These are challenging times for the maritime industry. Shipping companies around the world constantly navigate a wide range of operational and commercial decisions – changing consumer demand, strict new regulations on carbon emissions, and geopolitical events that have thrown trade routes into turmoil.
The complexity of marine planning is impossible to ignore. The volume of environmental and operational data available to make fleet decisions has increased. The planning variables used to optimize each trip have expanded significantly. Margins of error are shrinking. The industry is facing labor shortage in operational tasks. And the tools used for planning today were not designed for an industry trying to compete and grow while reaching net zero carbon emissions by 2050.
This is not a challenge unique to Maritime. Companies providing a wide range of products and services are faced with processing large amounts of information in the course of doing 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 current technologies and historical knowledge for increasingly complex planning.
Companies today are slowly adopting proven artificial intelligence technology to transform their productivity and competitiveness. It’s transforming industries around the world, and maritime is well-positioned to take advantage of the power of AI. Shipping companies collect large amounts of operational, commercial and environmental data that can be used to train AI models. AI can optimize routing, speed and fuel consumption for individual journeys. AI can recommend operational parameters to reduce emissions and report compliance with global regulations. AI can seamlessly optimize an entire fleet of ships. And it can do it faster and more accurately than traditional planning processes.
Increasing decision complexity
Decisions made by modern maritime operations and environmental planning teams are unique to the markets they serve (e.g. container transport, car carriers, oil transport, passenger lines). AI tools designed to help these teams optimize their unique ship and fleet decisions must be designed to meet their specific needs.
For example, liner shipping companies serving the container transportation market move around the world with predictable and frequent proforma schedules. AI can be leveraged to improve individual line performance and emissions, or an entire global network. AI can analyze historical data, current operational parameters, and future projections to suggest adjustments such as rotating vessels between high- and low-emission routes. It can identify underperforming services and vessels and suggest alternatives to a given proforma schedule to reduce the environmental impact of the service. And AI can effectively align a liner company’s environmental goals with its financial goals.
An AI Decision Engine for Maritime
Shipping efficiently is difficult. And it’s getting harder as major new regulations come into effect around the world, including the Carbon Intensity Indicator (CII), EU ETS, Fuel EU and possible future IMO carbon tax measures. Bearing AI empowers shipping owners and operators to navigate the era of green shipping by optimizing commercial and operational decisions across their fleet with advanced AI.
Bearing AI has created the industry’s first maritime AI decision engine built on a large set of marine data to accurately profile vessel performance. Bearing prediction models aggregate a wide range of vessel 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 accurately recommends measures for operational improvement of the journey, and optimizes time for scheduled maintenance, such as speeding up cleaning schedules to reduce biofouling.
In both blind tests and field tests with leading shipping companies in the maritime industry, bearing AI predictions have consistently provided greater accuracy than traditional industry planning tools and physics-based ship models.
Special planning for liner companies
To address the unique planning challenges in liner shipping, Bearing AI has added a special liner module to its Maritime Decision Engine platform – the Bearing AI Deployment Planner. Bearing AI Deployment Planner provides a “deployment playground” where liner companies can experiment with ship deployments and schedule adjustments to quickly see the synthetic impact of these changes on schedule performance and emissions. Planning teams can simulate the performance of their ships deployed in different service schedules, simplifying the process of identifying the most cost- and emissions-efficient deployments for their fleets. Bearing AI provides liner companies with the strategic planning capabilities they need to turn compliance into business advantage.
“We see environmental compliance not as an obstacle, but as an opportunity,” said Christopher Manam, senior product leader at Bearing AI. “With the Bering AI deployment planner, liner companies can reduce emissions while increasing revenue. They can not only meet current regulations, but exceed them, allowing them to offer greener shipping at premium rates.” opportunity to do.”
Beyond Global Sustainability Compliance
The maritime industry transports 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 be at the forefront of sustainable shipping practices, fostering a greener and more efficient future for global shipping.
Learn more at https://bearing.ai/
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