In this notebook, the predictive maintenance problem is applied to air compressors.

• functions: created python files
• img: pictures
• models: machine learning models created for solving the problem
• notebooks: Jupyter Notebooks files
• streamlit: file to execute the streamlit app

By analysing the working variables of air compressor, and tracking vibrations, pressure, temperature and currents, is possible to predict whether a compressor will fail in the following X days ("Diagnostics") and determine the Remaining Useful Life ("Prognostics")