Computer vision

In the life cycle of high-value products or parts, defects arise and need to be repaired. Geometric complexity leads to costly and time-consuming manual operations. The aim is to automatise and optimise material deposition operations to improve efficiency and reduce costs.

DISCMAM aims to reduce military operational downtimes by utilizing metal AM technologies for on-site spare parts manufacturing. The project develops a secure digital thread for remote assistance, demonstrated through Powder Bed Fusion and Directed Energy Deposition Laser-based technologies. Benefits include eliminating the need for specialized on-site operators, reducing supply time and costs, minimizing non-usage time of critical assets, and optimizing on-site stocks in the EU defense sector.

WAVETAILOR intends to create a highly intelligent, flexible and reconfigurable laser-based additive manufacturing processes to overcome the current weaknesses in manufacturing geometrically complex multi-material components and assemblies by additive manufacturing. This will provide material savings, increase overall equipment efficiency and minimize defects.

The project aims to develop a swift, reliable human-oriented quality control solution for timely defect detection in composite processes. It determines in-situ corrective actions, striving for a zero-defect LRI manufacturing process, reducing polymer composites waste. Results will be tested and demonstrated in two industrial cases (yacht part and wing box).

NINFA drives research and development to efficiently and industrialise the aerospace sector in a cost-effective way while maintaining high quality standards. From design to post-processing, in collaboration with the supply chain. In addition, it seeks to apply developments in other sectors such as the medical-dental sector. Focusing on light alloys, cost-benefit analysis, industrialisation and process and material quality, NINFA covers the entire supply chain, including research into heat and surface treatments, process monitoring, mechanical characteristics, non-destructive methods, and distortion modelling for product design.

ROLIAC enables lightweight military-grade part design and manufacture, leveraging additive manufacturing (AM) for EU defense. Key benefits include robust supply chains, lightweight high-performance components, and use of novel materials. ROLIAC focuses on generative design, rapid production, and robust quality control, demonstrated in ground, air, and space applications

Project that develops and validates an ecosystem of new digital technologies for the main processes of national shipyards in order to achieve their technological leap towards digitalization according to Industry 4.0 guidelines, positioning the national sector as a technological benchmark in the international context.

The MADISON project, a continuation of CEFAM 2020-2022, aims to enhance participation in the additive manufacturing (AM) value chain. It addresses challenges in AM technologies applied to metals, promotes excellence in training, and attracts talent. It develops strategies for dynamization, transfer, and industrial protection to enhance results. Technically, it fabricates and simulates five materials (Ti64, Cu, Al, steels, and Ni alloys), improves AM technologies and material processability, designs non-destructive inspection methods, and analyzes the sustainability of the processes.

To implement an inspection system for thermocouples and magnetic groups in Orkli’s Gas Safety range, critical components that require rigorous quality control. Traditionally, this inspection was performed visually by operators, a labor-intensive process due to the small size of the parts and the high production volume.

Renault España lidera este innovador proyecto para la creación de un ecosistema industrial centrado en la fabricación de vehículos eléctricos y conectados aglutinando 31 iniciativas entorno a la descarbonización, la conectividad y la movilidad como servicio.