DATA MODELING STUDIO

• US 20140278312A1
• Filed: 03/17/2014
• Published: 09/18/2014
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: Fisher-Rosemount Systems Incorporated (Emerson Electric Company)
• Original Assignee: Fisher-Rosemount Systems Incorporated (Emerson Electric Company)
• Inventors: Nixon, Mark J., Blevins, Terrence, Christensen, Daniel Dean, Muston, Paul Richard, Beoughter, Ken
• Granted Patent: US 9,740,802 B2
• Time in Patent Office: Days
• US Class Current: 703/6
• CPC Class Codes: G05B 19/0426 Programming the control sequence
• CPC Class Codes: G05B 2219/23258 GUI graphical user interface, icon, function bloc editor, labview
• CPC Class Codes: G06F 3/0482 Interaction with lists of selectable items, e.g. menus
• CPC Class Codes: G06F 3/04842 Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06F 3/04855 Interaction with scrollbars
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: G06F 8/34 Graphical or visual programming
• CPC Class Codes: G06F 8/36 Software reuse
• CPC Class Codes: G06F 9/44505 Configuring for program initiating, e.g. using registry, configuration files
• CPC Class Codes: G06F 9/4494 data driven

Abstract

A data modeling studio provides a structured environment for graphically creating and executing models which may be configured for diagnosis, prognosis, analysis, identifying relationships, etc., within a process plant. The data modeling studio includes a configuration engine for generating user interface elements to facilitate graphical construction of a model and a runtime engine for executing data models in, for example, an offline or an on-line environment. The configuration engine includes an interface routine that generates user interface elements, a plurality of templates stored in memory that serve as the building blocks of the model and a model compiler that converts the graphical model into a data format executable by the run-time engine. The run time engine executes the model to produce the desired output and may include a retrieval routine for retrieving data corresponding to the templates from memory and a modeling routine for executing the executable model.

Claims

1. A computer system for facilitating graphical construction of a data model, wherein the data model analyzes data from a process plant to produce an output, the computer system comprising:

a non-transitory computer readable memory that stores a plurality of data model templates including one or more data source templates defining data sources within the process plant, one or more functional templates defining data processing routines to be performed on data retrieved from the data sources and one or more data output templates indicating processing to be performed on outputs of the data processing routine;

a configuration engine that operates on a computer processing device, including;

an interface routine that generates, via a user interface device;

a library region that displays graphical depictions of the plurality of data model templates including the data source templates, the functional templates and the data output templates; and

a canvas region that receives and displays user selections of the graphical depictions of one or more data model templates and one or more interconnections defining the connections between the selected and displayed data model templates;

wherein the configuration engine further operates to execute a software routine to enable a user to modify the data model templates depicted in the canvas region by defining specific parameters to be used in the data model templates and the interconnections between data model templates, to create interconnected model blocks forming a data model, wherein the data model includes a model input block defining a specific data source of data to be retrieved for the data model, one or more model functional blocks defining data processing procedures to be performed on the data from the specific data source and a model output block defining an operation associated with the output of the one or more functional blocks; and

a runtime engine that operates on a computer processing device to execute the data model.

2. The computer system of claim 1, wherein the plurality of data model templates further includes at least one of a data flow template that graphically defines the movement of data within the data model.

3. The computer system of claim 1, wherein one or more of the data source templates defines data stored in a big data appliance of the process plant.

4. The computer system of claim 3, wherein the big data appliance includes a unitary, logical data storage area including one or more data storage devices configured to store, using a common format, data corresponding to at least one of the process plant or a process that is controlled in the process plant, the data including multiple types of data.

5. The computer system of claim 4, wherein multiple types of data include process plant configuration data, process plant control data, and process plant event data corresponding to the operation of the process plant.

6. The computer system of claim 1, wherein at least one of the functional templates defines a mathematical procedure to be performed on data input to the at least one of the functional templates.

7. The computer system of claim 6, wherein the at least one of the functional templates defines one of a correlation procedure, a filtering procedure, a statistical processing procedure, a thresholding procedure, a partial least squares regression procedure, or a classification procedure.

8. The computer system of claim 1, wherein at least one of the data output templates produces an instruction to be provided to a process controller within the process plant.

9. The computer system of claim 1, wherein at least one of the data output templates defines a message to be provided to a user interface within or associated with the process plant.

10. The computer system of claim 9, wherein the at least one of the data output templates defines a format in which an output of the data model is to be displayed on a user interface within or associated with the process plant.

11. The computer system of claim 1, wherein at least one of the data output templates defines an alarm to be provided to a user interface within or associated with the process plant.

12. The computer system of claim 1, wherein the runtime engine iteratively executes the data model using an output of a first execution of the data model as in input to a second execution of the data model.

13. The computer system of claim 1, wherein the runtime engine executes the data model on a periodic basis.

14. The computer system of claim 1, wherein the runtime engine executes the data model on a continuous basis.

15. The computer system of claim 1, wherein a first one of the data input templates defines a data source of a first data schema and a second one of the data input templates defines a data source of a second data schema.

16. The computer system of claim 1, wherein one of the data input templates defines a data source including a hierarchical structure associated with process plant configuration data.

17. The computer system of claim 16, wherein the hierarchical structure includes a control system level and a physical process plant level.

18. The computer system of claim 1 wherein at least one of the data input templates defines a data source that streams data in real time or near real time using a streaming service.

19. The computer system of claim 1, wherein at least one of the functional templates implements one of:

a data integration technique that combines data from multiple data sources;

a data transformation technique that transforms data into a data format usable by another block of the data model; and

a data mining routine that identifies data patterns from data stored in a database.

20. The computer system of claim 1, wherein the configuration engine enables a user to interactively select data to be associated with a data input block of the data model.

21. The computer system of claim 20, wherein the configuration engine includes a data explorer that enables a user to view data stored in a big data appliance of the process plant and to specify data within the big data appliance as data to be associated with a data input block of the data model.

22. A computer implemented method of facilitating graphical construction of a data model, wherein the data model analyzes data from a process plant to produce an output, the method comprising:

generating, by one or more processors, a library region that displays one or more graphical depictions of a plurality of data model templates, wherein the data model templates include one or more data source templates defining data sources within the process plant, one or more functional templates defining data processing routines to be performed on data retrieved from the data sources and one or more data output templates indicating processing to be performed on outputs of the data processing routine;

receiving, via a user interface device, a user selection of the graphical depictions of one or more data model templates, one or more specific parameters to be used in the data model templates and one or more interconnections defining the connections between the selected and displayed data model templates;

modifying, by the one or more processors, the received data model templates to create interconnected model blocks forming a data model, wherein the data model includes a model input block defining a specific data source of data to be retrieved for the data model, one or more model functional blocks defining data processing procedures to be performed on the data from the specific data source and a model output block defining an operation associated with the output of the one or more functional blocks;

generating, by the one or more processors, a canvas region displaying the data model; and

executing, by the one or more processors, the data model.

23. The computer implemented method of claim 22, further comprising receiving, via the user interface device, a user selection of a data source template defining a data source for data from a specific time period.

24. The computer implemented method of claim 22, further comprising receiving, via the user interface device, an adjusted user selection of the data model templates after the data model has been executed.

25. The computer implemented method of claim 22, further comprising receiving, via the user interface device, the user selection of a data source template defining data stored in a big data appliance of the process plant, wherein the big data appliance includes a unitary, logical data storage area including one or more data storage devices configured to store, using a common format, data corresponding to at least one of the process plant or a process that is controlled in the process plant, the data including multiple types of data.

26. The computer implemented method of claim 22, further comprising receiving, via the user interface device, a user selection of a data flow template that graphically defines the movement of data within the data model.

27. The computer implemented method of claim 22, further comprising receiving, via the user interface device, a user selection of a data source template defining one of process plant configuration data, process plant control data or process plant event data corresponding to the operation of the process plant.

28. The computer implemented method of claim 22, further comprising receiving, via the user interface device, a user selection of at least one of the functional templates defining a mathematical procedure to be performed, wherein the at least one of the functional templates defines one of a correlation procedure, a filtering procedure, a statistical processing procedure, a thresholding procedure, a partial least squares regression procedure, or a classification procedure.

29. The computer implemented method of claim 22, further comprising receiving, via the user interface device, a user selection of a data output template defining an instruction to be provided to a process controller within the process plant.

30. The computer implemented method of claim 22, further comprising receiving, via the user interface device, a user selection of a data output template defining a message to be provided to a user interface within or associated with the process plant.

31. The computer implemented method of claim 22, further comprising receiving, via the user interface device, a user selection of a data output template defining a format in which an output of the data model is to be displayed on a user interface within or associated with the process plant.

32. The computer implemented method of claim 22, further comprising receiving, via the user interface device, a user selection of a data output template defining an alarm to be provided to a user interface within or associated with the process plant.

33. The computer implemented method of claim 22, further comprising executing, by the one or more processors, the data model iteratively using an output of a first execution of the data model as in input to a second execution of the data model.

34. The computer implemented method of claim 22, further comprising executing, by the one or more processors, the data model on a periodic basis.

35. The computer implemented method of claim 22, further comprising executing, by the one or more processors, the data model on a continuous basis.

36. The computer implemented method of claim 22, further comprising receiving, via the user interface device, a user selection of a first one of the data input templates defining a data source of a first data schema and a second one of the data input templates defining a data source of a second data schema.

37. The computer implemented method of claim 22, further comprising receiving, via the user interface device, a user selection of the data input templates defining a data source including a hierarchical structure associated with process plant configuration data, wherein the hierarchical structure includes a control system level and a physical process plant level.

38. The computer implemented method of claim 22, further comprising receiving, via the user interface device, a user selection of the data input templates defining a data source that streams data in real time or near real time using a streaming service.

39. The computer implemented method of claim 22, further comprising receiving, via the user interface device, a user selection of the functional template, wherein the functional template implements one of:

a data integration technique that combines data from multiple data sources;

a data transformation technique that transforms data into a data format usable by another block of the data model; and

a data mining routine that identifies data patterns from data stored in a database.

40. The computer implemented method of claim 22, further comprising generating, via the one or more processors, an interface to enable a user to interactively select data to be associated with a data input block of the data model.

41. The computer implemented method of claim 22, further comprising generating, via the one or more processors, a data explorer displaying data stored in a big data appliance of the process plant and receiving, via the user interface device, a user selection specifying data within the big data appliance as data to be associated with a data input block of the data model.

42. A computer implemented method of facilitating knowledge discovery within a process plant database to analyze process control data from a process plant as stored in the process plant database to produce an output, the method comprising:

receiving, via a user interface device, a user selection of a data model, wherein the data model defines a first processing routine to be performed on one or more data sources to produce an output;

generating, by the one or more processors, a data exploration interface that displays indications of process control data stored on a big data appliance of the process plant, including a unitary, logical data storage area with one or more data storage devices including;

configuration data defining hardware and software modules used in the process plant;

hierarchical data defining one or more hierarchical relationships between the hardware and software modules in the process plant;

connection data defining one or more interconnections between the hardware and software modules in the process plant; and

process measurement data corresponding to values recorded from the hardware and software modules;

receiving, via the user interface routine, a selection of process control data defining an input to be processed by the data model;

executing, by the one or more processors, the data model on the selected process control data to produce the output; and

generating an output exploration interface, via a user interface device, that allows a user to view the output of the model.

43. The computer implemented method of claim 42, further comprising receiving, via the user interface device, a user selection of the hierarchical data, wherein the hierarchical data belongs to a hierarchical structure including a control system level and a physical process plant level.

44. The computer implemented method of claim 42, further comprising receiving, via the user interface device, a user selection of the process control data defining a data source that provides on-line or historical process parameter data as measured in or generated in a process plant.

45. The computer implemented method of claim 42, further comprising executing, by the one or more processors, the data model iteratively using an output of a first execution of the data model as in input to a second execution of the data model.

46. The computer implemented method of claim 45, further comprising executing, by the one or more processors, at least one of the iterations of the knowledge discovery method without user interaction.

47. The computer implemented method of claim 45, further comprising receiving a second selection of process control data defining a second input to be processed by the data model and executing, by the one or more processors, the data model on the second selection of process control data to produce a second output.

48. The computer implemented method of claim 42, further comprising receiving, via a user interface device, a user selection of a data model specifying at least one of:

a data mining routine, a data preprocessing routine, a data merging routine, or a function to be performed on the output of the data model.