System, method, and computer program product for fault prediction in vehicle monitoring and reporting system

• US 7,230,527 B2
• Filed: 11/10/2004
• Issued: 06/12/2007
• Est. Priority Date: 11/10/2004
• Status: Active Grant

• Current Assignee: The Boeing Co.
• Original Assignee: The Boeing Co.
• Inventors: Tjoelker, Rodney A., Basu, Sabyasachi, Paul, Ranjan K., Song, Shuguang, Maggiore, John B., Frans, William R., Fresnedo, Roman D., Thompson, Valeria V., Wheway, Virginia L.
• Primary Examiner(s): Hofsass; Jeffery
• Assistant Examiner(s): Lu; Shirley
• Application Number:
  US10/985,601
• Publication Number:
  US 20060097854A1
• Time in Patent Office: 944 Days
• Field of Search: 340/345.2, 340/506, 340/2.43, 700/83, 700/17, 700/525, 701/1, 701/99, 701 29- 30, 701/33, 701/35
• US Class Current: 340/506
• CPC Class Codes: G07C 5/006 Indicating maintenance

Abstract

A system, method, and computer program product for predicting failure of a vehicle system or subsystem by using statistical analysis of prior maintenance messages and vehicle failures, such that the predictions of failures may be incorporated into a vehicle monitoring and reporting system. Maintenance message data and vehicle system or subsystem failure data are collected from a central maintenance computer of a vehicle, such as an aircraft. This maintenance message and vehicle system or subsystem failure data are analyzed to discern relationships between maintenance messages and vehicle system or subsystem failures which will enable future failures to be predicted. By predicting future failures, maintenance can be performed in time to prevent the vehicle failure and thereby avoid unnecessary costs and unscheduled interruptions of vehicle operations.

Claims

1. A method of predicting when to perform maintenance affecting operation of a vehicle, wherein the method comprises:

receiving maintenance message data and fault message data associated with operation of the vehicle, wherein the maintenance message data comprise a plurality of maintenance messages and the fault message data comprise a plurality of fault messages;

determining a predictive relationship between the maintenance message data and the fault message data such that the occurrence of at least one of the plurality of maintenance messages indicates a corresponding one of the plurality of fault messages will occur in the future; and

performing maintenance on the vehicle upon the occurrence of one of the plurality of maintenance messages to prevent the occurrence of the corresponding one of the plurality of fault messages.

2. A method for predicting faults affecting operation of a vehicle, wherein the method comprises:

receiving maintenance message data and fault message data associated with operation of the vehicle, wherein the maintenance message data comprise a plurality of maintenance messages and the fault message data comprise a plurality of fault messages;

determining which types of the plurality of maintenance messages occur within a predefined number of vehicle operations from a respective one of the plurality of fault messages;

counting occurrences of at least one type of maintenance message occurring within the predefined number of vehicle operations from the respective fault message;

counting total occurrences of the at least one type of maintenance message; and

determining if the at least one type of maintenance message is predictive of the respective fault message based on the count of the occurrences of the at least one type of maintenance message occurring within the predefined number of vehicle operations from the respective fault message and based on the count of the total occurrences of the at least one type of maintenance message.

3. The method of claim 2, wherein determining if the at least one type of maintenance message is predictive of the respective fault message comprises:

calculating a first ratio of the occurrences of the at least one type of maintenance message occurring within the predefined number of vehicle operations from the respective fault message to the total occurrences of the at least one type of maintenance message; and

eliminating any types of maintenance messages with the first ratio being less than a first cutoff threshold.

4. The method of claim 2 further comprising:

counting total occurrences of the respective fault message; and

determining if the at least one type of maintenance message is predictive of the respective fault message based on the count of the occurrences of the at least one type of maintenance message occurring within the predefined number of vehicle operations from the respective fault message and based on the count of the total occurrences of the respective fault message.

5. The method of claim 4, wherein determining if the at least one type of maintenance message is predictive of the respective fault message comprises:

calculating a second ratio of the occurrences of the at least one type of maintenance message occurring within the predefined number of vehicle operations from the respective fault message to the total occurrences of the respective fault message; and

eliminating any types of maintenance messages with the second ratio being less than a second cutoff threshold.

6. The method of claim 3 further comprising ranking the first ratio and eliminating any types of maintenance messages with the ranking of the first ratio being lower than a third cutoff threshold.

7. The method of claim 5 further comprising ranking the second ratio and eliminating any types of maintenance messages with the ranking of the second ratio being lower than a fourth cutoff threshold.

8. The method of claim 2 further comprising eliminating maintenance message data and fault message data associated with testing of the vehicle.

9. The method of claim 2 wherein the vehicle is an aircraft.

10. The method of claim 2 further comprising counting vehicle operations between the occurrence of each maintenance message and the occurrence of the respective fault message.

11. The method of claim 10 further comprising determining origins and destinations for the vehicle operations, and determining a duration of each vehicle operation using industry average durations.

12. The method of claim 2 wherein the vehicle comprises a plurality of systems and wherein each of the plurality of maintenance messages is related to one of the plurality of vehicle systems and each of the plurality of fault messages is related to one of the plurality of vehicle systems.

13. The method of claim 12 further comprising:

receiving vehicle event data related to the operation of the vehicle wherein the vehicle event data comprise a plurality of vehicle events and wherein each of the plurality of vehicle events is related to one of the plurality of vehicle systems;

determining which of the plurality of vehicle events occurred on the same vehicle as the one of the plurality of fault messages, occurred on the same day as the one of the plurality of fault messages, and are related to the same vehicle system as the one of the plurality of fault messages.

14. The method of claim 13 wherein the plurality of vehicle events comprises delay events, cancellation events, turn-back events, and diversion events.

15. A system for predicting faults affecting operation of a vehicle comprising:

a processing element comprising;

a data gathering element for receiving maintenance message data and fault message data associated with operation of the vehicle, wherein the maintenance message data comprise a plurality of maintenance messages and the fault message data comprise a plurality of fault messages;

a first determination element for determining which types of the plurality of maintenance messages occur within a predefined number of vehicle operations from a respective one of the plurality of fault messages;

a counting element for counting occurrences of at least one type of maintenance message occurring within the predefined number of vehicle operations from the respective fault message, and for counting total occurrences of the at least one type of maintenance message; and

a second determination element for determining if the at least one type of maintenance message is predictive of the respective fault message based on the count of the occurrences of the at least one type of maintenance message occurring within the predefined number of vehicle operations from the respective fault message and based on the count of the total occurrences of the at least one type of maintenance message.

16. The system of claim 15, wherein determining if the at least one type of maintenance message is predictive of the respective fault message comprises:

calculating a first ratio of the occurrences of the at least one type of maintenance message occurring within the predefined number of vehicle operations from the respective fault message to the total occurrences of the at least one type of maintenance message; and

eliminating any types of maintenance messages with the first ratio being less than a first cutoff threshold.

17. The system of claim 15:

wherein the counting element counts total occurrences of the respective fault message; and

wherein the second determination element determines if the at least one type of maintenance message is predictive of the respective fault message based on the count of the occurrences of the at least one type of maintenance message occurring within the predefined number of vehicle operations from the respective fault message and based on the count of the total occurrences of the respective fault message.

18. The system of claim 17, wherein determining if the at least one type of maintenance message is predictive of the respective fault message comprises:

calculating a second ratio of the occurrences of the at least one type of maintenance message occurring within the predefined number of vehicle operations from the respective fault message to the total occurrences of the respective fault message; and

eliminating any types of maintenance messages with the second ratio being less than a second cutoff threshold.

19. The system of claim 16 wherein the second determination element determines a ranking of the first ratio and eliminates any types of maintenance messages with the ranking of the first ratio being lower than a third cutoff threshold.

20. The system of claim 18 wherein the second determination element determines a ranking of the second ratio and eliminates any types of maintenance messages with the ranking of the second ratio being lower than a fourth cutoff threshold.

21. The system of claim 15 further comprising a discrimination element for eliminating maintenance message data and fault message data associated with testing of the vehicle.

22. The system of claim 15 wherein the vehicle is an aircraft.

23. The system of claim 15 where the counting element counts vehicle operations between the occurrence of each maintenance message and the occurrence of the respective fault message.

24. The system of claim 23 further comprising a third determination element for determining origins and destinations for the vehicle operations, and for determining a duration of each vehicle operation using industry average durations.

25. The system of claim 15 wherein the vehicle comprises a plurality of systems and wherein each of the plurality of maintenance messages is related to one of the plurality of vehicle systems and each of the plurality of fault messages is related to one of the plurality of vehicle systems.

26. The system of claim 25 further comprising:

a second data gathering element for receiving vehicle event data related to the operation of the vehicle wherein the vehicle event data comprise a plurality of vehicle events and wherein each of the plurality of vehicle events is related to one of the plurality of vehicle systems;

a fourth determination element for determining which of the plurality of vehicle events occurred on the same vehicle as the one of the plurality of fault messages, occurred on the same day as the one of the plurality of fault messages, and are related to the same vehicle system as the one of the plurality of fault messages.

27. The system of claim 26 wherein the plurality of vehicle events comprises delay events, cancellation events, turn-back events, and diversion events.

28. A computer program product for predicting faults affecting operation of a vehicle, the computer program product comprising at least one computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising:

a first executable portion for receiving maintenance message data and fault message data associated with operation of the vehicle, wherein the maintenance message data comprise a plurality of maintenance messages and the fault message data comprise a plurality of fault messages;

a second executable portion for determining which types of the plurality of maintenance messages occur within a predefined number of vehicle operations from a respective one of the plurality of fault messages;

a third executable portion for counting occurrences of at least one type of maintenance message occurring within the predefined number of vehicle operations from the respective fault message;

a fourth executable portion for counting total occurrences of the at least one type of maintenance message; and

a fifth executable portion for determining if the at least one type of maintenance message is predictive of the respective fault message based on the count of the occurrences of the at least one type of maintenance message occurring within the predefined number of vehicle operations from the respective fault message and based on the count of the total occurrences of the at least one type of maintenance message.

29. The computer program product of claim 28, wherein determining if the at least one type of maintenance message is predictive of the respective fault message comprises:

calculating a first ratio of the occurrences of the at least one type of maintenance message occurring within the predefined number of vehicle operations from the respective fault message to the total occurrences of the at least one type of maintenance message; and

eliminating any types of maintenance messages with the first ratio being less than a first cutoff threshold.

30. The computer program product of claim 28 further comprising:

a sixth executable portion for counting total occurrences of the respective fault message; and

a seventh executable portion for determining if the at least one type of maintenance message is predictive of the respective fault message based on the count of the occurrences of the at least one type of maintenance message occurring within the predefined number of vehicle operations from the respective fault message and based on the count of the total occurrences of the respective fault message.

31. The computer program product of claim 30, wherein determining if the at least one type of maintenance message is predictive of the respective fault message comprises:

calculating a second ratio of the occurrences of the at least one type of maintenance message occurring within the predefined number of vehicle operations from the respective fault message to the total occurrences of the respective fault message; and

eliminating any types of maintenance messages with the second ratio being less than a second cutoff threshold.

32. The computer program product of claim 29 further comprising:

an sixth executable portion for ranking the first ratio and eliminating any types of maintenance messages with the ranking of the first ratio being lower than a third cutoff threshold.

33. The computer program product of claim 31 further comprising:

a eighth executable portion for ranking the second ratio and eliminating any types of maintenance messages with the ranking of the second ratio being lower than a fourth cutoff threshold.

34. The computer program product of claim 28 further comprising:

a sixth executable portion for eliminating maintenance message data and fault message data associated with testing of the vehicle.

35. The computer program product of claim 28 wherein the vehicle is an aircraft.

36. The computer program product of claim 28 further comprising:

an sixth executable portion for counting vehicle operations between the occurrence of each maintenance message and the occurrence of the respective fault message.

37. The computer program product of claim 36 further comprising:

a seventh executable portion for determining origins and destinations for the vehicle operations, and determining a duration of each vehicle operation using industry average durations.

38. The computer program product of claim 28 wherein the vehicle comprises a plurality of systems and wherein each of the plurality of maintenance messages is related to one of the plurality of vehicle systems and each of the plurality of fault messages is related to one of the plurality of vehicle systems.

39. The computer program product of claim 38 further comprising:

a sixth executable portion for receiving vehicle event data related to the operation of the vehicle wherein the vehicle event data comprise a plurality of vehicle events and wherein each of the plurality of vehicle events is related to one of the plurality of vehicle systems;

a seventh executable portion for determining which of the plurality of vehicle events occurred on the same vehicle as the one of the plurality of fault messages, occurred on the same day as the one of the plurality of fault messages, and are related to the same vehicle system as the one of the plurality of fault messages.

40. The computer program product of claim 39 wherein the plurality of vehicle events comprises delay events, cancellation events, turn-back events, and diversion events.

41. A method for predicting faults affecting operation of a vehicle, wherein the method comprises:

receiving maintenance message data and fault message data associated with operation of the vehicle, wherein the maintenance message data comprise a plurality of maintenance messages and the fault message data comprise a plurality of fault messages;

determining any temporal relationship between each type of maintenance message and each type of fault message; and

classifying each type of maintenance message with respect to its ability to predict a fault with a classification selected from the group consisting of trigger, precursor, both trigger and precursor, and neither trigger nor precursor.