1. Selection of Aircraft Industry datasets fitting the research scope and model requirements.
2. Clean the data, removing anomalies not representative of the dataset.
3. Shape the data to (X, Y, Z) dimensions: X datasets, Y timesteps, Z features.
4. Train the chosen model for time series synthesis.
5. Measure the performance of each model using fidelity testing metrics like Autocorrelation and Kullback-
Leibler, and optimise accordingly.
6. Gather final results using fidelity metrics and visual inspection.