J. Grell, H. Meyer, F. Raddatz, S. Pulham

Further development of digitalization and technology increases the amount of usable data and the possibilities of using it. With increasing competition in aviation around the world and decreasing profits, the value of this flight data is rising. Therefore, it is not surprising, that ways of misusing the data are growing likewise, which in some cases has led to compromised safety [1]. Hence storing and using data in a suitable way is one of the major challenges these days. One of the many stakeholders in this difficult process of finding an appropriate way of handling this kind of data are the pilots. They are the ones, who are producing the flight data and who can primarily face consequences by the misuse of such data. In the LuFo project OBSERVATOR predictive maintenance technologies are examined. Therefore, the acceptance from commercial pilots to use flight data for predictive maintenance is measured through structural equation modelling. Especially the influence of facilitating conditions and the pilots perceived risk are considered. The findings of this paper reveal that while the facilitating conditions have a positive impact on the perceived usefulness, which positively affects the intention to allow such usage of flight data, they also have a negative impact on the perceived risk, which negatively influences said intention. Furthermore, we asked the pilots what would help them feel more comfortable with the flight data being used for predictive maintenance and whom they trust the most with handling their flight data. The results of this give some advice on what future systems should consider.

Deutscher Luft- und Raumfahrtkongress 2021

Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V., Bonn, 2021

Conference Paper

englisch

21,0 x 29,7 cm, 7 Seiten

urn:nbn:de:101:1-2021092413084297638769

10.25967/550192

Flight Data, Predictive Maintenance

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Grell, J.; Meyer, H.; et al. (2021): Measuring the Acceptance from Commercial Pilots towards the Usage of Flight Data for Predictive Maintenance. Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V.. (Text). https://doi.org/10.25967/550192. urn:nbn:de:101:1-2021092413084297638769.

24.09.2021