Telematics, machine learning, data analytics and condition-based maintenance can be used to improve vessel performance
Tug owners can use digitalisation technology and analytics to monitor the performance of their vessels’ propulsion systems, including telematics with remote diagnostics and analytics provided by an original engine manufacturer (OEM). This way owners can maximise vessel performance, minimise maintenance and optimise energy delivery while reducing fuel consumption.
According to Caterpillar marine digital general manager Jim Newman there are several digitalisation technologies owners can request from OEMs. He says owners should select the technology from “what is attainable and valuable to your business today”.
These technologies can be applied to help drive maintenance decisions, improve fuel and energy efficiency, inform decision making, reduce unplanned maintenance and risks and enable better fleet management, says Mr Newman.
He highlights technologies including telematics, machine learning, physics- and engineering-based analytics and condition-based maintenance.
“Business drivers are the keys to selecting the technology solutions,” he explains. “The technologies already exist to achieve your goals. It is about picking the right one.”
Telematic solutions provide remote access to data, reports and diagnostics on a fleet of tugs, allowing operators to interpret the information and decide on a course of action.
Analytics provides analysis and actionable condition-driven recommendations, based on transformed data.
Machine learning uses artificial intelligence to automate data analysis. Systems learn from data, identify patterns and make decisions with minimal human intervention.
Mr Newman says owners need to select the right technologies for their organisation.
“[Owners] need to ask themselves, ‘What business outcomes are keeping me awake at night?’” he says. They should also consider the amount of historical operating data they would require to attain the maximum business value from certain technologies.
“Machine learning assumes you have vast amounts of data,” says Mr Newman. “To do these super-advanced calculations, you are required to know that. How do you get that?” he asks.
One way to generate that kind of data would be to collaborate with other tug owners, which the European Tugowners Association called for in 2019 to demonstrate cross-industry emissions reductions.
“If you want to drive costs out of those assets, it means you might have to share data with a competitor,” says Mr Newman. “The combined datasets from the two companies might allow owners to take advantage of these super-predictive capabilities.” However, owners may not be comfortable sharing information with a competitor. “Then, it might mean the application is not right for you,” says Mr Newman. Another option, collaborating with an OEM, may be a better solution.
Caterpillar offers owners greater visibility into how their assets are operating and gives expert advice on condition-based maintenance.
As an example, Caterpillar assisted an owner of a new vessel with hybrid propulsion, when the owner was concerned with the fuel bill. Mr Newman explains the owner said the hybrid vessel was costing more to operate than a conventional diesel-powered vessel.
However, the data told a different story. It showed one master operated the vessel exactly as instructed and “his fuel savings were immense,” says Mr Newman. “The other captain did not trust the system.” Instead of operating the vessel in electric mode in transit, this master used his large diesel engines in hot standby the entire time. This resulted in fuel consumption 37% higher than the other captain.
Through its data analysis, Caterpillar identified that by changing the operational profile of the equipment and captains, the owner could achieve 8% savings on fuel and 76% on annual maintenance per vessel.
Jim Newman was speaking at Riviera Maritime Media’s Annual Offshore Support Journal Conference, Awards, and Exhibition in London in February