Discrete manufacturing hybrid cloud solution architecture

• US 10,866,582 B2
• Filed: 07/19/2019
• Issued: 12/15/2020
• Est. Priority Date: 08/31/2017
• Status: Active Grant

• Current Assignee: Rockwell Automation Technologies Incorporated (Allen-Bradley Co., Inc.)
• Original Assignee: Rockwell Automation Technologies Incorporated (Allen-Bradley Co., Inc.)
• Inventors: Manturana, Francisco P
• Primary Examiner(s): Kasenge, Charles R
• Application Number:
  US16/517,093
• Publication Number:
  US 20190339681A1
• Time in Patent Office: 515 Days
• CPC Class Codes: G05B 2223/06 Remote monitoring
• CPC Class Codes: G05B 23/0227 Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions
• CPC Class Codes: G05B 23/0283 Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL] preventive maintenance, i.e. planning maintenance according to the available resources without monitoring the system G06Q10/06
• CPC Class Codes: G05B 23/0294 Optimizing process, e.g. process efficiency, product quality
• CPC Class Codes: G06F 9/5072 Grid computing

Abstract

A hybrid data collection and analysis infrastructure combines edge-level and cloud-level computing to perform high-level monitoring and control of industrial systems and processes. Edge devices located on-premise at one or more plant facilities can collect data from multiple industrial devices on the plant floor and perform local edge-level analytics on the collected data. In addition, the edge devices maintain a communication channel to a cloud platform executing cloud-level data collection and analytic services. As necessary, the edge devices can pass selected sets of data to the cloud platform, where the cloud-level analytic services perform higher level analytics on the industrial data. The hybrid architecture operates in a bi-directional manner, allowing the cloud-level and edge-level analytics to send control instructions to industrial devices based on results of the edge-level and cloud-level analytics.

Claims

1. An edge device, comprising:

a memory that stores executable components; and

a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising;

a collection services component configured to collect industrial data from data tags of an industrial device and to generate a compressed data file containing the industrial data, wherein the data tags from which the industrial data is collected are defined by an edge-level data manifest file;

a queue processing component configured to package the compressed data file with header information based on message queuing information maintained in a message queuing data store to yield a compressed data packet and to send the compressed data packet to a cloud analytics system executing on a cloud platform; and

an edge analytics component configured to perform an edge-level analytic procedure on a first subset of the industrial data, wherein the edge-level analytic procedure identifies a pattern in the first subset of the industrial data indicative of a pneumatic air leak, and the edge-level analytic procedure is defined by an edge-level metrics manifest file,

wherein

the edge analytics component is configured to, in response to identification of the pattern, send a first command to the industrial device instructing the industrial device to alter a controlled industrial process,

the queue processing component is further configured to receive an analytic result from the cloud analytics system, the analytic result generated based on a cloud-level analytic procedure performed on a second subset of the industrial data by the cloud analytics system, and

the edge analytics component is further configured to send a second command to the industrial device based on the analytic result.

2. The edge device of claim 1, wherein the first subset of the industrial data comprises pressure values.

3. The edge device of claim 1, wherein the first command instructs the industrial device to alter the controlled industrial process to at least one of bypass a pipe experiencing the pneumatic air leak, reduce a usage priority of the pipe, or slow the controlled industrial process.

4. The edge device of claim 1, wherein the edge analytics component is further configured to send notification data to the cloud analytics system in response to identification of the pattern.

5. The edge device of claim 1, wherein the cloud-level analytic procedure is configured to generate a trend of the second subset of the industrial data over time and to identify another pattern in the trend indicative of a performance degradation of an industrial device.

6. The edge device of claim 5, wherein the edge analytics component is configured to generate the second command to alter the controlled industrial process or another controlled industrial process based on the performance degradation.

7. The edge device of claim 5, wherein the performance degradation is a loss of position accuracy of an electro-pneumatic actuator.

8. The edge device of claim 1, wherein the edge-level analytic procedure performs a comparison of a trend of the first subset of the industrial data with a model of performance degradation, and generates the first command based on a result of the comparison.

9. The edge device of claim 1, further comprising a user interface component configured to send a notification of the analytic result to a client device,

wherein the edge analytics component is configured to send the second command to the industrial device in response to receipt of confirmation input from the client device.

10. A method for processing industrial data, comprising:

collecting, by a system comprising a processor, industrial data from data tags of an industrial device, wherein the data tags from which the industrial data is collected are identified by an edge-level data manifest file;

generating, by the system, a compressed data file containing the industrial data;

adding, by the system, header information to the compressed data file to yield a compressed data packet, wherein the header information is based on message queuing information maintained in a message queuing data store to yield a compressed data packet;

sending, by the system, the compressed data packet to a cloud analytics system executing on a cloud platform;

performing, by the system, an edge-level analytic procedure on a first subset of the industrial data, wherein the edge-level analytic procedure is defined by an edge-level metrics manifest file and identifies a pattern in the first subset of the industrial data corresponding to a pneumatic air leak;

sending, by the system, a first command to the industrial device in response to identification of the pattern, wherein the first command is configured to alter a controlled industrial process;

receiving, by the system, an analytic result from the cloud analytics system, wherein the analytic result is generated based on a cloud-level analytic procedure performed on a second subset of the industrial data by the cloud analytics system; and

sending, by the system, a second command to the industrial device based on the analytic result.

11. The method of claim 10, wherein the first subset of the industrial data comprises pressure values, and the pattern is a time-series pattern.

12. The method of claim 11, wherein the first command instructs the industrial device to alter the controlled industrial process to at least one of bypass a pipe affected by the pneumatic air leak, reduce a usage priority of the pipe, or slow the controlled industrial process.

13. The method of claim 10, further comprising sending a notification to the cloud analytics system in response to identifying of the pattern.

14. The method of claim 10, wherein the receiving the analytic result comprises receiving, as the analytic result, an identification of another pattern in a time-based trend of the second subset of the industrial data, wherein the other pattern corresponds to a performance degradation of an industrial device.

15. The method of claim 14, wherein the sending the second command comprises generating the second command to alter the controlled industrial process or another controlled industrial process based on the performance degradation.

16. The method of claim 14, further comprising identifying, based on the analytic result, a loss of position accuracy of an electro-pneumatic actuator.

17. The method of claim 14, wherein the adding comprises adding, as the header information, at least a customer identifier associated with the industrial enterprise and priority information specifying a processing priority for the industrial data.

18. A non-transitory computer-readable medium having stored thereon instructions that, in response to execution, cause an edge device comprising a processor to perform operations, the operations comprising:

collecting industrial data from data tags of an industrial device, wherein the data tags from which the industrial data is collected are defined by an edge-level data manifest file;

generating a compressed data file containing the industrial data;

appending header information to the compressed data file to yield a compressed data packet, wherein the header information is based on message queuing information maintained in a message queuing data store to yield a compressed data packet;

sending the compressed data packet to a cloud analytics system executing on a cloud platform;

identifying, based on an edge-level analytic procedure defined by an edge-level metrics manifest file and performed on a first subset of the industrial data, a pattern in the first subset of the industrial data corresponding to a pneumatic air leak;

in response to the identifying, instructing the industrial device to alter a controlled industrial process;

receiving an analytic result from the cloud analytics system, wherein the analytic result is generated based on a cloud-level analytic procedure performed on a second subset of the industrial data by the cloud analytics system; and

sending a second control instruction to the industrial device based on the analytic result.

19. The non-transitory computer-readable medium of claim 18, wherein the receiving the analytic result comprises receiving, as the analytic result, an identification of pattern in a time-based trend of the second subset of the industrial data, wherein the pattern corresponds to a performance degradation of an industrial device.

20. The non-transitory computer-readable medium of claim 18, wherein the instructing the industrial device comprises instructing the industrial device to alter the controlled industrial process to at least one of bypass a pipe affected by the pneumatic air leak, reduce a usage priority of the pipe, or slow the controlled industrial process.