REGIONAL BIG DATA IN PROCESS CONTROL SYSTEMS

• US 20160098021A1
• Filed: 10/06/2014
• Published: 04/07/2016
• Est. Priority Date: 10/06/2014
• Status: Active Grant

• Current Assignee: Fisher-Rosemount Systems Incorporated (Emerson Electric Company)
• Original Assignee: Fisher-Rosemount Systems Incorporated (Emerson Electric Company)
• Inventors: Zornio, Peter, Nixon, Mark J., Wojsznis, Wilhelm K., Lucas, J. Michael, Rotvold, Eric D., Blevins, Terrence L., Muston, Paul Richard, Law, Gary K.
• Granted Patent: US 9,823,626 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G05B 13/0265 the criterion being a learning criterion
• CPC Class Codes: G06F 16/00 Information retrieval; Database structures therefor; File system structures therefor
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition

Abstract

A regional big data node oversees or services, during real-time operations of a process plant or process control system, a respective region of a plurality of regions of the plant/system, where at least some of the regions each includes one or more process control devices that operate to control a process executed in the plant/system. The regional big data node is configured to receive and store, as big data, streamed data and learned knowledge that is generated, received, or observed by its respective region, and to perform one or more learning analyses on at least some of the stored data. As a result of the learning analyses, the regional big data node creates new learned knowledge which the regional big data node may use to modify operations in its respective region, and/or which the regional big data node may transmit to other big data nodes of the plant/system.

Claims

1. A regional big data node for supporting big data in a process plant controlling a process, the regional big data node comprising:

a network interface that communicatively connects the regional big data node to one of a plurality of regions of the process plant, the one of the plurality of regions comprising a plurality of local big data nodes, each of which transmits, in real-time, data generated from the control of the process by the process plant as the process is being controlled in real-time;

a big data storage area comprising one or more tangible, non-transitory, computer-readable storage media configured to store regional big data;

a big data receiver configured to receive the data transmitted by the plurality of local big data nodes and received at the regional big data node via the network interface, and store the received data in the big data storage area; and

a big data analyzer configured to;

perform a learning analysis on at least a portion of the regional big data;

generate learned knowledge based on a result of the learning analysis; and

cause a change in operations of at least a portion of the process plant based on the result of the learning analysis, including causing the learned knowledge to be transmitted to a recipient big data node corresponding to the at least the portion of the process plant.

2. The regional big data node of claim 1, wherein the one of the plurality of regions is formed according to at least one of a geographical, physical, functional, or logical grouping.

3. The regional big data node of claim 1, wherein:

the plurality of local big data nodes of the one of the plurality of regions includes at least one of;

a process control device, a gateway device, an access point, a routing device, a historian device, or a network management device included in the process plant; and

the process control device is one of a controller, a field device performing a physical function to control at least a part of the process, or an input/output (I/O) device communicatively coupling the controller and the field device.

4. The regional big data node of claim 1, wherein the regional big data includes multiple types of data, and a set of types of data includes continuous data, event data, measurement data, batch data, calculated data, diagnostic data, configuration data, data corresponding to the learned knowledge, and data corresponding to other learned knowledge.

5. The regional big data node of claim 1, wherein the learning analysis includes at least one of:

a partial least square regression analysis, a random forest, a pattern recognition, a predictive analysis, a correlation analysis, a principle component analysis, data mining, data discovery, or other machine learning techniques including heuristic learning.

6. The regional big data node of claim 1, wherein:

the change in the operations of the at least the portion of the process plant based on the result of the learning analysis comprises a modification to an operation being performed in the one of the plurality of regions based on the learned knowledge, and

the big data analyzer is further configured to cause an indication of the modification to be transmitted to the recipient big data node in conjunction with the learned knowledge.

7. The regional big data node of claim 1, wherein:

the learned knowledge is first learned knowledge, the learning analysis is a first learning analysis, and the one of the plurality of regions is a first region;

the big data receiver is further configured to receive second learned knowledge generated by another big data node of a second region of the plurality of regions; and

the big data analyzer is further configured to at least one of (i) cause a modification, based on the received second learned knowledge, to an operation being performed in the first region, or (ii) perform a second learning analysis on the received second learned knowledge and at least some of the regional big data.

8. The regional big data node of claim 7, wherein the another big data node of the second region is a regional big data node servicing the second region.

9. The regional big data node of claim 1, wherein the learned knowledge includes at least one of:

additional data resulting from control of the process that was previously unknown to the regional big data node, an application, a service, a routine, a function, or another learning analysis.

10. The regional big data node of claim 1, wherein the big data analyzer is further configured to perform in-context searching based on the learned knowledge.

11. The regional big data node of claim 1, wherein the big data analyzer is further configured to provide recommendations to users based on the learned knowledge.

12. The regional big data node of claim 1, wherein:

the network interface communicatively connects the regional big data node to a user interface big data node, the user interface big data node including a user interface and one or more respective analytics routines;

the big data receiver is further configured to receive, using the network interface, data generated based on a result of the one or more respective analytics routines executing at the user interface big data node based on a user input received via the user interface of the user interface big data node, and store the data received from the user interface big data node in the big data storage area; and

the big data analyzer is further configured to perform the learning analysis or another learning analysis on another portion of the regional big data including the data received from the user interface big data node.

13. The regional big data node of claim 1, wherein:

the network interface communicatively connects the regional big data node to a centralized big data node;

the centralized big data node includes one or more respective analytics routines;

the big data receiver of the regional big data node is further configured to receive, using the network interface, data generated based on a result of the one or more analytics routines executing at the centralized big data node, and store the data received from the centralized big data node in the big data storage area; and

at least one of;

the big data analyzer is further configured to perform the learning analysis or another learning analysis on another portion of the regional big data including the data received from the centralized big data node, or

the regional big data node is configured to modify an operation based on the data received from the centralized big data node.

14. The regional big data node of claim 1, wherein at least a portion of at least one of the big data receiver or the big data analyzer is included on one or more integrated circuit chips.

15. The regional big data node of claim 1, wherein at least a portion of at least one of the big data receiver or the big data analyzer comprises computer-executable instructions stored on a memory of the regional big data node and executable by a processor of the regional big data node.

16. A method of utilizing regional big data to improve the operation of a process plant controlling a process, the method comprising:

collecting data at one or more regional big data nodes of the process plant, wherein;

each of the one or more regional big data nodes corresponds to a respective region included in a plurality of regions of the process plant,

the collected data includes data transmitted by a respective plurality of local big data nodes of the respective region, and

each local big data node transmits, in real-time, respective data resulting from on-line operations of the respective region of the each local big data node;

storing the collected data as regional big data at the one or more regional big data nodes;

performing, by the one or more regional big data nodes, one or more learning analyses on at least a portion of the regional big data;

generating learned knowledge based on results of the one or more learning analyses; and

causing a change in operations of at least a portion of the process plant based on the results of the one or more learning analysis, including transmitting the learned knowledge to a recipient big data node corresponding to the at least the portion of the process plant.

17. The method of claim 16, wherein the method is autonomously performed without using any real-time user input.

18. The method of claim 16, wherein each of the one or more regional big data nodes is formed according to one of a geographical, physical, functional, or logical grouping.

19. The method of claim 16, wherein:

collecting the data at the one or more regional big data nodes comprises collecting data transmitted by at least one of;

a process control device, a gateway device, an access point, a routing device, a historian device, a user interface device, or a network management device of the process plant;

the process control device is one of a controller, a field device performing a physical function to control at least a part of the process, or an input/output (I/O) device communicatively coupling the controller and the field device; and

the collected data includes at least one type of data included in a set of data types comprising continuous data, event data, measurement data, batch data, calculated data, diagnostic data, configuration data, and data corresponding to other learned knowledge.

20. The method of claim 16, wherein the learned knowledge is first learned knowledge, and wherein collecting the data at the one or more regional big data nodes comprises collecting second learned knowledge generated by the one or more regional big data nodes or by another big data node of the process plant.

21. The method of claim 16, further comprising at least one of:

selecting a first at least one of the one or more learning analyses, or deriving a second at least one of the one or more learning analyses.

22. The method of claim 16, wherein generating the learned knowledge comprises generating at least one of:

additional data that was previously unknown to the one or more regional big data nodes, a new or modified application, a new or modified function, a new or modified routine, a new or modified learning analysis, or a new or modified service.

23. The method of claim 16, wherein:

the at least the portion of the regional big data is a first at least a portion of the regional big data; and

the method further comprises performing the new or modified learning analysis on a second at least a portion of the regional big data.

24. The method of claim 16, wherein performing the one or more learning analyses comprises performing at least one of a machine learning analysis, a predictive analysis, data mining, or data discovery.

25. The method of claim 16, wherein:

performing the one or more learning analyses by the one or more regional big data nodes comprises performing the one or more learning analyses by more than one regional big data nodes; and

generating the learned knowledge based on the results of the one or more learning analyses comprises generating the learned knowledge based on results of the one or more learning analyses performed by the more than one regional big data nodes.

26. A system for supporting regional big data in a process plant comprising:

one or more regional big data nodes;

a plurality of local big data nodes; and

a communications network communicatively connecting the one or more regional big data nodes and the plurality of local big data nodes, the plurality of local big data nodes being arranged into a plurality of regions, each of which is serviced by a respective regional big data node included in the one or more regional big data nodes, wherein the respective regional big data node is configured to;

collect data generated in real-time by a set of local big data nodes associated with the respective region serviced by the respective regional big data node, the data generated in real-time by the set of local big data nodes due to real-time control of a process in the process plant;

store the collected data as respective regional big data at a big data storage area included in the respective regional big data node; and

perform, using a big data analyzer included in the respective regional big data node, a learning analysis on at least a portion of the stored respective regional big data, and

generate learned knowledge based on the result of the performed learning analysis; and

at least one of (i) store, at the big data storage area, the learned knowledge as additional respective regional big data, or (ii) transmit the learned knowledge to a recipient big data node included in the process plant.

27. The system of claim 26, wherein the plurality of local big data nodes are arranged into the plurality of regions according to at least one of a geographical, physical, functional, or logical grouping.

28. The system of claim 26, wherein the learned knowledge includes at least one of:

additional data resulting from the real-time control of the process, an application, a function, a service, a routine, or another learning analysis.

29. The system of claim 26, wherein the result of the performed learning analysis includes a prediction based on properties of the at least the portion of the stored respective regional big data.

30. The system of claim 26, further comprising a user interface big data node having a respective learning analysis, and wherein:

the collected data is first collected data, and

the respective regional big data node is further configured to;

collect second data generated by a performance of the respective learning analysis at the user interface big data node;

store the second collected data at the big data storage area included in the respective regional big data node; and

at least one of;

perform the learning analysis or another learning analysis on a set of stored respective regional data including the second collected data, or cause the second collected data to be transmitted to another big data node.

31. The system of claim 26, further comprising at least one of a centralized big data node or another type of big data node, and wherein:

the collected data is first collected data; and

the respective regional big data node is further configured to;

collect second data generated by a performance of a learning analysis at the at least one of the centralized big data node or the another type of big data node;

store the second collected data at the big data storage area included in the respective regional big data node; and

perform the learning analysis or another learning analysis on a set of stored respective regional data including the second collected data.

32. The system of claim 26, wherein the data generated in real-time by the set of local big data nodes includes data generated in real-time by one or more of:

a field device;

a controller configured to receive a set of inputs, determine, based on the set of inputs, a value of an output, and cause the output to be transmitted to the field device to control the process executed by the process plant, the field device being configured to perform a physical function based on the output of the controller to control the process;

an input/output (I/O) device having an interface to the controller and an interface to the field device;

a gateway device;

an access point;

a routing device;

a historian device;

or

a network management device.

33. The system of claim 26, wherein the learned knowledge is transmitted to the recipient big data node, and wherein the recipient big data node causes at least one of (i) a modification, based on the received learned knowledge, to the recipient big data node, or (ii) a modification to a provider of big data to the recipient big data node.