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1. US20190347875 - Method for predicting the life expectancy of a component of an observed vehicle and processing unit

Note: Text based on automatic Optical Character Recognition processes. Please use the PDF version for legal matters

[ EN ]

Claims

1. A method of predicting a life expectancy of a component of an observed vehicle, the method comprising:
feeding status data of selected components of a plurality of vehicles to a processing unit;
feeding to the processing unit an operating parameter for each of the selected components of the plurality vehicles, the operating parameter influencing the status data of the respective selected component;
determining a function between the operating parameter and the status data for each of the selected components;
selecting one function, which fits best for the component of the observed vehicle, by way of an algorithm;
feeding to the processing unit an operating parameter of the component of the observed vehicle;
predicting the life expectancy of the component of the observed vehicle with the processing unit using the one function and the operating parameter of the component of the observed vehicle;
determining the function between the operating parameter and the status data for each of the selected components, each of the determined functions having a slope;
selecting one slope, which fits best for the component of the observed vehicle, by way of an algorithm, and predicting the life expectancy of the component of the observed vehicle by way of the selected slope; and
at least one of performing maintenance on the component of the observed vehicle or exchanging the component of the observed vehicle based on the life expectancy of the component of the observed vehicle predicted in the predicting step.
2. The method according to claim 1, wherein the operating parameter for each of the selected components of the plurality vehicles is at least one parameter selected from the group consisting of a mileage, an operating time, an operating number, and an operating power.
3. The method according to claim 1, wherein the status data are at least one of current or past status data, and the status data represent wear of the respective component.
4. The method according to claim 1, wherein the status data comprises at least one of information regarding inspection, maintenance, or exchange of the respective component or regarding the status of the respective component.
5. The method according to claim 4, which comprises selecting the information from maintenance data of the respective vehicles by text analysis.
6. The method according to claim 5, which comprises selecting the information from the maintenance data by text mining.
7. The method according to claim 5, wherein the text analysis comprises:
structuring the text of the maintenance data;
creating a keyword dictionary;
searching the text of the maintenance data for keywords of the keyword dictionary; and
finding the information contained in the text.
8. The method according to claim 1, wherein the slope is an average slope.
9. The method according to claim 1, which comprises determining whether or not a number of maintenances or exchanges within a given time interval is time-dependent, and, when the number of maintenances or exchanges within the given time interval is time-dependent, the determined function between the operating parameter and the status data is time-dependent within the given time interval.
10. The method according to claim 1, which comprises, when at least one of a maintenance or exchange are caused by a reason that is independent from the operating parameter, neglecting the at least one of the maintenance or exchange of a component of at least one of the plurality of vehicles for predicting the life expectancy of the component of the observed vehicle.
11. The method according to claim 1, wherein predicting the life expectancy of a component comprises predicting when at least one of a maintenance or a replacement of the component becomes necessary.
12. A method for operating a vehicle, the method comprising:
observing the vehicle and executing the method according to claim 1 for determining and predicting a life expectancy of a component; and
when the predicted life expectancy of the component is reached subjecting the component to at least one of maintenance or exchanging the component.
13. A method for operating an observed vehicle, the method comprising:
executing the method according to claim 1;
comparing a previous maintenance strategy regarding a point of time at which the component was at least one of maintained or exchanged in the past, with a required point of time for at least one of maintaining or exchanging.
14. A method for operating an observed vehicle, the method comprising:
executing the method according to claim 1;
determining reasons which lead to at least one of maintenance or exchange of the component, and a probability thereof, determining a most frequent reason, and decreasing or eliminating the most frequent reason by changing/optimizing the component.
15. A method of predicting a life expectancy of a component of an observed vehicle, the method comprising:
feeding status data of selected components of a plurality of vehicles to a processing unit;
feeding to the processing unit an operating parameter for each of the selected components of the plurality vehicles, the operating parameter influencing the status data of the respective selected component;
determining a function between the operating parameter and the status data for each of the selected components;
selecting one function, which fits best for the component of the observed vehicle, by way of an algorithm;
feeding to the processing unit an operating parameter of the component of the observed vehicle;
predicting the life expectancy of the component of the observed vehicle with the processing unit using the one function and the operating parameter of the component of the observed vehicle;
determining whether at least one of a number of maintenances or replacements depends on the operating parameter;
when the at least one of a number of maintenances or replacements depends on the operating parameter, determining a range of the operating parameter with a highest number of maintenances or exchanges; and
at least one of performing maintenance on the component of the observed vehicle or exchanging the component of the observed vehicle based on the life expectancy of the component of the observed vehicle predicted in the predicting step.