Anomaly Detection for Industry 4.0 Sensor Data

JournalIndustrie 4.0 Management
Issue Volume 33, 2017, Edition 4, Pages 53-56
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Abstract

In the BMBF-funded project “Provenance Analytics” research groups at the Bauhaus-Universität Weimar and the Hochschule Ostwestfalen-Lippe develop approaches for detecting anomalies in sensor data. In this short survey, we review the main methods for predicting failures in the production processes of manufacturing machines and give a brief overview of the activities planned in the project.

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