US 11,851,034 B2
Predicting vehicle repair operations
James Gareth Davies, Ann Arbor, MI (US); Anthony Peter Griffiths, Swansea (GB); Christopher Lee Davies, Swansea (GB); Martyn Neil Jones, Llandarcy (GB); Stephen David Norris, London (GB); Christopher George Reed, London (GB); Patrick James Tudor, Sketty (GB); Timothy Peter Davis, Warwick (GB); David Hong Sau Chung, London (GB); Michael Paul Nicholas, Ann Arbor, MI (US); Kelly Marie Nock, Cardiff (GB); Jonathan Michael Phillips, Bridgend (GB); Ashley Steven Burgess, St. Thomas (GB); Nicholas Peter Rees, London (GB); and Steffan Rees, London (GB)
Assigned to WE PREDICT LIMITED
Filed by We Predict Limited, Swansea (GB)
Filed on Aug. 12, 2021, as Appl. No. 17/400,490.
Application 17/400,490 is a continuation of application No. 16/834,036, filed on Mar. 30, 2020, granted, now 11,117,555.
Application 16/834,036 is a continuation of application No. PCT/US2018/053718, filed on Oct. 1, 2018.
Application PCT/US2018/053718 is a continuation of application No. PCT/US2017/069021, filed on Dec. 29, 2017.
Claims priority of provisional application 62/570,469, filed on Oct. 10, 2017.
Claims priority of provisional application 62/570,456, filed on Oct. 10, 2017.
Claims priority of provisional application 62/565,933, filed on Sep. 29, 2017.
Claims priority of provisional application 62/565,927, filed on Sep. 29, 2017.
Prior Publication US 2021/0380076 A1, Dec. 9, 2021
This patent is subject to a terminal disclaimer.
Int. Cl. B60S 5/00 (2006.01); G05B 23/02 (2006.01); G07C 5/08 (2006.01)
CPC B60S 5/00 (2013.01) [G05B 23/0283 (2013.01); G07C 5/085 (2013.01); G07C 5/0808 (2013.01); G07C 5/0816 (2013.01)] 17 Claims
OG exemplary drawing
 
1. A method of predicting machine repair operations or machine component faults for a pre-defined variant of a machine variant class, the method comprising, at a processing stage:
selecting, by a predictive algorithm executed at the processing stage, a set of machine repair records for use in making a prediction, each of the machine repair records being a record of a machine repair performed after the machine entered active service, each of which comprises or indicates a historical machine age or usage value, and records a repair operation or machine component fault,
wherein the predictive algorithm uses the selected set of machine repair records to predict a number of, or resource value for, repair operations or machine component faults for a set of machine records, each of the machine records being a record of a machine entering active service, based on: a number of machines recorded in the set of machine records being of the pre-defined variant, and a current age or usage of each of the recorded machines; and
determining a profile for the set of machine repair records based on a number of, or resource value for, repair operations or machine component faults recorded in the set of machine repair records for different historical machine age or usage values, the profile being used to make the prediction,
wherein the step of determining the profile comprises: determining a total number of, or resource value for, repair operations/machine component faults recorded in the filtered set of machine repair records, each resource or count value being calculated as a proportion of the total,
wherein an earnings value is calculated for each of the historical machine age or usage values of the profile based on the corresponding resource or count value of the profile and the number of machines recorded in the set of machine records whose current age or usage matches that historical machine age or usage value of the profile.