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Transformative AI for the Modern Maritime Industry

Transformative AI for the Modern Maritime Industry
April 8, 2024

These are challenging times for the maritime industry. Shipping companies across the globe constantly navigate a broad range of operational and commercial decisions – shifting customer demand, strict new regulations on carbon emissions, and geopolitical events that have thrown established trade routes into turmoil.

The complexity of maritime planning is impossible to ignore. The volume of environmental and operational data available for fleet decision making has soared. Planning variables used to optimize every voyage have significantly proliferated. Margins for error are getting smaller. The industry is increasingly faced with a labor shortage across operational functions. And the tools used for planning today weren’t built for an industry trying to compete and thrive while reaching net zero carbon emissions by 2050.

This is not a unique challenge to maritime. Companies delivering a wide range of products and services are faced with processing massive amounts of information in the course of business. Much of this data is digital, but non-electronic data continues to play a large part in the day-to-day operations of many traditional industries. There are limits to the effectiveness of existing technologies and historical knowledge for increasingly complex planning.

Companies today are progressively embracing proven artificial intelligence technology to transform their productivity and competitiveness. It is transforming industries across the globe, and maritime is well positioned to leverage the power of AI. Shipping companies collect vast amounts of operational, commercial and environment data that can be used to train AI models. AI can optimize routing, speed, and fuel consumption for individual voyages. AI can recommend operational parameters to reduce emissions and report compliance with global regulations. AI can seamlessly optimize entire fleets of vessels. And it can do it faster and more accurately than traditional planning processes.
Increased Decision Complexity

The decisions made by modern maritime operations and environmental planning teams are unique to the markets that they serve (e.g. container transportation, car carriers, oil transportation, passenger lines). The AI tools built to enable these teams to optimize their unique vessel and fleet decisions must be designed to support their distinct needs.

For example, liner shipping companies serving the container transportation market move with predictable and repetitive proforma schedules around the globe. AI can be leveraged to optimize an individual line’s performance and emissions, or an entire global network. AI can analyze historical data, current operational parameters, and future projections to suggest adjustments like rotating vessels between high- and low-emission routes. It can identify underperforming services and vessels and propose alternatives for a given proforma schedule to reduce a service’s environmental impact. And AI can efficiently align a liner company’s environmental goals with its financial goals.
An AI Decision Engine for Maritime

Shipping efficiently is hard to do. And it’s only getting harder as major new regulations come into effect around the globe, including Carbon Intensity Indicator (CII), EU ETS, Fuel EU and potential future IMO carbon tax initiatives. Bearing AI empowers maritime shipping owners and operators to navigate the era of green shipping by optimizing their fleetwide commercial and operations decisions with advanced AI.

Bearing AI has created the industry’s first Maritime AI Decision Engine built on massive sets of maritime data to accurately profile ship performance. Bearing’s prediction models aggregate a broad range of ship profile data and daily voyage specific data to provide advanced tools for performance and compliance optimization.

The Bearing AI platform allows shipping companies to analyze the performance of individual ships and entire fleets, project CII scores, and estimate EU ETS obligations. Bearing AI proactively and precisely recommends actions for voyage operational improvements, and optimizes timing for scheduled maintenance, such as accelerating cleaning schedules to reduce biofouling.

In both blind tests and field tests with the maritime industry’s leading shipping companies, Bearing AI’s predictions have consistently delivered higher accuracy than traditional industry planning tools and physics-based vessel models.
Specialized Planning for Liner Companies

To address the unique planning challenges in liner shipping, Bearing AI has added a specialized liner module to its Maritime Decision Engine platform – the Bearing AI Deployment Planner. The Bearing AI Deployment Planner provides a “deployment playground” where liner companies can experiment with vessel deployments and schedule adjustments to instantly see the simulated effects of these changes on schedule performance and emissions. Planning teams can simulate the performance of their vessels deployed across different service schedules, simplifying the process of identifying the most cost-effective and emissions-efficient deployments for their fleet. Bearing AI provides liner companies the strategic planning capabilities they need to turn compliance into a business advantage.

“We see environmental compliance not as an obstacle but an opportunity,” said Kristofer Maanum, Bearing AI Senior Product Leader. “With the Bearing AI Deployment Planner, liner companies can reduce emissions while increasing revenues. They can not only meet current regulations, but exceed them, giving them the opportunity to offer greener shipping at premium rates.”
Beyond Compliance to Global Sustainability

The maritime industry moves 90% of global trade. AI is a proven technology that has great potential to positively transform the industry by improving safety, efficiency, and sustainability. Bearing AI’s comprehensive decision engine platform enables maritime companies to lead at the forefront of sustainable shipping practices, promoting a greener and more efficient future for global shipping.
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