The IoT platform collects production data either from MES systems or PLCs/SCADA when MES is not deployed, energy data, WH data, etc. to identify previously undetectable high-value added correlations.

The edge component of the IoT platform is deployed on premise to normalize and aggregate data before feeding the cloud. Furthermore, statistical process control and analytics are performed on premise for a more closed loop (fog computing) within the factory.

Advanced calculations and machine learning are available on cloud.

Number of produced pieces, OEE, etc. are used to forecast energy consumption curves. These are evaluated with respect to the actual real-time energy consumes coming from different sources (lighting, heating, cooling, etc.). This assures to early detect eventual reasons why the consumes are higher than foreseen. 

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