Yara Marine Technologies conducts semi-autonomous voyage planning trial

Yara Marine Technologies, working with Artificial Intelligence (AI) application developer Molflow, Chalmers University of Technology, Halmstad University and Gothenburg University, has conducted trials of a new AI-based semi-autonomous voyage planning system developed as part of a three-year research project.

Initiated in August 2020, the Via Kaizen project aimed to explore how AI and machine learning can enable more energy-efficient voyage planning for ship operators. Funded by the Swedish Transport Administration Trafikverket, the project utilised tools including Yara Marine’s propulsion optimisation system FuelOpt and performance management and vessel data reporting tool Fleet Analytics, as well as Molflow’s vessel modelling system Slipstream, to find ways of increasing optimising ship operations.

Existing work practices onboard were analysed during the design process to create a new system, which was then trialled on board two vessels, a PCTC car carrier operated by UECC and a Rederiet Stenersen product tanker.

The results indicated successful energy efficiency optimisation based on estimated time of arrival (ETA), Yara notes, with one of the two trial vessels opting to continue using the system following the conclusion of the tests.

“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,” said Mikael Laurin, Head of Vessel Optimisation at Yara Marine Technologies.

“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. Similarly, new technologies can streamline operations but require collaboration and buy-in from stakeholders across the board, necessitating crew familiarisation and training, proactive design, and new corporate strategies.”

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

The Via Kaizen project demonstrated that incorporating machine-learning algorithms for improved predictive modelling of ship propulsion power can result in more accurate performance forecasting and optimisation.

“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,” said Joakim Möller, CEO at Moflow.

“Recent advances in vessel data tracking and analysis, weather information, and more can be used to gauge where operations have the potential to be streamlined. 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.”

Following the conclusion of this project, additional funding has been secured from the Swedish innovation agency Vinnova to further explore a selection of its findings.

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Rob O'Dwyer

Rob is Chief Network Officer and one of the founders of Smart Maritime Network. He also serves as Chairman of the Smart Maritime Council. Rob has worked in the maritime technology sector since 2005, managing editorial for a range of leading publications in the transport and logistics sector. Get in touch by email by clicking here, or on LinkedIn by clicking here.

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