Fincantieri’s IPCEI-CIS portfolio is building the digital backbone for the smart shipyard and autonomous ship of the future. By orchestrating data across IoT, edge and cloud environments, the initiative tackles integration, automation and cybersecurity challenges, enabling Industry 4.0 capabilities, lifecycle optimisation and more intelligent maritime operations.

As maritime systems grow more complex through automation, alternative fuels and advanced mission requirements, understanding vessel-wide impacts of failures becomes increasingly challenging. This research introduces an AI-enabled decision support system that leverages functional architectures to assess mission feasibility, guide recovery actions and enhance situational awareness, offering a powerful tool for safer, more resilient naval operations.

Digital twins are transforming maritime engineering by connecting virtual ship models with real-world operational data. Drawing on advances in simulation, IoT, AI and cloud technologies, this research traces the evolution from virtual prototyping to lifecycle-wide digital twins, revealing new opportunities to enhance design, training, maintenance, operational performance and long-term asset management.

Predictive motion analysis is advancing the safe deployment of crewed and uncrewed air and sea vehicles at sea. By combining real-time ship motion forecasting, deck-condition sensing and integrated simulation, new approaches improve launch and recovery operations, support autonomous systems, and enable predictive maintenance, enhancing safety, reliability and operational effectiveness.

Predictive motion analysis is advancing the safe deployment of crewed and uncrewed air and sea vehicles at sea. By combining real-time ship motion forecasting, deck-condition sensing and integrated simulation, new approaches improve launch and recovery operations, support autonomous systems, and enable predictive maintenance, enhancing safety, reliability and operational effectiveness.

Digital collaboration is becoming essential to the future of European shipbuilding. As specialist shipyards increasingly rely on partnerships and subcontracting, interoperable digital twins and shipbuilding-specific lifecycle management technologies are enabling secure information sharing, reducing collaboration risks and strengthening competitiveness in the delivery of complex, innovation-driven maritime programmes.

Advanced defect detection techniques are enhancing maritime reliability by transforming operational time-series data into machine-learning-ready visual representations. Combining Gramian Angular Fields, Recurrence Plots and Markov Transition Fields with convolutional neural networks, the approach improves fault classification accuracy, demonstrating how AI-driven analytics can strengthen quality assurance, maintenance strategies and operational safety.

Shipbuilding organisations are increasingly turning to Product Lifecycle Management to manage growing design complexity, traceability requirements and supplier networks. Drawing on implementation experience, this perspective outlines practical foundations for shipbuilding-specific PLM adoption, highlighting how integrated digital processes can improve collaboration, visibility and lifecycle control while reducing reliance on fragmented tools and expertise.

AI is strengthening corrosion prevention by transforming ICCP system monitoring from reactive maintenance to predictive lifecycle management. Using LSTM-based deep learning to analyse current and voltage time-series data, the solution identifies system health trends, forecasts degradation and automates reporting, helping operators improve reliability, optimise maintenance schedules and reduce lifecycle risk.

Discrete Event Simulation is evolving beyond traditional shipyard planning to support lifecycle-wide decision-making. New simulation libraries and digital workflows are enabling more effective modelling of material flows, sustainability and circular economy processes. Emerging capabilities for recycling analysis, ecological footprint assessment and data management promise smarter, more resilient maritime operations ahead.

Explainable AI is bringing greater transparency to maritime optimisation, helping organisations understand how advanced algorithms reach decisions. By revealing the reasoning behind evolutionary and other black-box techniques, emerging approaches can strengthen trust, improve solution quality and enable more effective optimisation of complex operational and engineering challenges at sea today onward.

Model-Based Systems Engineering is transforming naval operational analysis by connecting SysML-based system models with Monte Carlo simulation to evaluate complex mission scenarios. Demonstrated through a submarine case study, the approach enables exploration of design trade-offs, optimisation of operational effectiveness, and more informed decision-making while highlighting the value of interoperable digital engineering tools.