Workflow tracking and identification using an industrial monitoring system

• US 10,401,839 B2
• Filed: 03/21/2017
• Issued: 09/03/2019
• Est. Priority Date: 09/26/2016
• Status: Active Grant

• Current Assignee: Rockwell Automation Technologies Incorporated (Allen-Bradley Co., Inc.)
• Original Assignee: Rockwell Automation Technologies Incorporated (Allen-Bradley Co., Inc.)
• Inventors: Billi-Duran, Sharon M., Como, Christopher W., Gray, Edward A., Reissner, Kyle K., Walter, Jonathan D., Singhai, Mohit, Reichard, Douglas J., Sandler, Scott N., Bliss, Ronald E., Pantaleano, Michael J., Cahalane, Ryan, Korpela, Jessica L., McCleave, Jr., Bruce T.
• Primary Examiner(s): Lee, Thomas C
• Assistant Examiner(s): Sharmin, Anzuman
• Application Number:
  US15/465,246
• Publication Number:
  US 20180088564A1
• Time in Patent Office: 896 Days
• CPC Class Codes: G05B 19/41865 characterised by job scheduling, process planning, material flow
• CPC Class Codes: G05B 2219/31449 Monitor workflow, to optimize business, industrial processes
• CPC Class Codes: G05B 2219/31464 Select between different models corresponding to diff process control configurations
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

An industrial workflow tracking and identification system captures optimal employee workflows for addressing maintenance issues or operating industrial systems, and renders these workflows at appropriate times in order to guide operators and maintenance personnel through optimal sequences for carrying out operations or addressing maintenance issues. The system monitors and indexes both plant-wide system data as well as employee behaviors, and identifies correlations between operational outcomes and user workflows. In this way, the system tracks and captures optimal employee workflows for addressing particular maintenance issues, performing certain procedures, or achieving preferred production outcomes. By identifying and recording correlations between observed employee behaviors and production outcomes, the system creates a library of best practices that can be used as a training tool, as well as to provide substantially real-time guidance to maintenance staff and operators in connection with solving a problem or performing a task.

Claims

1. A system for learning industrial workflows, comprising:

a memory that stores executable components;

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

a discovery component configured to collect industrial data items from multiple data sources of an industrial facility, and to collect behavioral data from one or more client devices within the industrial facility, the behavioral data representing behaviors of one or more users associated with the one or more client devices;

a workflow generation component configured to generate and store workflow data based on a correlation of the industrial data items with the behavioral data, wherein the workflow data defines a sequence of user actions for performing a task relating to an industrial system; and

a notification component configured to send the workflow data to client devices associated with selected user identities in response to a determination by a monitoring component that a performance metric of the industrial system has deviated from a defined tolerance range, wherein the workflow data is rendered on the respective client devices as a workflow conveying the sequence of user actions, and the workflow comprises controls configured to permit selected steps of the workflow to be hidden,

wherein

the workflow generation component is further configured to,

in response to receipt, from a client device associated with a user identity of the selected user identities, of an indication of selected steps of the workflow to be hidden, generate personalized workflow data comprising the workflow data with the selected steps omitted, and

save the personalized workflow data in association with the user identity, and

the notification component is further configured to, in response to a subsequent determination by the monitoring component that the performance metric of the industrial system has deviated from the defined tolerance range, send the personalized workflow data to the client device associated with the user identity.

2. The system of claim 1, the executable components further comprising an indexing component configured to record the industrial data items and behavioral data in a federated data model.

3. The system of claim 1, wherein the behavioral data comprises at least one of user location data, user identity data, data indicative of an interaction between a user and the industrial system, biometric data, or multimedia data collected by the one or more client devices.

4. The system of claim 1, wherein the workflow generation component is further configured to, based on analysis of the behavioral data and at least a subset of the industrial data items, identify a sequence of interactions with the industrial system that causes the performance metric of the industrial system to satisfy a defined criterion, and to record the sequence of interactions in the workflow data as the sequence of user actions.

5. The system of claim 4, wherein the workflow generation component is further configured to tag the workflow data with an identifier of the industrial system.

6. The system of claim 1, further comprising a notification component configured to select the user identities based on at least one of an identity of the industrial system, a role associated with at least one of the user identities, or a current location determined for at least one of the user identities.

7. The system of claim 1, wherein the workflow data comprises instructions that, in response to execution on the client devices, cause the client devices to render at least one of alphanumeric instructions or graphical instructions for performing the sequence of user actions.

8. The system of claim 1, wherein the workflow generation component is further configured to identify a type of a client device of the client devices, and to customize the workflow data for rendering of the workflow in accordance with a capability of the type of the client device.

9. The system of claim 8, wherein the workflow generation component is further configured to, in response to determining that the type of the client device is a wearable computer, customize the workflow data to render the workflow as an augmented reality presentation.

10. The system of claim 1, wherein the system is configured to execute on a cloud platform.

11. The system of claim 1, wherein

the discovery component is further configured to identify a message log stored in a database comprising an instant message discussion or an email discussion between two or more users in connection with performing the task relating to the industrial system, and

the workflow generation component is further configured to include the message log as part of the workflow data.

12. The system of claim 1, wherein the device interface component is further configured to, during display of a step of the workflow corresponding to a prescribed user action, monitor and analyze user data collected from at least one of the client device or the industrial system to confirm that the prescribed user action is being performed, wherein the user data comprises at least one of a location of the client device or orientation data identifying a current orientation of the client device.

13. A method for creating and delivering industrial workflows, comprising:

collecting, by a system comprising at least one processor, industrial data from an automation system of a plant facility;

collecting, by the system, behavioral data from one or more client devices within the plant facility, the behavioral data representing behaviors of one or more users associated with the one or more client devices;

correlating, by the system, the behavioral data with at least a subset of the industrial data;

generating, by the system, workflow data based on the correlating, wherein the workflow data defines a sequence of user actions for performing a task relating to the automation system;

in response to determining that a performance metric of the automation system has deviated from a tolerance range, rendering, by the system, the workflow data on client devices associated with selected users, wherein the rendering comprises;

rendering the workflow data as a workflow indicating the sequence of user actions, and

rendering controls that permit selected steps of the workflow to be hidden;

in response to receiving, from a client device associated with a user of the selected users, an indication of one or more selected steps of the workflow to be hidden,

generating, by the system, personalized workflow data comprising the workflow data with the one or more selected steps omitted, and

saving, by the system, the personalized workflow data in association with the user; and

in response to a subsequent determining that the performance metric of the automation system has deviated from the tolerance range, rendering, by the system, the personalized workflow data on the client device associated with the user.

14. The method of claim 13, wherein the collecting comprises indexing the industrial data and behavioral data in a federated data model.

15. The method of claim 13, wherein the collecting the behavioral data comprises collecting at least one of user location data, user identity data, data indicative of an interaction between a user and the automation system, biometric data, or multimedia data collected by the one or more client devices.

16. The method of claim 13, wherein the generating the workflow data comprises:

based on the correlating, identifying a sequence of user interactions with the automation system that causes the performance metric of the automation system to satisfy a defined criterion; and

recording the sequence of interactions as the workflow data.

17. The method of claim 16, further comprising storing, by the system, the workflow data and the personalized workflow data in association with an identifier of the automation system.

18. The method of claim 17, further comprising selecting the selected users based on at least one of an identity of the automation system, a role associated with the user, or a determined current location associated with the user.

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

collecting industrial data items generated by industrial devices of an industrial system;

collecting behavioral data from one or more client devices within an industrial facility associated with the industrial system, the behavioral data representing behaviors of one or more users associated with the one or more client devices;

analyzing the behavioral data and at least a subset of the industrial data items;

generating workflow data based on a result of the analyzing, wherein the workflow data defines a sequence of user actions for performing a task relating to the industrial system;

in response to determining that a performance indicator of the industrial system does not satisfy a performance criterion, rendering the workflow data on client devices associated with selected users, wherein the rendering comprises;

displaying the workflow data as a workflow indicating the sequence of user actions, and

displaying controls that allow selected steps of the workflow to be hidden;

in response to receiving, from a client device associated with a user of the selected users, an indication of one or more selected steps of the workflow to be hidden,

generating personalized workflow data based on the workflow data with the one or more selected steps omitted, and

saving the personalized workflow data in association with the user; and

in response to a subsequent determining that the performance metric of the industrial system does not satisfy the performance criterion, rendering the personalized workflow data on the client devices associated with the user.

20. The non-transitory computer-readable medium of claim 19, wherein the collecting the behavioral data comprises collecting at least one of user location data, user identity data, data indicative of an interaction between a user and the industrial system, biometric data, or multimedia data collected by the one or more client devices.