Study of Effects of Process Parameters and Implementation of DOE in Deep Drawing Process using CAE Simulations

Abstract

FEA has been proven as a vital and effective tool in sheet metal forming industries. Accurate prediction of forming results, determination of the thickness distribution and identifying the material of the blank would decrease the time spent in manual labor and iterations, but improve the productivity and efficiency of the overall process. In this project, a methodology has been tried to be created, for successful implementation and analysis of a deep drawing project, using CAE simulations. In the first phase, the important process parameters involved in the process have been identified and its effect has been studied plotted. A finite element model is developed for the 2-D (Shell) numerical simulation of the process by using Altair HYPERFORM as a pre-processor and RADIOSS as the solver. Geometric parameters such as the die and punch profiles have not been taken into consideration. In the second phase, the concept of DOE has been implemented to optimize the process parameters. Taguchi and Full factorial methods are used and compared. the developed model can then predict the thickness distribution and the thinning of the blank with the process parameters. Important parameters and their interactions affecting the process have been determined. Furthermore, with the numerical simulation, the working parameters can be optimized without expensive shop trials and experimentations. MINITAB is used for the analytical analysis and solution.