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

IF 1.6 Q2 ENGINEERING, MULTIDISCIPLINARY International Journal of System Assurance Engineering and Management Pub Date : 2024-07-09 DOI:10.1007/s13198-024-02374-z
Ankush Tripathi, M. Hari Prasad
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Abstract

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.

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使用遗传算法优化基于 RCM 的船用柴油机维护策略
在现代社会,任何行业的机械设备的可用性都至关重要。正是在正确的时间进行正确的维护,这些机器才能继续工作。维护的主要目的是避免或减轻设备故障的后果。维护计划有多种类型,如故障维护、预防性维护、基于状态的维护等。在所有这些方案中,以可靠性为中心的维护(RCM)是最新的一种,它的应用将提高生产率和可用性。RCM 可确保更长的系统正常运行时间,同时了解所涉及的风险。因此,在本研究中,考虑使用 RCM 对船用柴油发动机的维护方案进行优化。由于可靠性数据稀缺,特别是在海洋环境中,一些部件的数据必须根据运行经验进行估算。由于 FTA 基于二元状态视角,假定系统要么处于正常运行状态,要么处于故障状态,因此有些部件(其性能随时间变化而变化,并会退化)无法使用 FTA 建模。因此,本文采用马尔可夫模型对性能退化部件进行可靠性建模,并通过状态监测技术评估所需数据。在获得船用柴油机的可用性后,根据重要性排序,获得了用于优化维护计划的关键部件。本文采用遗传算法进行优化。对所获得的结果进行了比较,并提出了新的维护方案。
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来源期刊
CiteScore
4.30
自引率
10.00%
发文量
252
期刊介绍: This Journal is established with a view to cater to increased awareness for high quality research in the seamless integration of heterogeneous technologies to formulate bankable solutions to the emergent complex engineering problems. Assurance engineering could be thought of as relating to the provision of higher confidence in the reliable and secure implementation of a system’s critical characteristic features through the espousal of a holistic approach by using a wide variety of cross disciplinary tools and techniques. Successful realization of sustainable and dependable products, systems and services involves an extensive adoption of Reliability, Quality, Safety and Risk related procedures for achieving high assurancelevels of performance; also pivotal are the management issues related to risk and uncertainty that govern the practical constraints encountered in their deployment. It is our intention to provide a platform for the modeling and analysis of large engineering systems, among the other aforementioned allied goals of systems assurance engineering, leading to the enforcement of performance enhancement measures. Achieving a fine balance between theory and practice is the primary focus. The Journal only publishes high quality papers that have passed the rigorous peer review procedure of an archival scientific Journal. The aim is an increasing number of submissions, wide circulation and a high impact factor.
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