Integrating Data-Driven and Model-Based Systems Engineering for End-to-End Small-Satellite Design

The aerospace industry is currently experiencing a significant transition towards the digitalisation of spacecraft development processes. This shift presents several challenges, including technical limitations in data exchange systems and the increasing complexity of space systems. Over the years, a variety of System Engineering (SE) approaches have been adopted with the objective of managing information as it passes between engineering teams, ensuring consistent design data across different projects and activities, and reducing mission costs and development times. The most relevant of these approaches are Data-Driven Systems Engineering (DDSE) and Model-Based Systems Engineering (MBSE). The DDSE centralises and integrates all space mission engineering data, creating a single source of truth for rapid and collaborative decision-making and enabling faster automation and iteration. The MBSE employs a model-centric approach to the design of complex space systems, promoting a coherent understanding and early validation of mission architectures. To address the challenges currently being experienced in the aerospace industry, the design of small satellites requires a methodology that is more agile than traditional approaches. Moreover, a single modelling tool is often inadequate. This thesis proposes an integration of the Data-Driven System Engineering (DDSE) and Model-Based System Engineering (MBSE) methodologies with the aim of enhancing and facilitating the preliminary small satellite design development. To achieve this objective, two complementary tools have been selected: Valispace, a DDSE tool that provides a user-friendly digital environment for engineering data, ensuring the integrity of data while encouraging real-time collaboration; Capella, an MBSE tool that implements the ARCADIA method to create, visualize and simulate the models of the systems, improving the comprehension of the project even at an early stage. The integrated approach is based on the combination of these two methodologies, thereby ensuring a more comprehensive and clear understanding of the space system being modelled, and achieving a more efficient and dynamic management of all data. This, in turn, allows for the maintenance of a single source of truth, guaranteeing the continuity of information between the two tools and fostering the collaboration between engineering teams and stakeholders. The present thesis illustrates the methodology, the integration of the tools and the results from a small-satellite case study. It demonstrates how the combination of DDSE and MBSE has optimised the design development process, thereby ensuring a more agile solution that mitigates risks and improves decision-making processes.