Machine learning and artificial intelligence enable accurate performance analytics

4 September, 2018 |

Machine learning and artificial intelligence enable accurate performance analytics

Many companies in the shipping industry have already started their digital journey by automating data collection from their vessels. This connected mode of operations introduces a new level of transparency to onboard operations, but also has a downside – namely the ever-increasing amounts of information produced that is far beyond the capacity of any single person to process. What is needed to make data even more useful is a way to automatically process gathered information and provide insights and feasible scenarios going forward.

With this kind of smart operation, a vessel’s automated data collection system uses cloud-based technologies to automatically analyze data in real time. Performance analytics are based on machine learning. Machine learning techniques improve the interpretation of data in a vessel-specific context, enabling accurate performance analytics and thus decision-making.

With smart operation, one can go beyond mere data collection to create situational awareness. The first step is to combine information from what’s happening onboard with information about the vessel’s sailing environment, such as weather data. Then, by applying intelligent analytics based on machine learning methodologies, one can move beyond answering the question “What happened in the past?” or even “What’s happening now?” to “What will most likely happen in the future?”.

Smart operations rely on algorithms, machine learning, and artificial intelligence to analyze data, simulate future scenarios, and identify possible risks – as well as find more optimal ways of operating. Increased transparency helps decision makers to react to issues in a timely fashion, plan more effectively, and enhance efficiency and safety. The idea is to divide data into manageable chunks and make sure they are shared with the right people at the right time.

In order to move from traditional or connected to smart, the following elements are key:

  • A plan for ensuring a shift in mindset – previously the onboard officers were responsible for vessel performance follow-up and optimization; with smart operations, onshore staff can help and supervise them
  • An understanding of how data processing and decision-making will move from onboard to onshore through automated processes
  • A system that allows moving from data collection and equipment monitoring to automated data/information analysis
  • New processes to ensure that personnel are able to utilize real-time data in place of one-shot data coming in on a daily or weekly basis
  • A plan for getting onboard crew engaged and committed to using the new technology, backed by strong support from top management
  • Ensuring that the human role is not underestimated – smart operation functions best when humans and computers are making decisions together, complementing each other’s strengths and compensating for each other’s weaknesses
  • Making sure that digitalization is not run as a typical one-off IT project but instead is a more long-term commitment from the whole business

 

Want to find out more? Get in touch >

Leo Laukkanen
Product Manager, Eniram

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