Prediction Model

Objective: In major Automobile Firm, welding is performed by Robotic system and hence we need to define the tip dressing time. This model helps the client to predict the right time for tip dressing. Analytical Approach: We fetch the data from data provider for all timer name and perform data pre-processing & EDA. After that perform feature engg to find the relevant data for model. Here I implement cluster analysis, linear regression and Random Forest Business Benefit: Since the whole system is automated so previously the tip dressing time was after every 15 cars but after using this model we can set the dressing time based on some important variable