DISTRIBUTED INDUSTRIAL PERFORMANCE MONITORING AND ANALYTICS

• US 20170102678A1
• Filed: 09/23/2016
• Published: 04/13/2017
• Est. Priority Date: 03/04/2013
• Status: Active Grant

• Current Assignee: Fisher-Rosemount Systems Incorporated (Emerson Electric Company)
• Original Assignee: Fisher-Rosemount Systems Incorporated (Emerson Electric Company)
• Inventors: Nixon, Mark John, Enver, Alper Turhan, Bell, Noel Howard, Kidd, Joshua Brian, Muston, Paul R.
• Granted Patent: US 10,649,424 B2
• Time in Patent Office: Days
• CPC Class Codes: G05B 17/02 electric
• CPC Class Codes: G05B 19/4185 characterised by the network communication
• CPC Class Codes: G05B 2219/31088 Network communication between supervisor and cell, machine group
• CPC Class Codes: G05B 2219/31167 Object, data object as network variable
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
• CPC Class Codes: Y02P 90/80 Management or planning

Abstract

Distributed industrial process monitoring and analytics systems and methods are provided for operation within a process plant. A plurality of distributed data engines (DDEs) may be embedded within the process plant to collect and store data generated by data sources, such as process controllers. Thus, the data may be stored in a distributed manner in the DDEs embedded throughout the process plant. The DDEs may be connected by a data analytics network to facilitate data transmission by subscription or query. The DDEs may be configured as a plurality of clusters, which may further include local and centralized clusters. The local clusters may obtain streaming data from data sources and stream selected data to a data consumer. The centralized cluster may register the local clusters, receive data therefrom, and perform data analytic functions on the received data. The analyzed data may be further sent to a data consumer.

Claims

1. A distributed industrial process monitoring and analytics system, comprising:

a plurality of distributed data engines (DDEs) embedded within a process plant that is operating to control a process, each of the DDEs coupled to respective one or more data sources that are generating data as a result of the process being controlled by the process plant, and each of the DDEs storing the data being generated by the respective one or more data sources; and

a data analytics network supporting streaming of analytics data amongst the plurality of distributed data engines and transmission of queries for data stored at the plurality of DDEs.

2. The system of claim 1, wherein the data analytics network is overlaid over other process control communication networks of the process plant.

3. The system of claim 1, wherein the data analytics network is disposed in parallel with other process control communication networks of the process plant.

4. The system of claim 1, wherein at least one DDE of the plurality of DDEs is integral with a process control device operating to control the process.

5. The system of claim 4, wherein the process control device transmits signals over a process control communication network to another process control device to control the process.

6. The system of claim 1, wherein a query for data that is stored at the plurality of DDEs is generated by one or more of the DDEs, a user interface, or an application.

7. The system of claim 6, wherein the query for the data that is stored at the plurality of DDEs comprises a query for data that is stored across more than one DDE.

8. The system of claim 1, wherein the stored data at the plurality of DDEs is periodically transferred, via the data analytics network, to an analytics data historian.

9. The system of claim 8, wherein the analytics data historian is independent of a process control data historian that is accessible via process control communication networks of the process plant.

10. The system of claim 1, wherein each of the DDEs includes a cache in addition to a data storage area storing the data generated by the respective one or more data sources.

11. The system of claim 1, wherein a first DDE of the plurality of DDEs advertises a cluster with which the respective one or more data sources coupled to the first DDE register.

12. The system of claim 11, wherein the respective one or more data sources coupled to the first DDE publish, to the cluster advertised by the first DDE, the data being generated by the respective one or more data sources as a result of the process being controlled.

13. The system of claim 11, wherein data published by the first DDE includes a result of a data analysis performed by the first DDE using at least some of the data generated by the respective one or more data sources coupled to the first DDE.

14. The system of claim 11, wherein the cluster advertised by the first DDE is a local cluster, and wherein a second DDE advertises a regional cluster with which the first DDE registers and to which the first DDE publishes data.

15. The system of claim 14, wherein the second DDE corresponding to the regional cluster provides at least one of a location service or a data dictionary used to establish data exchange with another regional cluster.

16. The system of claim 14, wherein one or more additional DDEs corresponding to one or more additional local clusters are registered with the regional cluster and publish data to the regional cluster.

17. The system of claim 14, wherein a third DDE advertises a centralized cluster with which the second DDE registers and to which the second DDE publishes data.

18. The system of claim 17, wherein the second DDE publishes, to the centralized cluster via the data analytics network, at least a portion of the data stored at the second DDE.

19. The system of claim 17, wherein the data published by the second DDE to the centralized cluster includes a result of a data analysis performed by the second DDE using data received at the second DDE from another DDE.

20. The system of claim 17, wherein one or more additional DDEs corresponding to one or more additional regional clusters are registered with the centralized cluster and publish data to the centralized cluster.

21. The system of claim 17, wherein the centralized cluster is hosted in a cloud computing environment.

22. The system of claim 17, wherein the process plant is a first process plant, and wherein other clusters corresponding to other process plants are registered with the centralized cluster and publish data to the centralized cluster.

23. The system of claim 17, wherein the centralized cluster stores a set of rules for the data analytics network, the set of rules including rules corresponding to at least one of replication or backup.

24. The system of claim 1, further comprising a user interface to administrate a set of rules for the data analytics network, the set of rules including rules corresponding to at least one of replication or backup.

25. The system of claim 1, wherein one of the DDEs publishes, to the data analytics network, at least some of the data being generated by the respective one or more data sources corresponding to the one of the DDEs.

26. The system of claim 25, wherein another one of the DDEs subscribes to the at least some of the data being generated by the respective one or more data sources corresponding to the one of the DDEs and published by the one of the DDEs.

27. The system of claim 26, wherein the another one of the DDEs performs one or more data analytics functions on the subscribed data.

28. The system of claim 27, wherein a result of the one or more data analytics functions performed by the another one of the DDEs is published to the data analytics network.

29. The system of claim 1, further comprising a data analytics model executing in the data analytics network to obtain data stored at the one or more DDEs and perform one or more data analytics functions on the obtained data to generate analytic output.

30. The system of claim 29, wherein the one or more data analytics functions includes a descriptive analytic function, and wherein the analytic output includes a characteristic of the process plant determined by performing the descriptive analytic function.

31. The system of claim 29, wherein the one or more data analytics functions includes a predictive analytic function, and wherein the analytic output includes one or more predicted values determined by performing the predictive analytic function.

32. The system of claim 31, wherein the one or more predicted values includes at least one of:

a value indicative of a predicted performance, a value indicative of a predicted fault or failure, a value indicative of a predicted time interval, or a value indicative of another characteristic of at least a portion of the process plant.

33. The system of claim 29, wherein the one or more data analytics functions includes a prescriptive analytic function, and wherein the analytic output includes one or more prescriptive actions for the process plant.

34. The system of claim 33, wherein the one or more prescriptive actions mitigate effects of a fault or failure within the process plant.

35. The system of claim 33, wherein the one or more prescriptive actions decreases a likelihood of an occurrence of a predicted event or condition, the predicted event or condition corresponding to a fault, a failure, a level of performance, or a level of degradation of at least a portion of the process plant.

36. The system of claim 1, further comprising a data analytics user interface application via which a user develops a data analytics model that obtains data stored at one or more DDEs and predicts one or more values of the process plant based on the data obtained from the one or more DDEs.

37. The system of claim 36, wherein:

the data obtained by the data analytics model from the one or more DDEs includes continuously updated data generated by the process plant while controlling the process; and

the data analytics model continuously executes on the continuously updated data obtained from the one or more DDEs, thereby generating a continuous output, the continuous output including continuous updates to the one or more predicted values of the process plant.

38. The system of claim 37, wherein the continuously updated data obtained by the data analytics model from the one or more DDEs comprises data streamed via the data analytics network from the one or more DDEs to the data analytics model.

39. The system of claim 37, where the data analytics model transmits, via the data analytics network, a query to the one or more DDEs to obtain the continuously updated data.

40. The system of claim 37, wherein the continuous output generated by the data analytics model is displayed on a user interface using a continuously updated graphical visualization.

41. The system of claim 40, wherein the continuously updated graphical visualization of the one or more predicted values is displayed on the user interface in conjunction with a continuously updated graphical visualization of one or more actual values generated by the process plant and corresponding to the one or more predicted values.

42. The system of claim 41, further comprising presenting an indication of an accuracy of the data analytics model, the accuracy based on a comparison of the one or more predicted values and the one or more actual values.

43. The system of claim 37, wherein the continuous output generated by the data analytics model is streamed to at least one of the plurality of DDEs.

44. The system of claim 1, further comprising a user interface for the user to obtain data stored at any of the plurality of DDEs.

45. The system of claim 1, wherein the analytics data streamed via the data analytics network includes results of data analytics functions performed by the plurality of DDEs and at least one of:

data generated by process control devices while controlling the process within the process plant, historized data, and other data.

46. The system of claim 45, wherein the results of the data analytics functions performed by the plurality of DDEs include a new analytic function generated by another data analytic function.

47. The system of claim 45, wherein:

the data generated by process control devices while controlling the process within the process plant is (i) transmitted over one or more process control communication networks to control the process, and (ii) transmitted over the data analytics network; and

the historized data is (iii) transmitted over one or more process control communication networks to a process control data historian for storage, and (iv) transmitted over the data analytics network to an analytics data historian for storage.

48. The system of claim 1, wherein at least some of the DDEs respectively store the data being generated by the respective one or more data sources using different formats.

49. A method, comprising:

advertising, by a cluster included in a data analytics network of a process control plant that is operating to control a process, a presence of the cluster;

registering, by the cluster, a data source that responds to the advertising and that generates continuous data resulting from the control of the process in the process control plant;

receiving, by the cluster, the continuous data generated by the data source;

streaming, by the cluster via the data analytics network, at least some of the continuous data generated by the data source to a data consumer.

50. The method of claim 49, where the data consumer is bound to the data source.

51. The method of claim 49, wherein the data analytics network is overlaid over all other process control communication networks utilized in the process plant to control the process.

52. The method of claim 49, wherein:

the data source is a process control device that transmits the continuous data over a process control communication network to control the process; and

receiving the continuous data generated by the process control device comprises receiving, via the data analytics network, a copy of at least some of the contents of the continuous data transmitted by the process control device over the process control communication network to control the process.

53. The method of claim 49, wherein receiving the continuous data generated by the data source comprises receiving data that has been generated and published to the cluster by the data source.

54. The method of claim 49, further comprising:

storing, at the cluster, the continuous data generated by the data source; and

caching, at the cluster, at least a portion of the continuous data generated by the data source.

55. The method of claim 54, further comprising periodically historizing data stored at the cluster, including transmitting, via the data analytics network, the data stored at the cluster to an analytics data historian.

56. The method of claim 49, further comprising receiving, via the data analytics network from the data consumer, a query for the at least some of the continuous data generated by the data source, and wherein streaming the at least some of the continuous data generated by the data source to the data consumer is based on the query.

57. The method of claim 49, wherein streaming the at least some of the continuous data to the data consumer comprises streaming the at least some of the continuous data to a user interface.

58. The method of claim 49, wherein streaming the at least some of the continuous data to the data consumer comprises streaming, to a data analytics application, the at least some of the continuous data to be used as input into a data analytics function.

59. The method of claim 49, wherein the cluster is a local cluster, and the method further comprises:

detecting, by the local cluster, an advertisement generated by a regional or centralized cluster;

registering, by the local cluster, the local cluster with the regional or centralized cluster; and

streaming, by the local cluster via the data analytics network to the regional or centralized cluster, analytics data corresponding to the local cluster.

60. The method of claim 59, wherein streaming, to the regional or centralized cluster, the analytics data corresponding to the local cluster comprises publishing, to the regional or centralized cluster, the analytics data corresponding to the local cluster.

61. The method of claim 59,

further comprising performing, by the local cluster, one or more data analytics functions on at least a portion of the continuous data generated by the data source;

and

wherein streaming, to the regional or centralized cluster, the analytics data corresponding to the local cluster comprises streaming, to the regional or centralized cluster, results of the one or more data analytics functions performed on the at least the portion of the continuous data generated by the data source.

62. The method of claim 61, wherein performing the one or more data analytics functions on the at least the portion of the continuous data generated by the data source comprises performing the one or more data analytics functions on the at least a portion of the continuous data generated by the data source and on data generated by another data source registered with the local cluster.

63. The method of claim 49, wherein the cluster comprises one or more of a plurality of distributed data engines (DDEs) embedded within the process plant and coupled to the data analytics network.

64. A method, comprising:

advertising, by a centralized cluster included in a data analytics network, a presence of the centralized cluster;

registering, by the centralized cluster, a local cluster that responds to the advertising and that is configured to store and stream continuous data that is generated as a result of controlling a process in a process control plant, wherein the local cluster is embedded in the process plant and communicatively coupled to one or more data sources that generate at least a portion of the continuous data while operating to control the process;

receiving, by the centralized cluster from the local cluster, at least a portion of the streamed continuous data;

performing one or more data analytics functions on the at least a portion of the streamed continuous data received from the local cluster; and

streaming, via the data analytics network, an output of the one or more data analytics functions to a data consumer.

65. The method of claim 64, wherein the data consumer is bound to the centralized cluster.

66. The method of claim 64, where the data analytics network is overlaid over all other process control communication networks utilized in the process plant to control the process.

67. The method of claim 64, wherein the one or more data sources communicatively coupled to the local cluster include a process control device, and wherein the at least a portion of the streamed continuous data is received at the centralized cluster from the local cluster via the data analytics network and includes a copy of at least some of the contents of data transmitted by the process control device over a process control communication network to control the process.

68. The method of claim 64, wherein receiving the at least a portion of the streamed continuous data from the local cluster comprises receiving data that has been published to the centralized cluster by the local cluster.

69. The method of claim 64, further comprising storing, at the centralized cluster, the at least the portion of the streamed continuous data received from the local cluster and the output of the one or more data analytics functions.

70. The method of claim 69, further comprising periodically historizing data stored at the centralized cluster, including transmitting, via the data analytics network, the data stored at the centralized cluster to an analytics data historian.

71. The method of claim 64, further comprising receiving, via the data analytics network from the data consumer, a query for the output of the one or more data analytics functions, and wherein the streaming of the output of the one or more data analytics functions is based on the query.

72. The method of claim 64, wherein the output of the one or more data analytics functions is a continuous output.

73. The method of claim 64, wherein streaming the output of the one or more data analytics functions to the data consumer comprises streaming the output of the one or more data analytics functions to a user interface.

74. The method of claim 64, wherein streaming the output of the one or more data analytics functions to the data consumer comprises streaming the output of the one or more data analytics functions to a data analytic application executing in the data analytics network.

75. The method of claim 64, wherein streaming the output of the one or more data analytics functions to the data consumer comprises streaming the output of the one or more data analytics functions to a subscriber.

76. The method of claim 64,

further comprising registering one or more additional local clusters to the centralized cluster and receiving respective data from the one or more additional local clusters;

and

wherein performing the one or more data analytics functions on the at least a portion of the streamed continuous data received from the local cluster comprises performing the one or more data analytics functions on at least a portion of the streamed continuous data received from the local cluster and the respective data received from the one or more additional local clusters.

77. The method of claim 64,

further comprising registering, by the centralized cluster, the centralized cluster with another centralized cluster;

and

wherein streaming the output of the one or more data analytics functions to the data consumer comprises streaming the output of the one or more data analytics functions to the other centralized cluster.

78. The method of claim 77, wherein the other centralized cluster is hosted in a cloud computing environment.

79. The method of claim 64, wherein the centralized cluster is hosted in a cloud computing environment.

80. The method of claim 64, wherein the centralized cluster comprises one or more of a plurality of distributed data engines (DDEs) embedded within the process plant.

81. The method of claim 64, further comprising providing, by the centralized cluster, at least one of a location service or a data dictionary used to establish analytics data exchange between clusters.

82. The method of claim 64, further comprising providing, by the centralized cluster, an interface via which a user administrates a set of rules for replication and backup within the data analytics network.