Abstract
The key requirement of forging industry is to obtain a defect-free part with minimal trials on the shop floor. But the hit and trial method used by the industries does not give optimum results. The use of FEA for the optimization of parts is a better option. The definition of input parameters basically defines the metal flow within the die cavity during the forging process. In this paper, the process parameters have been optimized for better metal flow in two different parts. The simulated study was done using the input parameters of billet size, temperature, and coefficient of friction. The Response Surface Method (RSM) was used for the design of experiment, the results of which revealed the significant responses affecting the forging process. The optimization of the process was done for minimum effective strain rate, minimum die wear, and maximum material flow rate. The predictive models of the responses were obtained. Then, the comparison of the parts was done in terms of the responses. It was observed that the biggest part had the largest inhomogeneity, while the smaller part with higher shape complexity factor had larger homogeneity during deformation. It was easy to deform the bigger, yet simpler part. The material flow rate gave the opposite results. The bigger and simpler shape had minimum variation in the material flow rate, while the complex shapes had larger variation. The smallest part with complex contour had the highest associated die wear. The results could be used as an empirical form to frame the forging of new parts with minimum trials. The novelty of the research lies in the quantitative analysis of the responses in relation to metal flow, which has not been reported in the literature.
Published Version
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