How to overcome the three main hurdles in vessel performance monitoring

While interest is growing in collecting performance data to analyse it, 80% of the global fleet still lacks live data, sensors or any form of more sophisticated data collection techniques.

Given the rise in fuel prices (23% up in just 2 months time!), vessel operators are aware that data collection, and analysing this data, is essential to reduce fuel consumption, optimise vessel performance and reduce CO2 emissions.

This was evident from responses to polls taken at a recent Riviera webinar, held in January. Overwhelmingly, 77% of respondents to a poll said they plan on using more advanced technologies in the future to reduce their fleet’s fuel consumption. Just as interesting, only 23% were currently using technologies for that purpose.

Clearly, there is lots of interest but limited progress. So, what's blocking the maritimeindustry to move forward?

Hurdles in advanced performance monitoring

While it’s encouraging to hear that operators are driving towards digitalisation, a key takeaway from recent webinars, blogs and articles is that the industry still may not be moving fast enough, which could cause issues in complying with the forthcoming EU and IMO emission regulations. But, maybe even more relevant, endanger your companies competitiveness.

We see 3 main issues blocking progress:

1. Older vessels

Measuring something requires data. But most of today’s commercial fleet is over 20 years old. And these ships were built before digital connectivity was available.  

2. Data inequality

Some have the data, while others really need the data. Especially charterers that are picking up the tab for the fuel. An estimated 80% of the chartered world fleet runs effectively off-the-grid without sensors or sophisticated data collection.

3. Data quality

Another obstacles standing in the way of collecting usable data become apparent from feedback from different sources. When asked by Riviera in a poll, the biggest challenge with collecting fuel consumption data, 41% of respondents said “sensor malfunctions”, while 24% answering said “human/crew error”.

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How a model-based approach can help

To further accelerate the transition to a data-driven performance assessment, a new approach is needed. Instead of relying on manual reported data, and overcoming the issues with sensor malfunctions, a model-based approach may be the answer.

Bt collecting data from objective and reliable data source, such as satellites, weather models and other automated data feeds. a higher frequency on data such as vessel speed, currents and weather can be collected without human intervention.

Feeding that data into a model, based on vessel specifications, a near real-time and objective data stream is generated without the need to rely on sensors. For example, We4Sea collects up to 480 data points per day, with over 95% global coverage without installing any sensor onboard.

This solves all 3 issues mentioned above.

The solution can be applied to all vessels, irrespective their age or connnectivity status, does not require an engineer to be onboard and connect sensors.

Also, it solves the data inequality issues. The collected data is available to both charterers and owners alike, meaning maximize visibility with a single-source-of-truth for vessel performance.

Last, the data quality is extremely high. As there is no human in the loop, (typing) errors have no effect on the data. Also, the data is objective as there is no human interpretation for reporting weather conditions, currents or other data.

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Advance your performance monitoring today

In order to stay competitive as an operator, now and in the future, it is essential to improve ship- and fleet efficiency.

A model-based approach such as developed by We4Sea offers data-driven solutions to improve your company's competitiveness, increase you fleet efficiency and reduce costs for fuel consumption and reduce emissions of vessels.

Interested in what we can do for you? Request a demo or a pilot on your fleet.

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Trust us, you will be amazed.

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