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Title: US7509235: Method and system for forecasting reliability of assets
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Country: US United States of America

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Inventor: Bonissone, Piero Patrone; Schenectady, NY, United States of America
Aggour, Kareem Sherif; Niskayuna, NY, United States of America
Varma, Anil; Clifton Park, NY, United States of America

Assignee: General Electric Company, Niskayuna, NY, United States of America
other patents from GENERAL ELECTRIC COMPANY (218550) (approx. 30,796)
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Published / Filed: 2009-03-24 / 2005-08-31

Application Number: US2005000216940

IPC Code: Advanced: G06F 11/30;
Core: more...

ECLA Code: G06Q40/00C;

U.S. Class: 702/184; 702/181; 702/034;

Field of Search: 702/033-35,81-84,177,179-184 700/079-81 714/001,47

Government Interest: STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH AND DEVELOPMENT
    The U.S. Government may have certain rights in this invention pursuant to contract number 621-004-S-0031 awarded by the Defense Advanced Research Projects Agency (DARPA) of the Department of Defense (DoD).

Priority Number:
2005-08-31  US2005000216940

Abstract:     A method and system of forecasting reliability of an asset is provided. The method includes identifying peer units of the asset by using selected criteria, performing a search for the peer units based upon the selected criteria, and constructing local predictive models using the peer units. The method also includes estimating the future behavior of the asset based upon the local predictive models and dynamically updating the local predictive models to reflect at least one change in the criteria.

Attorney, Agent or Firm: Asmus, Scott J. ;

Primary / Asst. Examiners: Barbee, Manuel L;

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First Claim:
Show all 20 claims
    1. A method of forecasting remaining useful life of an asset, comprising:

identifying peer units of the asset from a set of potential peer units by using selected criteria and performing a search for the peer units based upon the selected criteria;

using a first evolutionary algorithm for processing a defined degree of closeness between said peer units and said asset;

constructing local predictive models using the peer units;

estimating the remaining useful life of the asset based upon the local predictive models; and

updating the local predictive models to reflect at least one change in the criteria using a second evolutionary algorithm.



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U.S. References: Go to Result Set: All U.S. references   |  No patents reference this one   |   Backward references (17)   |   Citation Link

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Patent  Pub.Date  Inventor Assignee   Title
Buy PDF- 12pp US4336595  1982-06 Adams et al.  Lockheed Corporation Structural life computer
Buy PDF- 18pp US4719587  1988-01 Berte  Combustion Engineering, Inc. Future behavior equipment predictive system
Buy PDF- 14pp US6564213  2003-05 Ortega et al.  Amazon.com, Inc. Search query autocompletion
Buy PDF- 15pp US6567752  2003-05 Cusumano et al.  The Penn State Research Foundation General method for tracking the evolution of hidden damage or other unwanted changes in machinery components and predicting remaining useful life
Buy PDF- 41pp US6847854  2005-01 Discenzo  Rockwell Automation Technologies, Inc. System and method for dynamic multi-objective optimization of machine selection, integration and utilization
Buy PDF- 12pp US7103509  2006-09 Shah et al.  General Electric Company System and method for predicting component failures in large systems
Buy PDF- 17pp US7181364  2007-02 Lancaster et al.  Network Appliance, Inc. Automated detecting and reporting on field reliability of components
Buy PDF- 14pp US20020019826A1  2002-02 Tan   Method and system for user-configurable clustering of information
Buy PDF- 14pp US20020128751A1  2002-09 Engstrom et al.   System and method for real-time recognition of driving patters
Buy PDF- 32pp US20030158803A1  2003-08 Darken et al.   System and method for estimation of asset lifetimes
Buy PDF- 24pp US20030184307A1  2003-10 Kozlowski et al.   Model-based predictive diagnostic tool for primary and secondary batteries
Buy PDF- 56pp US20030187701A1  2003-10 Bonissone et al.   Process for optimization of insurance underwriting suitable for use by an automated system
Buy PDF- 56pp US20030187702A1  2003-10 Bonissone et al.   System for optimization of insurance underwriting suitable for use by an automated system
Buy PDF- 20pp US20040039499A1  2004-02 Felke et al.   Relational database for maintenance information for complex systems
Buy PDF- 14pp US20040210545A1  2004-10 Branke et al.   Method and system for implementing evolutionary algorithms
Buy PDF- 16pp US20060247798A1  2006-11 Subbu et al.   Method and system for performing multi-objective predictive modeling, monitoring, and update for an asset
Buy PDF- 17pp US20070088550A1  2007-04 Filev et al.   Method for predictive maintenance of a machine
       
Foreign References: None

Other References:
  • Article entitled “Predicting the Best Units within a Fleet: Prognostic Capabilities Enabled by Peer Learning, Fuzzy Similarity, and Evolutionary Design Process” published in the Proceedings of 2005 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE'05); May 22-25, 2005.
  • K. Aggour et al., “Selecting the Best Units in a Fleet: Prediction from Equipment Peers,” Proc. 7th Int. Conference on Case-Based Reasoning (ICCBR) 2005, Chicago, IL, Aug. 23-26.
  • P. Bonissone et al., “An Evolutionary Process for Designing and Maintaining a Fuzzy Instance-based Model (FIM),” Proc. First workshop of Genetic Fuzzy Systems (GFS 2005), Granada Spain, Mar. 17-19.
  • P. Bonissone, “The life cycle of a fuzzy knowledge-based classifier,” Proc. North American Fuzzy Information Processing Society (NAFIPS 2003), Chicago, IL, Aug. 2003, pp. 488-494.
  • P. Bonissone et al., “Evolutionary Optimization of Fuzzy Decision Systems for Automated Insurance Underwriting,” Proc. FUZZ-IEEE 2002, Honolulu, HI, May 2002, pp. 1003-1008.
  • K. Aggour et al., “SOFT-CBR: A self optimizing fuzzy tool for case-based reasoning,” Proc. 5th Int. Conference on Case-Based Reasoning (ICCBR) 2003, Lecture Notes in Artificial Intelligence, Trondheim, Norway, 2003, pp. 5-19.
  • A. Patterson et al., “Six Sigma Quality Applied Throughout the Lifecycle of an Automated Decision System,” Journal of Qualilty and Reliability Engineering International, Apr. 21, 2005, pp. 275-292.
  • P. Bonissone et al., “Design of local fuzzy models using evolutionary algorithms,” Computational Statistics and Data Analysis, 51, 2006, pp. 398-416.
  • K. Aggour et al., “Automating the Underwriting of Insurance Applications,” AI Magazine, 27, Fall 2006, pp. 36-50.
  • Piero P. Bonissone et al., “System and Method for Equipment Remaining Life Estimation, ” U.S. Appl. No. 11/608,058, filed Dec. 7, 2006, General Electric.
  • Kai F. Gobel et al., “System and Method for Equipment Life Estimation,” U.S. Appl. No. 11/608,076, filed Dec. 7, 2006, General Electric.


  • Continuity Data:
    Application Number Filed Notes

    US2005000216940 2005-08-31  is a related to the prior publication
         US20070061232A1 issued 2007-03-15  Method and system for forecasting reliability of assets


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