Fleet Management Decision Making With Individual Aircraft Tracking Data

Fleet Management Decision Making With Individual Aircraft Tracking Data

Newcamp, Jeffrey (TU Delft Air Transport & Operations)
Verhagen, W.J.C. (TU Delft Air Transport & Operations)
Curran, R. (TU Delft Air Transport & Operations)

2017

Individual aircraft tracking data can be used by aircraft fleet managers to detect patterns in historical usage as a means to aid aging aircraft decision-making. This work tackles two aspects of applying these tracking data: investigating retirement patterns and assessing how base assignment can impact usage. The A-10, C-17 and F-35 acquisition schedules were analyzed to set the expectation for retirement forecasting. Then three types of retirement patterns were assessed - the Cliff, Multi-Step and Ramp - and the merits of each are presented. Equivalent flight hours were used as an approximation for fatigue life expended in the analysis of retirement patterns in tracking data. A candidate set of tracking data was investigated to uncover base usage variations across a network. The dissimilar mission type requirements at each base led to unique loading profiles for aircraft at each of the bases in the network. These findings lead to the natural conclusion that base assignment can be used as a way to modify the loading accumulation on individual tail numbers and across a fleet.

http://resolver.tudelft.nl/uuid:96e675a1-f1ba-46fc-b35b-0c5aff6bafd4

Proceedings of the 35th Conference and 29th ICAF Symposium – Nagoya, 7–9 June 2017

35 Conference and 29th International Committee on Aeronautical Fatigue Symposium, 2017-06-05 → 2017-06-09, Winch Aichi, Nagoya, Japan

Institutional Repository

conference paper

© 2017 Jeffrey Newcamp, W.J.C. Verhagen, R. Curran