Belgian shipping company EXMAR has agreed a deal to implement the vessel performance optimisation platform developed by maritime tech start-up Toqua across its fleet, with the aim of leveraging EXMAR’s existing repository of big data.
The deal follows an initial trial project with the system, which indicated that significant potential improvements could be generated through the deployment of the technology.
Toqua’s Physics-Informed Machine Learning platform aims to overcome the limitations of traditional performance analysis methods, such as comparisons against sea trial curves or analysis of noon reports, by utilising a wider scope of operational data from sensors and other sources to create models it calls Ship Kernels.
Toqua says that these Ship Kernels represent the best possible model that can be created from the combination of available data sources and are used to simulate all possible operating conditions for analysis. They can also be continuously updated to reflect the latest performance data from the vessel, improving accuracy in analysis and in the models themselves.
EXMAR will use these models and their corresponding speed-fuel numbers to drive improvements in areas such as hull performance monitoring, chartering decisions, sister vessel comparisons, engine monitoring, and voyage optimisation.
“At EXMAR we are investing in high-frequency data collection. Toqua helps us put the data to work to maximise the return on our data investment,” said Kristof Vercammen, Fleet Manager, EXMAR.
“By embedding Toqua’s Ship Kernels into our current voyage optimisation solution, we were able to increase fuel savings by up to 3%, helping us reduce total emissions even further.”
