SYSTEMS AND METHODS FOR RECOMMENDING COMPONENTS FOR AN INDUSTRIAL SYSTEM

• US 20160282854A1
• Filed: 09/30/2015
• Published: 09/29/2016
• Est. Priority Date: 03/27/2015
• Status: Active Grant

• Current Assignee: Rockwell Automation Technologies Incorporated (Rockwell Automation, Inc.)
• Original Assignee: Rockwell Automation Technologies Incorporated (Rockwell Automation, Inc.)
• Inventors: Jauquet, John J., Michalscheck, Jimi R., Michalscheck, Kelly A., Korpela, Jessica L., Reissner, Kyle K., Vasko, David A., Fordenwalt, Matthew W., Ericsson, Matthew R., Wilber, Andrew
• Granted Patent: US 10,185,309 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: F16K 31/00 Actuating devices; Operating means; Releasing devices regulating means G05D
• CPC Class Codes: F16K 35/00 Means to prevent accidental or unauthorised actuation
• CPC Class Codes: F16K 37/0025 Electrical or magnetic means F16K37/0075 takes precedence
• CPC Class Codes: G05B 19/042 using digital processors G05B19/05 takes precedence
• CPC Class Codes: G05B 19/406 characterised by monitoring or safety G05B19/19 takes precedence
• CPC Class Codes: G05B 19/4183 characterised by data acquisition, e.g. workpiece identification
• CPC Class Codes: G05B 19/4184 characterised by fault tolerance, reliability of production system
• CPC Class Codes: G05B 19/4185 characterised by the network communication
• CPC Class Codes: G05B 19/41875 characterised by quality surveillance of production
• CPC Class Codes: G05B 2219/21147 Time critical I-O shut off by I-O module, otherwise by processor
• CPC Class Codes: G05B 2219/31229 Supervisor, master, workstation controller, automation, machine control
• CPC Class Codes: G05B 2219/32368 Quality control
• CPC Class Codes: G05B 2219/39251 Autonomous distributed control, joint and link is a subsystem, communication intensive
• CPC Class Codes: G05B 2219/50193 Safety in general
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G07C 3/00 Registering or indicating the condition or the working of machines or other apparatus, other than vehicles
• CPC Class Codes: G07C 9/00309 operated with bidirectional data transmission between data carrier and locks
• CPC Class Codes: G07C 9/00896 specially adapted for particular uses
• CPC Class Codes: G07C 9/28 the pass enabling tracking or indicating presence
• CPC Class Codes: H02J 4/00 Circuit arrangements for mains or distribution networks not specified as ac or dc
• CPC Class Codes: Y02P 80/10 : Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier
• 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

In one embodiment, a tangible, non-transitory computer-readable medium includes computer instructions stored thereon. The computer instructions, when executed by a processor, may cause the processor to receive historical data associated with placing a machine in an industrial environment offline, to determine one or more recommendations for the machine, one or more parts of the machine, or both based on the historical data, to determine an authority level of one or more users requesting to place the machine offline, and to display the one or more recommendations based on the authority level of the one or more users.

Claims

1. A tangible, non-transitory computer-readable medium comprising computer instructions stored thereon, wherein the computer instructions, when executed by a processor, are configured to cause the processor to:

receive historical data associated with placing a machine in an industrial environment offline;

determine one or more recommendations for the machine, one or more parts of the machine, or both based on the historical data;

determine an authority level of one or more users requesting to place the machine offline; and

display the one or more recommendations based on the authority level of the one or more users.

2. The computer-readable medium of claim 1, wherein determining the one or more recommendations for the machine, the one or more parts of the machine, or both based on the historical data comprises:

determining whether the machine has been placed offline more than a threshold number of times within a certain time period;

determining whether the machine has been locked out more than a threshold number of times within a certain time period;

receiving other historical data associated with placing one or more other machines in the industrial environment offline, wherein the one or more other machines are similar to the machine; and

determining whether the machine has been placed offline or locked out more than the one or more other machines within a certain time period.

3. The computer-readable medium of claim 2, wherein the computer instructions, when executed by the processor, are configured to cause the processor to learn the threshold number of times based on the historical data.

4. The computer-readable medium of claim 1, wherein the one or more recommendations comprise a recommendation to service the machine or the one or more parts, a recommendation to optimize performance of the machine or the one or more parts by increasing production, reducing energy consumption, or both, a recommendation to replace the machine or the one or more parts, a price quote for a replacement machine or part, or some combination thereof.

5. The computer-readable medium of claim 1, wherein the computer instructions are configured to cause the processor to:

retrieve status information related to the machine, the one or more parts, or both, wherein the status information indicates whether the machine, the one or more parts, or both are recalled, discontinued, obsolete, or some combination thereof; and

display the status information.

6. The computer-readable medium of claim 5, wherein the computer instructions that cause the processor to display the one or more recommendations, the status information, or both are configured to cause the processor to:

capture a visual representation of a portion of a facility comprising the machine as image data;

display a first real object configured to visually represent physical features of the machine in the portion of the facility based at least in part on the image data; and

display a first virtual object superimposed on at least a portion of the first real object based at least on the one or more recommendations, the status information, or both for the machine, the one or more parts, or both.

7. The computer-readable medium of claim 5, wherein the computer instructions are configured to cause the processor to send the one or more recommendations to users with an authority level that grants purchasing permissions when the machine, the one or more parts, or both are recalled, discontinued, obsolete, or some combination thereof, wherein the one or more recommendations includes a notice of the status, a recommendation to replace the machine, the one or more parts, or both, and proper handling instructions.

8. The computer-readable medium of claim 1, wherein the computer instructions are configured to cause the processor to send the one or more recommendations based on a priority level of the one or more recommendations and the authority level of the one or more users.

9. The computer-readable medium of claim 1, wherein the computer instructions are configured to cause the processor to display the one or more recommendations to users with an authority level that grants purchasing permissions when the one or more recommendations recommend purchasing a replacement machine or one or more replacement parts.

10. The computer-readable medium of claim 1, wherein the authority levels comprises a first authority level and a second authority level, wherein the first authority level comprises more permissions than the second authority level.

11. The computer-readable medium of claim 1, wherein the instructions are configured to:

receive user identification information;

determine the authority level of the user based on the user identification information;

enable functionality based on the authority level of the user; and

wherein the functionality comprises creating a lockout tagout procedure, reading the lockout tagout procedure, updating the lockout tagout procedure, deleting the lockout tagout procedure, or some combination for a first authority level.

12. A method, comprising:

receiving, via a processor, historical data associated with placing a machine in an industrial environment offline;

determining, via the processor, one or more recommendations for the machine, one or more parts of the machine, or both based on the historical data;

determining, via the processor, an authority level of one or more users requesting to place the machine offline; and

sending, via the processor, the one or more recommendations to the one or more users based on the authority level of the one or more users.

13. The method of claim 12, wherein determining the one or more recommendations for the machine, the one or more parts of the machine, or both based on the historical data comprises:

determining, via the processor, whether the machine has been placed offline more than a threshold number of times within a certain time period;

determining, via the processor, whether the machine has been locked out more than a threshold number of times within a certain time period;

receiving, via the processor other historical data associated with placing one or more other machines in the industrial environment offline, wherein the one or more other machines are similar to the machine; and

determining, via the processor, whether the machine has been placed offline or locked out more than the one or more other machines within a certain time period.

14. The method of claim 13, comprising learning, via the processor, the threshold number of times based on the historical data.

15. The method of claim 12, wherein the one or more recommendations comprise a recommendation to service the machine or the one or more parts, a recommendation to optimize performance of the machine or the one or more parts, a recommendation to replace the machine or the one or more parts, a price quote for a replacement machine or part, or some combination thereof.

16. The method of claim 12, comprising:

retrieving status information related to the machine, the one or more parts, or both, wherein the status information indicates whether the machine, the one or more parts, or both are recalled, discontinued, obsolete, or some combination thereof; and

sending the status information to the users.

17. The method of claim 12, comprising displaying the one or more recommendations, the status information, or both by:

capturing a visual representation of a portion of a facility comprising the machine as image data;

displaying a first real object configured to visually represent physical features of the machine in the portion of the facility based at least in part on the image data; and

displaying a first virtual object superimposed on at least a portion of the first real object based at least on the one or more recommendations, the status information, or both for the machine, the one or more parts, or both.

18. An electronic device, comprising:

a processor configured to;

receive historical data associated with placing a machine in an industrial environment offline;

determine one or more recommendations for the machine, one or more parts of the machine, or both based on the historical data;

determine an authority level of one or more users, wherein the authority level grants one or more permissions to perform one or more actions related to the machine; and

display the one or more recommendations based on the authority level of the one or more users.

19. The electronic device of claim 18, wherein determining the one or more recommendations for the machine, the one or more parts of the machine, or both based on the historical data comprises:

determining whether the machine has been placed offline more than a threshold number of times within a certain time period;

determining whether the machine has been locked out more than a threshold number of times within a certain time period;

receiving other historical data associated with placing one or more other machines in the industrial environment offline, wherein the one or more other machines are similar to the machine; and

determining whether the machine has been placed offline or locked out more than the one or more other machines within a certain time period.

20. The electronic device of claim 19, wherein the processor is configured to learn the threshold number of times based on the historical data.

21. The electronic device of claim 18, wherein the one or more recommendations comprise a recommendation to service the machine or the one or more parts, a recommendation to optimize performance of the machine or the one or more parts by increasing production, reducing energy consumption, or both, a recommendation to replace the machine or the one or more parts, a price quote for a replacement machine or part, or some combination thereof.

22. The electronic device of claim 18, wherein the processor is configured to:

retrieve status information related to the machine, the one or more parts, or both, wherein the status information indicates whether the machine, the one or more parts, or both are recalled, discontinued, obsolete, or some combination thereof; and

display the status information.

23. The electronic device of claim 22, wherein displaying the one or more recommendations, the status information, or both comprises:

capturing a visual representation of a portion of a facility comprising the machine as image data;

displaying a first real object configured to visually represent physical features of the machine in the portion of the facility based at least in part on the image data; and

displaying a first virtual object superimposed on at least a portion of the first real object based at least on the one or more recommendations, the status information, or both for the machine, the one or more parts, or both.