Implementation and Validation of a Corporate Concurrent Engineering Framework through a Solar Sail-Propelled CubeSat for a NEA Survey Mission

Space mission design represents a complex challenge due to the vast and highly non-linear trade spaces, the complex and interconnected analyses required, and the need to address every mission phase, from procurement to end-of-life, while considering both technical and programmatic considerations. This thesis work was carried out within the Research & Development Unit of the Italian company Argotec and aims at implementing a Concurrent Engineering (CE) framework in a corporate environment to enhance the efficiency and effectiveness of mission formulation and design, which is referred to as the Advanced Concepts Laboratory (ACLab ). Unlike traditional sequential approaches, which can lead to late-stage redesigns, missed opportunities, or suboptimal designs, CE promotes teamwork and real-time design sessions, enabling simultaneous progress across all aspects of a space mission. CE enhances trade space exploration, decision-making, and the concurrent evaluation of all relevant factors, resulting in valuable, feasible, and consistent designs while reducing the overall effort required. This work addresses the challenges of implementing CE in a corporate context, which include managing relationships with clients and potential external partners, dealing with limited resource availability due to staff being frequently engaged in other flight projects, staff training, and integrating technical aspects with programmatic ones. The work initially focused on implementing tools to support mission design and integrating the COMET tool within the framework to support data and study management. Additionally, a methodology was developed to encompass multiple aspects, from client relations and session planning to trade space exploration and point design. The implemented CE framework also introduces innovative elements, including the adoption of a SCRUM-based approach to prioritize tasks, improve session planning, and identify critical areas requiring more time and resources, as well as the integration of a RAG (Retrieval-Augmented Generation) pipeline, a tool from the field of Natural Language Processing (NLP), to optimize the systems engineering process, particularly for information retrieval. The methodology and tools were tested through a Phase 0 study of a solar sail-propelled CubeSat mission for near-Earth asteroid survey and were refined based on the feedback gathered. The results of the case study demonstrate the benefits of designing a mission through this new approach while also analyzing the challenges encountered, tracing their causes and proposing possible solutions.