Study of Ship Fuel Oil Consumption Monitoring in a Shipping Company Based on Big Data Architecture

Sea transportation as being the most cost-effective method of moving commodities and raw materials throughout the world makes around 80% of global commerce via marine routes. In total, 75% of ships operational budget is used on fuel oil consumption and efficiency in ship operation is the main problem for shipping companies that have large fleet of ships. Ship industries are one of the oldest and most traditional industries that still rely on intuition rather than data in making decision particularly due to network and planning challenge. The objective of this research is to establish data architecture and digital operational data mechanisms for assisting shipping stakeholders in making informed decisions, one of which regarding ship fuel efficiency. The maritime big data architecture has been structured by collected historical data to calculate the difference in fuel consumption rates for all equipment compared with observational data and then predicting it using a regression approach. Fuel oil consumption for main engines in comparison with the influence of parameters such as distance, speed, draft, RPM, cargo load, wind conditions, and wave speed is the output data that will be displayed in the big data architecture. These data assist decision-makers in optimizing it according to actual conditions.