Model-driven aviation training family of systems architecture

The Ph.D. project has evolved from focusing on the technical problem of the integration and interoperability of an assemblage of complex systems and SoS within a flight training system to development of a workflow process using frameworks to aid the decision making process for the selection of optimal flight training blending mixes. The focus of the research involved developing a methodology to satisfy research project proposal requirements agreed upon with the industrial sponsor. This thesis investigates the complexity of a modern flight training systems and the need for understanding that it is supported by a complex Family of Systems (FoS) including Virtual Reality Training Environments such as flight simulators, to live training aircraft with various configurations of avionic controls. One of the key technical problems today is how best to develop and assemble a family of flight training system into an integrated Live / Synthetic mix for aircrew training to optimise organisation and training objectives. With the increased use of emulation/synthetic data on aircraft for live training, the synthetic boundary is becoming increasingly blurred. Systematic consideration of the most appropriate blend is needed. The methodology used in the research is model driven and the architecture produced is described at a level of abstraction to enable communication to all stakeholders for the means of understanding the structure involved in the system design process. Relational Oriented Systems Engineering and Technology Trade-Off Analysis (ROSETTA) frameworks are described using Model Based Systems Engineering (MBSE) techniques for supporting capability based trade-off decisions for selection of optimal flight training FoS mixes dependent on capability. The research proposes a methodology and associated methods including a high-level systematic closed loop information management structure for blended device/tool aircrew training and a modelling and analysis approach for the FoS aviation training problem to enhance the existing training programmes to provide a more efficient and agile training environment. The mathematical formalisms used provide a method of quantifying subjective opinions and judgements for trade studies to be accomplished on the suitability of technology for each student pilot in relation to training and organisational objectives. The methodology presented is by no means a final solution, but a path for further research to enable a greater understanding of the suitability of training tools / technology used to train individual pilots at various stages throughout the training pipeline lifecycle(s).