Yara Marine Technologies, artificial intelligence (AI) application developer Molflow, Chalmers University of Technology, Halmstad University and Gothenburg University have collaborated for over three years to develop an AI-based semi-autonomous voyage planning system. and tested.
Launched in August 2020, the Via Kaizen project explores how AI and machine learning can enable more energy-efficient voyage planning for ship operators. This project demonstrated that incorporating machine learning algorithms to improve predictive modeling of vessel propulsion enables more accurate performance prediction and optimization.
Funded by the Swedish Transport Authority Trafikverket, the project leverages existing tools to enable advanced digitization and automation of ship operations. These include Yara Marine’s propulsion optimization system FuelOpt, performance management and vessel data reporting tool Fleet Analytics, and Molflow’s vessel modeling system Slipstream.
The resulting system was tested on two vessels, a PCTC car carrier and a Rederiet Stenersen product tanker operated by UECC. Widespread results indicate successful energy efficiency optimization based on Estimated Time of Arrival (ETA), with one of her two test vessels choosing to continue using the system. bottom.
Mikael Rollin, Head of Vessel Optimization, Yara Marine Technologies, said: “The Via Kaizen project speaks directly to the current state of shipping: the intersection of digitization, decarbonization and crew will determine our success in addressing climate change.” AI and Machine Learning Using to plan and forecast energy efficient voyages is important for industries looking to reduce emissions while coping with rising fuel costs.
“Similarly, new technologies can streamline operations, but require collaboration and buy-in from all stakeholders, crew familiarization and training, proactive design, and new corporate strategies. The insights and information gained from will have broader significance for the future of our industry.”
Moflow CEO Joakim Möller said: “We can use recent advances in ship data tracking and analysis, weather information, and more to determine where we might be able to streamline our operations. As we seek to leverage, AI and machine learning can play a key role in processing and simplifying available data for clear and actionable results.”
Throughout the trials, the crew played a key role in determining the success of the energy efficient voyage. This demonstrates the need to give ship crews and management every opportunity to engage, understand and embrace the value of AI-powered vessel operational support technologies that support their daily operations on board and onshore.
Following the completion of this project, additional funding was secured from Swedish innovation agency Vinnova to further explore some of the findings.
