(An improved integrated modeling approach from ship design to scarping for complex vessel SoS.)

Rationale: To deliver an integrated digital solution that boosts the sustainability and efficiency of ship operations across their lifecycle.

Expected Outcome:  Fully integrated system of systems (SoS) DT models for 4 Pilot vessels, merging design-phase simulations and operational data with advanced analytics across the vessel lifecycle. 

(An open source data ‘rich’ handling platform that hosts the DT-enabled DSS with required security and privacy levels.)

Rationale: Promote widespread adoption and industry-led advancement of DT in shipping through a scalable, open-source digital platform, ensuring innovation, interoperability, and collaboration with essential data security and safety measures.

Expected Outcomes: Adaptation of existing ‘VesselAI digital platform’, featuring established data standards, linking Pilot vessels and a port for live data exchange, designed to facilitate green vessel DT/DSS integration and operation with bespoke data security tailored for maritime needs.

(A structured database of existing & future vessel technologies, including green fuels for DT development.)

Rationale: To ensure interoperability and secure data exchange, it's essential to set up open standards and develop a centralized Vessel Data Cloud Space (VDCS) in VesselAI, leveraging Knowledge Graphs/Ontology for efficient data management.

Expected Outcomes: Implement open standards in the DT/DSS framework through a VDCS for secure, streamlined data exchange and storage, facilitating global data integration & organization to seamlessly incorporate ship design simulation and operational data supported by current and emerging green fuel and technology information.

(A tool for evaluating DT model performance that supports the DT standards development.)

Rationale: Creating a comprehensive evaluation methodology and standards for DT models is essential to ensure their effectiveness and reliability in maritime operations.

Expected Outcomes: Developing a detailed model evaluation methodology (MEM) with industry-standard criteria for assessing DT models' performance and accuracy, including hardware-in-the-loop (HIL) experiments and both internal & external model evaluations. This ensures DT models are consistently validated, refined, and practically applicable.

(For detecting, identifying, isolating, and recovering (possible) anomalies captured from extreme data.)

Rationale: Data quality improvement is imperative for ensuring the integrity, accuracy, and reliability of extreme data used for the DT models.

Expected Outcomes: Establishing a Data Quality Governance Strategy (DQGS) to set clear guidelines for data quality assessment, enhancement, and upkeep, ensuring DTs utilize high-quality, relevant, and secure data for more reliable model outputs

( Trailed in 3 real-world vessels & one futuristic conceptual vessel by end-user and via series of user-testing workshops.)

Rationale: Real-world validation is essential to prove the effectiveness and reliability of the DT/DSS framework in practical maritime operations.

Expected Outcomes: Successful deployment and operational enhancement of DT/DSS in 3 diverse Pilot vessels—RoRo, RoPax, and chemical tanker—over 6 months, plus a simulated unmanned, net zero-emission RoRo vessel powered by green & renewable energy as the TwinShip futuristic vessel.

(A tool that turns DT model insights into actionable strategies for ship designers, owners, and operators for short to long-term ship lifecycle decisions, including AI-driven voyage optimization, environmental impact assessment (EIA), and life cycle cost analysis  (LCCA) within a simulated environment.)

Rationale: Enhancing operational efficiency and minimizing environmental footprint are crucial for complying with IMO regulations and attaining sustainability objectives in the maritime sector, both currently and in foreseeable future scenarios.

Expected Outcomes: Significant reductions in design and operational costs, fuel usage, and GHG emissions achieved through the onboard and onshore modules of the DT-enabled DSS framework, towards zero emission vessels.

(Extrapolate the innovation impact of the project contribution to shipping sector priorities through dissemination, exploitation and communication (DE&C) activities through the industrial partners, and benchmark against performances recorded in current state-of-art to foster industry-wide adaptation, on existing and new build vessels.)

Rationale: For the DT/DSS framework to have a significant impact on the maritime industry, it must be adopted widely by ship designers, builders, owners, and operators through DE&C activities.

Expected Outcomes: Increased market penetration and adoption of the DT/DSS framework across different segments of the maritime industry, specifically by Wartsila, Grimaldi, Stena, & ABS, who are leading the DE&C activities.