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Precursors to using energy data as a manufacturing process variable.
| Content Provider | CiteSeerX |
|---|---|
| Author | Brown, Neil Greenough, Rick Vikhorev, Konstantin Uk, Leicester |
| Abstract | 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. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Energy Data Manufacturing Process Variable Available Analysis Technique Front-end Instrumentation Data Stream Analysis Processing Technique Co-dependent Issue Many Sector Near Real Time Data Frequency Artificial Intelligence Basic Time Series Analysis Data Structure Process Health Conventional Energy Data Data Quality Energy Efficiency Fiscal Metering Step Change Off-line Process Control Energy Use Complex Event Processing Half-hourly Time Interval |
| Content Type | Text |
| Resource Type | Article |
