Data quality issues for vibration sensors: a case study in ferrosilicon production

Waszak, Maryna; Moen, Terje; Eidnes, Sølve; Stasik, Alexander Johannes; Hansen, Anders; Bouquet, Gregory; Pultier, Antoine; Ma, Xiang; Tørlen, Idar; Henriksen, Bjørn; Aamodt, Arianeh; Roman, Dumitru
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https://hdl.handle.net/11250/3041386
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2022
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Proceedings of the 2nd International Workshop on Software Engineering and AI for Data Quality in Cyber-Physical Systems/Internet of Things (SEA4DQ 2022). 2022, 22-23.   10.1145/3549037.3561273
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Digitisation in the mining and metal processing industries plays a key role in their modernisation. Production processes are more and more supported by a variety of sensors that produce large amounts of data that meant to provide insights into the performance of production infrastructures. In the metal processing industry vibration sensors are essential in the monitoring of the production infrastructure. In this position paper we present the installation of vibration sensors in a real industrial environment and discuss the data quality issues we encountered while using such sensors.
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Association for Computing Machinery (ACM)
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