Optimization of multiple responses in the lost wax process using Taguchi method and grey relational analysis

Abstract

Investment casting process is one of the most versatile and flexible process which produces near net-shape metal components. The disposable pattern employed in the process is generally made up of wax blend, whose accuracy has a direct effect on the accuracy achievable in the final cast part. This article addresses an approach based on Taguchi method in integration with grey relational analysis for multi-response optimization of wax patterns made by the investment casting process. The experiments are planned using Taguchi’s L₁₈ orthogonal array. The responses considered in this study are linear shrinkage, surface roughness and penetration, respectively. A grey relational grade obtained from grey relational analysis is used to determine the optimal process parameters. The significance of the process parameters on overall quality characteristics of the wax patterns has been evaluated quantitatively by the analysis of variance method. Optimal results have been verified through confirmation experiments, which indicate that the multi-performance characteristics of the wax patterns can be improved effectively through this approach. It was also found that though high injection temperature increases the surface finish of the wax blends, it adversely affects the mechanical properties of the wax blends.