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Fuzzy RAM Analysis of the Screening Unit in a Paper Industry by Utilizing Uncertain Data

机译:利用不确定数据对造纸行业筛选装置进行模糊RAM分析

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Reliability, availability, and maintainability (RAM) analysis has helped to identify the critical and sensitive subsystems in the production systems that have a major effect on system performance. But the collected or available data, reflecting the system failure and repair patterns, are vague, uncertain, and imprecise due to various practical constraints. Under these circumstances it is difficult, if not possible, to analyze the system performance up to desired degree of accuracy. For this, Artificial Bee Colony based Lambda-Tau (ABCBLT) technique has been used for computing the RAM parameters by utilizing uncertain data up to a desired degree of accuracy. Results obtained are compared with the existing Fuzzy Lambda-Tau results and we conclude that proposed results have a less range of uncertainties. Also ranking the subcomponents for improving the performance of the system has been done using RAM-Index. The approach has been illustrated through analyzing the performance of the screening unit of a paper industry.
机译:可靠性,可用性和可维护性(RAM)分析有助于确定生产系统中对系统性能有重要影响的关键和敏感子系统。但是由于各种实际限制,反映系统故障和维修模式的收集或可用数据是模糊,不确定和不精确的。在这种情况下,很难(如果不可能)分析系统性能达到所需的准确度。为此,基于人工蜂群的Lambda-Tau(ABCBLT)技术已被用于通过利用不确定数据达到期望的准确度来计算RAM参数。将获得的结果与现有的模糊Lambda-Tau结果进行比较,我们得出的结论是,拟议的结果具有较小的不确定性范围。还使用RAM-Index完成了用于改进系统性能的子组件排名。通过分析造纸行业筛选装置的性能已说明了该方法。

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    Department of Mathematics, Indian Institute of Technology, Roorkee 247667, Uttarakhand, India;

    Department of Mathematics, Indian Institute of Technology, Roorkee 247667, Uttarakhand, India;

    Department of Mathematics, Indian Institute of Technology, Roorkee 247667, Uttarakhand, India;

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