Yara concludes AI testing for vessel optimisation

Yara concludes testing AI-based project to optimise vessel performance

Yara Marine Technologies has come together with partners to create a semi-autonomous voyage planning system based on artificial intelligence (AI).

The project was carried out in partnership with Molflow, Chalmers University of Technology, and social science experts from Halmstad University and Gothenburg University.

The Via Kaizen voyage planning system aims to investigate if AI and machine learning can enable more energy-efficient journey planning for ship operators.

The project, which was funded by the Swedish Transport Administration Trafikverket, used pre-existing instruments to enable a higher level of digitisation and automation in vessel operations.

These included Yara Marine’s FuelOpt propulsion optimisation system, Fleet Analytics performance management, and vessel data reporting tool, as well as Molflow’s Slipstream vessel modelling system.

According to Yara, the existing work practises and user demands were reviewed during the design phase to ensure the technology-assisted activities and decisions had the greatest impact on energy efficiency.

READ: Valenciaport employs AI to predict truck flow

The resulting system was trialled onboard two vessels, a Pure car, truck carrier (PCTC) operated by United European Car Carriers (UECC) and a Rederiet Stenersen product tanker.

The wide-ranging results presented successful energy efficiency optimisation based on estimated time of arrival, with one of the two trial vessels opting to continue using the system.

Mikael Laurin, Head of Vessel Optimisation at Yara Marine Technologies, said: “The Via Kaizen project speaks directly to where shipping is at the moment, where the intersections of digitalisation, decarbonisation and crewing determine our success in addressing climate change.

“The use of AI and machine learning to plan and predict energy-efficient voyages has significance for an industry looking to lower emissions while addressing rising fuel costs.

“As a result, the insights and information gained from the project carry broader significance for our industry’s future.”

READ: Yara Clean Ammonia, Cepsa supply clean hydrogen to Europe

The Via Kaizen project, according to Yara, demonstrated that adding machine-learning algorithms for enhanced predictive modelling of ship propulsion power may result in more accurate performance forecasts and optimisation.

Joakim Möller, CEO at Moflow, stated: “The Via Kaizen project afforded an invaluable opportunity to explore and advance industry understandings of the role big data, data handling and model development can play in supporting lower emission strategies and maximised fuel efficiencies.

As the maritime industry seeks to utilise good data to inform decision-making, AI and machine learning can play a key role in processing and simplifying available data for clear, actionable outcomes.”

Martin Viktorelius of Halmstad University explained: “Maritime’s ability to successfully decarbonise is dependent on its highly skilled workforce, and necessitates that we invest in creating seafarer support for digitalisation and decarbonisation.

“Clean technologies must prioritise intuitive, user-friendly interfaces and understand existing operations to maximise crew support and uptake of AI-powered solutions.”

In June of this year, chemical manufacturer, BASF, and Yara Clean Ammonia launched a joint study to develop and build a world-scale low-carbon blue ammonia production facility in the US Gulf Coast.

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