In particular, synchronizing and analyzing data from multiple sources will enable operators to make more informed decisions faster and improve the management of vessel performance in key areas such as fuel consumption, energy management, emission control, monitoring the health of the vessel’s equipment and equipment, and route optimization (e.g. , taking into account weather conditions and underwater currents).
Thus, data mining in the shipping industry will have a positive impact on the safety and quality of service for customers, give a competitive advantage for the shipping company and bring new knowledge and added value to managers. The availability of digitized data and the methodology for processing them for maintenance prediction helps in making more efficient decisions, monitoring assets and making optimal use of both an individual vessel and the entire fleet.
Onboard and shipboard sensors are already being used to measure various aspects of a ship’s performance, such as fuel consumption, engine torque, RPM and power, as well as temperature, pressure, electrical load, ship speed, and a host of other parameters. At the same time, an unprecedented amount of data on ships and engines, not to mention the weather, sea state and other external factors, is generated from different sources and in different formats. In fact, it has been estimated that a modern ship generates over 20 gigabytes of onboard data every day.
However, while this amount of information undoubtedly provides added value to the operator, without effective analysis it can also create serious problems.
