The Project

The project provides a next-generation solution for total ship operational optimization based on DT technology capable of automated adaptation according to ship/vessel types and operational profiles, to incentivize investments towards full decarbonization. This will utilize the DT4GS (Green Shipping) Dataspace as part of the Open DT4GS infrastructure for robust data collection, transmission, analysis, simulation and optimization to enable operational and energy efficiency improvements for decarbonization and emissions reduction. Furthermore, it will support condition-based ship surveys and operations which are remote and more automated. Our planned use of fog/edge computing technology will provide latency and security benefits and added levels of intelligence, orchestration and autonomy in ships. More specifically, advancements, largely building on assets available through the project’s partners include:

(1) DT auto-adapting capabilities for ship/vessel class and associated vessel operational profiles;

(2) robotic data acquisition with 3D reconstruction;

(3) a novel automated and distributed Trust and Identity Management Framework enforcing the NIS directive, GDPR and Cybersecurity acts;

(4) automated and instrumented analysis-ready ship data generated by events or dynamically at query time;

(5) development of DT blueprints for ship operational performance optimization and creation of quantum analogues for AI/ML and optimization models, targeting increased accuracy, standardization, and reusability;

(6) intelligent monitoring and control connectors (IMCCs);

(7) the DT4GS (Green Shipping) Dataspace wirh innovation across data value, interoperability, trust and governance and new IMCCs particularly to support automated configuration of DT Edge components in ships using quantum models;

(8) control points business logic for automated configuration and updating of ship models;

(9) integration of advanced 5G capabilities.

DT4GS delivers a Virtual Testbed and Decision Support System, embedding a zero-emission shipping methodology, and built on top of the DT4GS Dataspace to enable different stakeholder communities to iteratively search through alternative technologies and compose optimized designs helping realize the 2030 55% CO2e reduction and longer term zero emission shipping. This is achieved through the:
(1) Establishment of a Decarbonization Knowledge Hub linked to knowledge networks for key features of the ship, energy and ICT domains. Collection, aggregation, processing, dissemination and exploitation of existing knowledge supported by roadmaps for addressing existing gaps in knowledge and technology;
(2) Provision of a taxonomy of green shipping technologies and a robust assessment/benchmarking method taking into account the quality, reliability and timeliness of the evidence that supports the decision-making process;
(3) Data-driven Green Ship 2050 reference models per ship type, by employing blueprints for specific ship/vessel types, taking into account size and other parameters, exploiting synergies between emerging ship and energy innovations, and new production methods;
(4) A zero emissions shipping Virtual Testbed for the sector which will enable:
(i) Shipping companies to explore the impact of alternative decarbonization options, (ii) Equipment manufacturers to upload models of their equipment to test performance under alternative configurations; (iii) Policy Makers to continuously analyze the state of the art, assess policies for zero-emission shipping. (5) Modeling digital transformation procedures and organizational processes (including governance and security s) to support adoption of DTs;

The reluctance of the shipping sector to embrace digitalisation in general, is also reflected into a conservative posture towards the adoption of DTs. Lack of hard evidence on DT value, combined with data sharing mistrust, are important issues that remain unaddressed. DT4GS addresses this head-on, by establishing a SC-centred innovation ecosystem, for the co-creation, collective experimentation and evaluation of innovative ideas, scenarios, concepts and related technological artifacts in real life use cases. Such user driven DTs operational in 4 ships by month 16 will enable the consortium to build a strong DT4GS Cluster and will give DANAOS, and SEASTEMA powerful value propositions as market leaders in shipping digitalization.

An important challenge with regard to designing effective DTs lies not only in meeting shipping’s goals, but also in achieving a more holistic perspective, which incorporates the evolution of critical adjacent areas. This link between shipping, green energy production, storage, and distribution technologies, compatible with real-world operations, green mobility technologies, and environmental and social considerations, is currently missing. DT4GS goes beyond the state-of-the-art by combining models from the shipping and transport domain with models from green fuels and green energy production, distribution, and optimization. This ensures both the achievement of synergies and also the parallel evolution of DTs in line with developments in the shipping and energy domains and future integrated autonomous mobility systems.

DT implementations so far have been focused on distinct areas such as machinery, hull, energy or port call optimisation. This has significant shortcomings, spanning from the business level (i.e. inability to capture the added value and efficiencies that integrated DTs can bring), down to the implementation level (i.e. data fragmentation and interoperability barriers). DT4GS goes beyond the state of the art, by integrating all these functionalities and linking to specific implementation horizons (see Figure 1–6) to guide adopters in their usage and achieve a strong impact on the collective capability of the waterborne industry to harmonize efforts and increase synergies between DT applications in shipyards, equipment manufacturers, class societies, ports, and policy makers.