Investment casting process is a versatile and flexible manufacturing technique whose application is rapidly increasing, specifically for producing high quality, near net shape complex components. Shrinkage in wax pattern is one of the most significant problem in the investment casting process. The shrinkage depends upon various parameters such as wax material, mold temperature, injection temperature, injection time, cooling time etc. In this present work, the analyses have been performed as per Taguchi orthogonal arrays L9 in the MoldFlow simulation program to find volumetric shrinkage then a regression analysis was done to determine the mathematical relationship between the volumetric shrinkage and process parameter by utilizing the analysis data. Teaching learning based optimization (TLBO) technique was then applied for optimizing the process parameters. The results of confirmation analysis reveal that TLBO can effectively acquire an optimal combination of the process parameters. Hence, dimensional accuracy of wax pattern in the investment casting process can be significantly improved through this approach.
