No one washes a rental car*
We think this saying encapsulates an important idea. There is little incentive to wash or maintain a car that one does not own. For example, the renter does not benefit from the resale of the rental car. In fact, the renter may never see the car again. However, a person who owns something has a strong incentive to take care of it.
However, what you should do is Own the Outcome.
The most important outcome of not maintaining a car (or a vessel) that you do not own is fuel consumption.
One of the biggest performance killers that all shipping companies face is hull fouling. Keeping ships’ hulls clean can reduce a ship’s fuel consumption by up to 25 percent, according to the preliminary findings of a IMO study.
So, while the cleaning may be done by an owner, it is in the charterer’s interest to have a clean hull, as he is impacted by the outcome, the fuel bill.
Typically, ship owners clean their vessels at regular intervals. But as a charterer, impacted by the outcome, it would be better if you would be in control of this process. But hull condition monitoring for a charterer is a very complex task.
Daily vessel reports, with averages over 24 hours, will not help you to show the impact of fouling.
Here a Digital Twin model-based approach can help. By combining a Digital Twin with noon reports, you can correct for the effects of weather, draft, and speed.
By comparing the reported fuel consumption with a benchmark Digital Twin performance model, which takes into account changes in speed, draft, and weather, the effect of fouling and the business case of a hull cleaning can be calculated.
Impact the Outcome
An example of how model-based monitoring can help charterers to impact the Outcome, is to analyze the net effect of fouling on performance.
It is good to understand that our Digital Twin is representing a clean vessel, with no fouling and no aging. When feeding the Digital Twin with real-time operational data, it calculates a baseline consumption, taking into account actual speed through water, draft, and weather impact.
If the reported consumption comes in (either by noon reports or sensors), you can calculate the difference between the expected performance and the reported performance. The difference is inefficiencies like hull fouling.
By reporting the difference and the trend over time, you can see a difference. Below, the difference is about 25%. By repeating the exercise after a cleaning, you can check the effect of the intervention. In this case, the difference dropped about 20% to just 5%. You can now calculate the improvement (in MT per day saved) and the business case for cleaning the hull.
Data of one of our clients showed that the noon-reported consumption had a 10% difference with the Digital Twin model-based data. Our customer, who was Time-Chartering the vessel, decided to perform a hull-cleaning.
After the hull cleaning, the difference dropped to 0,2% for the first month, a saving of 2,1 MT per day. The savings on fuel costs were 150,000 USD in just 6 months’ time.
We also saw the effect of fouling building up again, as shown in the below graph. After 7 months, the difference decreased to 5,3%. You can use this trend line to decide on the next cleaning. Read the full customer case here.
Own the Outcome
While you may not own the vessel, we can help you Own the Outcome. Real-time, accurate data with full transparency on vessel performance is essential for charterers. New, model-based tools are available to help in the real-time performance monitoring of your chartered vessels. And the good thing: you can start today!