制造系统的数据分析

A. Vodencarevic, T. Fett
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引用次数: 3

摘要

数据分析在构建智能系统中发挥着关键作用之一,它将自动化提升到安全、可靠性和效率的新水平,同时降低了用户感知的复杂性。在本文中,我们提出了数据分析在制造业中的目标,并举例说明了我们在Reifenhäuser REICOFIL GmbH & Co. KG成功工作的几个应用场景。其中包括使用虚拟传感器的过程监控和异常检测、根本原因分析、工厂模拟和优化、评估产品质量标准之间的权衡以及从数据中提取知识。此外,我们列出了数据分析在制造环境中通常面临的一些挑战,并通过几个具体示例进行了演示。
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Data analytics for manufacturing systems
Data analytics plays one of the key roles in building intelligent systems, which bring automation to the new level of safety, reliability and efficiency, at the same time lowering the perceived complexity for the user. In this paper, we present the goals of data analytics in manufacturing and illustrate several application scenarios we have successfully worked on at Reifenhäuser REICOFIL GmbH & Co. KG. These include process monitoring and anomaly detection using virtual sensors, root cause analysis, plant simulation and optimization, assessing trade-offs between product quality criteria and extracting knowledge from data. Furthermore, we list a number of challenges that data analytics typically faces in manufacturing environments, demonstrating them on several concrete examples.
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