A repository containing some of the prototyping code notebooks I wrote during my time with the IITD-AIA Foundation for Smart Manufacturing.
My work is focussed on developing a machine learning model to predict equipment failures and enable proactive maintenance. By analyzing historical sensor data, maintenance records, and operational parameters of industrial equipment, our model aims to identify patterns and indicators that precede equipment failures. This project aims to enhance maintenance strategies, reduce downtime, and optimize the reliability and performance of critical machinery.
Some of the current preliminary prototyping is being done on the NASA Turbofan Jet Engine Data Set. The dataset can be accessed on https://www.kaggle.com/datasets/behrad3d/nasa-cmaps.