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 maintenance data and operational data,
• evaluating the importance of each of a plurality of operational data features in predicting each of a plurality of maintenance events of the maintenance data, using a supervised machine learning classification model,
• displaying a quantitative result of the evaluation for each operational data feature in a graphical user interface,
• receiving a selection of one or more operational data features of the plurality of operational data features,
• generating a predictive maintenance model, using the selected one or more operational data features according to a machine learning method.

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,
• evaluate correlation between each of a plurality of operational data features and maintenance events of the maintenance data, using iteration of a supervised machine learning classification model with recursive feature elimination,
• display a quantitative result of the evaluation for each operational data feature in a graphical user interface,
• receive a selection of one or more operational data features of the plurality of operational data features, and
• generate a predictive maintenance model, using the selected one or more operational data features according to a machine learning method.