Multi-objective optimization of dimensional accuracy, surface roughness and hardness of hybrid investment cast components

Abstract

PurposeThe purpose of this paper is to optimize the process parameters to obtain the best dimensional accuracy, surface finish and hardness of the castings produced by using fused deposition modeling (FDM)-based patterns in investment casting (IC).Design/methodology/approachIn this paper, hip implants have been prepared by using plastic patterns in IC process. Taguchi design of experiments has been used to study the effect of six different input process parameters on the dimensional deviation, surface roughness and hardness of the implants. Analysis of variance has been used to find the effect of each input factor on the output. Multi-objective optimization has been done to find the combined best values of output.FindingsThe results proved that the FDM patterns can be used successfully in IC. A wax coating on the FDM patterns improves the surface finish and dimensional accuracy. The improved dimensional accuracy, surface finish and hardness have been achieved simultaneously through multi-objective optimization.Research limitations/implicationsA thin layer of wax is used on the plastic patterns. The effect of thickness of the layer has not been considered. Further research is needed to study the effect of the thickness of the wax layer.Practical implicationsThe results obtained by the study would be helpful in making decisions regarding machining and/or coating on the parts produced by this process.Originality/valueIn this paper, multi-objective optimization of dimensional accuracy, surface roughness and hardness of hybrid investment cast components has been performed.