Over the last decade, Unmanned Aerial Vehicles (UAVs) have experienced an accelerated growth, and nowadays they are being deployed in a variety of missions that have traditionally been covered by manned aircraft. This unprecedented market expansion has created new and unforeseen challenges for the manufacturing industry which is now called to further reduce the idea-to-market times while simultaneously delivering designs of even higher performance. In this environment of uncertainty and risk, it is without a doubt crucial for the involved actors to find ways to secure their strategic advantage, and hence, implementing the latest design tools has become a critical consideration in every Product Development Process (PDP).

To this end, a method that has been frequently applied in the PDP and has shown many successful results in the development of complex engineering products is Multidisciplinary Design Optimization (MDO). In general, MDO can bring additional knowledge regarding the best-suited designs much earlier in the process, and in this respect, it can lead to significant cost and time savings by reducing the total number of refinement iterations. Nevertheless, the organizational and cultural integration of MDO has been often overlooked, while at the same time, several technical aspects of the method for UAV design are still at an elementary level. On the whole, research on MDO is showing a slow progress, and to this date, there are many limitations in both the disciplinary models and the available analysis capabilities.

In light of the above, this thesis focuses on the particulars of the MDO methodology, and more specifically, on how it can be best adapted and evolved in order to enhance the development process of UAVs. The primary objective is to study the current trends and gaps of the MDO practices in UAV applications, and subsequently to build upon that and explore how these can be included in a roadmap that will be able to serve a guide for newcomers in the field. Compared to other studies, the problem is herein approached from both a technical as well as organizational perspective, and thus, this research not only aims to propose techniques that can lead to better designs but also solutions that will be meaningful to the PDP. Having established the above foundation, this work shows that the traditional MDO frameworks for UAV design have been neglecting several important features, and it elaborates on how those novel elements can be modeled in order to enable a better integration of MDO into the organizational functions. Overall, this thesis presents quantitative and qualitative data which illustrate the effectiveness of the new framework enhancements in the development process of UAVs, and concludes with discussions on the possible improvement directions towards achieving more and better MDO capabilities.

Over the last years, Unmanned Aerial Vehicles (UAVs) have gradually become a more efficient alternative to manned aircraft, and at present, they are being deployed in a broad spectrum of both military as well as civilian missions. This has led to an unprecedented market expansion with new challenges for the aeronautical industry, and as a result, it has created a need to implement the latest design tools in order to achieve faster idea-to-market times and higher product performance.

As a complex engineering product, UAVs are comprised of numerous sub-systems with intricate synergies and hidden dependencies. To this end, Multidisciplinary Design Optimization (MDO) is a method that can identify systems with better performance through the concurrent consideration of several engineering disciplines under a common framework. Nevertheless, there are still many limitations in MDO, and to this date, some of the most critical gaps can be found in the disciplinary modeling, in the analysis capabilities, and in the organizational integration of the method.

As an aeronautical product, UAVs are also expected to work together with other systems and to perform in various operating environments. In this respect, System of Systems (SoS) models enable the exploration of design interactions in various missions, and hence, they allow decision makers to identify capabilities that are beyond those of each individual system. As expected, this significantly more complex formulation raises new challenges regarding the decomposition of the problem, while at the same time, it sets further requirements in terms of analyses and mission simulation.

In this light, this thesis focuses on the design optimization of UAVs by enhancing the current MDO capabilities and by exploring the use of SoS models. Two literature reviews serve as the basis for identifying the gaps and trends in the field, and in turn, five case studies try to address them by proposing a set of expansions. On the whole, the problem is approached from a technical as well as an organizational point of view, and thus, this research aims to propose solutions that can lead to better performance and that are also meaningful to the Product Development Process (PDP).

Having established the above foundation, this work delves firstly into MDO, and more specifically, it presents a framework that has been enhanced with further system models and analysis capabilities, efficient computing solutions, and data visualization tools. At a secondary level, this work addresses the topic of SoS, and in particular, it presents a multi-level decomposition strategy, multi-fidelity disciplinary models, and a mission simulation module. Overall, this thesis presents quantitative data which aim to illustrate the benefits of design optimization on the performance of UAVs, and it concludes with a qualitative assessment of the effects that the proposed methods and tools can have on both the PDP and the organization.