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Human Reliability Analysis Technique Selection for Life Support Systems Maintenance of Orbital Space Stations Using Fuzzy AHP and ANN

机译:使用模糊AHP和ANN的人力可靠性分析技术选择终身支持系统维护轨道空间站的维护

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A methodology for assessment of a suitable Human Reliability Analysis (HRA) technique for Orbital Space Station (OSS) Environment Control and Life Support System (ECLSS) maintenance considering the ones proposed from other industries is presented. This paper presents a hybrid model using Fuzzy analytic hierarchy process (Fuzzy AHP) and artificial neural networks (ANNs) theory to develop a suitable HRA methodology for OSS ECLSS maintenance. The model consists of two modules: Module 1 applies Fuzzy AHP using pair wise comparison of criteria for existing methods as proposed from other industrial domains. Four criteria that are decided are adequacy, costs, effectiveness and efficacy. The four HRA methodologies that are considered to be evaluated are THERP, CREAM, NARA and SPAR-H. Module 2 utilizes the results of Fuzzy AHP decision matrix into Artificial Neural Network (ANN) model for ranking of all selected HRA methodologies. The results yield the best HRA model for OSS ECLSS maintenance with appropriate scores to compare the performance of each HRA model.
机译:考虑到从其他行业提出的那些,对轨道空间站(OSS)环境控制和终身支持系统(ECLS)维护进行评估的方法的评估方法。本文介绍了使用模糊分析层次处理(模糊AHP)和人工神经网络(ANNS)理论的混合模型,为OSS ECLS维护开发合适的HRA方法。该模型由两个模块组成:模块1使用与其他工业域提出的现有方法的标准的标准进行模糊AHP应用模糊AHP。决定的四个标准是充分性,成本,有效性和功效。被评估的四种HRA方法是THRP,奶油,奈良和翼垫-H。模块2利用模糊AHP决策矩阵的结果,进入人工神经网络(ANN)模型,用于排名所有选定的HRA方法。结果为OSS ECLSS维护提供了最佳的HRA模型,以进行适当的分数来比较每个HRA模型的性能。

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