I am a new knime user and I am looking for some guidance on how to set up a workflow to identify fault patterns in airplane maintenance data. The data is time stamped, has each airplane tail number and reported fault plus fault code and corrective action. I am looking for some way to identify repeat faults on a single airplane system over the space of approximately 1 to 3 months.
Any guidance would be most useful.
Predictive maintenance is a big topic.
If you have fault examples, you might want to apply any predictive techniques. See for example https://www.knime.org/knime-applications/churn-prediction Instead of churn flags you use fault flags.
However, if you do not have many fault examples, you can check this whitepaper on how to do predictive maintenance without fault examples https://www.knime.org/files/Anomaly_Detection_Time_Series_final.pdf
I hope one of these two examples can help you