In the Industry 4.0 context, especially when considering large factories producing costly goods, monitoring sensor values is important to ensure high quality. This reduces large costs for mending faulty products or re...
详细信息
ISBN:
(数字)9781728168234
ISBN:
(纸本)9781728168234
In the Industry 4.0 context, especially when considering large factories producing costly goods, monitoring sensor values is important to ensure high quality. This reduces large costs for mending faulty products or recall of those. Different approaches are used to ensure efficient monitoring and validation of sensor values. The distributed data validation network (DDVN) can remove single points of failure. Still, not every anomaly in the validation procedure means that errors or attacks have occurred. Oilier reasons like maintenance procedures, updates of firmware, or changed materials can lead to False-Positive (FP) or False-Negative (FN) detection of errors. To reduce these, we incorporate context information in the validation procedure. Further, we show how the appropriate context information is selected and used on a real machine data set.
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