Vehicle Outer Body Panel Oil Canning Performance Prediction Using Machine Learning

Thin plates buckle after applying load and return to normal position after the load is released, this process is called oil canning. Waviness in thin panels can be seen on various plates of metals. Oil canning is a major issue if panels are too thin and these panels create vibration and noise in the vehicle body panel. If the panels are wider, then there are more chances of oil canning issues. Different digital simulations and physical techniques are currently available to check the canning performance, but they required geometrical data and physical setup. In this paper machine learning (ML) approach to predict the oil canning performance is presented. This approach adds a new process to the existing process of vehicle door design, but it helps avoid the number of simulations and unwanted structural modifications at the early design stage, making it a handy and powerful tool for the designer.