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.

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.

An industrial integrated development environment (IDE) provides a development framework for designing, programming, and configuring multiple aspects of an industrial automation system using a common design environment and data model. Projects creating using embodiments of the IDE system can be built on an object-based model rather than, or in addition to, a tag-based architecture. To this end, the IDE system can support the use of automation objects that serve as building blocks for this object-based development structure. To ensure consistency within and between projects, as well as to ensure that a given industrial project is dynamically updated to reflect changes to an industrial asset's attributes (e.g., control code, visualization definitions, testing scripts, analytic code, etc.), embodiments of the IDE system can use automation object inheritance features to propagate changes made to an automation object definition to all instances of the automation object used throughout a control project.

An industrial integrated development environment (IDE) provides a development framework for designing, programming, and configuring multiple aspects of an industrial automation system using a common design environment and data model. Projects creating using embodiments of the IDE system can be built on an object-based model rather than, or in addition to, a tag-based architecture. To this end, the IDE system can support the use of automation objects that serve as building blocks for this object-based development structure. To ensure consistency within and between projects, as well as to ensure that a given industrial project is dynamically updated to reflect changes to an industrial asset's attributes (e.g., control code, visualization definitions, testing scripts, analytic code, etc.), embodiments of the IDE system can use automation object inheritance features to propagate changes made to an automation object definition to all instances of the automation object used throughout a control project.

An industrial integrated development environment (IDE) provides a development framework for designing, programming, and configuring multiple aspects of an industrial automation system using a common design environment and data model. Projects creating using embodiments of the IDE system can be built on an object-based model rather than, or in addition to, a tag-based architecture. To this end, the IDE system can support the use of automation objects that serve as building blocks for this object-based development structure. To ensure consistency within and between projects, as well as to ensure that a given industrial project is dynamically updated to reflect changes to an industrial asset's attributes (e.g., control code, visualization definitions, testing scripts, analytic code, etc.), embodiments of the IDE system can use automation object inheritance features to propagate changes made to an automation object definition to all instances of the automation object used throughout a control project.

An industrial integrated development environment (IDE) provides a development framework for designing, programming, and configuring multiple aspects of an industrial automation system using a common design environment and data model. Projects creating using embodiments of the IDE system can be built on an object-based model rather than, or in addition to, a tag-based architecture. To this end, the IDE system can support the use of automation objects that serve as building blocks for this object-based development structure. To ensure consistency within and between projects, as well as to ensure that a given industrial project is dynamically updated to reflect changes to an industrial asset's attributes (e.g., control code, visualization definitions, testing scripts, analytic code, etc.), embodiments of the IDE system can use automation object inheritance features to propagate changes made to an automation object definition to all instances of the automation object used throughout a control project.

A method for configuring a control system for a process plant using a dynamic model of the process plant, the dynamic model being based on at least one of thermo fluidic correlations, thermo dynamic correlations, phenomenological correlations, and equations, and being based on geometry and/or topology of components of the process plant, the dynamic model receiving process parameters as input values, the dynamic model being adapted to represent a transition from one to another state of the process plant and the dynamic model covering the entire operating range of the process plant wherein the dynamic model is used in an offline mode, in which the dynamic model is used in stand-alone fashion, wherein, based on input and output values of the dynamic model, a behaviour of the process plant is predicted, and wherein, based on the predicted behaviour of the process plant, the control system is configured.

A method for operating a process plant using a dynamic model of the process plant, the dynamic model being based on at least one of thermo fluidic correlations, thermo dynamic correlations, phenomenological correlations, and equations, and being based on geometry and/or topology of components of the process plant, the dynamic model receiving process parameters as input values, the dynamic model being adapted to represent a transition from one to another state of the process plant, wherein the dynamic model is used in an online mode, in which the dynamic model is used in parallel with the operation of the process plant, wherein signals from a control system of the process plant, the signals representing values of at least one first process parameter, are received and fed into the dynamic model.

Provided is an analysis apparatus comprising: a variation model storage unit configured to store a plurality of variation models indicating variation in characteristics of a plant corresponding to an operating condition of the plant; a model extraction unit configured to acquire structure information indicating a structure model of an analysis target plant and to extract the variation model corresponding to the structure model; and an analysis unit configured to analyze the analysis target plant, based on the structure model of the analysis target plant and the variation model extracted by the model extraction unit.

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.