Streamlining and customizing users troubleshooting workflow

1 . A non-transitory, computer-readable storage medium storing instructions, which, when executed by at least one data processor of a system, cause the system to:

obtain, from a sensor associated with a machine, a first input indicating a machine experiencing an error, and the error experienced by the machine,

wherein the machine includes a heavy-duty vehicle;

obtain an indication of a plurality of user groups solving a plurality of errors previously experienced by a plurality of machines,

wherein the plurality of user groups are created according to a first multiplicity of user attributes including geographic location and demographic information associated with the plurality of user groups,

wherein the demographic information associated with the plurality of user groups includes age, gender or education;

obtain second multiplicity of user attributes associated with a user solving the error experienced by the machine,

wherein the second multiplicity of user attributes includes geographic location and demographic information associated with the user,

wherein the demographic information associated with the user includes age, gender or education:

based on the first multiplicity of user attributes and second multiplicity of user attributes, assign the user solving the error experienced by the machine into a particular group among the plurality of user groups;

based on the first input and the particular group to which the user solving the error experienced by the machine belongs, generate a first plurality of relevance indicators and a first plurality of troubleshooting procedures,

wherein a troubleshooting procedure among the first plurality of troubleshooting procedures indicates a test to perform or a repair step,

wherein a relevance indicator among the first plurality of relevance indicators is associated with the troubleshooting procedure among the first plurality of troubleshooting procedures, and

wherein the first plurality of relevance indicators includes different relevance indicators, and

wherein the first plurality of relevance indicators indicates a first troubleshooting procedure to perform next;

provide the first plurality of relevance indicators and the first plurality of troubleshooting procedures to the user; and

perform following steps iteratively:

receive a second input indicating a performed troubleshooting procedure among the first plurality of troubleshooting procedures;

receive an indication of a result associated with the performed troubleshooting procedure;

based on the indication of the result associated with the performed troubleshooting procedure, generate a second plurality of relevance indicators associated with a second plurality of troubleshooting procedures,

wherein the second plurality of relevance indicators indicates a second troubleshooting procedure to perform next;

until either the error is resolved or the second plurality of troubleshooting procedures is empty, whichever comes first.

2 . The non-transitory, computer-readable storage medium storing instructions of claim 1 , wherein the instructions to generate the first plurality of relevance indicators and the first plurality of troubleshooting procedures comprise instructions to:

provide to an artificial intelligence the first input indicating the machine experiencing the error, and the error experienced by the machine;

obtain, from a database, multiple machines and multiple troubleshooting procedures associated with the multiple machines;

determine whether the machine experiencing the error is included among the multiple machines;

upon determining that the machine experiencing the error is not included among the multiple machines, determine, by the artificial intelligence, the troubleshooting procedure among the multiple troubleshooting procedures that is most likely to resolve the error experienced by the machine even though the troubleshooting procedure is not associated with the machine experiencing the error; and

upon determining that the machine experiencing the error is included among the multiple machines, determine, by the artificial intelligence, the troubleshooting procedure among the multiple troubleshooting procedures that is most likely to resolve the error experienced by the machine,

wherein the troubleshooting procedure is associated with the machine experiencing the error.

3 . The non-transitory, computer-readable storage medium storing instructions of claim 1 , wherein the instructions to generate the first plurality of relevance indicators and the first plurality of troubleshooting procedures comprise instructions to:

obtain multiple inputs associated with multiple users resolving multiple errors associated with multiple machines,

wherein a particular input among the multiple inputs includes an indication of a particular machine experiencing a particular error, and an indication of the error experienced by the particular machine; and

based on the multiple inputs, train an artificial intelligence to receive the first input and to provide a most likely repair associated with the error experienced by the machine.

4 . The non-transitory, computer-readable storage medium storing instructions of claim 1 , wherein the instructions to generate the first plurality of relevance indicators and the first plurality of troubleshooting procedures comprise instructions to:

provide to an artificial intelligence the first input indicating the machine experiencing the error, and the error experienced by the machine; and

obtain from the artificial intelligence the first plurality of relevance indicators and the first plurality of troubleshooting procedures.

5 . The non-transitory, computer-readable storage medium storing instructions of claim 1 , wherein the instructions to obtain the first input comprise instructions to:

receive a natural language input describing the machine experiencing the error and/or the error experienced by the machine;

obtain multiple predetermined diagnostic codes associated with multiple errors; and

map the natural language input to a predetermined diagnostic code among the multiple predetermined diagnostic codes.

6 . The non-transitory, computer-readable storage medium storing instructions of claim 1 , comprising instructions to:

obtain session duration, success rate associated with historical troubleshooting sessions; and

based on the session duration and the success rate associated with the historical troubleshooting sessions, provide time, complexity, a number of parts, and a material cost required to perform the troubleshooting procedure.

7 . The non-transitory, computer-readable storage medium storing instructions of claim 1 , wherein instructions to provide the first plurality of relevance indicators and the first plurality of troubleshooting procedures comprise instructions to:

order the first plurality of relevance indicators in a descending sequence;

obtain multiple predetermined categories associated with the first plurality of relevance indicators,

wherein the multiple predetermined categories indicate ranges associated with the first plurality of relevance indicators, and

wherein the multiple predetermined categories are color coded;

color the first plurality of relevance indicators based on the multiple predetermined categories; and

present the colored first plurality of relevance indicators in the descending sequence.

8 . A method comprising:

obtaining, by a processor and from a sensor associated with a device, a first input indicating a device experiencing an error, and the error experienced by the device,

wherein the device includes a heavy-duty vehicle;

obtaining, by the processor, an indication of a plurality of user groups solving a plurality of errors previously experienced by a plurality of devices,

wherein the plurality of user groups are created according to a first multiplicity of user attributes including geographic location and demographic information associated with the plurality of user groups,

wherein the demographic information associated with the plurality of user groups includes age, gender or education;

obtaining by the processor, second multiplicity of user attributes associated with a user solving the error experienced by the device,

wherein the second multiplicity of user attributes includes geographic location and demographic information associated with the user,

wherein the demographic information associated with the user includes age, gender or education;

based on the first multiplicity of user attributes and second multiplicity of user attributes, assigning, by the processor, the user solving the error experienced by the device into a particular group among the plurality of user groups;

based on the first input and the particular group to which the user solving the error experienced by the device belongs, providing, by the processor a first plurality of relevance indicators and a first plurality of troubleshooting procedures,

wherein a troubleshooting procedure among the first plurality of troubleshooting procedures indicates a test to perform or a repair step,

wherein a relevance indicator among the first plurality of relevance indicators is associated with the troubleshooting procedure among the first plurality of troubleshooting procedures, and

wherein the first plurality of relevance indicators includes different relevance indicators, and

wherein the first plurality of relevance indicators indicates a first troubleshooting procedure to perform next;

receiving, by the processor, a second input including a performed troubleshooting procedure among the first plurality of troubleshooting procedures;

receiving by the processor an indication of a result associated with the performed troubleshooting procedure; and

based on the indication of the result associated with the performed troubleshooting procedure, generating, by the processor, a second plurality of relevance indicators associated with a second plurality of troubleshooting procedures,

wherein the second plurality of relevance indicators indicates a second troubleshooting procedure to perform next.

9 . The method of claim 8 , wherein obtaining the first input comprises:

receiving a natural language input describing the device experiencing the error and/or the error experienced by the device;

obtaining multiple predetermined diagnostic codes associated with multiple errors; and

mapping the natural language input to a predetermined diagnostic code among the multiple predetermined diagnostic codes.

10 . The method of claim 8 , wherein generating the first plurality of relevance indicators and the first plurality of troubleshooting procedures comprises:

providing to an artificial intelligence the first input indicating the device experiencing the error, and the error experienced by the device;

obtaining, from a database, multiple devices and multiple troubleshooting procedures associated with the multiple devices;

determining whether the device experiencing the error is included among the multiple devices;

upon determining that the device experiencing the error is not included among the multiple devices, determining, by the artificial intelligence, the troubleshooting procedure among the multiple troubleshooting procedures that is most likely to resolve the error experienced by the device even though the troubleshooting procedure is not associated with the device experiencing the error, and

upon determining that the device experiencing the error is included among the multiple devices, determining, by the artificial intelligence, the troubleshooting procedure among the multiple troubleshooting procedures that is most likely to resolve the error experienced by the device,

wherein the troubleshooting procedure is not associated with the device experiencing the error.

11 . The method of claim 8 , wherein generating the first plurality of relevance indicators and the first plurality of troubleshooting procedures comprises:

obtaining multiple inputs associated with multiple users resolving multiple errors associated with multiple devices,

wherein a particular input among the multiple inputs includes an indication of a particular device experiencing a particular error, and an indication of the error experienced by the particular device; and

based on the multiple inputs, training an artificial intelligence to receive the first input and to provide a most likely repair associated with the error experienced by the device.

12 . The method of claim 8 , wherein generating the first plurality of relevance indicators and the first plurality of troubleshooting procedures comprises:

providing to an artificial intelligence the first input indicating the device experiencing the error, and the error experienced by the device; and

obtaining from the artificial intelligence the first plurality of relevance indicators and the first plurality of troubleshooting procedures.

13 . The method of claim 8 , wherein providing the first plurality of relevance indicators and the first plurality of troubleshooting procedures comprises:

ordering the first plurality of relevance indicators in a descending sequence;

obtaining multiple predetermined categories associated with the first plurality of relevance indicators,

wherein the multiple predetermined categories indicate ranges associated with the first plurality of relevance indicators, and

wherein the multiple predetermined categories are color coded;

coloring the first plurality of relevance indicators based on the multiple predetermined categories; and

providing the colored first plurality of relevance indicators in the descending sequence.

14 . A system comprising:

at least one hardware processor; and

at least one non-transitory memory storing instructions, which, when executed by the at least one hardware processor, cause the system to:

obtain, from a sensor associated with a device a first input indicating a device experiencing an error, and the error experienced by the device,

wherein the device includes a heavy-duty vehicle;

obtain an indication of a plurality of user groups solving a plurality of errors previously experienced by a plurality of devices,

wherein the plurality of user groups are created according to a first multiplicity of user attributes including geographic location and demographic information associated with the plurality of user groups,

wherein the demographic information associated with the plurality of user groups includes age, gender or education;

obtain second multiplicity of user attributes associated with a user solving the error experienced by the device,

wherein the second multiplicity of user attributes includes geographic location and demographic information associated with the user,

wherein the demographic information associated with the user includes age, gender or education;

based on the first multiplicity of user attributes and second multiplicity of user attributes, assign the user solving the error experienced by the device into a particular group among the plurality of user groups;

based on the first input and the particular group to which the user solving the error experienced by the device belongs, provide a first plurality of relevance indicators and a first plurality of troubleshooting procedures,

wherein a troubleshooting procedure among the first plurality of troubleshooting procedures indicates a test to perform or a repair step,

wherein a relevance indicator among the first plurality of relevance indicators is associated with the troubleshooting procedure among the first plurality of troubleshooting procedures, and

wherein the first plurality of relevance indicators includes different relevance indicators, and

wherein the first plurality of relevance indicators indicates a first troubleshooting procedure to perform next;

receive a second input including a performed troubleshooting procedure among the first plurality of troubleshooting procedures;

receive an indication of a result associated with the performed troubleshooting procedure; and

based on the indication of the result associated with the performed troubleshooting procedure, generate a second plurality of relevance indicators associated with a second plurality of troubleshooting procedures,

wherein the second plurality of relevance indicators indicates a second troubleshooting procedure to perform next.

15 . The system of claim 14 , wherein the instructions to obtain the first input comprise instructions to:

receive a natural language input describing the device experiencing the error and/or error experienced by the device;

obtain multiple predetermined diagnostic codes associated with multiple errors; and

map the natural language input to a predetermined diagnostic code among the multiple predetermined diagnostic codes.

16 . The system of claim 14 , wherein the instructions to generate the first plurality of relevance indicators and the first plurality of troubleshooting procedures comprise instructions to:

provide to an artificial intelligence the first input indicating the device experiencing the error, and the error experienced by the device; and

obtain, from a database, multiple devices and multiple troubleshooting procedures associated with the multiple devices;

determine whether the device experiencing the error is included among the multiple devices;

upon determining that the device experiencing the error is not included among the multiple devices, determine, by the artificial intelligence, the troubleshooting procedure among the multiple troubleshooting procedures that is most likely to resolve the error experienced by the device even though the troubleshooting procedure is not associated with the device experiencing the error; and

upon determining that the device experiencing the error is included among the multiple devices, determine, by the artificial intelligence, the troubleshooting procedure among the multiple troubleshooting procedures that is most likely to resolve the error experienced by the device,

wherein the troubleshooting procedure is not associated with the device experiencing the error.

17 . The system of claim 14 , wherein the instructions to generate the first plurality of relevance indicators and the first plurality of troubleshooting procedures comprise instructions to:

obtain multiple inputs associated with multiple users resolving multiple errors associated with multiple devices,

wherein a particular input among the multiple inputs includes an indication of a particular device experiencing a particular error, and an indication of the error experienced by the particular device; and

based on the multiple inputs, train an artificial intelligence to receive the first input and to provide a most likely repair associated with the error experienced by the device.

18 . The system of claim 14 , wherein the instructions to generate the first plurality of relevance indicators and the first plurality of troubleshooting procedures comprise instructions to:

provide to an artificial intelligence the first input indicating the device experiencing the error, and the error experienced by the device; and

obtain from the artificial intelligence the first plurality of relevance indicators and the first plurality of troubleshooting procedures.

19 . The system of claim 14 , comprising instructions to:

obtain session duration, success rate associated with historical troubleshooting sessions; and

based on the session duration and the success rate associated with the historical troubleshooting sessions, provide time, complexity, a number of parts, and a material cost required to perform the troubleshooting procedure.

20 . The system of claim 14 , wherein instructions to provide the first plurality of relevance indicators and the first plurality of troubleshooting procedures comprise instructions to:

order the first plurality of relevance indicators in a descending sequence;

obtain multiple predetermined categories associated with the first plurality of relevance indicators,

wherein the multiple predetermined categories indicate ranges associated with the first plurality of relevance indicators, and

wherein the multiple predetermined categories are color coded;

color the first plurality of relevance indicators based on the multiple predetermined categories; and

provide the colored first plurality of relevance indicators in the descending sequence.