One of the available definitions of Big Data is as follows:
” [..] a broad term for data sets so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, data curation, search, sharing, storage transfer, visualization, and querying and information privacy. The term often refers simply to the use of predictive analytics or certain other advanced methods to extract value from data, and seldom to a particular size of data set. Accuracy in Big Data MAY lead to more confident decision making. And better decisions can result in greater operational efficiency, cost reduction and reduced risk.”
The key word is MAY. Before a decision on using big data analytics is taken it is important that someone starts with the right questions. Some of the questions that need to be answered are:
- What do I want to know?
- Does it worth it?
- Who will analyze the data?
- What are the sources of data?
- What about data and cyber security?
Big amount of data can produce answers to things that don’t really matter.
TCM is a ship management company, and as such we focus on measures that will help us improve the energy efficiency of our operations. It must be noted that we are certified against ISO Standard 50001 for Energy Management Systems. In line with the requirements of 50001, an energy risk assessment has to be conducted as to identify significant energy users onboard and prioritize action plans. Energy wise, ship operations can be divided into 3 major areas:
- Voyage planning, execution and propulsion,
- Electricity production, and
- Steam production
Worst case scenario revealed that for a tanker vessel an increase in the order of 40% in energy consumption might occur, even within the first year after the drydock. Worst case scenario includes a prolonged idle stay of a vessel (without having the appropriate antifouling system), improper operational routines, not properly tuned or maintained internal combustion engines, inefficient cargo handling procedures, etc. By far the most significant area is voyage planning, execution and propulsion, having hull & propeller efficiency as the more significant component.
Hence our first priority was to Quantify Hull and Propeller Performance (Picture 1).
Through quantification of hull and propeller performance we have a clear picture of the efficiency of our dry dock strategy. The term dry dock strategy includes hull treatment, antifouling system selection and its application. Furthermore, it is a tool that allows us to timely identify the need of a hull cleaning or even make predictions which is very important as well.
There are various methods that can be used, or even combined, to derive conclusions on hull and propeller performance. These could include analysis of noon data, dedicated speed trials, visual observations, etc. but the most important information is the accuracy of the output. And here is where Big Data comes into the picture.
With the use of telemetry nowadays we have real time access to any kind of information that we need from a vessel, provided that the vessel is adequately equipped. This high frequency information collected from a vessel, combined with information from other sources and the proper method of analysis, can be used to increase the level of accuracy and lead to a more confident decision making, and according to the definition of the Big Data, better decisions can result in greater operational efficiency, cost reduction and reduced risk.
Once a reliable monitoring system is established then realistic goal setting is the next step.
Picture 3 above depicts on the x axis the dry dock performance and on the y axis the savings resulting from underwater maintenance of a vessel. What we are trying to achieve is the highest possible dry-dock performance that will result in the minimum underwater maintenance savings. The better the job that we do in the dry dock the less corrective actions will be required between the drydock periods.
Whenever an underwater maintenance of a hull takes place there is a risk involved, which can result in a cycle of even increasing vessel operating costs. Besides the obvious benefit of minimizing this risk, we also safeguard undisrupted and unrestricted trading by reducing potential off hire time and ensuring regulatory compliance (biofouling).
Above article is an edited version of Mr. Michael Servos presentation during the 2016 SMART4SEA Forum
Please click here to view his video presentation
The views presented hereabove are only those of the author and not necessarily those of SAFETY4SEA and are for information sharing and discussion purposes only.
About Michael Servos
Michael Servos since January 2015 is serving as Energy Manager at Tsakos Columbia Shipmanagement Corporation (TCM). Michael is a graduate of National Technical University of Athens with a Degree in Naval Architecture and Marine Engineering.
At the beginning of his career was he was actively involved to a number of ships’ repairs and conversions. He has also conducted various types of surveys and audits including shipboard energy audits & environmental compliance audits. Prior joining TCM he was a Senior Vessel Performance Analyst, at Operational & Environmental Performance Department of ABS.
Michael is also an Energy Management Systems (EnMS) Lead Auditor and member of the Greek National Committee in ISO/Technical Committee 8 / Sub Committee 2 (Environmental Protection).