DISCRETE RESOURCE MANAGEMENT

• US 20100274611A1
• Filed: 04/24/2009
• Published: 10/28/2010
• Est. Priority Date: 04/24/2009
• Status: Active Grant

• Current Assignee: Rockwell Automation Technologies Incorporated (Allen-Bradley Co., Inc.)
• Original Assignee: Rockwell Automation Technologies Incorporated (Allen-Bradley Co., Inc.)
• Inventors: Walker, Marcia Elaine, Kaufman, Philip John
• Granted Patent: US 10,223,167 B2
• Time in Patent Office: Days
• US Class Current: 705/8
• CPC Class Codes: G06F 16/22 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/907 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: G06F 9/5061 Partitioning or combining of resources
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/063 Operations research, analysis or management
• CPC Class Codes: Y02D 10/00 Energy efficient computing, e.g. low power processors, power management or thermal management
• 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 90/82 Energy audits or management systems therefor
• CPC Class Codes: Y02P 90/84 Greenhouse gas [GHG] management systems

Abstract

Discrete resource tracking systems (and corresponding methodologies) that collect, tag and store resource consumption and usage values associated with industrial environment processes are provided. The specification can track water, air, gas, electricity, or steam consumption and usage view of a discrete (or batch) processes. Emissions and/or effluents associated with processes and sub-processes can also be collected, tagged and stored as desired. These stored resource consumption and usage and/or emissions and/or effluents data elements can be used for a variety of purposes including, but not limited to, simulation, planning, forecasting, valuating, optimizing, etc.

Claims

1. A system that facilitates discrete resource management, comprising:

a collection component that obtains a plurality of process-related resource data elements; and

a marking component that tags each of the process-related resource data elements with descriptive data, wherein the descriptive data relates to an industrial environment.

2. The system of claim 1, wherein each of the process-related resource elements is associated with a defined process within the industrial environment.

3. The system of claim 1, further comprising a storage component that facilitates retaining the tagged process-related data elements.

4. The system of claim 3, wherein the storage is located in at least one of a local, remote, distributed or cloud-based store.

5. The system of claim 3, further comprising an indexing component that records location of each of the tagged process-related data elements within a store.

6. The system of claim 1, further comprising a detection component that monitors the industrial environment to gather the process-related resource data elements.

7. The system of claim 6, wherein the detection component comprises a plurality of autonomous sensor components.

8. The system of claim 1, further comprising an association component that associates each of the process-related resource data elements with the descriptive data based at least upon production level.

9. The system of claim 1, further comprising:

an analysis component that evaluates contextual factors related to each of the process-related resource data elements; and

a tagging component that marks each of the process-related data elements with a subset of the contextual factors.

15. The computer-implemented method of claim 1, further comprising relating a subset of the process-related contextual data elements to each of the process-related resource elements.

10. A computer-implemented method for discrete resource management on an industrial environment, comprising:

employing a processor that executes computer executable instructions stored on a computer readable storage medium to implement the following acts;

receiving a plurality of process-related resource data elements;

receiving a plurality of process-related contextual data elements; and

marking a subset of the process-related resource data elements with a subset of the process-related contextual data elements.

11. The computer-implemented method of claim 10, further comprising:

monitoring a plurality of processes within the industrial environment; and

collecting the plurality of process-related resource data elements from a subset of the processes.

12. The computer-implemented method of claim 10, further comprising:

monitoring a plurality of processes within the industrial environment; and

collecting the plurality of process-related contextual data elements from a subset of the processes.

13. The computer-implemented method of claim 10, further comprising storing the plurality of marked process-related resource data elements.

14. The computer-implemented method of claim 13, further comprising indexing each of the plurality of marked process-related resource data elements.

16. A computer-executable system, comprising:

means for obtaining resource data that relates to a process within an industrial environment;

means for obtaining contextual data that relates to the process;

means for associating a subset of the resource data with a subset of the contextual data.

17. The computer-executable system of claim 16, further comprising means for tagging the subset of resource data with the associated contextual data.

18. The computer-executable system of claim 16, further comprising means for storing the tagged data in at least one of a local, remote, distributed or cloud-based store.

19. The computer-executable system of claim 16, further comprising means for indexing the tagged data.

20. The computer-executable system of claim 16, further comprising means for monitoring the process to facilitate obtaining at least one of the energy or contextual data.