A computer system for monitoring the technical status of an industrial process system being under control of an advanced process controller, the industrial process system having an operation part for processing flow materials, the advanced process controller being responsive to one or more sensor signals, the computer system comprising: an interface module configured to receive technical status data describing the current technical state of the industrial process system with regards to a respective processing component or the processed material wherein the technical status data corresponds to or is derived from the one or more sensor signals, and to output an anomaly alert configured to enable deactivating of the advanced process controller in case of an anomaly detection for the industrial process system; characterized in that the computer system further comprises an anomaly detection module configured to apply a plurality of Machine Learning Models (MLMn) to the received technical status data to analyze the technical status data for detecting one or more indicators of an abnormal technical status prevailing in the industrial process system wherein the plurality of Machine Learning Models (MLMn) are trained on historic raw or pre-processed sensor data, the anomaly detection module further configured to generate the anomaly alert based on the one or more indicators; wherein the received technical status data is assigned to signal groups (SG1 to SG3) and the generated anomaly alert is a vector (AAv) with each vector element (AA1 to AA3) representing a group anomaly indicator for the respective signal group wherein each vector element is determined by applying a respective group specific Machine Learning Model (MLM1 to MLM3), and wherein signal groups are defined by any one of the following grouping criteria: grouping based on physical location of the respective signals within the industrial process system, grouping of correlated signals identified by correlation analysis, grouping of signals with dependencies as a result of domain knowledge. an interface module configured to receive technical status data describing the current technical state of the industrial process system with regards to a respective processing component or the processed material wherein the technical status data corresponds to or is derived from the one or more sensor signals, and to output an anomaly alert configured to enable deactivating of the advanced process controller in case of an anomaly detection for the industrial process system; to receive technical status data describing the current technical state of the industrial process system with regards to a respective processing component or the processed material wherein the technical status data corresponds to or is derived from the one or more sensor signals, and to output an anomaly alert configured to enable deactivating of the advanced process controller in case of an anomaly detection for the industrial process system; characterized in that the computer system further comprises an anomaly detection module configured to apply a plurality of Machine Learning Models (MLMn) to the received technical status data to analyze the technical status data for detecting one or more indicators of an abnormal technical status prevailing in the industrial process system wherein the plurality of Machine Learning Models (MLMn) are trained on historic raw or pre-processed sensor data, the anomaly detection module further configured to generate the anomaly alert based on the one or more indicators; wherein the received technical status data is assigned to signal groups (SG1 to SG3) and the generated anomaly alert is a vector (AAv) with each vector element (AA1 to AA3) representing a group anomaly indicator for the respective signal group wherein each vector element is determined by applying a respective group specific Machine Learning Model (MLM1 to MLM3), and wherein signal groups are defined by any one of the following grouping criteria: grouping based on physical location of the respective signals within the industrial process system, grouping of correlated signals identified by correlation analysis, grouping of signals with dependencies as a result of domain knowledge.