MOL introduces an application for performance degradation tracking 'Fouling Analysis'
Mitsui O.S.K. Lines, Ltd. released an application called "Fouling Analysis" as part of the big data utilization project "FOCUS", according to the company's release. This application uses big data to analyze in detail the state and causes of marine biofouling (fouling) on the underwater surfaces of ships and proposes optimal maintenance (such as hull cleaning during operation and painting work during docking). Additionally, by utilizing this application, it significantly reduces unnecessary fuel consumption caused by propulsion performance degradation due to biofouling, contributing to the reduction of the greenhouse gas (GHG) emissions.
In "Fouling Analysis," the state and cause of fouling are analyzed using sensor data collected at intervals of several minutes and voyage data recorded daily since the ship's delivery, combined with MOL's unique expertise. Even for older ships, it is possible to monitor the degradation of propulsion performance from the time of ship's delivery to the present.
By displaying the docking periods in bands, color-coding based on phytoplankton concentration, linking 3D hull surface photos, and considering the type of paint and the amount of speed deterioration, it is possible to analyze the causes of performance degradation and evaluate antifouling paints. Based on the accumulated data and analysis results, optimal cleaning, selection of the best antifouling paint according to the ship's operation, and high-quality painting work can be carried out, thereby suppressing propulsion performance degradation and achieving efficient ship operation without unnecessary fuel consumption.
Furthermore, from the 3D hull surface photos, it is possible to calculate the fouling areas and their sizes. This information is used to select the optimal paint, evaluate the skills of painting contractors, optimize the coating for each area, and verify the accuracy of the propulsion performance degradation analysis results.
This application incorporates the knowledge of MOL Ship Management Co., Ltd., a group ship management company, and is used in the maintenance planning of approximately 500 ships operated by MOL. Currently, a highly accurate analysis model using AI is under development, further evolving the process of formulating optimal maintenance plans from big data and contributing to GHG reduction through improved ship management quality.
