Customer cases and downloads
“We achieved a fuel cost saving of $150,000 in just 6 months’ time. The Digital Twin proved to be essential for the analysis in which we monitored the impact of hull fouling on fuel consumption. Using only noon-reported data, this analysis could not have been done."
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“Unifeeder has signed a cooperation agreement to roll-out the We4Sea Digital Twin based performance monitoring solution across Unifeeder’s fleet. The aim is to reduce the fuel consumption and emissions of the ships."
Go to Unifeeder.com
"We4Sea assisted Jumbo to maintain service speed with a minimal fuel consumption per mile. The result: a 5.4% fuel efficiency gain and a 9.4% time gain. The Digital Twin proved to be essential for this analysis, as it could normalize the data for weather, speed, and draught. Using only noon-reported data, this analysis could not have been done."
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"Hardware-based solutions come at a high cost. To put a sensor on board, a factor 10 often can be applied to the purchase cost of the sensor itself, due to installation, maintenance, and calibration. Model-based monitoring can be done at a fraction of the cost."
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The Ultimate Guide to Model Based Performance monitoring systems for ships
After reading this white paper, you will have acquired knowledge about what Model Based Monitoring is and how it works.
We'll explain how Model Based monitoring compares to noon report- and sensor-based monitoring, and how the Digital Twin can help you improve your vessel performance - without upfront investments in hardware.
This white paper also includes a table with an overview of the characteristics of the different monitoring solutions, for easy comparison.
