Predictive maintenance model design system

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

• receiving a historical dataset relating to each system of a plurality of systems, the historical dataset including time-labeled maintenance and operational data,
• receiving a first selection of a first operational data feature and a first system,
• displaying operational data associated with the first operational data feature and the first system on a timeline in a graphical user interface,
• displaying maintenance data associated with the first system on the timeline,
• receiving a second selection of a second operational data feature, and
• generating a predictive maintenance model, using the second operational data feature according to a machine learning method.

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 comprising:
• at least one instruction to receive a historical dataset relating to each system of a plurality of systems, the historical dataset including time-labeled maintenance and operational data,
• at least one instruction to receive a first selection of a first operational data feature and a first system,
• at least one instruction to display operational data associated with the first operational data feature and the first system on a timeline in a graphical user interface,
• at least one instruction to display maintenance data associated with the first system on the timeline,
• at least one instruction to receive a second selection of a second operational data feature, and
• at least one instruction to generate a predictive maintenance model, using the second operational data feature according to a machine learning method.