Since the LSTM gave a significant improvement, this model was chosen for the more ambitious target of predicting future product formation. Because current product can be predicted relatively accurately (MAE of 1.2%), a time-series of predicted product values was obtained. These predicted product values and the sensor data are then fed into a second model to predict the product conversion in the future. The results from the cross-validation of the two LSTM models are shown in Figure . There is a large (but unsurprising) increase in error when predicting just 30 minutes ahead.