GENEX project aims at developing a novel end-to-end digital twin-driven framework based on enhanced computational models, which embed the interdisciplinary knowledge of the aircraft components and the manufacturing/repairing processes, to support the optimized manufacturing of composites parts, enable the continuous operation of aircraft and improve the composites repairing processes for ensuring aircraft´s safety and airworthiness. First, an  Automated Tape Laying (ATL) process coupled with THz-based in-process monitoring together with hybrid-twin simulation methods will be developed for eco-efficient and advance manufacturing of innovative reprocessable-repairable-recyclable (3R)-resin-and state-of-the-art thermoplastic composites. Second, innovative data- and physics-based machine learning algorithms for damage detection and location combined with advanced High-Performance Computing (HPC)-based multi-physics and artificial intelligent-powered digital twin tools for fatigue life prediction, will be implemented to transform information from optimized onboard piezoresistive sensors data networks interfaced with a low-power wireless communication platform to health and usage assessment and prognosis. Third, augmented reality tools together with novel laser-assisted methods for surface cleaning and monitoring, smart monitoring, and in-situ tailored heating of composite repair blankets will be further developed to provide additional assistance in manual scarf repair operations, increasing the reliability of the repair process, while supporting the modification and virtual certification of MRO practices. Thus, a novel digital twin-driven framework will be implemented into a common IIoT platform to integrate the developed models and data acquired, providing bidirectional dataflow, and enabling the implementation of a holistic and comprehensive data management methodology ensuring to create, capture, share, and reuse knowledge along the entire aircraft lifecycle.