Effect of ship loading on marine diesel engine fuel consumption for bulk carriers based on the fuzzy clustering method

Abstract

The loading of the ship is investigated under fully loaded and ballast conditions. Each case is categorized numerically under 1 and 0 for fully loaded and ballast conditions, respectively. The multi criteria decision making (MCDM) method is applied to advance and support the decision-making system for ship operations and ship owners. The parameters analysed in this research include wind speed, wave height, ship speed, distance travelled, and shaft speed. The fuzzy analytical hierarchy process (Fuzzy-AHP) method has been used to prioritise the weight of criteria decision making. They will provide a fundamental criterion to support the commercial stakeholders, loading & navigation of the vessels. The novelty methodology indicates that machine learning could be used in decision making for optimal loading of the ship. The optimal loading of the ship and fuel oil consumption of the main diesel engine has been achieved from this research by the proposed methodology. The results of this research are useful for shipping transportation companies and especially as a tool for the Master and the Chief Engineer of ships and researchers in the field of ship energy efficiency management.