Modeling and multi-response optimization of pressure die casting process using response surface methodology

Modeling of pressure die casting process is carried out in the present work. Design of experiment has been utilized to collect the experimental data. The input–output relations have been developed by using response surface methodology. Optimal process parameters have been determined by using desirability function. The process parameters, namely, fast shot velocity, injection pressure, phase changeover point, and holding time, have been considered as the input to the model. Porosity, surface roughness, and hardness are measured and represented as the responses. Based on the experiments carried out, two nonlinear models have been developed using central composite design and Box-Behnken design. These two models have been tested for their statistical adequacy and prediction accuracy through analysis of variance (ANOVA) and some practical test cases, respectively. The performance of central composite design is found to be better than Box-Behnken design (BBD) for the response surface roughness and hardness, whereas the latter is found better than the former for the response porosity. The performance is adjudged based on the average absolute percent deviation in predicting the responses. The absolute percent deviation values for the responses surface roughness, hardness, and porosity are found to be equal to 5.95, 1.29, and 63.94, respectively, in central composite design (CCD). On the other hand, corresponding values in BBD are found to be equal to 14.19, 3.04, and 4.94. Further, an attempt is made to minimize the porosity and surface roughness along with maximization of hardness of die cast component. The objective of multi-response optimization was met with a high desirability value of 0.9490.

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