IDENTIFICATION OF SIGNIFICANT SEQUENCES OF FAULT CODES BY STATISTICAL HYPOTHESIS TESTING

• US 20130046724A1
• Filed: 08/15/2011
• Published: 02/21/2013
• Est. Priority Date: 08/15/2011
• Status: Active Grant

• Current Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Original Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Inventors: Zhao, Shi
• Granted Patent: US 8,972,330 B2
• Time in Patent Office: Days
• US Class Current: 706/52
• CPC Class Codes: G06F 11/079 Root cause analysis, i.e. error or fault diagnosis in a hardware test environment G06F11/22; in a software test environment G06F11/36
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06Q 10/20 Administration of product repair or maintenance

Abstract

In some aspects of the present application, a method for identifying significant events related to machine problems. The method includes receiving one or more machine problems; determining one or more machine problem classifications based on the one or more machine problems; generating a probability distribution that the one or more machines problems are related to the one more machine problem classifications; determining if one or more events are associated with the one or more machine problems during a predetermined time interval; and determining if the one or more events are significantly related to the one or more machine problem classifications using a statistical algorithm.

Claims

1. A method for identifying significant events related to machine problems, the method comprising:

receiving one or more machine problems;

determining one or more machine problem classifications based on the one or more machine problems;

generating a probability distribution that the one or more machines problems are related to the one more machine problem classifications;

determining if one or more events are associated with the one or more machine problems during a predetermined time interval; and

determining if the one or more events are significantly related to the one or more machine problem classifications using a statistical algorithm.

2. The method according to claim 1, wherein the one or more events include one or more fault codes related to a fault associated with the one or more machine problem classifications.

3. The method according to claim 1, wherein the predetermined time interval is between about 2 and 10 days.

4. The method according to claim 1, further comprising receiving an identification of the one or more machine problems, one or more machine problem classifications, a fault code related to the one or more machine problems, or combinations thereof from a user.

5. The method according to claim 1, further comprising:

determining if two or more events for a particular machine problem are significantly related using hypothesis testing; and

arranging the two or more events into an event sequence if the two or more events that are determined to be significant.

6. The method according to claim 5, wherein the determining includes determining if the event sequence is significant if and only if any events in the event sequence are pair wise favorably associated.

7. The method according to claim 5, wherein the determining includes determining if the event sequence is significant if and only if there is a path of events in the event sequence which is step wise favorably associated.

8. The method according to claim 1, wherein the machine problem classifications include one or more subsystems related to a machine type.

9. The method according to claim 1, wherein the probability distribution is a multinomial distribution.

10. An apparatus arranged to identify significant sequences of fault codes related to machine problems, the apparatus comprising:

a processor in communication with a memory having instructions, that when executed by the processor cause the processor to;

receive one or more machine problems;

determine one or more machine problem classifications based on the one or more machine problems;

generate a probability distribution that the one or more machines problems are related to the one more machine problem classifications;

determine if one or more events are associated with the one or more machine problems during a predetermined time interval; and

determine if the one or more events are significantly related to the one or more machine problem classifications using a statistical algorithm.

11. The apparatus according to claim 10, wherein the one or more events include one or more fault codes related to a fault associated with the one or more machine problem classifications.

12. The apparatus according to claim 10, wherein the predetermined time interval is between about 2 and 10 days.

13. The apparatus according to claim 10, wherein the processor is further configured to receive an identification of the one or more machine problems, one or more machine problem classifications, a fault code related to the one or more machine problems, or combinations thereof from a user.

14. The apparatus according to claim 10, wherein the processor is further configured to determine if two or more events for a particular machine problem are significantly related using hypothesis testing and arrange the two or more events into an event sequence if the two or more events that are determined to be significant.

15. The apparatus according to claim 14, wherein the event sequence is significant if and only if any events in the event sequence are pair wise favorably associated.

16. The apparatus according to claim 14, wherein the event sequence is significant if and only if there is a path of events in the event sequence which is step wise favorably associated.

17. The apparatus according to claim 10, wherein the machine problem classifications include one or more subsystems related to a machine type.

18. The apparatus according to claim 10, wherein the probability distribution is a multinomial distribution.

19. An article of manufacture comprising:

a storage medium having instructions, that when executed by a processor cause the processor to;

receive one or more machine problems;

determine one or more machine problem classifications based on the one or more machine problems;

generate a probability distribution that the one or more machines problems are related to the one more machine problem classifications;

determine if one or more events are associated with the one or more machine problems during a predetermined time interval; and

determine if the one or more events are significantly related to the one or more machine problem classifications using a statistical algorithm.

20. The article according to claim 19, further comprising instructions to cause the processor to determine if two or more events for a particular machine problem are significantly related using hypothesis testing and arrange the two or more events into an event sequence if the two or more events that are determined to be significant.

21. The article according to claim 20, wherein the event sequence is significant if and only if any events in the event sequence are pair wise favorably associated.

22. The article according to claim 20, wherein the event sequence is significant if and only if there is a path of events in the event sequence which is step wise favorably associated.