Methods and Systems for Clustering of Repair Orders Based on Inferences Gathered from Repair Orders

• US 20170132577A1
• Filed: 11/05/2015
• Published: 05/11/2017
• Est. Priority Date: 11/05/2015
• Status: Active Grant

• Current Assignee: Snap-On Incorporated
• Original Assignee: Snap-On Incorporated
• Inventors: Merg, Patrick S., Foreman, Jacob G., Lewis, Bradley R.
• Granted Patent: US 10,134,013 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06Q 10/20 Administration of product repair or maintenance
• CPC Class Codes: G07C 5/00 Registering or indicating the working of vehicles

Abstract

A processor may determine that a particular computer-readable vehicle repair order (RO) (e.g., including first and second RO portions) corresponds to an existing cluster of ROs due to the particular RO including RO data that refers to a particular vehicle symptom. The processor may determine that the first RO portion includes first data representative of a non-specific vehicle component and may then responsively also determine that the second RO portion includes second data that the at least one processor can use to determine a specific vehicle component associated with the particular RO. Responsively, the processor may determine the specific vehicle component based on the first and second data and may then add the particular RO to a different cluster of ROs that is arranged to contain ROs that correspond to the particular vehicle symptom and to the specific vehicle component.

Claims

1. A method comprising:

determining, by at least one processor, that a particular computer-readable vehicle repair order (RO) corresponds to an existing cluster of ROs due to the particular RO including RO data that refers to a particular vehicle symptom, wherein the existing cluster is arranged to contain ROs that correspond to the particular vehicle symptom, and wherein the particular RO comprises at least a first RO portion and a second RO portion;

determining, by the at least one processor, that the first RO portion includes first data representative of a non-specific vehicle component;

in response to determining that the first RO portion includes the first data, the at least one processor determining that the second RO portion includes second data that the at least one processor can use to determine a specific vehicle component associated with the particular RO;

in response to determining that the second RO portion includes the second data, the at least one processor determining the specific vehicle component based on the first and second data; and

in response to determining the specific vehicle component, the at least one processor adding the particular RO to a different cluster of ROs, wherein the different cluster is arranged to contain ROs that correspond to the particular vehicle symptom and to the specific vehicle component.

2. The method of claim 1,

wherein the particular vehicle symptom includes a particular diagnostic trouble code (DTC) identifier;

wherein determining that the second RO portion includes the second data comprises determining that the second RO portion includes the particular DTC identifier; and

wherein determining the specific vehicle component based on the first and second data comprises determining the specific vehicle component based on the non-specific vehicle component and the particular DTC identifier.

3. The method of claim 2, wherein the particular RO is one of a plurality of ROs stored within a data storage device, and wherein determining the specific vehicle component based on the non-specific vehicle component and the particular DTC identifier comprises:

the at least one processor recognizing ROs, from among the plurality of ROs, that are each associated with the particular DTC identifier;

the at least one processor determining that a threshold percentage of the recognized ROs include repair data referring to the particular DTC identifier and to a given vehicle component that is related to the non-specific vehicle component; and

in response to determining that a threshold percentage of the recognized ROs include the repair data, the at least one processor determining that the given vehicle component is the specific vehicle component.

4. The method of claim 2, further comprising:

determining, by the at least one processor, that the particular RO includes specific data that refers to a particular vehicle having particular vehicle attributes,

wherein determining the specific vehicle component based on the first and second data further comprises determining the specific vehicle component based on the non-specific vehicle component, the particular DTC identifier, and the particular vehicle attributes.

5. The method of claim 4, wherein the particular RO is one of a plurality of ROs stored within a data storage device, wherein the particular vehicle is related to a set of one or more vehicles, and wherein determining the specific vehicle component based on the non-specific vehicle component, the particular DTC identifier, and the particular vehicle attributes comprises:

the at least one processor identifying ROs, among the plurality of ROs, that include further data referring to at least one vehicle from the set;

the at least one processor recognizing ROs, from among the identified ROs, that are each associated with the particular DTC identifier;

the at least one processor determining that a threshold percentage of the recognized ROs include repair data referring to the particular DTC identifier and to a given vehicle component that is related to the non-specific vehicle component; and

in response to determining that a threshold percentage of the recognized ROs include the repair data, the at least one processor determining that the given vehicle component is the specific vehicle component.

6. The method of claim 4, wherein the particular vehicle attributes comprise one or more of:

(i) a vehicle year attribute, (ii) a vehicle make attribute, (iii) a vehicle model attribute, (iv) a vehicle engine attribute, (v) a vehicle system attribute, (vi) a vehicle-year-make-model attribute, (vii) a vehicle-year-make-model-submodel attribute, (viii) a vehicle engine code, (ix) a vehicle drive type, and (x) a vehicle fuel system type.

7. The method of claim 1,

wherein determining that the second RO portion includes the second data comprises determining that the second RO portion includes symptom data representative of the particular vehicle symptom;

and

wherein determining the specific vehicle component based on the first and second data comprises (i) determining that the particular vehicle symptom is associated with a particular vehicle system and (ii) determining the specific vehicle component based on the non-specific vehicle component and the particular vehicle system.

8. The method of claim 7, wherein the non-specific vehicle component corresponds to a first text string that is representative of the non-specific vehicle component, wherein the particular vehicle system corresponds to a second text string that is representative of the particular vehicle system, and wherein determining the specific vehicle component based on the non-specific vehicle component and the particular vehicle system comprises:

generating, by the at least one processor, a particular text string based on a combination of at least a portion of the first text string and at least a portion of the second text string;

the at least one processor referring to a data storage device containing a taxonomy term database that includes a plurality of computer-readable taxonomy terms; and

while referring to the data storage device, the at least one processor determining that the particular text string matches at least one taxonomy term of the plurality of taxonomy terms.

9. The method of claim 8, wherein determining the specific vehicle component based on the non-specific vehicle component and the particular vehicle system further comprises:

determining that the at least one taxonomy term is representative of the specific vehicle component.

10. The method of claim 1,

wherein determining that the second RO portion includes the second data comprises determining that the second RO portion includes replacement data specifying a replaced vehicle component;

and

wherein determining the specific vehicle component based on the first and second data comprises determining the specific vehicle component based on the non-specific vehicle component and the replaced vehicle component.

11. The method of claim 10, wherein the second RO portion comprises a labor line, and wherein the labor line includes the replacement data specifying the replaced vehicle component.

12. The method of claim 10, wherein the non-specific vehicle component corresponds to a first text string that is representative of the non-specific vehicle component, wherein the replaced vehicle component corresponds to a second text string that is representative of the replaced vehicle component, and wherein determining the specific vehicle component based on the non-specific vehicle component and the replaced vehicle component comprises:

determining, by the at least one processor, that at the first text string matches at least a portion of the second text string; and

in response to determining that at the first text string matches at least a portion of the second text string, determining, by the at least one processor, that the second text string is representative of the specific vehicle component.

13. The method of claim 1, wherein determining that the first RO portion includes the first data comprises determining that the first RO portion includes replacement data specifying replacement of the non-specific vehicle component.

14. The method of claim 13, wherein the first RO portion comprises an RO text field, and wherein the RO text field includes the replacement data specifying replacement of the non-specific vehicle component.

15. The method of claim 1,

wherein determining that the second RO portion includes the second data comprises determining that the second RO portion includes identification data specifying a particular vehicle part number associated with the non-specific vehicle component;

and

wherein determining the specific vehicle component based on the first and second data comprises determining the specific vehicle component based on the particular vehicle part number associated with the non-specific vehicle component.

16. The method of claim 15, wherein determining the specific vehicle component based on the particular vehicle part number comprises:

the at least one processor referring to a data storage device containing a part number database that includes mapping data that maps each of a plurality of vehicle part numbers to a respective part number description;

while referring to the data storage device, determining that the particular vehicle part number matches at least one the plurality of vehicle part numbers; and

in response to determining that the particular vehicle part number matches at least one the plurality of vehicle part numbers, the at least one processor (i) referring to the mapping data to determine the respective part number description of the particular vehicle part number and (ii) determining the specific vehicle component based on the respective part number description of the particular vehicle part number.

17. The method of claim 1, wherein the first RO portion comprises a parts line.

18. The method of claim 1, wherein the first RO portion is different from the second RO portion.

19. The method of claim 1, wherein the first RO portion is the same as the second RO portion.

20. The method of claim 1, wherein the first data comprises a given text string, and wherein determining that the first RO portion includes first data representative of a non-specific vehicle component comprises:

the at least one processor referring to a data storage device containing a vehicle component database that includes a plurality of computer-readable vehicle component terms;

while referring to the data storage device, determining that the given text string substantially matches two or more vehicle component terms of the plurality of vehicle component terms; and

in response to determining that the given text string substantially matches two or more vehicle component terms of the plurality of vehicle component terms, determining that the given text string is representative of a non-specific vehicle component.

21. The method of claim 20, wherein determining that the given text string substantially matches two or more vehicle component terms comprises determining that the given text string matches at least a portion of each of the two or more vehicle component terms.

22. The method of claim 1, wherein determining the specific vehicle component based on the first and second data comprises:

based on the first and second data, the at least one processor determining a given text string;

the at least one processor referring to a data storage device containing a vehicle component database that includes a plurality of computer-readable vehicle component terms;

while referring to the data storage device, determining that the given text string matches a distinct vehicle component term of the plurality of vehicle component terms; and

in response to determining that the given text string matches a distinct vehicle component term of the plurality of vehicle component terms, determining that the given text string is representative of a specific vehicle component.

23. A computing system comprising:

a data storage device having stored thereon a plurality of computer-readable vehicle repair orders (ROs); and

at least one processor coupled to the data storage device and programmed to;

determine that a particular RO of the plurality of ROs corresponds to an existing cluster of ROs due to the particular RO including RO data that refers to a particular vehicle symptom, wherein the existing cluster is arranged to contain ROs that correspond to the particular vehicle symptom, and wherein the particular RO comprises at least a first RO portion and a second RO portion;

determine that the first RO portion includes first data representative of a non-specific vehicle component;

in response to determining that the first RO portion includes the first data, determine that the second RO portion includes second data that the at least one processor can use to determine a specific vehicle component associated with the particular RO;

in response to determining that the second RO portion includes the second data, determine the specific vehicle component based on the first and second data; and

in response to determining the specific vehicle component, add the particular RO to a different cluster of ROs, wherein the different cluster is arranged to contain ROs that correspond to the particular vehicle symptom and to the specific vehicle component.

24. The computing system of claim 23,

wherein the particular vehicle symptom includes a particular diagnostic trouble code (DTC) identifier;

wherein the at least one processor being programmed to determine that the second RO portion includes the second data comprises the at least one processor being programmed to determine that the second RO portion includes the particular DTC identifier; and

wherein the at least one processor being programmed to determine the specific vehicle component based on the first and second data comprises the at least one processor being programmed to determine the specific vehicle component based on the non-specific vehicle component and the particular DTC identifier.

25. The computing system of claim 24, wherein the at least one processor being programmed to determine the specific vehicle component based on the non-specific vehicle component and the particular DTC identifier comprises the at least one processor being programmed to:

recognize ROs, from among the plurality of ROs, that are each associated with the particular DTC identifier;

determine that a threshold percentage of the recognized ROs include repair data referring to the particular DTC identifier and to a given vehicle component that is related to the non-specific vehicle component; and

in response to determining that a threshold percentage of the recognized ROs include the repair data, determine that the given vehicle component is the specific vehicle component.

26. The computing system of claim 24,

wherein the at least one processor is further programmed to determine that the particular RO includes specific data that refers to a particular vehicle having particular vehicle attributes, and

wherein the at least one processor being programmed to determine the specific vehicle component based on the first and second data further comprises the at least one processor being programmed to determine the specific vehicle component based on the non-specific vehicle component, the particular DTC identifier, and the particular vehicle attributes.

27. The computing system of claim 26, wherein the particular vehicle is related to a set of one or more vehicles, and wherein the at least one processor being programmed to determine the specific vehicle component based on the non-specific vehicle component, the particular DTC identifier, and the particular vehicle attributes comprises the at least one processor being programmed to:

identify ROs, among the plurality of ROs, that include further data referring to at least one vehicle from the set;

recognize ROs, from among the identified ROs, that are each associated with the particular DTC identifier;

determine that a threshold percentage of the recognized ROs include repair data referring to the particular DTC identifier and to a given vehicle component that is related to the non-specific vehicle component; and

in response to determining that a threshold percentage of the recognized ROs include the repair data, determine that the given vehicle component is the specific vehicle component.

28. The computing system of claim 26, wherein the particular vehicle attributes comprise one or more of:

(i) a vehicle year attribute, (ii) a vehicle make attribute, (iii) a vehicle model attribute, (iv) a vehicle engine attribute, (v) a vehicle system attribute, (vi) a vehicle-year-make-model attribute, (vii) a vehicle-year-make-model-submodel attribute, (viii) a vehicle engine code, (ix) a vehicle drive type, and (x) a vehicle fuel system type.

29. The computing system of claim 23,

wherein the at least one processor being programmed to determine that the second RO portion includes the second data comprises the at least one processor being programmed to determine that the second RO portion includes symptom data representative of the particular vehicle symptom;

and

wherein the at least one processor being programmed to determine the specific vehicle component based on the first and second data comprises the at least one processor being programmed to (i) determine that the particular vehicle symptom is associated with a particular vehicle system and (ii) determine the specific vehicle component based on the non-specific vehicle component and the particular vehicle system.

30. The computing system of claim 29, wherein the non-specific vehicle component corresponds to a first text string that is representative of the non-specific vehicle component, wherein the particular vehicle system corresponds to a second text string that is representative of the particular vehicle system, wherein the data storage device has stored thereon a taxonomy term database that includes a plurality of computer-readable taxonomy terms, and wherein the at least one processor being programmed to determine the specific vehicle component based on the non-specific vehicle component and the particular vehicle system comprises the at least one processor being programmed to:

generate a particular text string based on a combination of at least a portion of the first text string and at least a portion of the second text string;

refer to the data storage device having stored thereon the taxonomy term database; and

while referring to the data storage device, determine that the particular text string matches at least one taxonomy term of the plurality of taxonomy terms.

31. The computing system of claim 30, wherein the at least one processor being programmed to determine the specific vehicle component based on the non-specific vehicle component and the particular vehicle system further comprises the at least one processor being programmed to:

determine that the at least one taxonomy term is representative of the specific vehicle component.

32. The computing system of claim 23,

wherein the at least one processor being programmed to determine that the second RO portion includes the second data comprises the at least one processor being programmed to determine that the second RO portion includes replacement data specifying a replaced vehicle component;

and

wherein the at least one processor being programmed to determine the specific vehicle component based on the first and second data comprises the at least one processor being programmed to determine the specific vehicle component based on the non-specific vehicle component and the replaced vehicle component.

33. The computing system of claim 32, wherein the second RO portion comprises a labor line, and wherein the labor line includes the replacement data specifying the replaced vehicle component.

34. The computing system of claim 32, wherein the non-specific vehicle component corresponds to a first text string that is representative of the non-specific vehicle component, wherein the replaced vehicle component corresponds to a second text string that is representative of the replaced vehicle component, and wherein the at least one processor being programmed to determine the specific vehicle component based on the non-specific vehicle component and the replaced vehicle component comprises the at least one processor being programmed to:

determine that at the first text string matches at least a portion of the second text string; and

in response to determining that at the first text string matches at least a portion of the second text string, determine that the second text string is representative of the specific vehicle component.

35. The computing system of claim 23, wherein the at least one processor being programmed to determine that the first RO portion includes the first data comprises the at least one processor being programmed to determine that the first RO portion includes replacement data specifying replacement of the non-specific vehicle component.

36. The computing system of claim 35, wherein the first RO portion comprises an RO text field, and wherein the RO text field includes the replacement data specifying replacement of the non-specific vehicle component.

37. The computing system of claim 23,

wherein the at least one processor being programmed to determine that the second RO portion includes the second data comprises the at least one processor being programmed to determine that the second RO portion includes identification data specifying a particular vehicle part number associated with the non-specific vehicle component;

and

wherein the at least one processor being programmed to determine the specific vehicle component based on the first and second data comprises the at least one processor being programmed to determine the specific vehicle component based on the particular vehicle part number associated with the non-specific vehicle component.

38. The computing system of claim 37, wherein the data storage device has stored thereon a part number database that includes mapping data that maps each of a plurality of vehicle part numbers to a respective part number description, and wherein the at least one processor being programmed to determine the specific vehicle component based on the particular vehicle part number comprises the at least one processor being programmed to:

refer to the data storage device having stored thereon the part number database;

while referring to the data storage device, determine that the particular vehicle part number matches at least one the plurality of vehicle part numbers; and

in response to determining that the particular vehicle part number matches at least one the plurality of vehicle part numbers, (i) refer to the mapping data to determine the respective part number description of the particular vehicle part number and (ii) determine the specific vehicle component based on the respective part number description of the particular vehicle part number.

39. The computing system of claim 23, wherein the first RO portion comprises a parts line.

40. The computing system of claim 23, wherein the first RO portion is different from the second RO portion.

41. The computing system of claim 23, wherein the first RO portion is the same as the second RO portion.

42. The computing system of claim 23, wherein the data storage device has stored thereon a vehicle component database that includes a plurality of computer-readable vehicle component terms, wherein the first data comprises a given text string, and wherein the at least one processor being programmed to determining that the first RO portion includes first data representative of a non-specific vehicle component comprises the at least one processor being programmed to:

refer to the data storage device having stored thereon the vehicle component database;

while referring to the data storage device, determine that the given text string substantially matches two or more vehicle component terms of the plurality of vehicle component terms; and

in response to determining that the given text string substantially matches two or more vehicle component terms of the plurality of vehicle component terms, determine that the given text string is representative of a non-specific vehicle component.

43. The computing system of claim 42, wherein the at least one processor being programmed to determine that the given text string substantially matches two or more vehicle component terms comprises the at least one processor being programmed to determine that the given text string matches at least a portion of each of the two or more vehicle component terms.

44. The computing system of claim 23, wherein the a data storage device has stored thereon a vehicle component database that includes a plurality of computer-readable vehicle component terms, and wherein the at least one processor being programmed to determine the specific vehicle component based on the first and second data comprises the at least one processor being programmed to:

based on the first and second data, determine a given text string;

refer to the data storage device having stored thereon the vehicle component database;

while referring to the data storage device, determine that the given text string matches a distinct vehicle component term of the plurality of vehicle component terms; and

in response to determining that the given text string matches a distinct vehicle component term of the plurality of vehicle component terms, determine that the given text string is representative of a specific vehicle component.

45. A computer readable medium having stored thereon instructions executable by at least one processor to cause a computing system to perform functions comprising:

determining that a particular computer-readable vehicle repair order (RO) corresponds to an existing cluster of ROs due to the particular RO including RO data that refers to a particular vehicle symptom, wherein the existing cluster is arranged to contain ROs that correspond to the particular vehicle symptom, and wherein the particular RO comprises at least a first RO portion and a second RO portion;

determining that the first RO portion includes first data representative of a non-specific vehicle component;

in response to determining that the first RO portion includes the first data, determining that the second RO portion includes second data that the at least one processor can use to determine a specific vehicle component associated with the particular RO;

in response to determining that the second RO portion includes the second data, determining the specific vehicle component based on the first and second data; and

in response to determining the specific vehicle component, adding the particular RO to a different cluster of ROs, wherein the different cluster is arranged to contain ROs that correspond to the particular vehicle symptom and to the specific vehicle component.