Shipping in the Digital Era. In search of the Golden Equilibrium.
Shipping
industry is a conservative industry, sometimes too conservative. We
have built our “comfort zones” based on the conservative approach of
performing tasks for many years in a undoubtedly “safe”, however not
always “efficient” way. Safety of Navigation was the main, if not the
only concern.
The introduction of SEEMP back in 2013, and the unfortunate resonance of the global financial recession and the high prices of HFO, gave birth to the notion of “ Efficiency” in shipping.
We have to admit that the environmental implications of shipping were never the driving force for reducing the fuel consumption.
In this respect, we started evaluating hull designs, investing in new energy saving technologies to improve the propulsion efficiency, new antifouling coatings to reduce hull resistance and so on, and “surprisingly” we found out that we could operate more efficiently.That was actually a very big step for the conservative shipping industry.
Operating and navigating our ships with safety is not enough. We also have to be efficient ,so we reduce our operating costs and adapt to the new environmental regulations.
Can we improve our operating “efficiency” further?
The new trend in shipping is the Big Data Analysis, that will eventually lead one step further towards the “ Smart Ship”.
The notion of “ Smart” is quite familiar to us from our everyday life. The tendency in our “digital” life is to measure everything. We use smartphones and wearables to measure our health parameters. We measures steps, our heart rate , even our sleep cycle in order to identify our individual health KPIs so we become healthier.
Same is applicable for shipping industry.
With the advancements in technology, sensors and predictive maintenance, the concept of smart ships aims in using data to enhance ship performance.
This will eventually lead to a move from the planned maintenance scheme, towards a predictive maintenance, that will further reduce the operating costs and improve the operational reliability. The collection and assessment of operational data is another controversial issue.
The tendency is to gather data, but how much data is enough?
Collecting and transferring enormous amount of data for further assessment, without specific KPIs is useless. I strongly believe that diving into an “ endless” pool of data without a strategic plan is a waste of time and money.
Therefore, adapting baby steps and setting a handful of tangible practical KPIs is the the only solution.
The introduction of SEEMP back in 2013, and the unfortunate resonance of the global financial recession and the high prices of HFO, gave birth to the notion of “ Efficiency” in shipping.
We have to admit that the environmental implications of shipping were never the driving force for reducing the fuel consumption.
In this respect, we started evaluating hull designs, investing in new energy saving technologies to improve the propulsion efficiency, new antifouling coatings to reduce hull resistance and so on, and “surprisingly” we found out that we could operate more efficiently.That was actually a very big step for the conservative shipping industry.
Operating and navigating our ships with safety is not enough. We also have to be efficient ,so we reduce our operating costs and adapt to the new environmental regulations.
Can we improve our operating “efficiency” further?
The new trend in shipping is the Big Data Analysis, that will eventually lead one step further towards the “ Smart Ship”.
The notion of “ Smart” is quite familiar to us from our everyday life. The tendency in our “digital” life is to measure everything. We use smartphones and wearables to measure our health parameters. We measures steps, our heart rate , even our sleep cycle in order to identify our individual health KPIs so we become healthier.
Same is applicable for shipping industry.
With the advancements in technology, sensors and predictive maintenance, the concept of smart ships aims in using data to enhance ship performance.
This will eventually lead to a move from the planned maintenance scheme, towards a predictive maintenance, that will further reduce the operating costs and improve the operational reliability. The collection and assessment of operational data is another controversial issue.
The tendency is to gather data, but how much data is enough?
Collecting and transferring enormous amount of data for further assessment, without specific KPIs is useless. I strongly believe that diving into an “ endless” pool of data without a strategic plan is a waste of time and money.
Therefore, adapting baby steps and setting a handful of tangible practical KPIs is the the only solution.
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