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Reliability, Availability and Maintainability Analysis of Industrial Systems Using PSO and Fuzzy Methodology

机译:基于PSO和模糊方法的工业系统可靠性,可用性和可维护性分析

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The purpose of this paper is to present a methodology for analyzing the system performance of an industrial system by utilizing uncertain data. Although there have been tremendous advances in the art and science of system evaluation, yet it is very difficult to assess their performance with a very high accuracy or precision. For handling of these uncertainties, fuzzy set theory has been used in the analysis while their corresponding membership functions are generated by solving a nonlinear optimization problem with particle swarm optimization. For finding the critical component of the system which affects the system performance mostly, a composite measure of reliability, availability and maintainability (RAM) named as the RAM-index has been introduced which influences the effects of failure and repair rate parameters on its performance. A time varying failure and repair rate parameters are used in the analysis instead of constant rate models. Finally, the computed results are finally compared with existing methodologies. The suggested framework has been illustrated with the help of a case.
机译:本文的目的是提出一种利用不确定数据分析工业系统的系统性能的方法。尽管在系统评估的艺术和科学方面已取得了巨大的进步,但是很难以很高的准确性或精度来评估它们的性能。为了处理这些不确定性,在分析中使用了模糊集理论,同时通过使用粒子群算法解决非线性优化问题来生成它们的相应隶属函数。为了找到对系统性能影响最大的关键组件,已引入了可靠性,可用性和可维护性(RAM)的综合度量,称为RAM-index,它会影响故障和修复率参数对其性能的影响。分析中使用时变故障和修复率参数,而不是恒定速率模型。最后,将计算结果最终与现有方法进行比较。借助案例说明了建议的框架。

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