Dealing with gaps in time series with TWA

My use case consist of machines sending data periodically (when machines are on). I want to predict failures.

I created a dataset with computed features for each on cycles and  then create a model on TWA.

But features are complexes to compute inside TW, so putting this model to production will be unconvinient.

I have 2 questions to make a better/easier use of TW for this use case (and for my personnal understanding of TW) :

• Is there a way that Thingworx can handle breaks in time series to create a model?
• Can Anomaly detection understand this kind of pattern and don't mind of time gaps between the next cycle (see joined image of a normal and failure cycle).