How can LSTM networks be implemented as part of preventative maitenance?

• Step 1 - Data collection (e.g., historical inspection data) • Step 2 - Data preprocessing (e.g., handle missing values, and normalize the data) • Step 3 - Design an LSTM network (e.g., input layers, LSTM layers, and output layers) • Step 4 – Training the model (e.g., Split the preprocessed data into training and validation sets) • Step 5 - Model evaluation (e.g., Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) ) • Step 6 - Predictive maintenance (e.g., schedule maintenance based on residual life prediction) • Step 7 - Continuous improvement (e.g., continuously collect new data for training)