VLCC's fuel consumption prediction modeling based on noon report and automatic identification system. Issue 1 (1st January 2019)

• Record Type: Journal Article
• Authors: Safaei, Ali Akbar; Ghassemi, Hassan; Ghiasi, Mahmoud
• Editors: Colmenares, Ramon Fernando
• Is Part Of: Cogent engineering. Volume 6:Issue 1(2019)
• Publication Date: 2019-01-01
• Subjects: fuel consumption -- sea state -- multiple linear regressions -- noon report data -- automatic identification system -- VLCC; Engineering -- Periodicals; Technology -- Periodicals; Engineering; Technology; Periodicals; 620
• DOI: 10.1080/23311916.2019.1595292
• Languages: English
• ISSNs: 2331-1916

Abstract

Abstract: It is extremely important for fuel saving by taking the correct decisions where cost efficiency and environmental friendliness are top priorities. The fuel consumption rate of the ship is influenced by many parameters, such as average daily sailing speed, ship displacement, cargo, ballast water and bunker, trim and sea conditions (wind, wave and current) in a complicated way. In this study, noon report (NR) and automatic identification system (AIS) datum of four Very Large Crude Carriers (VLCC) are widely used to establish a prediction model. Needless to say that, the accuracy of statistical models depends on consistency and quality of collected datum, hence a novel combination methodology applied to NR and AIS datum to prepare a series of pure valid data population of vessel speed, fuel consumption and sea state. Then the consistency of populations are enriched by eliminating the out ranged or junkie members in different methods, i.e., T -test, normality control and outlier score base (OSB). Finally, multiple linear regressions are applied considering all fuel consumption influential parameters. Results show a high correlation between the independent and dependent variables. Consequently, generated formula predicts fuel consumption of vessels at all variable conditions in good agreement with recorded fuel consumption data.