Abstract: A device (DS) monitors a process using at least one electronic device (EE1-EE4) in operation and generating first data of a metric. This device (DS) comprises: learning means (MA) configured to analyse automatically second data which are representative of events that have occurred in the course of the process, in order to determine anomalies of a chosen type, and then automatically determine an indicator representative of this metric, then a correlation between these determined anomalies and this indicator, and then at least one rule defining this correlation, and monitoring means (MS1) configured to analyse newly generated first data periodically, and group by group, by checking whether at least one value of the indicator determined on the basis of the aforesaid data satisfies this determined rule, in order to predict the occurrence of the anomaly in a future group of first data when this at least one value satisfies this rule.

Abstract: A device (DS) monitors a process using at least one electronic device (EE1-EE4) in operation and generating first data of a metric. This device (DS) comprises: learning means (MA) configured to analyse automatically second data which are representative of events that have occurred in the course of the process, in order to determine anomalies of a chosen type, and then automatically determine an indicator representative of this metric, then a correlation between these determined anomalies and this indicator, and then at least one rule defining this correlation, and monitoring means (MS1) configured to analyse newly generated first data periodically, and group by group, by checking whether at least one value of the indicator determined on the basis of the aforesaid data satisfies this determined rule, in order to predict the occurrence of the anomaly in a future group of first data when this at least one value satisfies this rule.