Owners of medium range (MR) product tankers can increase earnings by US$1000/day per ship by optimising vessel speed, according to Lean Marine chief executive Mikael Laurin.
He said owners can achieve around 20% reduction in fuel consumption by optimising propulsion, during his presentation at Riviera Maritime Media’s Tanker Shipping & Trade Conference in London on 27 November.
But, to achieve these reductions, owners need to monitor and analyse tanker performance more frequently than using a daily report.
“If you want to learn something more you need to be able to measure it,” said Mr Laurin.
This means owners need to invest in onboard sensors, data transmission and analytics to understand how effectively they are reducing operating costs and emissions.
“If you can measure it, you can manage it,” said Mr Laurin. “You need the right tools on board and to educate people on how to use the technology.”
He thinks big data analytics should also include artificial intelligence and machine learning to identify more performance information to reduce operating costs.
“We can learn more and can compare performance against other ships, fleets and owners,” he said.
Also at the conference, Greensteam head of performance management Jonas Frederiksen said machine learning can enable shipping companies to identify areas to reduce greenhouse gas (GHG) emissions.
“Machine learning is a viable strategy for vessel optimisation,” he said. Owners can use machine learning to identify how to optimise trim, reduce speeds and manage hull fouling, for example.
“It is very important to get a clear view of where to target GHG reductions,” said Mr Frederiksen. “Machine learning gives owners clarity on GHG reduction and getting higher fuel savings.”
He said machine learning is a “zero-capex and zero off-hire investment” for owners to target 5% GHG emission reductions.
“Machine learning and vessel optimisation plays a vital role in reaching GHG reduction goals,” said Mr Frederiksen.
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