AI-enhanced energy efficiency measures for optimal ship operations to reduce GHG emissions

Important results from the project

The project demonstrated great potential for fuel savings with machine learning-based modeling and simulation of ship voyages. För Manta Marine laid the foundation for investments in data-driven tools to improve the company´s products in the area of fuel savings and emission reduction in shipping. För Molflow enabled the evaluation of data technologies, which broadened opportunities in other industries and increased revenue potential.

Expected long term effects

The result of the project has laid a foundation for technical solutions that contribute to fuel savings and reduced greenhouse gas emissions in shipping. The project has been given the opportunity to get direct connection from users of the system, which remains to create a greater understanding of customer requirements, the customers´ various internal processes and thus great improvement potential to meet customers´ future requirements with improved existing systems and new products.

Approach and implementation

The project was based on bi-weekly meetings to discuss progress and solve problems. When necessary, workshops were held for specific areas, which accelerated knowledge dissemination and problem solving. At Chalmers divided the project into phases: The planning phase had weekly meetings for ideas and preliminary results, the implementation phase had bi-weekly meetings for status and progress, and ended with a publication phase where the results were presented scientifically.