Data analysis to evaluate reliability of a main engine
journal contributionposted on 2023-05-20, 04:48 authored by Mohan AnantharamanMohan Anantharaman, T M Rabiul IslamT M Rabiul Islam, Khan, F, Vikrambhai GaraniyaVikrambhai Garaniya, Lewarn, SB
Maritime transportation is the essence of international economy. Today, around ninety percent of world trade happens by maritime transportation via 50,000 merchant ships. These ships transport various types of cargo and manned by over a million mariners around the world. Majority of these ships are propelled by marine diesel engines, hereafter referred to as main engine, due to its reliability and fuel efficiency. Yet numerous accidents take place due to failure of main engine at sea, the main cause of this being inappropriate maintenance plan. To arrive at an optimal maintenance plan, it is necessary to assess the reliability of the main engine. At present the main engine on board vessels have a Planned Maintenance System (PMS), designed by the ship management companies, considering, advise of the engine manufacturers and/or ship’s chief engineers and masters. Following PMS amounts to carrying out maintenance of a main engine components at specified running hours, without taking into consideration the assessment of the health of the component/s in question. Furthermore, shipping companies have a limited technical ability to record the data properly and use them effectively. In this study, relevant data collected from various sources are analysed to identify the most appropriate failure model representing specific component. The data collected, and model developed will be very useful to assess the reliability of the marine engines and to plan the maintenance activities on‐board the ship. This could lead to a decrease in the failure of marine engine, ultimately contributing to the reduction of accidents in the shipping industry.
Department/SchoolAustralian Maritime College
PublisherFaculty of Navigation, Gdynia Maritime University
Place of publicationPoland
Rights statementCopyright 2019 The Authors. Licensed under Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) https://creativecommons.org/licenses/by-nc/3.0/