Integration of Process Modeling and Design of Experiments for improving the pouring phase of the die casting process

The study presents a new approach in integrating the Process Modeling and Design of Experiments along with regression analysis to improve the quality of the pouring phase in the die-casting process. This study investigates the factors affecting the pouring process in pressure die-casting, constructs a computer model and uses design of experiments to develop an empirical model characterizing the pouring process. The study also goes on to optimize the pouring process model using response surface plots and specifies ranges of values for the factors for a robust model. The study is based on simulations performed in Flow3D code, which is widely used in simulating liquid metal flows. The factors affecting the pouring process were identified and an optimization design array was setup. Simulations were performed and the results were used to perform regression analysis to build the model. Response surface plots were plotted based on the model and were used to identify the most important factor affecting the process, which turned out to be the shot sleeve wall temperature. The ranges for the shot sleeve wall temperature were then fixed keeping in mind that the variations in the other factors do not affect the quality of the process for this range of shot sleeve wall temperature. This lead to a robust design for the pouring process.