Abstract
Often underestimated, (semi-)structured textual data sources are an important cornerstone in the manufacturing sector for product and process quality tracking. The ELG pilot project SLAPMAN develops novel methods for industrial text analytics in the form of scalable, reusable, and potentially stateful microservices, which can be easily orchestrated by domain experts in order to define quality anomaly patterns, e. g., by analysing machine states and error logs. The results are fully available as open source and integrated into the IIoT toolbox Apache StreamPipes.
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Wiener, P., Thoma, S. (2023). Streaming Language Processing in Manufacturing. In: Rehm, G. (eds) European Language Grid. Cognitive Technologies. Springer, Cham. https://doi.org/10.1007/978-3-031-17258-8_26
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DOI: https://doi.org/10.1007/978-3-031-17258-8_26
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Publisher Name: Springer, Cham
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Online ISBN: 978-3-031-17258-8
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