Processing

Please wait...

Settings

Settings

Goto Application

1. WO2018133919 - 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. Method for predicting the life expectancy (24) of a component of an observed vehicle, wherein

- a processing unit is fed with status data (8) of selected components of several vehicles,

- the processing unit is fed with an operating parameter (10) for each of these selected components of the several vehicles, which operating parameter (10) influences the status data (8) of the respective selected component,

- a function (16) between the operating parameter (10) and the status data (8) is determined for each of the selected components ,

- one function (16), which fits best for the component of the observed vehicle, is selected by means of an algorithm,

- the processing unit is fed with an operating parameter (22) of the component of the observed vehicle, and,

- the life expectancy (24) of the component of the observed vehicle is predicted by the processing unit using the se- lected function (16) and the operating parameter (22) of the component of the observed vehicle.

2. Method according to claim 1,

characterised in that

the operating parameter (10) is a mileage, an operating time, an operating number and/or an operating power.

3. Method according to claim 1 or 2,

characterised in that

the status data (8) are current and/or past status data (8), and that the status data (8) represent wear of the respective component .

4. Method according to any of the preceding claims,

characterised in that the status data (8) comprise information regarding inspection ( s ) , maintenance ( s ) , and/or exchange (s) of the respective component and/or regarding the status of the respective component.

5. Method according to claim 4,

characterised in that

the information is selected from maintenance data (4) of the respective vehicles by means of text analysis (6), particularly by means of text mining.

6. Method according to claim 5,

characterised in that,

by means of the text analysis (6),

text of the maintenance data (4) is structured,

a keyword dictionary is created,

the text of the maintenance data (4) is searched for keywords of the keyword dictionary, and

the information of the text is found.

7. Method according to any of the preceding claims,

characterised in that

- the function (16) between the operating parameter (10) and the status data (8) is determined for each of the selected components, wherein each of the determined functions (16) has a slope (20), particularly an averaged slope (20),

- one slope, which fits best for the component of the observed vehicle, is selected by means of an algorithm, and - the life expectancy (24) of the component of the observed vehicle is predicted by means of the selected slope.

8. Method according to any of the preceding claims,

characterised in that

it is determined, if a number of maintenances and/or exchanges within a given time interval is time-dependent, and, when the number of maintenances and/or exchanges within the given time interval is time-dependent, the determined function (16) between the operating parameter (10) and the status data (8) is time-dependent within the given time interval .

9. Method according to any of the preceding claims,

characterised in that

maintenance ( s ) and/or exchange (s) of a component of at least one of the several vehicles, which maintenance ( s ) and/or ex-change (s) are caused by a reason (28) that is independent from the operating parameter (10), are neglected for predicting the life expectancy (24) of the component of the observed vehicle .

10. Method according to any of the preceding claims,

characterised in that

it is determined, if a number of maintenances and/or replacements depends on the operating parameter (10), and

when the number of maintenances and/or replacements depends on the operating parameter (10), this range of the operating parameter (10) with the highest number of maintenances and/or exchanges is determined.

11. Method according to any of the preceding claims,

characterised in that

by predicting the life expectancy (24) of a component it is predicted when a maintenance and/or a replacement of the component is/are necessary.

12. Method for operating an observed vehicle, wherein the method according to any of the preceding claims is executed, characterised in that,

when the predicted life expectancy (24) of the component is reached, the component is maintained and/or exchanged.

13. Method for operating an observed vehicle, wherein the method according to any of the preceding claims is executed, characterised in that

a previous maintenance strategy regarding the point of time, at which the component has been maintained and/or exchanged in the past, is compared with a required point of time for maintaining and/or exchanging.

14. Method for operating an observed vehicle, wherein the method according to any of the preceding claims is executed, characterised in that

reasons (28) which lead to maintenance and/or exchange of the component, and their probability are determined, the most frequent reason is determined and the most frequent reason is decreased and/or eliminated by changing/optimising the component .

15. Processing unit for predicting the life expectancy (24) of a component of an observed vehicle,

wherein the processing unit is embodied

- to be fed with status data (8) of components of selected vehicles ,

- to be fed with an operating parameter (10) for each of these selected components of the several vehicles, which operating parameter (10) influences the status data (8) of the respective selected component,

- to determine a function (16) between the operating parame- ter (10) and the status data (8) for each of the selected components ,

- to select one function (16), which fits best for the component of the observed vehicle, by means of an algorithm,

- to be fed with an operating parameter (22) of the component of the observed vehicle, and

- to predict the life expectancy (24) of the component of the observed vehicle by means of the selected function (16) and on the basis of the operating parameter (22) of the component of the observed vehicle.