Prediction of defects in deep drawn rectangular parts using Finite Element Analysis (FEA) and Response Surface Methodology (RSM)

Abstract

Abstract Deep drawing defects such as thinning and earing present challenges to sheet metal forming industry while designers tend to favour the usage of new materials and production processes. The present work introduces an integrated approach using Design of Experiment, FEA experimentation and RSM to study the effect of deep drawing process parameters and resulting defects associated with sheet metal forming processes such as thinning and earing particularly in deep drawing of non-circular parts. The Design of Experiment (DoE) is used to generate a series of experiments for different process parameters in deep drawn rectangular products which are then simulated using Simulia 2022, a finite element package. The results are then fed to statistical analysis software, Design Expert 12.0, to develop regression equations that predict minimum sheet thickness and earing defects using RSM. FE models for deep drawing of different products have been built and results have been verified through comparisons with published data. Critical process parameters were selected for investigation in the present work. Based on the results of these experiments, a two-level design of experiment is conduct to generate 64 FE experiments. The relationships between these parameters and minimum sheet thickness after drawing and earing defects are then obtained using RSM. Optimum values of different parameters are obtained for maximum sheet thickness after drawing and minimum earing.