A computer-implemented method for determining an operational state of an industrial plant includes acquiring alarms raised within the plant and adding them to a pool of important alarms, determining whether a physical state of the plant indicated by a first alarm causes a second alarm or meets a predetermined state-dependent condition and, if so, moving the first alarm to a pool of informative alarms; and determining the operational state of the plant and/or a corrective action for improving this operational state based on the alarms in the pool of important alarms.

Various systems and methods for modeling a manufacturing assembly line are disclosed herein. Some embodiments relate to operating a processor to receive cell data and line production data, determine one or more production associations between the cell data and the line production data; evaluate the one or more production associations to identify one or more critical production associations; retrieve the cell data and the line production data associated with the one or more critical production associations; and train a predictive model with the retrieved cell data and the retrieved line production data to predict the production level of the manufacturing assembly line.

Various systems and methods for modeling a manufacturing assembly line are disclosed herein. Some embodiments relate to operating a processor to receive cell data, extract feature data from the cell data, determine a plurality of cell configurations, determine an efficiency score by applying the feature data to a predictive model generated for predicting a production level of the manufacturing assembly line, determine at least one target cell configuration from the cell configurations based on the efficiency score, and apply the at least one target cell configuration to at least one cell by implementing each target cell configuration to a corresponding cell.

A method of classifying machine alarms produced by a machine monitoring system may include: Collecting a plurality of machine alarms from the machine monitoring system, the machine alarms being indicative of out-of-range machine system parameters; collecting a plurality of alarm annotations associated with at least some of the machine alarms; grouping the plurality of machine alarms by criticality; determining a strength of alarm annotations; and developing an alarm classification policy for machine alarms based at least on the criticality of the alarms and the strength of the alarm annotations.

A monitoring system for an industrial operation having one or more machines, the monitoring system operates to obtain operational information comprising performance operating parameters and uses the operational information to create an operational baseline and reference thresholds and monitors real-time operational data to determine if an operating parameter exceeds a reference threshold.

Various systems and methods for modeling a manufacturing assembly line are disclosed herein. Some embodiments relate to operating a processor to receive cell data and line production data, determine one or more production associations between the cell data and the line production data; evaluate the one or more production associations to identify one or more critical production associations; retrieve the cell data and the line production data associated with the one or more critical production associations; and train a predictive model with the retrieved cell data and the retrieved line production data to predict the production level of the manufacturing assembly line.

Various systems and methods for modeling a manufacturing assembly line are disclosed herein. Some embodiments relate to operating a processor to receive cell data, extract feature data from the cell data, determine a plurality of faults, determine a priority level for each fault by applying the extracted feature data to a predictive model, determine at least one high priority fault, and generate at least one operator alert based on the at least one high priority fault.

Various systems and methods for modeling a manufacturing assembly line are disclosed herein. Some embodiments relate to operating a processor to receive cell data, extract feature data from the cell data, determine a plurality of cell configurations, determine an efficiency score by applying the feature data to a predictive model generated for predicting a production level of the manufacturing assembly line, determine at least one target cell configuration from the cell configurations based on the efficiency score, and apply the at least one target cell configuration to at least one cell by implementing each target cell configuration to a corresponding cell.

Various systems and methods for modeling a manufacturing assembly line are disclosed herein. Some embodiments relate to operating a processor to receive cell data and line production data, determine one or more production associations between the cell data and the line production data; evaluate the one or more production associations to identify one or more critical production associations; retrieve the cell data and the line production data associated with the one or more critical production associations; and train a predictive model with the retrieved cell data and the retrieved line production data to predict the production level of the manufacturing assembly line.

A monitoring system for an industrial operation having one or more machines, the monitoring system operates to obtain operational information comprising performance operating parameters and uses the operational information to create an operational baseline and reference thresholds and monitors real-time operational data to determine if an operating parameter exceeds a reference threshold.