Evergreen, Samsung Heavy Industries and ClassNK Test AI-Based Voyage Optimisation for Emissions Reduction

Evergreen Marine, Samsung Heavy Industries, Weathernews and ClassNK are partnering to verify whether AI-based voyage optimisation can deliver measurable reductions in ship fuel consumption and greenhouse gas emissions under real operating conditions.

The four companies have signed a memorandum of understanding establishing a framework to test the technology using an actual commercial vessel operated by Evergreen Marine Corporation.

The project will combine Samsung Heavy Industries’ autonomous navigation technology with meteorological and oceanographic data from Weathernews, while ClassNK will independently review the methodology and results.

AI to Optimise Vessel Routes and Speed

The project will use the Samsung Autonomous Ship (SAS) system developed by Samsung Heavy Industries.

SAS will apply a speed optimisation algorithm and real-time vessel control to support more efficient voyages. Weathernews will provide high-resolution weather and ocean forecasts, historical information and baseline voyage routes for comparison.

By combining vessel operating information with weather and sea-condition data, the partners aim to determine how AI-based voyage optimisation affects actual fuel consumption and emissions.

The technology is intended to improve voyage efficiency by allowing vessel operations to respond more effectively to changing conditions at sea.

Evergreen Provides Commercial Vessel for Trial

Evergreen will provide the commercial vessel used for the demonstration, together with operational and fuel-consumption data.

Its crew will also support the project during the trial.

Using an operating vessel rather than a simulation will allow the partners to assess the technology under actual maritime conditions, where fuel performance can be influenced by weather, waves, vessel condition and operational requirements.

Samsung Heavy Industries will install and maintain the SAS equipment while operating its speed optimisation algorithms and real-time vessel control technology.

Independent Verification Becomes Key Focus

ClassNK will be responsible for reviewing the project’s verification methodology and independently evaluating the results.

The classification society will also issue a Statement of Fact based on the findings.

Independent verification is an important part of the project because fuel savings from voyage optimisation can vary significantly depending on operating conditions.

Changes in weather, sea state, vessel performance and route requirements can make it difficult to determine whether reduced fuel consumption is directly attributable to an AI system.

The partners therefore aim to establish an objective methodology that can measure the impact of voyage optimisation under real-world conditions.

AI Supports Maritime Decarbonisation

Shipping companies are increasingly exploring technologies that can reduce fuel consumption while lowering greenhouse gas emissions.

Voyage optimisation and weather-routing systems are among the digital technologies being adopted to improve vessel efficiency without requiring major changes to propulsion systems.

AI can extend these capabilities by processing larger amounts of operational and environmental information and adjusting voyage strategies as conditions change.

The Evergreen project will examine whether combining autonomous navigation with weather and ocean data can produce measurable fuel and emissions savings during commercial operations.

Regional Maritime Companies Combine Expertise

The project brings together expertise from several parts of the Asia-Pacific maritime ecosystem.

Evergreen Marine, based in Taiwan, will contribute commercial shipping operations and vessel data.

Samsung Heavy Industries of South Korea will provide autonomous navigation and voyage-optimisation technology.

Japan-based Weathernews will supply weather and oceanographic information, while classification society ClassNK will provide independent technical verification.

The collaboration reflects the growing role of partnerships between shipowners, shipbuilders, technology providers and classification societies as digital technologies become more integrated into vessel operations.

Verifying Real-World Fuel and Emissions Savings

The project will ultimately analyse operational and fuel-consumption information from the Evergreen vessel to determine how effectively AI-based voyage optimisation can reduce fuel use and GHG emissions.

ClassNK said it will continue supporting technologies aimed at maritime decarbonisation and the practical implementation of advanced solutions for sustainable shipping.

As shipping companies look for ways to improve vessel efficiency, independently verified performance data could become increasingly important in demonstrating whether AI-based optimisation delivers measurable results under actual operating conditions.