Implementation of Innovative Strategies in Shipbuilding Production: The Experience of SHIPLEARNING on Friction Stir Welding and Reverse Engineering

Abstract

The shipbuilding industry is experiencing significant progress through the introduction of advanced technologies and sustainable methodologies. The SHIPLEARNING project, developed in a collaboration between the NAVTEC Technological District, the Tringali Shipyard and the Department of Engineering of the University of Messina, represents a strategic initiative aimed at improving the technological competitiveness of the maitime sector. Taking advantage of reverse engineering and advanced manufacturing techniques, the project addresses two key objectives: the acceleration of design and repair cycles by integrating 3D scanning technologies that accurately capture the geometric and structural data of complex components, facilitating efficient workflows for both novel designs and maintenance tasks; and the implementation of friction stir welding processes, which offer a superior, cost-effective and environmentally sustainable alternative to conventional welding methods, especially for applications involving dissimilar materials such as steel and aluminium. Pilot tests conducted within the Tringali Shipyard’s state-of-the-art facilities ensures that these innovations are validated under real-life conditions, with scalability and knowledge dissemination facilitated across the shipbuilding community. The results of SHIPLEARNING are expected to significantly improve productivity, efficiency and environmental sustainability in the shipping industry, while contributing to its global competitiveness. This research was funded by NextGenerationEU, National Recovery and Resilience Plan, Mission 4, Component 2, Investment 1.5, on the research program of “iNEST – Interconnected Nord-Est Innovation Ecosystem” Innovation Ecosystem Consortium, Spoke 5 “Smart and Sustainable Environments (Manufactuing, Working, Living)”, as part of the project “Shipbuilding innovation through introduction of 3D scanning and machine learning assisted FSW processes – SHIPLEARNING”.