Stochastic Approach in Performance Modelling of a Repairable Industrial System

Narendra Kumar
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Abstract

SUMMARY This paper aims to present a quantitative investigation of a case study based on a live industrial refrigeration system exhibiting complex and dynamic behaviour such as randomness, concurrency, and time dependency. The study employs a state-space stochastic Markovian process to model the interactions among the key functional elements of the system. Furthermore, the scientific approach pursued in this study would help improve the availability of the considered plant by establishing a trade-off between investment, economy and quality. Based on the analysis of results, a framework for Decision Support Priorities (DSP) is proposed, emphasizing the criticality of various functional units. This framework could also help set and prioritize maintenance, spare parts, and human resource requirements accordingly.
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可修复工业系统性能建模的随机方法
摘要 本文旨在介绍一项案例研究的定量调查,该案例研究基于一个现场工业制冷系统,该系统表现出复杂的动态行为,如随机性、并发性和时间依赖性。研究采用了状态空间随机马尔可夫过程来模拟系统关键功能元素之间的相互作用。此外,通过在投资、经济性和质量之间进行权衡,本研究采用的科学方法将有助于提高所考虑的工厂的可用性。在分析结果的基础上,提出了决策支持优先级(DSP)框架,强调了各功能单元的关键性。该框架还有助于确定维护、备件和人力资源需求的优先次序。
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来源期刊
International Journal for Engineering Modelling
International Journal for Engineering Modelling Engineering-Mechanical Engineering
CiteScore
0.90
自引率
0.00%
发文量
12
期刊介绍: Engineering Modelling is a refereed international journal providing an up-to-date reference for the engineers and researchers engaged in computer aided analysis, design and research in the fields of computational mechanics, numerical methods, software develop-ment and engineering modelling.
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