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.

Autonomous and self-sailing vessels depend on accurate, real-time situational awareness to operate safely and effectively. This paper explores Fincantieri NexTech’s integrated awareness platform, highlighting the challenges of sensor fusion, data management and human supervision. The solution combines diverse environmental data into a unified interface, supporting informed decision-making, enhanced safety and future vessel autonomy.

Integrating cryogenic fuel tanks safely is becoming critical as maritime decarbonisation accelerates. Using advanced CFD, conjugate heat transfer modelling and thermal-structural analysis, this research tackles low-temperature effects, condensation risks and material selection challenges for liquefied natural gas and hydrogen systems, supporting compliant, reliable integration of next-generation alternative fuel technologies

Game engine technology is emerging as a powerful enabler of digital ship design, offering immersive visualisation, interactive simulation and broad device support at relatively low cost. This research explores integrating game engines with engineering and business data systems, revealing both significant opportunities and critical challenges in managing dynamic shipbuilding information and workflows.

Digital innovation is helping shipyards optimise one of their most complex operational challenges. By combining discrete event simulation, automated planning and 3D visualisation, a new methodology reduces quay movements, improves outfitting efficiency and enables faster decisions. The approach offers a powerful foundation for smarter, more productive shipyard operations worldwide today

Automating ship piping design remains a major engineering challenge due to complex routing constraints, support requirements and regulatory demands. This research introduces a practical path-planning system that automatically generates compliant pipe layouts using predefined support-aware routing points, improving design efficiency, reducing manual effort and enabling more effective optimisation within increasingly complex shipbuilding projects.

Probabilistic damage stability assessment is increasing the complexity of ship safety verification, particularly for vessels with irregular compartment layouts. This research introduces an automated scenario-generation algorithm that maps complex compartment relationships and flooding pathways, enabling more accurate risk analysis, reducing modelling errors and improving compliance with modern damage stability requirements.

Designing electric river ferries demands balancing battery capacity, hull efficiency and route-specific constraints. This integrated methodology combines Python-based automation with advanced naval architecture and simulation tools to optimise vessel design, accelerate trade-off analysis and reduce development time, enabling cost-effective, energy-efficient ferry solutions tailored to challenging inland operating environments.

Natural language processing is transforming how maritime professionals access complex regulatory requirements. By converting classification rules into searchable semantic datasets and applying AI-powered similarity matching, this approach delivers more relevant results than traditional keyword searches, reducing compliance effort, improving efficiency and helping organisations navigate increasingly complex regulatory environments

Predictive maintenance is becoming essential as ship systems grow more complex and maintenance demands increase. By combining vessel monitoring data, artificial intelligence and physics-based modelling, this approach detects hull and propeller degradation in real time, enabling proactive maintenance planning, reducing operational burden and improving fleet efficiency, availability and long-term performance.

Digital twins are evolving beyond real-time vessel monitoring into powerful enablers of maritime AI development. By embedding operational ship data within realistic environmental simulations, organisations can generate large-scale training datasets, test scenarios and support predictive maintenance. This approach offers a cost-effective pathway to smarter, more capable autonomous systems while reducing reliance on expensive sea trials.

Artificial intelligence is poised to transform every stage of a ship’s lifecycle, from concept design and construction to operations, maintenance and disposal. This perspective explores practical applications, ethical considerations and engineering challenges, highlighting how human-AI collaboration, explainability and responsible governance can unlock innovation while managing risk effectively at scale responsibly