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An industrial analytics approach to predictive maintenance for machinery applications

机译:机械应用预测维护的工业分析方法

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A key challenge in nowadays machinery applications is to guaranty availability and to increase productivity while reducing production costs. Companies, which are able to use their produced data (e.g., process values) to overcome this challenge, will have a significant competitive advantage. This paper shows how data-analytics approaches can be used to realize predictive maintenance solutions, taking advantage of already existing data of production facilities, and reducing the realization effort. The main advantages of data-analytic approaches are explained by means of two industrial applications.
机译:当今机械应用中的一个关键挑战是保证可用性并提高生产率,同时降低生产成本。公司能够使用其产生的数据(例如,过程值)来克服这一挑战,将具有显着的竞争优势。本文展示了数据分析方法如何用于实现预测性维护解决方案,利用现有的生产设施数据,并降低实现努力。数据分析方法的主要优点是通过两个工业应用解释。

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