- Revolutionising Vessel Analysis with Toqua’s Ship Kernels.
- EXMAR Implements Machine Learning for Voyage Optimisation.
- Achieving Fuel Efficiency: EXMAR Integrates Toqua Technology.
EXMAR, a Belgium-based shipping company, has announced an exclusive partnership with maritime tech start-up Toqua to deploy the company’s vessel performance optimisation platform across its fleet. This collaboration comes after the success of a trial period, which revealed significant potential for improvement in using the software developed by Toqua, reports Smart Maritime Network.
New Technology: Toqua’s Ship Kernels
Toqua’s platform uses a Physics-Informed Machine Learning approach to bypass the limitations of traditional performance analysis methods, such as reliance on sea trial curves or noon reports. The platform uses diverse operational data from sensors and other sources to create advanced Ship Kernels models.
Ship Kernels simulate all the possible operating conditions for a given ship to provide of how things function and, therefore, an extensive produce of information from vessel data that improves accuracy over analysis time.
Optimising Fleet Performance
By adopting Toqua’s models and corresponding speed-fuel numbers, EXMAR aims to enhance performance across several critical areas, including:
- Hull performance monitoring
- Chartering decisions
- Sister vessel comparisons
- Engine monitoring
- Voyage optimisation
Driving Sustainability and Efficiency
EXMAR is integrating Toqua’s Ship Kernels into its existing voyage optimisation solutions to maximise fuel efficiency and reduce emissions. Fleet Manager Kristof Vercammen highlighted the benefits: “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.”
The implementation has already demonstrated success, achieving up to a 3% increase in fuel savings during the trial phase. This contributes directly to EXMAR’s sustainability goals by further reducing total emissions.
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Source: Smart Maritime Network
