Goals and measures for analyzing power consumption data in manufacturing enterprises

Journal of Data, Information and Management - Tập 3 Số 1 - Trang 65-82 - 2021
Sören Henning1, Wilhelm Hasselbring1, Heinz Burmester2, Armin Möbius3, Maik Wojcieszak4
1Software Engineering Group, Kiel University, 24098, Kiel, Germany
2Kieler Zeitung GmbH, Co. Offsetdruck KG, Radewisch 2, 24145, Kiel, Germany
3IBAK Helmut Hunger GmbH, Co. KG, Wehdenweg 122, 24148, Kiel, Germany
4wobe-systems GmbH, Edisonstraße 3, 24145, Kiel, Germany

Tóm tắt

AbstractThe Internet of Things adoption in the manufacturing industry allows enterprises to monitor their electrical power consumption in real time and at machine level. In this paper, we follow up on such emerging opportunities for data acquisition and show that analyzing power consumption in manufacturing enterprises can serve a variety of purposes. In two industrial pilot cases, we discuss how analyzing power consumption data can serve the goals reporting, optimization, fault detection, and predictive maintenance. Accompanied by a literature review, we propose to implement the measures real-time data processing, multi-level monitoring, temporal aggregation, correlation, anomaly detection, forecasting, visualization, and alerting in software to tackle these goals. In a pilot implementation of a power consumption analytics platform, we show how our proposed measures can be implemented with a microservice-based architecture, stream processing techniques, and the fog computing paradigm. We provide the implementations as open source as well as a public show case allowing to reproduce and extend our research.

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