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Application of Markov Process in Performance Analysis of Feeding System of Sugar Industry

机译:马尔可夫过程在制糖工业进料系统性能分析中的应用

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To analyse the performance measures of complex repairable systems having more than two states, that is, working, reduced and failed, it is essential to model suitably their states so that the system governs a stochastic process. In this paper, the application of time-homogeneous Markov process is used to express reliability and availability of feeding system of sugar industry involving reduced states and it is found to be a powerful method that is totally based on modelling and numerical analysis. The selection of appropriate units/components in designing a system with different characteristics is necessary for the system analyst to maintain the failure-free operation. Keeping this concept in this study, the steady state availability of concern system is analysed and optimized by using a popular search technique, genetic algorithm. The objective of this paper is to consider the system operative process as Markov process and find its reliability function and steady state availability in a very effective manner and also to obtain an optimal system designing constituents which will allow a failure-free operation for long time period as required for maximum system productivity. The system performance measures and optimized design parameters are described and obtained here by considering an illustrative example.
机译:为了分析具有两个以上状态(即工作,减少和失败)的复杂可修复系统的性能指标,必须对它们的状态进行适当建模,以便系统控制随机过程。本文采用时均马尔可夫过程来表示含糖状态降低状态的制糖业供料系统的可靠性和可用性,是一种完全基于建模和数值分析的有效方法。在设计具有不同特性的系统时,选择适当的单元/组件对于系统分析人员保持无故障运行是必要的。在本研究中保留这一概念,并通过使用流行的搜索技术遗传算法对关注系统的稳态可用性进行了分析和优化。本文的目的是将系统运行过程视为马尔可夫过程,并以一种非常有效的方式找到其可靠性函数和稳态可用性,并获得一种最佳的系统设计组件,该组件将允许长时间无故障运行根据最大系统生产力的要求。在此通过考虑说明性示例来描述和获得系统性能指标和优化的设计参数。

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