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Towards data mining based decision support in manufacturing maintenance

机译:寻求制造维护中基于数据挖掘的决策支持

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The current work presents a decision support system architecture for evaluating the features representing the health status to predict maintenance actions and remaning useful life of component. The evaluation is possible through pattern analysis of past and current measurements of the focused research components. Data mining visualization tools help in creating the most suitable patterns and learning insights from them. Estimations like features split values or measurement frequency of the component is achieved through classification methods in data mining. This paper presents how the quantitative results generated from data mining can be used to support decision making of domain experts.
机译:当前的工作提出了一种决策支持系统架构,用于评估代表健康状态的功能,以预测维护措施并保留部件的使用寿命。通过对重点研究内容的过去和当前测量值进行模式分析,可以进行评估。数据挖掘可视化工具可帮助创建最合适的模式并从中学习见解。像特征分割值或组件的测量频率这样的估计是通过数据挖掘中的分类方法来实现的。本文介绍了如何将数据挖掘产生的定量结果用于支持领域专家的决策。

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