Offshore support vessel (OSV) owner GulfMark, has trialled Enginei’s new auto-mode detection capability on its platform support vessel (PSV), Highland Prince, with successful results to date.
Enginei’s real-time monitoring and management solution provides better voyage planning and optimised speeds using volumetric and mass flow measurement to provide insight into the ships’ fuel consumption, operational data, emissions and power management. It records and presents the information through a display bridge and online dashboard.
In the conventional Enginei system, the operational mode the ship is in, such as standby, transit and dynamic positioning, are indicated by manually entering this into the system.
In the latest update, rather than manually entering the mode the ship is in, Newcastle University and Royston have developed a version that uses sophisticated data processing and statistical analysis to automatically identify the ship’s operational mode. This removes the risk of human-error and avoids misinterpretation from incorrect data and enables more reliable ship and engine performance data to be obtained.
The trials on the Highland Prince, which has a diesel-electric propulsion system with four Caterpillar engines and two auxiliary engines, enabled comparisons to be made between the auto and manual mode. Sensor and engine data was collected and analysed by the system to develop control limits for different modes of operation. The automatic identification mode showed close correlation between different types of operational activity with specific fuel consumption rates.
The new Enginei auto-mode successfully differentiated Highland Prince’s time spent in transit, standby and DP mode. This means that voyages can be better planned as optimum speeds and fuel consumption during transit can be estimated with higher accuracy. Using the data to optimise speeds, fuel consumption and CO2 emissions will also be able to be estimated and reduced.
Enabling automatic logging this way will save time for the crew and onshore staff and provide real-time performance data based on automatic detection of the ship’s operating mode and time.
Ship Efficiency Review News
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