RT-DAP: A Real-Time Data Analytics Platform for Large-Scale Industrial Process Monitoring and Control
RT-DAP: A Real-Time Data Analytics Platform for Large-Scale Industrial Process Monitoring and Control
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DOI：
10.1109/icii.2018.00015
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发表时间：
2018-02
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影响因子：
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通讯作者：
Song Han;Tao Gong;M. Nixon;Eric Rotvold;K. Lam;K. Ramamritham
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文献类型：
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作者：
Song Han;Tao Gong;M. Nixon;Eric Rotvold;K. Lam;K. Ramamritham
在当今的大多数过程控制系统中，过程测量被周期性地收集并存档在历史记录器中。分析应用程序处理数据，并离线或在与许多制造过程的性能相比相当慢的时间段内提供结果。沿着物联网（IoT）的普及和过程工业中“普适传感器”技术的引入，过程工厂中安装了越来越多的传感器和执行器来进行普适传感和控制，产生的过程数据量呈指数级增长。为了消化这些数据并满足不断增长的提高生产效率和提高产品质量的要求，需要一种方法来提高分析系统的性能并扩展系统以密切监控更大的工厂资源。在本文中，我们提出了一个实时数据分析平台，称为RT-DAP，以支持大规模的连续数据分析过程工业。RT-DAP旨在能够流式传输、存储、处理和可视化从异构工厂资源收集的大量实时数据流，并以实时方式反馈给控制系统和操作员。该平台的原型在Microsoft Azure上实现。我们广泛的实验验证了RT-DAP的设计方法，并证明其效率在组件和系统级别。
In most process control systems nowadays, process measurements are periodically collected and archived in historians. Analytics applications process the data, and provide results offline or in a time period that is considerably slow in comparison to the performance of many manufacturing processes. Along with the proliferation of Internet-of-Things (IoT) and the introduction of "pervasive sensors" technology in process industries, increasing number of sensors and actuators are installed in process plants for pervasive sensing and control, and the volume of produced process data is growing exponentially. To digest these data and meet the ever-growing requirements to increase production efficiency and improve product quality, there needs a way to both improve the performance of the analytic system and scale the system to closely monitor a much larger set of plant resources. In this paper, we present a real-time data analytics platform, referred to as RT-DAP, to support large-scale continuous data analytics in process industries. RT-DAP is designed to be able to stream, store, process and visualize a large volume of real-time data flows collected from heterogeneous plant resources, and feedback to the control system and operators in a real-time manner. A prototype of the platform is implemented on Microsoft Azure. Our extensive experiments validate the design methodologies of RT-DAP and demonstrate its efficiency in both component and system levels.