Shipowners and operators relying on sub-optimal hull cleaning strategies could face additional fuel costs of up to 20% when vessels resume operation
Tankers being used as storage that have been idle for some time face an additional operational challenge in the form of accelerated hull fouling according to GreenSteam, developers of machine learning-based vessel performance optimisation software.
The effects of vessel lay-ups vary across the industry. As it stands, some sectors have between 15-100% of vessels lying at anchor.
As a result of the most recent oil price crash, demand for floating oil storage rocketed from 75M bbls in February to 160M bbls in April 2020. This is higher than after the 2009 financial crash, which saw 100M bbls in floating storage. Analysts predict between 100-200 of the world fleet of 770 VLCC may satisfy the demand for floating storage as soft demand combines with crude oil producing states’ refusal to make meaningful production cuts.
The growth of organisms on a vessel hull increases its resistance to motion and if left unchecked, can increase fuel costs by over 20%. Runaway hull fouling also shortens coating life and can necessitate early docking. Vessels lying at anchor are subject to accelerated hull fouling. The first stage sees the attachment of biofilm or slime; this happens faster if a vessel is idle. The temperature of the sea surface speeds up hull fouling and so anchored vessels in warmer climates are at more severe risk.
This means that, once the shipping industry has successfully navigated the effects of Covid-19 and looks to return to business as usual, many owners, operators and charterers may be subject to increased fuel bills as a result of this excess hull fouling. All this is at a time when many will be looking to recuperate costs and rebuild after difficult months under the Covid-19 lockdown.
GreenSteam chief operating officer Simon Whitford said “Fouling follows an S-shaped growth curve. After the rate of fouling starts to accelerate it can soon pass a point of no return for inwater cleaning as the hull surface gets saturated by plant, then animal organisms. Cleaning before this point is usually reversible – we can turn back the clock on hull fouling. After this point it becomes increasingly difficult to clean without damaging the coating. Damaged coatings lead us to a future of expensive and ever worsening performance until the next drydock and recoating.”
Despite this S-shaped growth curve, a recent survey during a GreenSteam webinar found 78% of attendees with hull cleaning responsibilities did not use a monitored condition-based strategy, preferring to clean the hull at fixed ’rule of thumb’ or ’based on experience’, or reactively after a manual inspection or when fuel consumption spikes.
Alternatively, some owners and operators have used legacy non-machine learning methods which rely on a 2016 ISO 19030 standard for hull fouling measurement. ISO 19030 standardises what data can be used to compare two periods, with filters on wind speed, depth and time between hull/propeller cleanings. This is in contrast to GreenSteam’s machine learning software which uses all the ship’s valid data to build a very accurate picture of fouling, making it ideally placed to establish an optimal cleaning schedule.
GreenSteam head of performance management Jonas S Frederiksen said, “it is now possible for the industry to get ahead of the curve and move to a monitored condition-based strategy, which protects expensive coatings while reducing emissions. GreenSteam’s machine learning software uses both historical and live data to create a vessel performance model and applies this in conjunction with real-time and historical metocean data to build a complete picture of hull fouling. This allows a monitored, condition-based predictive strategy lowering both fuel and maintenance costs.”
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