Discrete manufacturing hybrid cloud solution architecture
First Claim
1. An edge device, comprising:
- a memory that stores executable components;
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 to yield a first analytic result, wherein the edge-level analytic procedure is defined by an edge-level metrics manifest file,whereinthe edge analytics component is configured to send a first command to the industrial device based on the first analytic result,the queue processing component is further configured to receive a second analytic result from the cloud analytics system, wherein the second analytic result is generated based on a cloud-level analytic procedure performed by the cloud analytics system that identifies a pattern in a trend of a second subset of the industrial data indicative of a loss of position accuracy of an actuator, andthe edge analytics component is further configured to send a second command to the industrial device based on the second analytic result.
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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.
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Citations
20 Claims
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1. An edge device, comprising:
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a memory that stores executable components; 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 to yield a first analytic result, wherein the edge-level analytic procedure is defined by an edge-level metrics manifest file, wherein the edge analytics component is configured to send a first command to the industrial device based on the first analytic result, the queue processing component is further configured to receive a second analytic result from the cloud analytics system, wherein the second analytic result is generated based on a cloud-level analytic procedure performed by the cloud analytics system that identifies a pattern in a trend of a second subset of the industrial data indicative of a loss of position accuracy of an actuator, and the edge analytics component is further configured to send a second command to the industrial device based on the second analytic result. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A method for processing industrial data, comprising:
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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 to yield a first analytic result, wherein the edge-level analytic procedure is defined by an edge-level metrics manifest file; sending, by the system, a first command to the industrial device based on the first analytic result; receiving, by the system, a second analytic result from the cloud analytics system, wherein the second analytic result is generated based on a cloud-level analytic procedure performed by the cloud analytics system that identifies a pattern in a time-based trend of a second subset of the industrial data, the pattern indicative of a loss of position accuracy of an actuator; and sending, by the system, a second command to the industrial device based on the second analytic result. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17)
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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:
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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; performing an edge-level analytic procedure on a first subset of the industrial data to yield a first analytic result, wherein the edge-level analytic procedure is defined by an edge-level metrics manifest file; sending a first control instruction to the industrial device based on the first analytic result; receiving a second analytic result from the cloud analytics system, wherein the second analytic result is generated based on a cloud-level analytic procedure performed by the cloud analytics system that identifies a pattern in a trend of a second subset of the industrial data, the pattern indicative of a loss of position accuracy of an actuator; and sending a second control instruction to the industrial device based on the second analytic result. - View Dependent Claims (19, 20)
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Specification