In International Shipping News 20/03/2018
Imagine the day when a Fuel Saving Indicator like the one we have in our cars will be installed on board our ships. When “Green” section, the Captain or the Chief Engineer he will know with confidence that he is sailing under the optimum conditions in terms of fuel economy.
Let’s be honest, apart from the Energy Performance addicts (like the undersigned) the marine industry does not care about the Speed Loss and the Power Speed curves, or the EEDI or whichever fancy Energy efficiency indicator you can think of.
At the end of the day Fuel Consumption is the dominant factor. If you are wondering why the Energy Performance Analysis of a Ship is so complicated the answer is quite simple. We have to have to deal with a dynamic and always evolving model.
We can’t control weather and sea environment, and we can’t predict with the maximum potential level of confidence how the ship will perform under all conditions, or can we?
If we are looking for the one and only Key Performance Indicator, that will describe the energy performance of the vessel in a absolute and holistic way, we are in trouble. At least for the time being.
I can’t say what will happen in the next 10 years when the AI models will be implemented, however for the time being it seems that the fundamental components that we need to built the complex models, that will describe the performance of the ship in a constantly changing environment are missing.
We don’t have to immerse too deep to realize that the biggest problem we have is the quality of data. Number one culprit is the accuracy of the sensors. We rely for delicate and essential information for our models on inaccurate sensors. There is a profound need for standardization in the data acquisition systems. Everybody is aware of the inaccuracies related to the Doppler Speed Log for instance and I am really quite tempted to elaborate further about the weather data accuracy and the Fuel Oil Flowmeters.
Even worst, in case where automatic data loggers are not installed and we have the human evolvement for the collection of the valuable data the situation becomes much more complicated.
For various reasons, I don’t want to sound pessimistic, mostly because at some point in the future (either near or far), we will find the “holy grail”, the one and only KPI that will be representative for the energy performance of the vessel.
Until that time comes we may consider another simplified approach. Of course, we can make complex models that will include the performance of the hull, the propeller the main engine the electrical generators and whatever you can think of.
However, the more complex is the model the more we increase the unreliability and inaccuracy of the results for the reasons I cited earlier. What if until that day comes, we adapt a simplified “LEGO” approach.
If our model is too complicated why not break it down to its fundamental blocks.
I can’t deny that there is a big correlation and interaction between the building blocks but let me elaborate further on this theory.
Instead of having the Hull-Propeller-Main Engine model we can break it down to simpler models or what I call “lego” blocks.
Main Engine Performance is not related to the hull. It may sound provocative but it’s the truth. We want the Main Engine to perform well under all loads, and we can monitor this quite efficiently through the SFOC KPI. I admit that when the hull is fouled more propulsive power is required but this is irrelevant with the performance of the main engine as long as the SFOC for the specific load is the expected.
Similarly, for the Hull- Propeller model, ISO 19030 seems to be a good “tool” in our toolbox despite the inherent problems related to filtering, corrections issues and the an-avoidable assumptions we have to make.
So, until we come up with a better tool, ISO 19030 is a quite promising aid that can be used for decision making for setting a hull propeller monitoring scheme.
At this point and for the record, I would like to comment that the practical use of the ISO at least for the undersigned should rely on the trend of the speed loss and not the absolute value.
It’s like using a not so accurate weight scale to monitor your weight. The trend in weight loss is more valuable than the accuracy of the scale itself (provided that it shows the same biased error).
Similarly, we can go after KPIs like the Electrical Generators performance the optimization of the electrical load, the optimization of the weather routing etc.
Instead of trying to optimize the total model we should optimize the performance of each individual “LEGO” block. I hope everybody understands why I am skeptical about the “BIG” data era. My main argument is the serious “quality” issue. If we don’t solve this, there is no point on transferring terabytes of useless data. Moreover, there is no point to accumulate data, if there is not a well-established performance management system in place to evaluate them.
Another critical link in the chain, maybe the most critical, is the education of our seafarers on the energy performance and the need for their active evolvement. Seafarers are our frontline, and every fancy energy saving measure is bound to fail if they are not actively involved.
I have written another article “Smart Ships vs Smart Seafarers” about this issue and I don’t want to elaborate further at this point.
There is a big chance that the Holy Grail is just a legend. I am quite sure however, that a number of romantic knights are still trying to find the mysterious castle which is guarded by a custodian called the Fisher King.
Studies say, that the average time a reader spends when reading an article is 37 seconds, (one of the cons of the digital era that is changing the way our brain neurons are functioning).
I am quite sure that you have exceeded that, so I you are reading this line I would like to thank you for your attention.
Source: Energy Efficiency Superintendent By Konstantinos Lourandos
