Abstract

Pressure die casting is successfully used in the manufacture of Aluminum alloys components for automobile and many other industries. Die casting is a process involving many process parameters having complex relationship with the quality of the cast product. Though various process parameters have influence on the quality of die cast component, major influence is seen by the die casting machine parameters and their proper settings. In the present work, non‐linear regression models have been developed for making predictions and analyzing the effect of die casting machine parameters on the performance characteristics of die casting process. Design of Experiments (DOE) with Response Surface Methodology (RSM) has been used to analyze the effect of effect of input parameters and their interaction on the response and further used to develop nonlinear input‐output relationships. Die casting machine parameters, namely, fast shot velocity, slow shot to fast shot change over point, intensification pressure and holding time have been considered as the input variables. The quality characteristics of the cast product were determined by porosity, hardness and surface rough roughness (output/responses). Design of experiments has been used to plan the experiments and analyze the impact of variables on the quality of casting. On the other‐hand Response Surface Methodology (Central Composite Design) is utilized to develop non‐linear input‐output relationships (regression models). The developed regression models have been tested for their statistical adequacy through ANOVA test. The practical usefulness of these models has been tested with some test cases. These models can be used to make the predictions about different quality characteristics, for the known set of die casting machine parameters, without conducting the experiments.

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