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Modelling a helicopter training continuum to support system transformation

Johnstone, Michael, Le, Vu, Khan, Burhan, Creighton, Doug, Novak, Ana, Nguyen, Vivian and Tracey, Luke 2015, Modelling a helicopter training continuum to support system transformation, in I/ITSEC 2015: Forging the Future Through Innovation. Interservice/Industry Training, Simulation, and Education Conference (NTSA), [National Training and Simulation Association], [Arlington, Va.], pp. 1-11.

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Title Modelling a helicopter training continuum to support system transformation
Author(s) Johnstone, MichaelORCID iD for Johnstone, Michael orcid.org/0000-0002-3005-8911
Le, Vu
Khan, Burhan
Creighton, DougORCID iD for Creighton, Doug orcid.org/0000-0002-9217-1231
Novak, Ana
Nguyen, Vivian
Tracey, Luke
Conference name NTSA Interservice/Industry Training, Simulation, and Education Conference (49th: 2015: Orlando, Fla.)
Conference location Orlando, Fla.
Conference dates 30 Nov. - 4 Dec. 2015
Title of proceedings I/ITSEC 2015: Forging the Future Through Innovation. Interservice/Industry Training, Simulation, and Education Conference (NTSA)
Publication date 2015
Start page 1
End page 11
Total pages 11
Publisher [National Training and Simulation Association]
Place of publication [Arlington, Va.]
Summary his study investigates the role of system dynamics (SD) modeling to support strategic decision making for an aviation training continuum that is going through major change. The Australian helicopter training continuum (HTC) is currently undergoing transformation, with restructure and consolidation of training schools and training platforms across multiple services. In this research, we introduce a novel SD-based HTC simulation architecture to facilitate the discovery of relationships between student and instructor development and flow dynamics. The proposed simulation architecture employs hybrid push – pull flow control to quantify transience and estimate recovery time after a policy change or disturbance. This architecture allows for multiple student and instructor types, and their respective intake levels and pass rates. Here the instructor variables include availability, specialization and experience. Enos (2011) successfully explored the application of SD modeling to understand the behavior for combat aviation training in an individual school. This research employs a similar modeling philosophy, but takes a higher level view of the system by looking across multiple training schools, which introduces complexity due to pooling, latency and the amplification of affects across the system. The ability to identify causal relationships allowed stakeholders to develop a deeper understanding of the underlying systemic problems, such as delayed transitions between schools and instructor shortages, whilst the hybrid “push-pull” design allowed us to quantify the pooling of students between schools.
Language eng
Field of Research 080110 Simulation and Modelling
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2015, NTSA
Persistent URL http://hdl.handle.net/10536/DRO/DU:30082979

Document type: Conference Paper
Collection: Centre for Intelligent Systems Research
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