Method and system for performing vehicle inspection
First Claim
1. A method for optimizing vehicle failure detection using data from various locations in a vehicle failure detection network, the method comprising:
- receiving, by a vehicle inspection computing device, inspection data of one or more parts of a vehicle from an inspection database associated with the vehicle failure detection network;
receiving, by the vehicle inspection computing device, field data of the one or more parts of the vehicle from a field failure database associated with the vehicle failure detection network;
associating, by the vehicle inspection computing device, the inspection data and the field data, based on an identification number of the vehicle, to obtain a joined data using an association algorithm;
identifying, by the vehicle inspection computing device, a set of relevant equivalent terms from the inspection data and the field data for a selected one of the one or more parts of the vehicle from one or more failure comments in the joined data using at least one of text mining algorithms, tagging, semantic rules, Natural Language Processing (NLP), or correlation plots;
determining, by the vehicle inspection computing device, a frequency of the set of relevant equivalent terms for the selected one of the one or more parts of the vehicle in the joined data;
detecting, by the vehicle inspection computing device, an existence of failure of the vehicle when the determined frequency of the set of relevant equivalent terms for the selected one of the one or more parts of the vehicle exceeds a predefined threshold frequency;
providing, by the vehicle inspection computing device, a notification indicating defects in the selected one of the one or more parts of the vehicle based on the existence of failure of the vehicle; and
providing, by the vehicle inspection computing device, a recommendation indicating one or more corrective actions with respect to the defects in the selected one of the one or more parts of the vehicle, wherein the one or more corrective actions comprise correcting the defects or replacing the selected one of the one or more parts of the vehicle.
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Abstract
The present disclosure relates to a method and system for performing vehicle inspection. In an embodiment, the system receives inspection data of one or more parts of vehicle from inspection database and field data of the one or more parts of the vehicle from the field database. The inspection database is at manufacturing unit of the vehicle and the field database is at service unit of the vehicle. The inspection data and the field data are associated to form a joined data. A user may select one of one or more parts of the vehicle from the joined database. The system identifies relevant terms for the selected part of the vehicle and also identifies the frequency of the selected part in the inspection data and the field data. If the frequency exceeds a threshold frequency, then the system detects the probability of failure of the vehicle.
3 Citations
18 Claims
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1. A method for optimizing vehicle failure detection using data from various locations in a vehicle failure detection network, the method comprising:
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receiving, by a vehicle inspection computing device, inspection data of one or more parts of a vehicle from an inspection database associated with the vehicle failure detection network; receiving, by the vehicle inspection computing device, field data of the one or more parts of the vehicle from a field failure database associated with the vehicle failure detection network; associating, by the vehicle inspection computing device, the inspection data and the field data, based on an identification number of the vehicle, to obtain a joined data using an association algorithm; identifying, by the vehicle inspection computing device, a set of relevant equivalent terms from the inspection data and the field data for a selected one of the one or more parts of the vehicle from one or more failure comments in the joined data using at least one of text mining algorithms, tagging, semantic rules, Natural Language Processing (NLP), or correlation plots; determining, by the vehicle inspection computing device, a frequency of the set of relevant equivalent terms for the selected one of the one or more parts of the vehicle in the joined data; detecting, by the vehicle inspection computing device, an existence of failure of the vehicle when the determined frequency of the set of relevant equivalent terms for the selected one of the one or more parts of the vehicle exceeds a predefined threshold frequency; providing, by the vehicle inspection computing device, a notification indicating defects in the selected one of the one or more parts of the vehicle based on the existence of failure of the vehicle; and providing, by the vehicle inspection computing device, a recommendation indicating one or more corrective actions with respect to the defects in the selected one of the one or more parts of the vehicle, wherein the one or more corrective actions comprise correcting the defects or replacing the selected one of the one or more parts of the vehicle. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A vehicle inspection computing device comprising a processor and a memory coupled to the processor which is configured to be capable of executing programmed instructions comprising and stored in the memory to:
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receive inspection data of one or more parts of a vehicle from an inspection database associated with a vehicle failure detection network; receive field data of the one or more parts of the vehicle from a field failure database associated with the vehicle failure detection network; associate the inspection data and the field data, based on an identification number of the vehicle, to obtain a joined data using an association algorithm; identify a set of relevant equivalent terms from the inspection data and the field data for a selected one of the one or more parts of the vehicle from one or more failure comments in the joined data using at least one of text mining algorithms, tagging, semantic rules, Natural Language Processing (NLP), or correlation plots; determine a frequency of the set of relevant equivalent terms for the selected one of the one or more parts of the vehicle in the joined data; and detect an existence of failure of the vehicle when the determined frequency of the set of relevant equivalent terms for the selected one of the one or more parts of the vehicle exceeds a predefined threshold frequency; provide a notification indicating defects in the selected one of the one or more parts of the vehicle based on the existence of failure of the vehicle; and provide a recommendation indicating one or more corrective actions with respect to the defects in the selected one of the one or more parts of the vehicle, wherein the one or more corrective actions comprise correcting the defects or replacing the selected one of the one or more parts of the vehicle. - View Dependent Claims (8, 9, 10, 11, 12)
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13. A non-transitory computer readable medium having stored thereon instructions for performing vehicle inspection comprising executable code which when executed by a process causes the processor to perform steps comprising:
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receiving inspection data of one or more parts of a vehicle from an inspection database associated with a vehicle failure detection network; receiving field data of the one or more parts of the vehicle from a field failure database associated with the vehicle failure detection network; associating the inspection data and the field data, based on an identification number of the vehicle, to obtain a joined data using an association algorithm; identifying a set of relevant equivalent terms from the inspection data and the field data for a selected one of the one or more parts of the vehicle from one or more failure comments in the joined data using at least one of text mining algorithms, tagging, semantic rules, Natural Language Processing (NLP), or correlation plots; determining a frequency of the set of relevant equivalent terms for the selected one of the one or more parts of the vehicle in the joined data; detecting an existence of failure of the vehicle when the determined frequency of the set of relevant equivalent terms for the selected one of the one or more parts of the vehicle exceeds a predefined threshold frequency; and providing a notification indicating defects in the selected one of the one or more parts of the vehicle based on the existence of failure of the vehicle; and providing a recommendation indicating one or more corrective actions with respect to the defects in the selected one of the one or more parts of the vehicle, wherein the one or more corrective actions comprise correcting the defects or replacing the selected one of the one or more parts of the vehicle. - View Dependent Claims (14, 15, 16, 17, 18)
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Specification