Being an emerging form of computing technology, AI is one of many critical technologies that will determine the future of the maritime industry. AI will power autonomous shipping, navigational support systems, and vessel performance optimisation solutions, and has the potential to deliver value to its users when implemented properly. In part-3 of our four article series on AI technologies in the maritime industry, we take a look at how AI can help ships become smarter and better for the environment.
AI technology for voyage optimisation is primarily focused on reducing vessel fuel consumption, resulting in the reduction of CO2 emissions and running costs.
One example is i4 Insight’s Greensteam AI technology which achieves this fuel reduction goal by first training on data to learn how the vessel performs. This involves combining both low and high frequency data sources to get as much data on the vessel as possible. Empirical legacy models often only look at 10% of vessel data whereas AI models ingest over 90% of vessel data to create extremely accurate vessel performance insights. Once the AI technology has developed a vessel specific model, this can be used to understand past performance and to generate predictive performance insights which enables better optimisation decision making. The AI model is continuously learning as more and more vessel data is collected so the model continues to get more accurate and always reflects the current vessel performance.
AI models can use 90% of the data generated and process it almost instantaneously to create extremely accurate vessel performance insights.
One of the major optimisation opportunities is based on route and speed optimization. The model analyses the current vessel performance and generates vessel specific speed consumption curves based on draft, trim and weather conditions. On average Route and Speed optimization delivers a 2-3% reduction in voyage costs. The outcome is an optimal set of voyage instructions (in terms of instructed fuel consumption, power, SOG and waypoints) which provides a voyage profile to minimise total voyage cost which is refreshed throughout the voyage.
This AI model is also being used to manage environmental factors like hull fouling. Hull fouling is the biggest preventable cause of excess fuel consumption and controllable GHG emissions in the worldwide shipping fleet. The AI technology creates a condition-based cleaning regime which optimises hull cleaning schedules to prevent over cleaning and damage to coatings, or under cleaning creating excess resistance. Optimum cleaning regimes ultimately cut costs and reduce emissions.
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ARTIFICIAL INTELLIGENCE SERIES
In collaboration with Lloyd’s Register, Thetius is delighted to present THE LEARNING CURVE, a report on the state of artificial intelligence in the maritime industry. Read by thousands of industry professionals across the globe, this report examines how Artificial Intelligence (AI) can allow maritime companies across the maritime asset value chain to not only get ahead of the market but accelerate their digital transformation and meet the challenges of the upcoming energy transition.
Over the coming weeks, we will be sharing a series of articles on Artificial Intelligence (AI) as a technology that will guide industry stakeholders in meeting the challenges of the evolving landscape of the maritime industry. Each article will look at an emerging form of artificial intelligence, discuss the opportunities that it can bring to improve an organisation’s competitive advantage, and present examples of innovative startups building upon this emerging technology.
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