Predictive maintenance (PdM) is a maintenance strategy that uses data analysis to predict when a machine or equipment is likely to fail. This allows for preventive maintenance to be performed before the failure occurs, avoiding costly downtime and repairs. By combining PdM with ML, it is possible to develop models that can accurately predict machine failures days, weeks, or even months in advance. This allows organizations to schedule preventive maintenance at the most opportune time, minimizing downtime and maximizing uptime.
git clone --depth 1 https://github.com/UdAyAn123/Predictive_Maintain
cd Machine-Predictive-Maintenance
python -m venv .venv
For windows
.venv/Scripts/activate
For linux
source .venv/bin/activate
pip install -r requirements.txt
Run train.py this will train the model and save the models into models folder
python myapp/modules/train.py
Run test.py to verify saved models work well
python myapp/modules/test.py
Run web app
python manage.py runserver 5000
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