GreenSteam Warns of COVID-19 Hull Cleaning Bill Shock
Copenhagen – Vessel owners, operators and charterers reacting to a sharp reduction in demand due to COVID-19 are soon to face an additional operational challenge in the form of accelerated hull fouling as more and more vessels lie idle at anchor or provide floating storage for petroleum products. This is 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. Of these sectors, bulkers were the first to be hit as raw material cargoes to China softened and the economy contracted earlier this year.
With their customers affected by faltering demand, empty supply chains and falling requirements, container ships have been forced to cancel routes or slow-steam leading to around 14% of global TEU capacity lying idle.
As a result of the most recent oil price crash, demand for floating oil storage rocketed from 75 million barrels in February to 160 million in April. This is higher than after the 2009 financial crash, which saw 100 million barrels 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 Oil states’ refusal to make meaningful production cuts.
However, it is cruise ships that are suffering the most. Worldwide, almost every cruise ship is at anchor with many lying in US waters susceptible to the approaching hurricane season.
While the situation changes frequently as movement restrictions are curtailed at different rates across the globe, we are now starting to understand and quantify the knock-on impact of so many stationary vessels when it comes to hull fouling.
The growth of organisms on a vessel hull increases its resistance to motion and if left un-checked, 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 owner, 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 re-build after difficult months under Covid-19 lockdown.
Simon Whitford, COO, GreenSteam 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 in-water 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 dry dock and re-coating,
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” periods, 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’s 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 whilst 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.”
Last year, the shipping industry was debating the environmental benefits of slow-steaming as more than 100 companies called upon the International Maritime Organisation (IMO) in April 2019 to mandate speed reductions in order to reduce emissions.
A year later, in the grip of the Covid-19 emergency, the global shipping industry reduces speed to ease the burden on customers’ fragile supply chains, provides floating storage to hold excessive oil stocks and mothballs excess capacity across the world.
However, once the challenges for shipping associated with the pandemic are slowly overcome, climate change will return firmly onto agendas, putting pressure on the shipping industry once more to reduce its carbon emissions. GreenSteam’s monitored, condition-based predictive hull cleaning strategy will safeguard hull coatings during lockdown and allow owners, operators and charterers to plan a low-emission mobilisation as the crisis lifts.
Simon continues, “higher fuel costs are the last thing many in the industry need right now, especially those working with vessels hit the hardest such as bulkers and cruise ships. We advise all owners, operators and charterers to get in touch so we can support them to proactively manage the effects of hull fouling and reduce their fuel costs and GHG emissions.”
The products and services herein described in this press release are not endorsed by The Maritime Executive.