US 12,227,307 B2
Predictive maintenance model design system
Robert Michael Leitch, Vancouver (CA); Yikan Wang, Burnaby (CA); and Bingjing Yu, Richmond (CA)
Assigned to The Boeing Company, Arlington, VA (US)
Filed by The Boeing Company, Chicago, IL (US)
Filed on Jul. 17, 2021, as Appl. No. 17/378,677.
Claims priority of provisional application 63/055,289, filed on Jul. 22, 2020.
Prior Publication US 2022/0024607 A1, Jan. 27, 2022
Int. Cl. B64F 5/40 (2017.01); B64F 5/60 (2017.01); G05B 23/02 (2006.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01); G06Q 10/20 (2023.01)
CPC B64F 5/40 (2017.01) [B64F 5/60 (2017.01); G05B 23/0216 (2013.01); G05B 23/0235 (2013.01); G05B 23/024 (2013.01); G05B 23/0281 (2013.01); G05B 23/0283 (2013.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G06Q 10/20 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A data processing system for generating predictive maintenance models, comprising:
one or more processors;
a memory including one or more digital storage devices; and
a plurality of instructions stored in the memory and executable by the one or more processors to:
receive a historical dataset relating to each system of a plurality of systems, the historical dataset including maintenance data and operational data,
display one or more algorithm templates and one or more data features calculated from the operational data in a graphical user interface (GUI),
receive from a user a selection of an algorithm template, a data feature, and a first value of a parameter associated with the algorithm template, via the GUI,
subsequently train and evaluate the selected algorithm template on the selected data feature according to the first value of the parameter,
display a first result of a metric of the evaluation in the GUI, and
generate a predictive maintenance model, using the selected algorithm template.