Assessment of Machining of Hastelloy Using WEDM by a Multi-Objective Approach

Superalloys are a much-needed material for abundant engineering fields, such as nuclear-powered reactor components and aeronautics. Owing to their exceptional characteristics, higher thermal conductivity, they can be difficult machine using conventional processes. Modern approaches machining have evolved utilize these materials. One of the techniques studied in this project is electrical discharge wire machine. This process help reduce energy consumption during negative impact on environment. In addition, shortening operation time minimize its The duration pulse applied current independent factors considered study. Material removal rate, surface roughness, dimensional deviation, form/orientation tolerance errors deemed performance measures. goal investigation required improve finish by implementing Grey-based artificial neural network model. method useful foretelling conditions Wire Electro Discharge Machining (WEDM) process. paper uses Taguchi design Analysis Variance (ANOVA) framework analyze model’s variable inputs. overall best coefficient correlation (R = 0.9981) fetched with an RMSE value 0.0086. rate has been increased decreasing taken removal, which gives possibility consuming minimum energy. finishing machined also improved. Moreover, shows how use Artificial Neural Network (ANN) model Grey Analysis. results comparative analysis show that values envisaged closer actual values. capacity confirmed developed