Remaining useful life (RUL) prediction of cutting tools is critical to effective condition based maintenance for reducing downtime, ensuring quality and avoiding accidents.
we worked on a research paper to build a Machine Learning model for predicting the remaining useful life of cutting tools.
Extracted different features from the dataset and developed an algorithm by using Support Vector Regression for the prediction of RUL.
The datset we were provided was from IEEE PHM 2012 Prognostic challenge
https://iopscience.iop.org/article/10.1088/1757-899X/576/1/012021/pdf