Ship Main Engine Lubricating Oil System’s Reliability Analysis by Using Bayesian Network Approach

Abstract

The friction of ship main engine mechanical moving parts, combined with the internal combustion of fuel, generate a great amount of heat, leading to the increase of their running temperature and acceleration of their wear. If the temperature and wear phenomena are not controlled and kept within the maker’s thresholds, it will result in a partial or total damage of the propulsion system. However, the oil lubrication system plays a vital role in reducing the friction of the moving parts and ensuring their cooling and cleaning. Therefore, it must be reliable enough and continuously available for a safe operation of the main engine. This work aims at studying the main engine lubrication oil system’s reliability. This will be achieved through using Bayesian Network method, in order to identify the system components weak points to improve their reliability and to propose a highly reliable system that may either be installed on board of a conventional ship or an autonomous ship. The benchmark of the improved system and the formal system shows a significant enhancement in reliability that has become close to 1. In the case of an autonomous ship, this system must operate autonomously without human intervention. An autonomous and remote monitoring system concept is proposed. In case of system failure or need of change of its functioning parameters, the shore control center team takes over the control and executes the necessary adjustment remotely.