SYSTEM AND METHOD FOR SELECTING A MAINTENANCE OPERATION

• US 20110093157A1
• Filed: 10/20/2009
• Published: 04/21/2011
• Est. Priority Date: 10/20/2009
• Status: Abandoned Application

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Prabhakaran, Manoj Kumar, McAndrew, Dennis, Goska, Aneta, Oracz, Dariusz, Hlozek, Pawel
• Application Number:
  US12/582,512
• Publication Number:
  US 20110093157A1
• Time in Patent Office: Days
• US Class Current: 701/30
• CPC Class Codes: G07C 5/006 Indicating maintenance
• CPC Class Codes: G07C 5/085 using electronic data carriers

Abstract

There is provided a method of selecting a maintenance operation to be performed on a device. An exemplary method comprises determining a health parameter for the device, the health parameter being predictive of a probability of failure of the device based on archival data about a plurality of devices similar to the device. The exemplary method also comprises performing a first maintenance operation on the device if the health parameter indicates that the probability of failure of the device is below a threshold. The exemplary method additionally comprises performing a second maintenance operation on the device if the health parameter indicates that the probability of failure of the device exceeds the threshold.

Claims

1. A method of selecting a maintenance operation to be performed on a device, the method comprising:

determining a health parameter for the device, the health parameter being predictive of a probability of failure of the device based on archival data about a plurality of devices similar to the device;

performing a first maintenance operation on the device if the health parameter indicates that the probability of failure of the device is below a threshold; and

performing a second maintenance operation on the device if the health parameter indicates that the probability of failure of the device exceeds the threshold.

2. The method recited in claim 1, wherein the archival data comprises engine health data.

3. The method recited in claim 2, wherein the engine health data comprises oil parameter data, fault log data, or parts usage data.

4. The method recited in claim 2, wherein the engine health data comprises oil parameter data, the oil parameter data relating to a viscosity, an alkalinity, an acidity, an amount of soot, oxidation, sulfation, nitration or a metal content.

5. The method recited in claim 1, wherein the health parameter is determined by a transfer function.

6. The method recited in claim 5, wherein the transfer function embodies information regarding to a magnitude of health data representative of a characteristic of the device and a slope of the health data representative of the characteristic of the device.

7. The method recited in claim 5, wherein the transfer function embodies a regression analysis, an area under a curve analysis or a time fulfillment analysis.

8. The method recited in claim 1, wherein the health parameter may predict potential failure of the device even though underlying health data on which the health parameter is based does not exceed an acceptable limit at a particular time.

9. The method recited in claim 1, wherein the first maintenance operation comprises a top deck maintenance process.

10. The method recited in claim 1, wherein the second maintenance operation comprises a complete overhaul.

11. The method recited in claim 1, wherein the device comprises a locomotive engine.

12. The method recited in claim 1, wherein the second maintenance operation comprises the first maintenance operation.

13. The method recited in claim 1, wherein the health parameter is adapted to indicate a potential problem with the device even though the health parameter indicates that the probability of failure of the device is below the threshold.

14. A computer system that is adapted to determine a maintenance operation to be performed on a device, the computer system comprising:

a processor; and

a tangible, machine-readable storage medium that stores machine-readable instructions for execution by the processor, the machine-readable instructions comprising;

code that, when executed by the processor, is adapted to cause the processor to determine a health parameter for the device, the health parameter being predictive of a probability of failure of the device based on archival data about a plurality of devices similar to the device;

code that, when executed by the processor, is adapted to cause the processor to identify a first maintenance operation to be performed on the device if the health parameter indicates that the probability of failure of the device is below a threshold; and

code that, when executed by the processor, is adapted to cause the processor to identify a second maintenance operation to be performed on the device if the health parameter indicates that the probability of failure of the device exceeds the threshold.

15. The computer system recited in claim 14, wherein the archival data comprises engine health data.

16. The computer system recited in claim 15, wherein the engine health data comprises oil parameter data, fault log data, or parts usage data.

17. The computer system recited in claim 14, wherein the engine health data comprises oil parameter data, the oil parameter data relating to a viscosity, an alkalinity, an acidity, an amount of soot, oxidation, sulfation, nitration or a metal content.

18. The computer system recited in claim 14, wherein the health parameter is determined by a transfer function.

19. The computer system recited in claim 18, wherein the transfer function embodies information regarding to a magnitude of health data representative of a characteristic of the device and a slope of the health data representative of the characteristic of the device.

20. The computer system recited in claim 18, wherein the transfer function embodies a regression analysis, an area under a curve analysis or a time fulfillment analysis.

21. The computer system recited in claim 14, wherein the health parameter may predict potential failure of the device even though underlying health data on which the health parameter is based does not exceed an acceptable limit at a particular time.

22. The computer system recited in claim 14, wherein the first maintenance operation comprises a top deck maintenance process.

23. The computer system recited in claim 14, wherein the second maintenance operation comprises a complete overhaul.

24. The computer system recited in claim 14, wherein the device comprises a locomotive engine.

25. The computer system recited in claim 14, wherein the second maintenance operation comprises the first maintenance operation.

26. The computer system recited in claim 14, wherein the health parameter is adapted to indicate a potential problem with the device even though the health parameter indicates that the probability of failure of the device is below the threshold.

27. A tangible, machine-readable medium that stores machine-readable instructions executable by a processor to select a maintenance operation to be performed on a device, the tangible-machine-readable medium comprising:

machine-readable instructions that, when executed by the processor, determine a health parameter for the device, the health parameter being predictive of a probability of failure of the device based on archival data about a plurality of devices similar to the device;

machine-readable instructions that, when executed by the processor, identify a first maintenance operation to be performed on the device if the health parameter indicates that the probability of failure of the device is below a threshold; and

machine-readable instructions that, when executed by the processor, identify a second maintenance operation to be performed on the device if the health parameter indicates that the probability of failure of the device exceeds the threshold.