Review of Computational Approaches used for Investment Casting Process

Abstract

Investment Casting (IC) is a manufacturing process used to manufacture products with superior surface finish, intricate shapes with tight tolerance for dimension of final product. In IC, wax pattern is dipped into ceramic slurry number of times to develop ceramic shell mold in which molten metal is poured. This paper deals with review of computational approaches carried out for IC. Computational approaches have a vital role in modernizing casting industry by eliminating the traditional methods. Computational approaches such as statistical methods, numerical simulations, and machine learning (ML) are explored in-depth, with case studies focusing on IC applications.

 IC has been divided in 3 major stages: 1) Pre-filling stage; includes sub-processes like a) wax pattern making focusing on calculation of shrinkage factor. b) Ceramic coating followed by dewaxing to create ceramic shell mold. 2) Filling is the nest stage of IC where liquid metal is filled into ceramic shell mold; further divided into a) effects of casting process parameters like fluidity, filling manner top or bottom, pouring temperature etc. b) Design of gating system which plays the major role for obtaining defect free casting using. 3) Post filling stage includes knock out & inspection of defect free casting and desired mechanical properties.