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首页> 外文会议>Digital Ecosystems Technologies (DEST), 2012 6th IEEE International Conference on >Precursors to using energy data as a manufacturing process variable
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Precursors to using energy data as a manufacturing process variable

机译：使用能源数据作为制造过程变量的先驱

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摘要

Energy efficiency can often learn much from manufacturing in terms of available analysis techniques, from basic time series analysis through to fuzzy and knowledge based systems and artificial intelligence. On the other hand, manufacturing in many sectors has yet to make use of energy data much beyond finance. Techniques such as complex event processing and data stream analysis can be applied in near real time to determine process health. Conventional energy data, with a half-hourly time interval through fiscal metering, has been sufficient for off-line process control in the past, but to increase the utility of manufacturing energy data, a step change is needed in data frequency, accuracy, precision, portability, and documentation. This paper brings together co-dependent issues of data structure, data quality, and front-end instrumentation which advanced processing techniques must build on, discussing what must be done to use gather and use energy data more effectively, to reduce energy use and emissions, improve quality, and save costs.
机译：从基本的时间序列分析到基于模糊和知识的系统以及人工智能，能源效率通常可以从制造中学到很多可用的分析技术。另一方面，许多行业的制造业尚未充分利用能源数据，而不仅仅是金融领域。诸如复杂事件处理和数据流分析之类的技术可以近乎实时地应用于确定过程的运行状况。过去，通过电量计量的半小时时间间隔的常规能源数据已经足以用于离线过程控制，但是要增加制造能源数据的效用，就需要在数据频率，准确性，精度上进行逐步更改。 ，可移植性和文档。本文汇集了必须依赖高级处理技术的数据结构，数据质量和前端仪器等相互依存的问题，讨论了为更有效地收集和使用能源数据以减少能源使用和排放所必须采取的措施，提高质量，节省成本。

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