Best Supply Chain, Manufacturing and Aircraft Systems identification leveraging a Model-based Product Line Engineering Approach

Public perception of aviation is a key driver of demand for enhanced environmental sustaina-bility, with the aim of mitigating the industry's effects on climate change. The Flightpath 2050 initiative reflects this perception by aiming for environmental neutrality, global leadership, and societal responsiveness. Achieving these objectives requires a shift in the approach used to the design aeronautical systems, particularly concerning the integration of manufacturing and supply chain processes. The systems for system approach (S4S) aims to interconnect these systems from the conceptual design phase, enhancing integration and efficiency while mini-mizing costs and time losses. The objective of this thesis is to propose a methodology that leverages concepts derived from Model-Based Systems Engineering (MBSE) and Product Line Engineering (PLE) to generate all possible S4S architectures variants. As consequence all the possible combinations, the architectures, obtained by changing variables related to the aircraft design (e.g. number of components), manufacturing (e.g. materials) and supply chain are cre-ated. In details, the process starts from the identification of the stakeholders´needs, which are then translated into systems requirements. It continues with the development of a system archi-tecture baseline. Variability is then introduced into the model by modifying materials, pro-cesses, and enterprises, driving the generation of the 150% model. Multiple variants of the baseline architecture are then generated and compared in terms of aircraft, manufacturing and supply chain performance (e.g. mass, production time). The best architecture is finally identified, based on the production and design criteria, by leveraging the value model theory. The approach proposed in this thesis enables a value-driven trade-off analysis that considers the performance of the aircraft system and the manufacturing and supply chain systems simulta-neously, seeking the optimal solution for stakeholders and for the overall performance of the three systems. An aeronautical case study demonstrates the benefits of applying the proposed methodology.