The digital revolution is affecting most industrial sectors, enabling the digital modelling of designs, manufacturing processes and operations. A wider and better development of Digital Twin (DT) models enables new functionalities for the design and operation of vessels to improve operational efficiency to be developed and validated with increased confidence without resorting to more costly physical testing. DT modelling can be founded and validated using sensor data, data mining and merging, big data, AI and self-learning to improve efficiency on all levels. Such developments increase owner confidence in the expected performance when procuring innovative green systems as well as providing operational feedback to the manufacturer which can be used to further improve energy efficiency. In this respect DT models are understood as wide-ranging tools with known application areas and those still to be explored.
The waterborne (transport) sector is characterised by very diverse requirements and market realities. Ships, their systems and related technical and commercial processes are already widely using digital technologies including virtual models but those are generally developed individually and with significant overlaps. Capital expenditure is often very high. The wider implementation and integration of digital technologies into more coherent Digital Twins on-board and onshore supporting user oriented decisions is still in its infancy. Whilst simulation environments are relatively mature maritime system tools, development to enable full exploitation of the potential functionalities is still lacking.
Project outputs and results are expected to contribute to all of the following expected outcomes:
Link with CMA Goals:
Goal II: A competitive, innovative and sustainable blue economy for the Black Sea
/ Priority 2: Promote transport and digital connectivity of the Black S