Utilizes high-frequency telemetry data to manage fleet-wide performance through KPIs. It supports a single-system approach—from environmental compliance to operational optimization.
Visualizes fleet KPIs and monitors charter-party conditions such as speed and consumption. With real-time trend views and notifications, users can identify operational deviations earlier to ensure contract compliance.
Ensures the quality of high-frequency data while visualizing fleet-wide performance. Detecting early signs of CII deterioration and fuel efficiency loss to enable faster decision-making based on reliable data.
Uses AI simulations to develop voyage plans that balance ETA, fuel, and emissions, supporting operational efficiency and environmental compliance through weather-based route adjustments and plan-versus-actual analysis.
Integrates onboard sensor data to compare baseline values with actual operation. By distinguishing whether fuel consumption changes are driven by external factors or performance degradation, it enables targeted energy-saving measures and data-driven maintenance decisions.
Uses AI digital twins to forecast and manage fuel efficiency and CII with high accuracy. By calculating appropriate routes and speeds based on weather and vessel condition, it supports emissions reduction through integration with automatic speed control.
Collects and analyzes onboard data across manufacturers to optimize fuel consumption and enable early detection of failure signs. Real-time visibility into operating conditions helps reduce downtime and maintenance costs.
Enables both fuel efficiency and schedule adherence through dynamic speed and route optimization based on weather. Monitors gaps between plan and actual performance to detect deviations early as a comprehensive management system.
Integrates onboard and onshore data, providing an end-to-end flow from visualization to machine-learning analysis. It reliably collects data even under challenging offshore connectivity, helping speed up onshore support.
Integrates automatic diagnostics for the engine room with advanced main engine analysis. Detects anomalies on a single platform to prevent propulsion loss and enable faster troubleshooting.
Collects and analyzes Mitsui engine data to monitor for early signs of anomalies. Drill down into specialized performance reports to support predictive maintenance and reduce crew workload.
Aggregates onboard data across manufacturers into a unified visualization and integration platform. Combined with analytical tools, it expands data utilization across fleet operations to improve overall efficiency.
Links ship and shore information to provide standardized incident response. AI-assisted watch support and operational visibility maintain maintenance efficiency, safe operations, and environmental compliance in an integrated way.
Integrates ship and shore data to centrally manage remote equipment monitoring and predictive maintenance. By consolidating fragmented information, it helps support both operational improvement and compliance with environmental regulations.
Brings together vessel data that is often fragmented between ship and shore in a cloud-based platform. With interoperability across multiple interfaces, it helps shore-based teams monitor vessel status more efficiently and make more informed decisions to improve fleet-wide operations.
Supports continuous remote monitoring and troubleshooting through secure satellite communications. By creating a cloud-based digital replica of onboard systems, it enables onshore experts to perform rapid fault finding and support crews remotely, helping reduce maintenance costs and avoid unplanned downtime.
A scalable digital solution that helps streamline fleet management by visualizing and analyzing machinery data. Using machine learning and IoT, it continuously monitors equipment down to the sub-component level and turns operational data into practical insights for large-scale fleet operations.
Combines advanced AI, rule-based diagnostics, and Wärtsilä’s OEM expertise for predictive maintenance. It analyzes real-time data to detect subtle anomalies early, providing expert recommendations tailored to each vessel to help avoid unexpected downtime and costly repairs.
Provides technology applications and services for 24/7 data-driven fleet management. Through Cat Remote Fleet Vision, operators can track mixed-brand assets globally while using customizable alert notifications to share critical information quickly and reduce the risk of major equipment issues.
Uses digital twin technology and machine learning algorithms to support fleet optimization. By comparing real-time operating conditions with baseline performance, it helps predict component failures before they escalate, supporting proactive maintenance and environmental compliance efforts.
