Abstract: A method includes obtaining data identifying values of one or more process variables associated with an industrial process controller and identifying one or more constraint violations using the data. The method also includes, for each identified constraint violation, analyzing a behavior of the controller, a behavior of an industrial process being controlled, and how the controller was being used by at least one operator for a period of time. At least part of the period of time is prior to the identified constraint violation. The method further includes generating a graphical display based on the analysis, where the graphical display identifies one or more probable causes for at least one of the one or more constraint violations.

Abstract: A method includes obtaining data associated with operation of an industrial process controller and identifying impacts of operational problems of the industrial process controller. The method also includes generating a graphical display for a user, where the graphical display presents one or more recommended actions to reduce or eliminate at least one of the impacts of at least one of the operational problems. The method further includes triggering at least one of the one or more recommended actions based on input from the user. The method could also include executing one or more analytic algorithms to process the obtained data and identify the operational problems of the industrial process controller. Each of the one or more analytic algorithms could be instantiated as a container, and multiple containers could be instantiated and executed as needed. Results of executing the one or more analytic algorithms could be transformed into a standard format.

Abstract: A method includes obtaining data associated with operation of a model-based industrial process controller. The method also includes identifying at least one estimated impact of at least one operational problem of the industrial process controller, where each estimated impact is expressed in terms of a lost opportunity associated with operation of the industrial process controller. The method further includes presenting the at least one estimated impact to a user. The at least one estimated impact could include impacts associated with noise or variance in process variables used by the industrial process controller, misconfiguration of an optimizer in the industrial process controller, one or more limits on one or more process variables, a quality of at least one model used by the industrial process controller, a quality of one or more inferred properties used by the industrial process controller, or one or more process variables being dropped from use by the industrial process controller.

Abstract: A method includes identifying one or more proxy limit variables to be used to define an operating envelope associated with an industrial process controller. The industrial process controller is associated with a number of process variables including the proxy limit variable(s). The method also includes maximizing and minimizing at least one of the proxy limit variable(s). The method further includes presenting maximum and minimum values of the at least one of the proxy limit variable(s) as the operating envelope in a graphical user interface to at least one user. A single proxy limit variable could be used, and maximum and minimum values of the single proxy limit variable can be presented in a one-dimensional representation of the operating envelope. Multiple proxy limit variables could also be used, and maximum and minimum values of the proxy limit variables can be presented in a multi-dimensional representation of the operating envelope.

Abstract: A method includes obtaining data associated with operation of a model-based industrial process controller. The method also includes identifying at least one estimated impact of at least one operational problem of the industrial process controller, where each estimated impact is expressed in terms of a lost opportunity associated with operation of the industrial process controller. The method further includes presenting the at least one estimated impact to a user. The at least one estimated impact could include impacts associated with noise or variance in process variables used by the industrial process controller, misconfiguration of an optimizer in the industrial process controller, one or more limits on one or more process variables, a quality of at least one model used by the industrial process controller, a quality of one or more inferred properties used by the industrial process controller, or one or more process variables being dropped from use by the industrial process controller.

Abstract: A method includes obtaining data associated with operation of an industrial process controller and identifying impacts of operational problems of the industrial process controller. The method also includes generating a graphical display for a user, where the graphical display presents one or more recommended actions to reduce or eliminate at least one of the impacts of at least one of the operational problems. The method further includes triggering at least one of the one or more recommended actions based on input from the user. The method could also include executing one or more analytic algorithms to process the obtained data and identify the operational problems of the industrial process controller. Each of the one or more analytic algorithms could be instantiated as a container, and multiple containers could be instantiated and executed as needed. Results of executing the one or more analytic algorithms could be transformed into a standard format.

Abstract: A method includes obtaining data identifying values of one or more controlled variables associated with an industrial process controller. The method also includes identifying periods when at least one of the one or more controlled variables has been moved to an associated limit by the controller. The method further includes, for each identified period, (i) identifying a standard deviation of predicted values for the associated controlled variable and (ii) determining a control giveaway value for the associated controlled variable based on the standard deviation. The control giveaway value is associated with an offset between the associated controlled variable's average value and the associated limit. In addition, the method includes identifying variances in the one or more controlled variables using the control giveaway values and generating a graphical display identifying one or more impacts or causes for at least some of the variances.

Abstract: A method includes obtaining data associated with operation of an industrial process controller and identifying impacts of operational problems of the industrial process controller. The method also includes generating a graphical display for a user, where the graphical display presents one or more recommended actions to reduce or eliminate at least one of the impacts of at least one of the operational problems. The method further includes triggering at least one of the one or more recommended actions based on input from the user. The method could also include executing one or more analytic algorithms to process the obtained data and identify the operational problems of the industrial process controller. Each of the one or more analytic algorithms could be instantiated as a container, and multiple containers could be instantiated and executed as needed. Results of executing the one or more analytic algorithms could be transformed into a standard format.

Abstract: A method includes obtaining data associated with operation of a model-based industrial process controller. The method also includes identifying at least one estimated impact of at least one operational problem of the industrial process controller, where each estimated impact is expressed in terms of a lost opportunity associated with operation of the industrial process controller. The method further includes presenting the at least one estimated impact to a user. The at least one estimated impact could include impacts associated with noise or variance in process variables used by the industrial process controller, misconfiguration of an optimizer in the industrial process controller, one or more limits on one or more process variables, a quality of at least one model used by the industrial process controller, a quality of one or more inferred properties used by the industrial process controller, or one or more process variables being dropped from use by the industrial process controller.

Abstract: A method includes obtaining parameter values for multiple process variables associated with at least one industrial process, where the parameter values for each process variable include low and high limits and a current value. The method also includes presenting a graphical display that includes radial lines each associated with a different one of the process variables, a first graphical indicator passing through the radial lines and identifying the low limits of the process variables, a second graphical indicator passing through the radial lines and identifying the high limits of the process variables, and third graphical indicators identifying the current values of the process variables along the radial lines.

Abstract: A method includes identifying one or more proxy limit variables to be used to define an operating envelope associated with an industrial process controller. The industrial process controller is associated with a number of process variables including the proxy limit variable(s). The method also includes maximizing and minimizing at least one of the proxy limit variable(s). The method further includes presenting maximum and minimum values of the at least one of the proxy limit variable(s) as the operating envelope in a graphical user interface to at least one user. A single proxy limit variable could be used, and maximum and minimum values of the single proxy limit variable can be presented in a one-dimensional representation of the operating envelope. Multiple proxy limit variables could also be used, and maximum and minimum values of the proxy limit variables can be presented in a multi-dimensional representation of the operating envelope.

Abstract: A method includes obtaining parameter values for multiple process variables associated with at least one industrial process, where the parameter values for each process variable include low and high limits and a current value. The method also includes presenting a graphical display that includes radial lines each associated with a different one of the process variables, a first graphical indicator passing through the radial lines and identifying the low limits of the process variables, a second graphical indicator passing through the radial lines and identifying the high limits of the process variables, and third graphical indicators identifying the current values of the process variables along the radial lines.

Abstract: A method includes obtaining data associated with operation of an industrial process controller and identifying impacts of operational problems of the industrial process controller. The method also includes generating a graphical display for a user, where the graphical display presents one or more recommended actions to reduce or eliminate at least one of the impacts of at least one of the operational problems. The method further includes triggering at least one of the one or more recommended actions based on input from the user. The method could also include executing one or more analytic algorithms to process the obtained data and identify the operational problems of the industrial process controller. Each of the one or more analytic algorithms could be instantiated as a container, and multiple containers could be instantiated and executed as needed. Results of executing the one or more analytic algorithms could be transformed into a standard format.

Abstract: A method includes obtaining data associated with operation of a model-based industrial process controller. The method also includes identifying at least one estimated impact of at least one operational problem of the industrial process controller, where each estimated impact is expressed in terms of a lost opportunity associated with operation of the industrial process controller. The method further includes presenting the at least one estimated impact to a user. The at least one estimated impact could include impacts associated with noise or variance in process variables used by the industrial process controller, misconfiguration of an optimizer in the industrial process controller, one or more limits on one or more process variables, a quality of at least one model used by the industrial process controller, a quality of one or more inferred properties used by the industrial process controller, or one or more process variables being dropped from use by the industrial process controller.

Abstract: A method includes obtaining data identifying values of one or more controlled variables associated with an industrial process controller. The method also includes identifying periods when at least one of the one or more controlled variables has been moved to an associated limit by the controller. The method further includes, for each identified period, (i) identifying a standard deviation of predicted values for the associated controlled variable and (ii) determining a control giveaway value for the associated controlled variable based on the standard deviation. The control giveaway value is associated with an offset between the associated controlled variable's average value and the associated limit. In addition, the method includes identifying variances in the one or more controlled variables using the control giveaway values and generating a graphical display identifying one or more impacts or causes for at least some of the variances.

Abstract: A method includes obtaining data identifying values of one or more process variables associated with an industrial process controller and identifying one or more constraint violations using the data. The method also includes, for each identified constraint violation, analyzing a behavior of the controller, a behavior of an industrial process being controlled, and how the controller was being used by at least one operator for a period of time. At least part of the period of time is prior to the identified constraint violation. The method further includes generating a graphical display based on the analysis, where the graphical display identifies one or more probable causes for at least one of the one or more constraint violations.

Abstract: A method includes obtaining historical data associated with an industrial process, which is associated with multiple independent variables. The method also includes automatically excluding at least one portion of the historical data and automatically extracting data segments from at least one non-excluded portion of the historical data. The method further includes iteratively performing model identification using the data segments to identify one or more models and using the model(s) to design, monitor, or tune at least one industrial process controller for the industrial process. Iteratively performing the model identification includes recursively analyzing the data segments to (i) select the data segment(s) associated with each variable that have a highest energy and provide a high signal to noise ratio and (ii) eliminate poorly performing segments associated with each variable.

Abstract: A method includes receiving one or more vibration signals representing physical vibrations generated by a shaft of a machine during operation. The method also includes determining a rotational speed of the shaft. The method further includes identifying one or more sets of frequency components of the vibration signals based on the speed of the shaft, where each set of frequency components is associated with an operational characteristic of the shaft. In addition, the method includes determining one or more health indicators of the shaft based on relative energy levels of the frequency components in each set of frequency components.