Knowledge Based Engineering (KBE) applications mainly reduce the lead-time in engineering design projects by translating product and process knowledge into application code. The problem with KBE applications is that they produce an output from some input, but it is unclear how it came to its conclusions. There are existing KBE methodologies such as MOKA that proposes a few models to help understand what the KBE application is doing, but these models are disconnected from the application code: there is no traceability of knowledge onto application code. Moreover, MOKA requires specialists which are often not available; this hinder adoption of the methodology. Therefore , this thesis proposes a new ontology that explains how to structure knowledge without specialists, and defines how that knowledge is connected to application code. Moreover, a platform has been developed which incorporates the new ontology, and enables users to structure knowledge and connect it to code.

The Unmanned Aerial Vehicle (UAV) market is growing, as the field of application becomes increasingly diverse. Various missions performed by UAVs such as transport, surveillance and monitoring missions can be less challenging and more efficient compared to missions carried out by manned aircraft. The new design principle of combining a helicopter and a conventional aircraft has been proven to be prominent, as it allows a UAV to be versatile and have capability of being retrofitted to different mission profiles; these Hybrid UAVs are able to operate at broader conditions, as they can take-off and land without a runway and have a horizontal flight performance of a conventional aircraft.