Data analytics case studies in the maintenance, repair and overhaul (MRO) industry

Abstract

Data analytics seems a promising approach to address the problem of unpredictability in MRO organizations. The Amsterdam University of Applied Sciences in cooperation with the aviation industry has initiated a two-year applied research project to explore the possibilities of data mining. More than 25 cases have been studied at eight different MRO enterprises. The CRISP-DM methodology is applied to have a structural guideline throughout the project. The data within MROs were explored and prepared. Individual case studies conducted with statistical and machine learning methods, were successfully to predict among others, the duration of planned maintenance tasks as well as the optimal maintenance intervals, the probability of the occurrence of findings during maintenance tasks.