Shipowners need to invest in data analytics, AI and machine learning to optimise fleet performance, reduce costs and lower emissions
Shipping companies should monitor the performance of their vessels and onboard systems to manage their assets more effectively. Those that include data analytics can also cut fuel costs by significant amounts, according to a technical expert and former ship operator.
Speaking at the Tanker Shipping & Trade Conference in London on 27 November 2019, Lean Marine chief executive Mikael Laurin said shipowners could cut operating costs by 20% by monitoring vessel performance and educating crew to use data analytics technology for fuel efficiency.
For example, owners of medium-range (MR) product tankers can increase earnings by US$1000/day per ship by optimising vessel speed, equivalent to US$365,000 per year, or US$3.65M for a fleet of 10 tankers.
To achieve these reductions, owners need to monitor and analyse tanker performance more frequently than using daily reports Mr Laurin said.
“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.
All this enables owners to understand how effective they are in fleet performance and reduce operating costs and emissions.
“If you can measure it, you can manage it,” said Mr Laurin. “You need the right tools onboard and to educate people on how to use the technology.”
He thinks big data analytics should also include artificial intelligence (AI) and machine learning to identify more performance information and help reduce operating costs further.
“We can learn more and can compare performance against other ships, fleets and owners,” he said. This way, owners, operators and charterers can manage their assets and their portfolio more effectively.
Voyage planning should include software and applications for speed optimisation, weather routeing, trim optimisation and managing cargo heating and cooling
During voyage execution, ship masters should follow the planned optimised route, follow best practice, optimise autopilot settings and slow turn to minimise resistance. They should follow advised speed and minimise variations in shaft power, keeping engines and propellers running in optimal conditions to save fuel and maintain continuous data logging to receive decision support from shore.
After the voyage, managers should review performance, analyse and compare routes, and analyse hull, propeller and engine performance.
Shipowners and operators could also use the latest in machine learning to manage fleet performance and reduce fuel consumption and greenhouse gas (GHG) emissions.
Shipping will be tasked with reducing GHG emissions by 40% over the next 10 years and must reach IMO’s 50% target by 2050. This will require all forms and methods of data processing and optimisation, according to Greensteam head of performance management Jonas Frederiksen, also speaking at the Tanker Shipping & Trade Conference.
“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.
“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 reductions 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.
Data collected from ships, meteorology and ocean conditions and AIS data indicates where and why a vessel uses excess fuel. These insights allow the crew to adjust operations, minimising fuel wastage, reducing cost and cutting emissions, Mr Frederiksen explained.
GreenSteam’s machine learning platform measures the contribution of complementary emissions reduction technologies.
Some of the largest fuel consumption savings come from minimising hull fouling. According to Safinah Group general manager Carl Barnes, speaking at the same conference, slime and weed fouling can increase drag by up to 10% and shell fouling by up to 40%. He said water temperature, illumination, nutrient levels, ship speed and idle time will influence fouling levels. This can be minimised depending on the hull coating.
Mr Barnes said data collected and processed during hull voyages enables owners to determine which coatings are most suitable. Analysed data should include vessel activity and speed, hull and propeller performance and arrival condition of the hull.
Owners should also analyse drydocking data to decide when and which yard to use for hull recoating.
Room for optimisation
Owners can turn to shipmanagers to support their performance management and fleet optimisation strategies – if they have the appropriate technology. Columbia Shipmanagement (CSM)’s new performance optimisation control room assists owners and charterers in reducing operating expenditure and emissions.
CSM president Mark O’Neil believes owners can save huge amounts by using a performance optimisation platform to manage fuel costs through fleet and vessel analytics.
“Digitalisation is a tool to get to ship optimisation,” he explained at Riviera Maritime Media’s Optimised Ship Forum in London on 10 December. “It is about preventing waste, using voyage routeing, managing speed and preventing delays at ports.”
CSM, which has about 370 ships under its management, includes data analytics in the performance optimisation control room to compare ship performance and benchmark against other fleets.
Mr O’Neil thinks real-time data and its analytics are vital for optimisation. “Owners should look at what can be done better and for any innovations that can help them do that,” he said. “They may only need to add small elements to existing software and hardware to do things better for less.”
Apart from optimising fuel and manning costs, Mr O’Neil thinks owners can reduce expenditure in other areas of operation: “Procurement will be the main battleground for achieving efficiencies.”
Owners can use e-procurement platforms to optimise spending on spares and services. They can also introduce predictive maintenance strategies to prevent wasteful spending on unnecessary spares and maintenance.
Potential for fuel saving
Speed optimisation: 20 - 30%
Hull condition: 5 - 25%
Propeller pitch optimisation: 5 - 20%
Waste heat recovery: 10%
Power management: 4 - 8%
Weather routeing: 3 - 8%
Optimised autopilot: 5%
Trim optimisation: 5%
Improved bulbous bow: 4 - 15%
Propeller improvements: 2 - 4%
Boiler consumption reduction : 3%
Energy saving lighting: 1%
Variable speed pumps & fans: < 2%
(Source: Lean Marine)