Abstract: Methods and systems for using natural language processing and machine-learning algorithms to process vehicle-service data to generate metadata regarding the vehicle-service data are described herein. A processor can discover vehicle-service data that can be clustered together based on the vehicle-service data having common characteristics. The clustered vehicle-service data can be classified (e.g., categorized) into any one of a plurality of categories. One of the categories can be for clustered vehicle-service data that is tip-worthy (e.g., determined to include data worthy of generating vehicle-service content (e.g., a repair hint). Another category can track instances of vehicle-service data that are considered to be common to an instance of vehicle-service data classified into the tip-worthy category. The vehicle-service data can be collected from repair orders from a plurality of repair shops. The vehicle-service content generated by the systems can be provided to those or other repair shops.

Abstract: In an embodiment, a method includes receiving, at a vehicle scan tool, a request for automated vehicle scan tool initialization, the request comprising a function identifier for a vehicle scan tool function and a vehicle identifier for a vehicle, where the vehicle scan tool is configured to display at least one navigable menu. The method additionally includes determining a current operating state of the vehicle scan tool. Based on the current operating state of the vehicle scan tool, the method further includes making a determination to initialize the vehicle scan tool according to the request for automated vehicle scan tool initialization. In response to making the determination, the method also includes using the function identifier and the vehicle identifier to initialize the vehicle scan tool to perform the vehicle scan tool function on the vehicle.

Abstract: An example method for outputting a PID filter list (PFL) includes: receiving RO data from one or more ROs that indicate particular vehicle identifying information (PVII), at least one symptom identifier, and a particular vehicle component; determining, symptom-to-parameter-identifier (PID) mapping data (MD) based on the received RO data and component-to-PID MD; determining, based on the set of available PIDs for the SOV and the symptom-to-PID MD, a PFL, wherein the PFL is associated with the PVII and the at least one symptom identifier, and wherein the PFL indicates a symptom-based subset of PIDs from the set of available PIDs for the SOV; receiving, a request sent over a communication network from a display device, wherein the request comprises the PVII and the at least one symptom identifier; and transmitting, over the communication network to the display device, a response to the request, the response comprising the PFL.

Abstract: A method comprising outputting, for transmission to a server, a request including an identifier of a service session record (SSR) corresponding to a vehicle. The SSR includes a timeline for tracking event(s) corresponding to the SSR. The method includes receiving, in response to the request, a graphical user interface (GUI) corresponding to the SSR, and displaying the GUI in a first display mode. Displaying the GUI in the first display mode includes displaying an event summary of the timeline. The event summary corresponds to a first event of the SSR and includes a user-selectable control selectable to trigger changing a display mode of the GUI. Furthermore, the method includes displaying, in response to a selection of the user-selectable control, the GUI in a second display mode. Displaying the GUI in the second display mode includes displaying a particular detail regarding the first event not shown in the first display mode.

Abstract: An example method includes determining identifying information for a vehicle to be serviced. The method further includes receiving at least one symptom identifier for the vehicle. The method further includes sending a request over a communication network to a remote server for a PID filter list for the vehicle, the request comprising the identifying information for the vehicle and the at least one symptom identifier for the vehicle. The method additionally includes receiving a response to the request over the communication network from the remote server, the response comprising the PID filter list for the vehicle. The method further includes determining, based on the PID filter list for the vehicle, a symptom-based subset of PIDs for the vehicle from a set of available PIDs. The method additionally includes displaying, on a display interface, the symptom-based subset of PIDs for the vehicle.

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.

Abstract: An example method includes determining identifying information for a vehicle to be serviced. The method further includes receiving at least one symptom identifier for the vehicle. The method further includes sending a request over a communication network to a remote server for a PID filter list for the vehicle, the request comprising the identifying information for the vehicle and the at least one symptom identifier for the vehicle. The method additionally includes receiving a response to the request over the communication network from the remote server, the response comprising the PID filter list for the vehicle. The method further includes determining, based on the PID filter list for the vehicle, a symptom-based subset of PIDs for the vehicle from a set of available PIDs. The method additionally includes displaying, on a display interface, the symptom-based subset of PIDs for the vehicle.

Abstract: Methods and systems for using natural language processing and machine-learning algorithms to process vehicle-service data to generate metadata regarding the vehicle-service data are described herein. A processor can discover vehicle-service data that can be clustered together based on the vehicle-service data having common characteristics. The clustered vehicle-service data can be classified (e.g., categorized) into any one of a plurality of categories. One of the categories can be for clustered vehicle-service data that is tip-worthy (e.g., determined to include data worthy of generating vehicle-service content (e.g., a repair hint). Another category can track instances of vehicle-service data that are considered to be common to an instance of vehicle-service data classified into the tip-worthy category. The vehicle-service data can be collected from repair orders from a plurality of repair shops. The vehicle-service content generated by the systems can be provided to those or other repair shops.

Abstract: An example method for outputting a PID filter list (PFL) includes: receiving RO data from one or more ROs that indicate particular vehicle identifying information (PVII), at least one symptom identifier, and a particular vehicle component; determining, symptom-to-parameter-identifier (PID) mapping data (MD) based on the received RO data and component-to-PID MD; determining, based on the set of available PIDs for the SOV and the symptom-to-PID MD, a PFL, wherein the PFL is associated with the PVII and the at least one symptom identifier, and wherein the PFL indicates a symptom-based subset of PIDs from the set of available PIDs for the SOV; receiving, a request sent over a communication network from a display device, wherein the request comprises the PVII and the at least one symptom identifier; and transmitting, over the communication network to the display device, a response to the request, the response comprising the PFL.

Abstract: A method for performing test set. After determining the test set and a vehicle identifier, a processor of a computing system determines: (1) a component test (CT) and a functional test command (FTC), (2) the CT and a first set of parameter identifiers (PIDs), or (3) the FTC and a second set of PIDs. The CT corresponds to a particular vehicle component. The FTC is for requesting control of a controllable vehicle component. If the CT is determined, a test device is configured to be in a mode to perform the CT. If the FTC is determined, a GUI including a user-selectable control corresponding to the FTC is displayed. If the first or second set of PIDs is determined, a set of parameter values corresponding to the determined set of PIDs is received and displayed in response to vehicle data messages transmitted by the computing system.

Abstract: A method comprising determining a functional test and one or more parameter identifiers (PIDs) corresponding to the functional test. The method also includes transmitting first and second sets of vehicle data messages to a vehicle. The first set of vehicle data messages includes a first vehicle data message to request performance of the functional test and the second set of vehicle data messages includes vehicle data messages including the one or more PIDs. Additionally, the method includes receiving, from the vehicle, a third set of vehicle data message including parameter values corresponding to the one or more PIDs. Furthermore, the method includes outputting, by the processor on a display, a first graphical user interface including a user-selectable control corresponding to performance of the functional test, a textual description corresponding to each of the one or more PIDs and parameter values corresponding to the one or more PIDs.

Abstract: Methods and systems for using natural language processing and machine-learning algorithms to process vehicle-service data to generate metadata regarding the vehicle-service data are described herein. A processor can discover vehicle-service data that can be clustered together based on the vehicle-service data having common characteristics. The clustered vehicle-service data can be classified (e.g., categorized) into any one of a plurality of categories. One of the categories can be for clustered vehicle-service data that is tip-worthy (e.g., determined to include data worthy of generating vehicle-service content (e.g., a repair hint). Another category can track instances of vehicle-service data that are considered to be common to an instance of vehicle-service data classified into the tip-worthy category. The vehicle-service data can be collected from repair orders from a plurality of repair shops. The vehicle-service content generated by the systems can be provided to those or other repair shops.

Abstract: An example method for outputting a PID filter list (PFL) includes: receiving RO data from one or more ROs that indicate particular vehicle identifying information (PVII), at least one symptom identifier, and a particular vehicle component; determining, symptom-to-parameter-identifier (PID) mapping data (MD) based on the received RO data and component-to-PID MD; determining, based on the set of available PIDs for the SOV and the symptom-to-PID MD, a PFL, wherein the PFL is associated with the PVII and the at least one symptom identifier, and wherein the PFL indicates a symptom-based subset of PIDs from the set of available PIDs for the SOV; receiving, a request sent over a communication network from a display device, wherein the request comprises the PVII and the at least one symptom identifier; and transmitting, over the communication network to the display device, a response to the request, the response comprising the PFL.

Abstract: A method includes a computer operating in a first state in which a parameter-identifier condition indicator is not displayed. The computer determines a vehicle identifier corresponding to a vehicle. The vehicle includes a component corresponding to a component identifier and system corresponding to a system identifier, and can exhibit a symptom corresponding to a symptom identifier. The computer determines the component identifier, system identifier, and/or symptom identifier, and a corresponding PID topic. The computer switches to a second state. The method includes determining, a parameter-identifier topic corresponding to parameter-identifier(s).

Abstract: A method includes determining a test drive script (TDS) to perform while a tool monitors an electronic system in a mobile machine during a test drive of the mobile machine. The TDS includes an ordered sequence of drive cycle procedures (DCPs). The ordered sequence of DCPs begins with an initial DCP and ends with a final DCP. Each DCP is indicative of a respective mobile machine state. The TDS includes a first particular DCP associated with both a first particular mobile machine state and a first condition pertaining to the first particular mobile machine state. The method also includes outputting a representation of at least a portion of the TDS. Additionally, the method includes determining and outputting one or more of: status information corresponding to achieving the first particular mobile machine state or status information corresponding to achieving the first condition pertaining to the first particular mobile machine state.

Abstract: An example method involves receiving, at a computing system, vehicle diagnostic information from a vehicle. The vehicle diagnostic information may include one or more sets of parameters corresponding to parameter identifiers (PIDs). The method further involves identifying a first set of parameters corresponding to a PID representing a state of a particular system of the vehicle and determining, using the first set of parameters, a current value of the PID. The method may also involve performing a comparison between the current value and a predetermined value for the PID and determining a health of the particular system of the vehicle such that the health reflects a difference between the current value and the predetermined value for the PID. The method may also involve displaying, by the computing system at a graphical interface, a vehicle health record representing the health of the particular system of the vehicle.

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.

Abstract: An example method involves receiving, at a computing system, vehicle diagnostic information from a vehicle. The vehicle diagnostic information may include one or more sets of parameters corresponding to parameter identifiers (PIDs). The method further involves identifying a first set of parameters corresponding to a PID representing a state of a particular system of the vehicle and determining, using the first set of parameters, a current value of the PID. The method may also involve performing a comparison between the current value and a predetermined value for the PID and determining a health of the particular system of the vehicle such that the health reflects a difference between the current value and the predetermined value for the PID. The method may also involve displaying, by the computing system at a graphical interface, a vehicle health record representing the health of the particular system of the vehicle.

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.

Abstract: A method includes determining a test drive script (TDS) to perform while a tool monitors an electronic system in a mobile machine during a test drive of the mobile machine. The TDS includes an ordered sequence of drive cycle procedures (DCPs). The ordered sequence of DCPs begins with an initial DCP and ends with a final DCP. Each DCP is indicative of a respective mobile machine state. The TDS includes a first particular DCP associated with both a first particular mobile machine state and a first condition pertaining to the first particular mobile machine state. The method also includes outputting a representation of at least a portion of the TDS. Additionally, the method includes determining and outputting one or more of: status information corresponding to achieving the first particular mobile machine state or status information corresponding to achieving the first condition pertaining to the first particular mobile machine state.