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Precursors to using energy data as a manufacturing process variable

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4 Author(s)
Neil Brown ; Institute of Energy and Sustainable Development, DeMontfort University, Leicester, UK ; Rick Greenough ; Konstantin Vikhorev ; Sanober Khattak

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.

Published in:

2012 6th IEEE International Conference on Digital Ecosystems and Technologies (DEST)

Date of Conference:

18-20 June 2012