Minimization of Casting Defects Using Taguchi Method

Introduction

Foundry suffers from weak quality and productivity due to a huge number of process parameters, lower automation and shortage of skilled workers. Defect-free products are demanded in the market but foundry often finds it difficult to meet the requirements. Foundry defects are analyzed by non-destructive methods and remedies must be carefully applied; otherwise, often new defects occur. This is not an easy task. For example, when a gas porosity defect occurs at high pouring temperature and the pouring temperature is decreased, it may lead to cold shut defects. Thus, casting despite its traditional usage is a very complex process from optimal parameter selection viewpoint. The success of a casting process depends greatly on the properties of the molding sand. These include strength, permeability, deformation, flowability, and refractoriness. The investigation of casting defect is the common interest of researchers, since failure in critical machines like aluminium alloy aircraft frames initiated from casting defects such as porosity (Li, Shen, & Hu, 2011). Bacaicoa et al (Bacaicoa, et al., 2017) characterized the casting defect of iron-rich aluminium-silicon-copper alloys using high-resolution scanning microscope and finite element analysis, in FEA the stress concentration was targeted and reported that the stress concentration observed to be larger on edges and inclusion of beta-Al-Si-Cu phases causes porosity. The casting products are sometimes subjected to fatigue loading for which the analysis was done by Wang et al (Wang, Apelian, & Lados, 2001) for A356-T6 casting alloy to study of the effect of casting defects on the fatigue behaviour, it was seen that the fatigue crack initiated from the casting defect i.e. porosity & oxide layers, out of which porosity is most harmful. Kunz et al (Kunz, Lukáš, Konečná, & Fintová, 2012) investigated high-temperature fatigue life of nickel super-alloy castings for the effect of casting defects and concluded that the casting defects becomes overwhelming at high-temperature applications, they should be reduced. Hamilton et al. (Hamilton, See, Butler, & Lee, 2003) used the macro scale and microscale modelling of defects in casting to predict them in aluminium alloy castings and the results were compared with experimental values and reported that the present tool can be used to reduce the casting defects. Whereas Kim et al. (Kim, Lee, & Nahm, 2006)analyzed the casting defects statistically in case of stainless-steel cast for correlating the casting defects to the fatigue life of the part. On the other hand, Borowiecki et al. (Borowiecki, Borowiecka, & Szkodzińska, 2011) used Pareto method to predict the casting defects like porosity, sand holes, slag inclusions, etc. Roy (Roy, 2013) analyzed the casting defects and presented a new approach i.e. simulation (CAE) for a possible solution in its reduction. The materials property variation also influences the casting defects, like increase in ductility of cast iron increases elongation at fracture, hence reduces casting defects (Nilsson & Vokál, 2009) and increase in tensile strength of the cast material reduces area fraction of defect in aluminium alloy castings (Caceres & Selling, 1996).