Abstract: A system processes historical facility data that relate to facility states and modes of operation. The historical facility data are clustered into groups representing the facility states and the modes of operation. The groups are used to determine a current state and mode of the facility. When the facility is in a normal state, the system determines whether an event in the facility is an abnormality. If an abnormality is identified, the system transmits a signal indicating the abnormality.

Abstract: Embodiments of the present disclosure provide for asset lifetime monitoring. Estimated values for factors representing root causes of operational anomalies of an asset may be generated utilizing one or more models. Estimated remaining lifetime values for one or more root cause variables may be generated that indicate a time until the value for a root cause variable is estimated to reach a particular limit threshold corresponding to the root cause variable, and/or an estimated second remaining lifetime value for an asset health index representing a combination of one or more root cause variables. The second remaining lifetime value for the asset health index may be provided to enable processing of the second remaining lifetime value as the remaining useful lifetime of the asset based on overall root cause variables.

Abstract: A trained machine learning algorithm processes time series production data. The time series production data are representative of a control process within a facility control loop. The machine learning training algorithm is trained using positive training data that are representative of a normal operation of components within the facility control loop and negative training data that are representative of an abnormal operation of components within the facility control loop. Output of the trained machine learning algorithm identifies abnormalities in the facility control loop.

Abstract: A system processes historical facility data that relate to facility states and modes of operation. The historical facility data are clustered into groups representing the facility states and the modes of operation. The groups are used to determine a current state and mode of the facility. When the facility is in a normal state, the system determines whether an event in the facility is an abnormality. If an abnormality is identified, the system transmits a signal indicating the abnormality.

Abstract: A system processes historical facility data that relate to facility states and modes of operation. The historical facility data are clustered into groups representing the facility states and the modes of operation. The groups are used to determine a current state and mode of the facility. When the facility is in a normal state, the system determines whether an event in the facility is an abnormality. If an abnormality is identified, the system transmits a signal indicating the abnormality.

Abstract: A method of alarm notification includes providing data for an industrial process including stored alarm event data and stored Key Performance Indicator (KPI) data, and an alarm event-KPI correlation and operator notification system. Patterns of relationships are discovered between the stored alarm event and KPI data to provide a reference pattern database that identifies KPI violation events in the KPI data as a function of the alarm event data or alarm events in the alarm event data as a function of the KPI data. Pattern matching uses a real-time alarm event and real-time KPI data to determine a pattern similarity by comparing a current sequence spanning a predetermined time of the real-time alarm event and KPI data to the patterns. When the pattern matching identifies a current alarm event or KPI violation event, an operator is notified and a predicted KPI value or feature or a predicted alarm event.

Abstract: An apparatus, method, and non-transitory machine-readable medium provide for accurate automatic determination of alarm-operator action linkage for operator assessment and alarm guidance using custom graphics and control charts. The apparatus includes a memory and a processor operably connected to the memory. The processor receives process control system data regarding a field device in an industrial process control and automation system; extracts information from the process control system data; generates a tuple based on the extracted information; and performs a rectifying operation in the industrial process control and automation system based on the generated tuple of the field device.

Abstract: A method includes receiving one or more operating conditions from one or more field devices of one or more industrial plants in response to receiving one or more alarm signals. The method also includes determining one or more industrial plant states based on the one or more operating conditions. The method further includes identifying one or more historical alarm episodes stored in one or more data stores based on the one or more industrial plant states. In addition, the method includes identifying one or more recommended historical alarm episodes of the one or more historical alarm episodes based on one or more benchmark metrics of the one or more historical alarm episodes. The method also includes generating the one or more recommended historical alarm episodes for display on a user interface.

Abstract: A method includes identifying changes in an alarm count for at least one alarm to be generated in an industrial process control and automation system. The changes in the alarm count are based on a plurality of different sets of alarm settings. The method also includes presenting the changes in the alarm count to a user and receiving a selection of one of the sets of alarm settings. The method further includes configuring the industrial process control and automation system with the selected set of alarm settings to enable the industrial process control and automation system to generate alarms using the selected set of alarm settings.

Abstract: An apparatus, method, and non-transitory machine-readable medium provide for accurate automatic determination of alarm-operator action linkage for operator assessment and alarm guidance using custom graphics and control charts. The apparatus includes a memory and a processor operably connected to the memory. The processor receives process control system data regarding a field device in an industrial process control and automation system; extracts information from the process control system data; generates a tuple based on the extracted information; and performs a rectifying operation in the industrial process control and automation system based on the generated tuple of the field device.

Abstract: A method, an electronic device and computer readable medium is provided. The method includes information associated with operational changes by personnel that operate an industrial plant. The method also includes identifying episodes of the operational changes, wherein each episode includes a triggering event and operational changes. The method also includes generating a causal pairing matrix that categorizes the identified episodes into a plurality of groupings, based on the triggering event of each of the at least two episodes being similar. The method further includes analyzing the at least two episodes to identify one of the at least two episodes as a bench mark episode, within each group. The method also includes comparing each of the at least two episodes to the identified bench mark episode to rank the at least two episodes, within each of the groups. The method further includes generating a report for the plurality of groupings.

Abstract: A method of alarm notification includes providing data for an industrial process including stored alarm event data and stored Key Performance Indicator (KPI) data, and an alarm event-KPI correlation and operator notification system. Patterns of relationships are discovered between the stored alarm event and KPI data to provide a reference pattern database that identifies KPI violation events in the KPI data as a function of the alarm event data or alarm events in the alarm event data as a function of the KPI data. Pattern matching uses a real-time alarm event and real-time KPI data to determine a pattern similarity by comparing a current sequence spanning a predetermined time of the real-time alarm event and KPI data to the patterns. When the pattern matching identifies a current alarm event or KPI violation event, an operator is notified and a predicted KPI value or feature or a predicted alarm event.

Abstract: A method includes identifying changes in an alarm count for at least one alarm to be generated in an industrial process control and automation system. The changes in the alarm count are based on a plurality of different sets of alarm settings. The method also includes presenting the changes in the alarm count to a user and receiving a selection of one of the sets of alarm settings. The method further includes configuring the industrial process control and automation system with the selected set of alarm settings to enable the industrial process control and automation system to generate alarms using the selected set of alarm settings.

Abstract: A system and method for calibrating a set-point for climate control includes a sensor network having a plurality of sensors configured to report a climate condition. A database is configured to receive reports from the sensors and generate one or more profiles reflecting at least one of historic climate control information and occupant preferences. A controller is configured to receive information from the profiles to generate a set-point based upon an optimization program. The optimization program is implemented to balance competing goals to generate the set-point for controlling climate control equipment in accordance with the set-point.

Abstract: A controller for controlling thermal sources affecting an air temperature in a space subjected to thermal variables, including a sensor network measuring the thermal variables; a feed forward controller generating a feed forward control signal based on an adaptive model including a model of the space and a model of the thermal sources, wherein the models are formed utilizing data from the sensor network; a feedback controller generating a feedback control signal based on a difference between an output of the feed forward controller and output from the space; and a combiner combining the feed forward and feedback control signals to produce a control signal for controlling the thermal sources to control the air temperatures of the space.

Abstract: A controller for controlling thermal sources affecting an air temperature in a space subjected to thermal variables, including a sensor network measuring the thermal variables; a feed forward controller generating a feed forward control signal based on an adaptive model including a model of the space and a model of the thermal sources, wherein the models are formed utilizing data from the sensor network; a feedback controller generating a feedback control signal based on a difference between an output of the feed forward controller and output from the space; and a combiner combining the feed forward and feedback control signals to produce a control signal for controlling the thermal sources to control the air temperatures of the space.