ABOUT BOOK

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