computing and Information Technology Pelt, Maurice Apostolidis, Asteris de Boer, Robert J. Borst, Maaik Broodbakker, Jonno Jansen, Ruud Helwani, Lorance Patron, Roberto Stamoulis, Konstantinos Data Mining in MRO |
| title | Data Mining in MRO |
| title_full | Data Mining in MRO |
| title_fullStr | Data Mining in MRO |
| title_full_unstemmed | Data Mining in MRO |
| title_short | Data Mining in MRO |
| title_sort | data mining in mro |
| topic | data mining thema EDItEUR::U Computing and Information Technology |
| topic_facet | data mining thema EDItEUR::U Computing and Information Technology |
| url | OCN: 1253405383 |
| work_keys_str_mv | AT peltmaurice datamininginmro AT apostolidisasteris datamininginmro AT deboerrobertj datamininginmro AT borstmaaik datamininginmro AT broodbakkerjonno datamininginmro AT jansenruud datamininginmro AT helwanilorance datamininginmro AT patronroberto datamininginmro AT stamouliskonstantinos datamininginmro |