Fault Detection of Smart Lathe Machine using Python

The system detects faults of a Smart Lathe machine from the data received from Industrial IoT devices to reduce decision and analysis latency. The model was saved using Joblib Python library for predicting the data given as input in the Frontend interface. Packaging was done and API endpoints were made using Flask library to trigger function calls. Streamlit library was used to design the front-end part of the application with which the user interacts to feed the data and get the required predictions.