USING AI TO LOWER CO2 EMISSIONS

Vooban identified three key processes that could be optimized to help CSL achieve its goals: improving the accuracy of ships’ estimated arrival time, reducing the amount of fuel used, and lowering CO2 emissions.

Since we implemented the AI model, vessel ETA can now be calculated with high accuracy, increasing its reliability by 30%. We have also created a second model that predicts fuel consumption with 96% accuracy. Additionally, the AI can plan the right time to carry out defouling maintenance on ships, as the build-up algae on the hull can affect up to 10% of a vessel's speed.

By accurately calculating these parameters, we can simulate the efficiency generated by the vessel. By managing speed and optimizing routes, we can reduce fuel usage and, therefore, GHG emissions. The nearly exact prediction of ETA enables us to optimize the time spent on operations and allow a more efficient planning of activities.

In the next year, this AI project should enable CSL’s Canadian fleet to significantly reduce its CO2 emissions and decrease average fuel consumption.

By accurately estimating ETA, the company's overall efficiency is increased. Indeed, when operations like crew changeover planning, navigation synchronization with dock and lock availability and material delivery coordination are optimized, the overall activities become more efficient and fluid. These changes enable CSL to further strengthen its supply chain reliability and cost management, allowing it to deliver maritime ingenuity worldwide!