Leveraging Artificial Intelligence for Proactive Maintenance
Predictive maintenance technology for marine vessels enhances reliability and safety by detecting potential failures in critical systems before they occur. Operating in challenging environments, vessels often experience accelerated deterioration, leading to unplanned downtime and premature replacements. Early detection of failures through predictive maintenance enables timely intervention, mitigating costly service disruptions and empowering operators to maintain efficient operations.
The Predictive Maintenance Dashboard
This technology leverages artificial intelligence (AI) to analyse time-series data from onboard sensors, enabling anomaly detection and root cause prediction. This proactive, data-driven approach to asset management and regulatory compliance aligns with reliability, safety, and environmental standards. Predictive maintenance solutions are set to transform operations across shipyards, ports, and technical ship management, revolutionising the maritime industry's approach to vessel maintenance and performance optimisation.
Exhibits
- Optimised Routes For Maximum Fuel Efficiency
- Tools for Smarter and Safer Maritime Fuel Operations
- Harnessing Wind Power for a Cleaner Maritime
- Promoting Safer Maritime Operation with the Near-misses Detection Platform and GPS Calibration Services
- Leveraging Artificial Intelligence for Proactive Maintenance
- Augmenting Maritime Network Coverage with VDES
- Subsea Vigilance with Underwater Sensing
- Advancing Offshore Wind Solutions for a Sustainable Future
- Seamless Connectivity for Advanced Yard and Port Operations
- Powering Seamless Coastal Operations with Optimal Charger Placement
- Advanced and Sustainable Manufacturing Technologies for Shipbuilding and Repair
- Promoting Safe Maritime Operations with Robotic Supervision and Sensor Calibration
A*STAR celebrates International Women's Day

From groundbreaking discoveries to cutting-edge research, our researchers are empowering the next generation of female science, technology, engineering and mathematics (STEM) leaders.