Data Acquisition and Preparation – Enabling Data Analytics Projects within Production

The increasing amount of available data in production systems is associated with great potential for process optimization. Due to lack of a data analytics methodology and low data quality within production these potentials often remain unused. Therefore, in this paper we present a model for data acquisition and data preparation including feature engineering for characteristic sensor signals of production machines. The model allows the extraction of relevant process information from the signal, which can be used for monitoring, KPI tracking, trend analysis and anomaly detection. The approach is evaluated on an industrial turning process.