RCM based optimization of maintenance strategies for marine diesel engine using genetic algorithms

In the modern world the availability of the machinery for any industry is of utmost importance. It is the right maintenance at right time which keeps these machineries available for their jobs. The primary goal of maintenance is to avoid or mitigate consequences of failure of equipment. There are various types of maintenance schemes available such as breakdown maintenance, preventive maintenance, condition based maintenance etc. Out of all these schemes Reliability Centred Maintenance (RCM) is most recent one and the application of which will enhance the productivity and availability. RCM ensures better system uptime along with understanding of risk involved. RCM has been used in various industries, however, it is very less explored and utilized in marine operations.Hence in the present study maintenance schemes of a marine diesel engine has been considered for optimization using RCM.Failure Modes and Effects Analysis and Fault Tree Analysis (FTA)are some of the basic steps involved in RCM. Due to the scarcity of reliability data particularly in the marine environment some of the components data had to be estimated based on the operating experience. As FTA is based on binary state perspective, assuming the system exist in either functioning or failed state, some of the components (whose performance varies with time and degrades) cannot be modeled using FTA. Hence, in this paper reliability modeling of performance degraded components is dealt with Markov models and the required data is evaluated from condition monitoring techniques. After obtaining the availability of the marine diesel engine, based on the importance ranking, critical components have been obtained for optimizing the maintenance schedules. In this paper genetic algorithm approach has been used for optimization. The results obtained have been compared and new maintenance scheme has been proposed.