DISCOVERABLE SERVICES

• US 20090043404A1
• Filed: 08/06/2007
• Published: 02/12/2009
• Est. Priority Date: 08/06/2007
• Status: Active Grant

• Current Assignee: Rockwell Automation Technologies Incorporated (Rockwell Automation, Inc.)
• Original Assignee: Rockwell Automation Technologies Incorporated (Rockwell Automation, Inc.)
• Inventors: Baier, John J., McGreevy, Robert J., Moor, Crisler Terrill, Ryan, Richard Lee, Rodenfels, Lance Christopher, Chao, Kevin
• Granted Patent: US 7,869,887 B2
• Time in Patent Office: Days
• US Class Current: 700/9
• CPC Class Codes: G05B 19/41865 characterised by job scheduling, process planning, material flow
• CPC Class Codes: G05B 2219/31396 Business management, production, document, asset, regulatory management, high level
• CPC Class Codes: G05B 2219/32328 Dynamic scheduling, resource allocation, multi agent negotiation
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

A goal or desired output can be stated in terms of a high-level overview in a natural language or other format. The high-level overview can be automatically partitioned into steps to be performed in order to achieve the stated goal, such as by interpreting terms within the overview, analyzing definitions, historical data or other information. Each step can be dynamically assigned to various resources distributed throughout an environment. Such resources can include agents or other machinery that are selected based on a multitude of criteria including location, availability, performance level as well as other factors. If needed, the resources can be dynamically balanced in order to achieve the desired output while mitigating wasted resources.

Claims

1. A system for automatic configuration of activities within an industrial automation environment, comprising:

an interpretation component that receives a high-level intent and partitions the high-level intent into a first activity and at least a second activity; and

a distributed network control component that assigns responsibility of completing the first activity to a first agent and the at least a second activity to a second agent, the first agent and second agent are located in an industrial automation environment.

2. The system of claim 1, the distributed network control component further monitors performance of the first activity and the at least a second activity.

3. The system of claim 2, the distributed network control component reassigns the first activity if performance of the first activity does not meet a predetermined performance expectation level.

4. The system of claim 1, the interpretation component receives the high-level intent in a natural language format.

5. The system of claim 1, further comprising a parse module that accesses a historical information repository to obtain information relating to a previously performed action that is similar to the high-level intent.

6. The system of claim 1, further comprising a parse module that accesses a data repository that retains data relating to the high-level intent.

7. The system of claim 1, further comprising an assignment module that accesses a plurality of agents to ascertain for each agent at least one of an availability, a location, a provided resource or combinations thereof.

8. The system of claim 1, the first agent and the at least a second agent communicate directly to each other.

9. The system of claim 1, further comprising an observation module that monitors the first activity and the at least a second activity and notifies an assignment module if there is a problem detected.

10. The system of claim 9, the assignment module dynamically reassigns responsibility of completing the first activity or the at least a second activity if a problem was detected.

11. The system of claim 1, further comprising a machine-learning component that facilitates automation of one or more system component.

12. A method for providing resources and completion of an output expressed as a high-level request, comprising:

receiving a high-level request;

partitioning the high-level request into a plurality of sub-processes;

assigning the plurality of sub-processes to agents, the agents autonomously perform the actions associated with the sub-processes; and

monitoring a performance of the agents and reassigning an action if an agent is not performing at a predetermined level of expectation.

13. The method of claim 12, further comprises identifying agents that can be reassigned from other responsibilities to perform an action associated with at least one of the plurality of sub-processes.

14. The method of claim 12, further comprises selectively enabling the agents to perform the assigned sub-process.

15. The method of claim 12, assigning the plurality of sub-processes to agents, comprising:

determining which agents are available to perform the sub-processes; and

identifying agents that can be reassigned from other responsibilities.

16. The method of claim 12, assigning the plurality of sub-processes to agents comprises determining a location of each agent and assigning the sub-processes based in part on the location of each agent.

17. The method of claim 12, assigning the plurality of sub-processes to agents comprises discovering services performed by each agent.

18. The method of claim 12, further comprising accessing a repository for historical data associated with the high-level request.

19. A computer executable system that facilitates discovery of services for completion of a stated goal, comprising:

means for receiving a stated goal expressed in a natural language format;

means for parsing the stated goal into at least two process steps;

means for selectively assigning the at least two process steps to two or more intelligent agents; and

means for dynamically redistributing at least one of the at least two process steps to a different intelligent agent if one of the two or more intelligent agents can no longer perform the assignment.

20. The computer executable system of claim 19, further comprising:

means for interpreting a natural language format of the stated goal;

means for locating the two or more intelligent agents within an industrial environment; and

means for monitoring a performance of the two or more intelligent agents.