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Predictive Maintenance Using LSTM and GRU on NASA Turbofan Engine Dataset Assignment Deliverable

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This project repository contains a code folder, PDF project report and generative AI appendix, visualizations folder, and this readme. Descriptions of each of these items can be found below.

Code Folder: -- main_rul.ipynb is a jupyter notebook in which the NASA CMAPSS Jet Simulated Data is loaded and processed, the LTSM and GRU models are executed and evaluated. This folder also stores the training, test, and actual RUL data as train_FD001.txt, test_FD001.txt, and RUL_FD001.txt respectively. When running main_rul.ipynb the user may have to uncomment the installation commands depending on whether they have their required packages on their machine. The current data file path is consistent with the working repository used too build this project. Please be advised to file path may need to be switch to run this program.

Report: -- report_rul.pdf consolidates the approach, methodology, results, and insights of this project.

Visualizations: -- All plots and visualizations of model evaluation are descriptively named and stored as png files in this folder.

Generative AI: -- All interactions with generative AI tools are recorded in the appendix file generative_ai.pdf

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