Risk assessment for industrial systems using big data

• US 10,026,049 B2
• Filed: 11/22/2013
• Issued: 07/17/2018
• Est. Priority Date: 05/09/2013
• Status: Active Grant

• Current Assignee: Rockwell Automation Technologies Incorporated (Allen-Bradley Co., Inc.)
• Original Assignee: Rockwell Automation Technologies Incorporated (Allen-Bradley Co., Inc.)
• Inventors: Asenjo, Juan L., Strohmenger, John, Nawalaniec, Stephen Thomas, Hegrat, Bradford Henry, Harkulich, Joseph A., Korpela, Jessica Lin, Wright, Jenifer Rydberg, Hessmer, Rainer, Dyck, John, Hill, Edward Alan, Conti, Salvatore T.
• Primary Examiner(s): Coupe, Anita
• Assistant Examiner(s): Stewart, Crystol
• Application Number:
  US14/087,821
• Publication Number:
  US 20140337086A1
• Time in Patent Office: 1,698 Days
• CPC Class Codes: G06F 3/0635 by changing the path, e.g. traffic rerouting, path reconfiguration
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/0635 Risk analysis of enterprise or organisation activities
• CPC Class Codes: H04L 41/0896 Bandwidth or capacity management, i.e. automatically increasing or decreasing capacities flow or congestion control using dynamic resource allocation, e.g. in-call renegotiation, H04L47/76
• CPC Class Codes: H04L 63/14 for detecting or protecting against malicious traffic
• CPC Class Codes: H04L 63/1433 Vulnerability analysis
• CPC Class Codes: Y02P 90/80 Management or planning

Abstract

A cloud-based risk assessment service collects industrial data from multiple relevant and connected sources for storage and analysis on a cloud platform. The service analyzes gathered data from internal and external sources and customers across different industries to identify operational trends as a function of industry type, application type, equipment in use, device configurations, and other such variables. Based on the analysis, the risk assessment service identifies risk factors inherent in a customer'"'"'s particular industrial enterprise. The cloud-based system generates a risk profile for the customer that identifies the determined risks and recommends risk aversion strategies based on the customer'"'"'s specific profile, compared to industry standards, product information, internal business expectations, external regulatory bodies, and/or past performance. Risk profiles are tailored for both plant-level users and business-level users to provide intelligent strategies to improve performance and prevent avoidable losses.

Claims

1. A system for performing risk assessment on an industrial enterprise, comprising:

a memory that stores executable components;

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

a device interface component configured to collect, via one or more wireless networks, data from a set of industrial devices of an industrial control system and store the data on a cloud platform, wherein the data comprises at least process data relating to an industrial process appended with device data identifying the industrial devices and customer data comprising a customer identifier of an industrial enterprise from which the data is collected;

a risk assessment component configured to

perform a collective analysis on the data and aggregated data stored on the cloud platform in association with one or more other customer identifiers of one or more other industrial enterprises,

identify, based on a result of the collective analysis and the data model, an operational trend as a function of an industry type, an industrial application type, and an industrial asset configuration, and

generate a risk profile identifying one or more risk factors for the industrial control system based on a data model of the industrial control system and a comparison of the data from the set of industrial control devices with the operational trend, wherein the one or more risk factors comprise at least a risk that data traffic through a network infrastructure device installed on a plant network at which the industrial control system resides will exceed a data traffic capacity of the network infrastructure device; and

a client interface component configured to send information contained in the risk profile to one or more client devices as risk assessment information, the risk assessment information rendering the one or more risk factors on the one or more client devices,

wherein the risk assessment component reconfigures the network infrastructure device to cause the network infrastructure device to redistribute the data traffic on the plant network based on identification of the risk that the data traffic will exceed the data traffic capacity.

2. The system of claim 1, wherein the device interface component is further configured to store the data on the cloud platform in association with the customer identifier associated with an owner of the industrial control system.

3. The system of claim 1, wherein the risk assessment component is further configured to generate risk aversion data specifying one or more risk aversion strategies for mitigating at least one of the one or more risk factors based on the result of the collective analysis.

4. The system of claim 1, wherein the device interface component is further configured to classify the data according to at least one of a device class, a process class, an asset class, or a system class.

5. The system of claim 1, wherein the device interface component is further configured to collect multi-enterprise data from a plurality of industrial enterprises associated with the one or more other customer identifiers and to store the multi-enterprise data on the cloud platform as the aggregated data.

6. The system of claim 5, wherein the risk assessment component is further configured to identify, based on the result of the collective analysis, the operational trend as a further function of at least one of an equipment type, an industrial device configuration setting, a firmware version, or a software version.

7. The system of claim 5, wherein the risk assessment component is further configured to generate an equipment compatibility matrix based on another result of the collective analysis, and identify the one or more risk factors based at least in part on a comparison of the data with the equipment compatibility matrix, wherein the equipment compatibility matrix records knowledge of compatibility between industrial devices.

8. The system of claim 5, wherein the device management component is configured to identify the one or more risk factors based on correlation of the data model with the aggregated data.

9. The system of claim 1, wherein the one or more risk factors further comprise at least one of a risk of device failure, a risk of degraded system performance, a risk of inventory shortage, a risk associated with loss of the network infrastructure device on the plant network, a risk of device incompatibility, or a risk of lost revenue opportunity.

10. The system of claim 1, wherein the risk assessment information is configured to cause the one or more client devices to render the one or more risk factors organized according to device-level risks and production-area-level risks.

11. A method for identifying risk factors in an industrial system, comprising:

collecting, by a system comprising at least one processor, industrial data from devices of an industrial automation system via one or more wireless networks;

associating, by the system, the industrial data with device data identifying the devices, and a customer identifier of an industrial enterprise associated with the industrial automation system, wherein the associating yields modified data;

storing, by the system, the modified data in cloud-based storage;

performing, by the system, a collective analysis on the modified data and aggregated data stored on the cloud platform, wherein the aggregated data is associated with one or more other customer identifiers of one or more other industrial enterprises, and wherein the performing comprises identifying, based on a result of the collective analysis, an operational trend as a function of an industry type, a type of industrial application, and a configuration of one or more of the devices;

determining, by the system, at least one risk factor inherent in the industrial automation system based on a data model of the industrial automation system and a comparison of the industrial data with the operational trend, the at least one risk factor comprising at least a risk that data traffic through a network infrastructure device installed on a plant network at which the industrial automation system resides will exceed a data traffic capacity of the network infrastructure device;

sending, by the system via at least one of the one or more wireless networks, report data identifying the at least one risk factor to a client device, wherein the report data causes the client device to render information about the at least one risk factor; and

reconfiguring, by the system, the network infrastructure device to cause the network infrastructure device to redistribute the data traffic on the plant network based on identification of the risk that the data traffic will exceed the data traffic capacity.

12. The method of claim 11, wherein the storing comprises storing the modified data in association with a customer profile associated with the industrial enterprise.

13. The method of claim 11, further comprising:

determining, by the system based on the result of the collective analysis, at least one risk mitigation strategy predicted to reduce or eliminate the at least one risk factor; and

generating, by the system, the report data to identify the at least one risk factor and the at least one risk mitigation strategy.

14. The method of claim 11, wherein the determining the at least one risk factor further comprises determining at least one of a risk of device failure, a risk of degraded system performance, a risk of inventory shortage, a risk associated with loss of the network infrastructure device on the plant network, a risk of device incompatibility, or a risk of lost revenue opportunity.

15. The method of claim 11, further comprising

collecting, by the system as the aggregated data, multi-enterprise data from multiple industrial systems associated with respective industrial enterprises,

wherein the performing the collective analysis further comprises analyzing, by the system, the aggregated data to identify the operational trend as a further function of at least one of an equipment type, an industrial device configuration setting, a firmware version, or a software version.

16. The method of claim 11, further comprising:

generating, by the system, an equipment compatibility matrix based on another result of the collective analysis, wherein the equipment compatibility matrix records knowledge of compatibility between industrial devices; and

determining, by the system, the at least one risk factor based at least in part on a comparison of the industrial data with the equipment compatibility matrix.

17. The method of claim 11, wherein the report data causes the client device to render the information about the at least one risk factor organized according to device-level risks and production-area-level risks.

18. A non-transitory computer-readable medium having stored thereon executable instructions that, in response to execution, cause a computing system to perform operations, the operations comprising

collecting, via one or more wireless networks, industrial data from a first industrial asset associated with a first industrial enterprise;

storing the industrial data on a cloud platform in association with an identity of the first industrial asset and a first customer identifier of the first industrial enterprise;

collectively analyzing the industrial data with multi-enterprise data collected from one or more second industrial assets associated with respective one or more second industrial enterprises, the multi-enterprise data stored on the cloud platform in association with one or more second customer identifiers of the one or more second industrial enterprises;

identifying, based on a result of the collectively analyzing, an operational trend as a function of an industry type, an industrial application type, and an industrial asset configuration;

identifying one or more risk factors associated with the first industrial asset based on a data model associated with the first industrial enterprise and a comparison of the industrial data from the first industrial asset with the operational trend, wherein the identifying the one or more risk factors comprises identifying at least a risk that data traffic through a network infrastructure device of a plant network of the first industrial enterprise will exceed a data traffic capacity of the network infrastructure device;

rendering information relating to the one or more risk factors on a client device; and

in response to identification of the risk that the data traffic will exceed the data traffic capacity, reconfiguring the network infrastructure device to redistribute the data traffic on the plant network.

19. The non-transitory computer-readable medium of claim 18, wherein the information comprises a risk assessment report that identifies the one or more risk factors and one or more risk aversion strategies for reducing or eliminating the one or more risk factors.

20. The non-transitory computer-readable medium of claim 18, wherein the identifying the one or more risk factors further comprises identifying at least one of a risk of device failure, a risk of degraded system performance, a risk of inventory shortage, a risk associated with loss of a network infrastructure device on a plant network, a risk of device incompatibility, or a risk of lost revenue opportunity.