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The CONTEXT Dataset containing Contextual Faults of a Smart Factory

Authors: Lukas Kaupp; Heiko Webert; Kawa Nazemi; Bernhard Humm; Stephan Simons;

The CONTEXT Dataset containing Contextual Faults of a Smart Factory

Abstract

Here you download the CONTEXT Dataset containing Contextual Faults of a Smart Factory. Our work as part of the Proceedings of the International Conference on Industry 4.0 and Smart Manufacturing is now published in Procedia Computer Science (Elsevier). If you refer to or use this dataset, cite this publication: Kaupp, Lukas; Webert, Heiko; Nazemi, Kawa; Humm, Bernhard; Simons, Stephan (2021): CONTEXT: An Industry 4.0 Dataset of Contextual Faults in a Smart Factory. In: Procedia Computer Science 180, S. 492–501. DOI: 10.1016/j.procs.2021.01.265. The dataset contains contextual faults recorded in the smart factory of the Darmstadt University of Applied Sciences. Each recording (CSV format) consists of an OPC-UA log file and log files of the corresponding machinery measured by our developed sensing units. Foldernames reflect experiment structure. <date>-<run>_<count of build relays>_<g(ood/ok)/n(ot/failure)>_<experiment name> You can find a detailed description of the experiments in our publication. Description Update for a better data assessment. OPC-UA Hierarchy - Factory Mapping: 'Station10' - Management Station (send production instructions / receive production updates)[not physically involved in the production process] 'Station 40 - Hochregallager' - High-Bay Storage Station 'Station 50 - Roboter' - Robot Station 'Station 60 - Presse' - Press Station 'St20 SoftSPS' - Optical & Weight Inspection Station 'Station30elPruefung' - Electrical Inspection Station

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Keywords

CONTEXT, smart factory, dataset, contextual faults, cyber-physical system

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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