Predictive maintenance model design system

A computer implemented method of generating a predictive maintenance model, comprising:

• receiving, by a device, a historical dataset relating to each system of a plurality of systems,
• wherein the plurality of systems includes a fleet of aircraft, and
• wherein the historical dataset includes maintenance data and operational data;
• receiving, by the device, a rule set for processing a first attribute of the operational data;
• calculating, by the device, a custom data feature from the historical dataset according to the received rule set;
• calculating, by the device, the custom data feature from a first sample of labelled data and a second sample of labelled data according to the received rule set,
• wherein the first sample of labelled data is randomly selected from flights having a first label, and the second sample of labelled data is randomly selected from flights having a second label;
• displaying, by the device, a comparison of the custom data feature for the first sample of labelled data and the second sample of labelled data,
• wherein the first sample of labelled data and second sample of labelled data are subsets of the operational data of the historical dataset, labelled according to a corresponding subset of maintenance data of the historical dataset;
• generating, by the device, a predictive maintenance model using the custom feature according to a machine learning method;
• receiving, by the device, additional operational data;
• inputting, by the device, the additional operational data to the predictive maintenance model;
• implementing, by the device, the predictive maintenance model;
• and
• causing, by the device, a preventative maintenance action to occur based on implementing the predictive maintenance model.

A computer program product for generating predictive maintenance models, the computer program product comprising:

• a non-transitory computer-readable storage medium having computer-readable program code embodied in the storage medium, the computer-readable program code configured to cause a data processing system to generate a predictive maintenance model, the computer-readable program code configured to:
• receive a historical dataset relating to each system of a plurality of systems,
• wherein the plurality of systems includes a fleet of aircraft, and
• wherein the historical dataset includes maintenance data and operational data;
• receive a rule set for processing a first attribute of the operational data;
• calculate a custom data feature from the historical dataset according to the received rule set;
• calculate the custom data feature from a first sample of labelled data and a second sample of labelled data according to the received rule set,
• wherein the first sample of labelled data is randomly selected from flights having a first label, and the second sample of labelled data is randomly selected from flights having a second label;
• display a comparison of the custom data feature for the first sample of labelled data and the second sample of labelled data,
• wherein the first sample of labelled data and second sample of labelled data are subsets of the operational data of the historical dataset, labelled according to a corresponding subset of maintenance data of the historical dataset;
• generate a predictive maintenance model using the custom feature according to a machine learning method;
• receive additional operational data;
• input the additional operational data to the predictive maintenance model;
• implement the predictive maintenance model;
• and
• cause preventative maintenance action based on implementing the predictive maintenance model,
• wherein the preventative maintenance action includes one or more of:
• an inspection of equipment,
• testing of the equipment,
• repair of the equipment, or
• replacement of the equipment.