Διερεύνηση της σχέσης της ταχύτητας των πλοίων σε σχέση με τις τιμές των καυσίμων με τη χρήση δεδομένων από το AIS (Automating Tracking System)
Investigating the relationship between vessels speed and fuel prices using AIS data
KeywordsΝαυτιλιακές εταιρείες ; Βελτιστοποίηση ταχύτητας ; Κατανάλωση καυσίμων ; Αυτόματο Σύστημα Αναγνώρισης (AIS) ; Ανάλυση δεδομένων ; Shipping companies ; Speed optimization ; Fuel consumption ; Automatic Identification Systems (AIS) ; Data analysis
The main purpose of this thesis is to investigate the relationship between the sailing speed that vessels use in regards the fuels prices based on data from the Automatic Identification System (AIS). The speed of vessels affects the fuels consumption and their relationship can be described by a cubic function. Fuels consumption can be decreased up to 23% by decreasing vessel’s speed by only one knot. The speed reduction is also expressed as speed optimization from the shipping companies as the best sailing speed for each voyage that must be selected based on the technical parameters of the vessel and the type of voyage. The two main departments that decide the speed of a vessel is the Technical department and the Operations department of shipping company. In order any vessel to sail with lower speed for a long-time many factors have to be considered. Vessels engines are manufactured to run smoothly under certain speed which is indicated by the manufacturer. Sailing in lower speed, outside the boundaries that manufacturer has set, leads to extra maintenance on the engine and several checks that must be added for the crew. Nowadays with the intelligence engines this has been minimized but also exist. In regards our analysis on how the fuel prices affect the vessels speed will be based on the information provided by the AIS from each ship like the ship speed, the ship type, the ship position, the ship IMO, the ship MMSI, etc. In order to extend our analysis extra variables will be used. In the end we will try to evaluate and explain the results of our research and identify extra variables that can be added on our analysis for better results.