Development of a decision support framework for systems architecting in aerospace applications

The exploration of the architectural solution space tends to be iterative, where multiple system architectures are explored over several cycles before a final solution is selected. However the time and cost required to conduct this activity can be significant in the presence of multiple system architectures. This thesis presents a decision support framework that assists the system architect in generating, analysing, and identifying optimal system architectures. The framework achieves this by using a formal modelling approach that represents the architectural decision-making process as a Constraint Optimisation Problem (COP), resulting in a graph representation of interconnected architectural decision variables. The graph-based approach provides computational tools that enables the system architect to automatically synthesise viable architectures based on the constraints defined, and calculate high-impact decision variables within the network. This capability is enabled by synthesising concepts from decision theory, multi-objective optimisation, and centrality measures from network analysis to provide a visual representation of high-impact decision variables. In applying this framework to the design of a low-cost Unmanned Aircraft System (UAS), we identify the choice of design alternatives relating to the implementation of the payload sensor system to have a high-impact on system properties and network connectivity. Suggesting that the exploration of the solution space should be focused towards payload implementation