VO X 2023

Offentlig prosjektsammendrag

Every Vessel sailing the seas today is largely custom built and without “standard off the shelf models” much like we have in the car industry or wind turbine industry it’s very difficult to apply one size fits all optimisations across a whole fleet of vessels as each vessel probably reacts very differently in different conditions. When trying to optimise various aspects of how a vessel performs in water normally the first step is to collect a lot of historical data (which takes time) and then create a digital representation of how that vessel performs in different load and weather conditions. This is an expensive and time consuming process that is hard to scale across a whole fleet of vessels. Navidium is working towards a new Fleet Learning approach which allows vessels to learn from each other and cluster some of the common aspects found between all of the vessels so they can learn about their commonalities and how that affects the vessel in water. With this approach it means building vessel models is fully automated and doesn’t require the up front collection of historical data thus allowing you to easily scale the solutions to your whole fleet.