System and method for dynamic multi-objective optimization of machine selection, integration and utilization

• US 8,417,360 B2
• Filed: 09/30/2008
• Issued: 04/09/2013
• Est. Priority Date: 08/10/2001
• Status: Active Grant

• Current Assignee: Rockwell Automation Technologies Incorporated (Allen-Bradley Co., Inc.)
• Original Assignee: Rockwell Automation Technologies Incorporated (Allen-Bradley Co., Inc.)
• Inventors: Sugars, Michael Eugene, Baier, John J., Discenzo, Frederick M., Sustaeta, Angel, Lin, Ka-Hing, Snyder, Ric, Theron, John Christopher, Funderburk, Mark
• Primary Examiner(s): ORTIZ RODRIGUEZ, CARLOS R
• Application Number:
  US12/242,546
• Publication Number:
  US 20090204234A1
• Time in Patent Office: 1,652 Days
• Field of Search: 700/28, 700/29, 700/32, 700/33, 705/7.12
• US Class Current: 700/28
• CPC Class Codes: G05B 13/024 in which a parameter or coefficient is automatically adjusted to optimise the performance
• CPC Class Codes: G05B 13/0265 the criterion being a learning criterion
• CPC Class Codes: G05B 13/0285 using neural networks and fuzzy logic
• CPC Class Codes: G05B 17/02 electric
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: H04L 67/125 involving control of end-device applications over a network
• CPC Class Codes: Y02P 90/82 Energy audits or management systems therefor

Abstract

Systems and methodologies are provided for controlling a process having computer-controlled equipment, which provide for optimized process performance according to one or more performance criteria, such as efficiency, component life expectancy, safety, emissions, noise, vibration, operational cost, or the like. The systems and methods provide for employing machine diagnostic and/or prognostic information in connection with optimizing an overall business operation over a time horizon.

Claims

1. A system comprising:

a memory having stored thereon computer-executable components for implementing the system, including;

a modeling component configured to construct model data representing a production model of a facility, the production model comprising one or more sub-models of a production process that model a source of a factor of production and a sink of the factor of production, and determine first data representing an operating strategy for the production process that satisfies at least two constraints identified by the production model, wherein the at least two constraints are associated with at least one business-level objective and at least one plant-level objective relating to an industrial machine, and wherein the factor of production is at least energy;

an energy optimization component configured to perform an analysis of the operating strategy in view of an energy demand model of the production process and an energy supply model of the production process, and determine second data representing an energy generating strategy based on the analysis;

a capacity management component configured to perform a profiling of the at least two constraints based in part on at least one of a current operation of the industrial machine or a predicted operation of the industrial machine,

a visualization component configured to render comparison data representing a comparison of a theoretical capacity and a current production rate of the production process; and

wherein the modeling component is further configured to determine a probability of achieving the at least one business-level objective or the at least one plant-level objective based on an analysis of the production model and to set third data representing an inventory target based on the first data and the second data, and wherein the inventory target controls an asset utilization of the production process; and

a processor, coupled to the memory, configured to facilitate execution of the computer-executable components.

2. The system of claim 1, wherein the visualization component is further configured to render a visual instrumentation of at least one of the one or more sub-models or the production model.

3. The system of claim 1, wherein the one or more sub-models correspond to respective one or more factors of production including the factor of production, wherein the one or more factors of production include at least one of energy, quality throughput, noise, capacity, or life cycle cost.

4. The system of claim 1, wherein the one or more sub-models model one or more of a historical customer order, an order size, an order accuracy, or an order change.

5. The system of claim 1, wherein the capacity management component is further configured to at least one of order a material or modify an inventory management variable based at least in part on the inventory target.

6. The system of claim 1, wherein the capacity management component is further configured to determine a potential economic gain associated with setting the third data based on the production model.

7. The system of claim 1, wherein the energy supply model of the production process comprises at least one economic sub-model that models a financial profile of an energy-generating asset associated with the production process.

8. The system of claim 7, wherein the at least one economic sub-model models the financial profile based at least in part on data from a financial system.

9. They system of claim 7, wherein the at least one economic sub-model models the financial profile based on at least one of a generating capacity, an efficiency curve, a reliability measure, or an operating cost associated with the energy-generating asset.

10. The system of claim 1, wherein the second data further represents an energy usage strategy.

11. The system of claim 1, wherein the modeling component is further configured to update the model data in accordance with updated production data.

12. A method employed in an industrial automation environment, comprising:

constructing production model data representing a production model of a facility, the production model comprising one or more sub-models of a source of a factor of production and a sink of the factor of production for a production process, wherein the factor of production is at least energy;

generating operating strategy data representing an operating strategy for the production process that satisfies at least two constraints identified in the production model data, wherein the at least two constraints are associated with at least one business-level objective and at least one plant-level objective relating to an industrial machine;

determining energy generating strategy data representing an energy generating strategy based on an analysis of the operating strategy data based on energy supply and demand model data representing an energy supply model of the production process and an energy demand model of the production process;

profiling the at least two constraints based in part on at least one of a current operation of the industrial machine or a predicted operation of the industrial machine;

rendering comparison data representing a comparison of a theoretical capacity and a current production rate of the production process;

determining a probability of achieving the at least one business-level objective or the at least one plant-level objective based on an analysis of the production model; and

controlling inventory target data that controls an asset utilization of the production process based on the operating strategy data and the energy generating strategy data.

13. The method of claim 12, further comprising manipulating the production model based at least in part on a prospective attribute associated with at least one of the source of the factor of production or the sink of the factor of production.

14. The method of claim 12, further comprising creating a visual instrumentation that graphically renders information relating to at least one of the one or more sub-models or the production model.

15. The method of claim 12, wherein the constructing comprises constructing the one or more sub-models for respective one or more factors of production.

16. The method of claim 12, wherein the constructing comprises modeling one or more of a historical customer order, an order size, an order accuracy, or an order change.

17. The method of claim 12, wherein the determining the energy generating strategy data includes determining the energy generating strategy based at least in part on a financial profile of an energy-generating asset that serves as an energy source for the production process.

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

modeling, with first data, a source of a factor of production and a sink of the factor of production yielding a production model, wherein the source of the factor of production and the sink of the factor of production are associated with one or more sub-models of a production process and the factor of production comprises at least energy;

determining second data representing an operating strategy for the production process determined to satisfy at least two constraints identified by the production model of the first data, wherein the at least two constraints comprise at least one business-level objective and at least one plant-level objective relating to an industrial machine;

determining third data representing an energy generating strategy for the operating strategy based on analysis of energy demand model data representing an energy demand model of the production process and energy supply model data representing an energy supply model of the production process;

profiling the at least two constraints based in part on at least one of a current operation of the industrial machine or a predicted operation of the industrial machine;

displaying comparison data representing a comparison between a theoretical capacity and a current production rate of the production process;

determining a probability of achieving a given economic return based on an analysis of the production model; and

determining fourth data representing an inventory target that controls an asset utilization of the production process based on the operating strategy of the second data and the energy generating strategy of the third data.

19. The non-transitory computer-readable medium of claim 18, the operations further including generating a visual instrumentation that displays a graphical representation of the production model.

20. The non-transitory computer-readable medium of claim 18, wherein the determining the third data includes determining the energy generating strategy based at least in part on a financial profile of an energy-generating asset that provides energy to the production process.