Application of desirability-based hybrid ANFIS model for optimization of electro discharge machining of hastealloy C-276

Abstract

Hastealloy C-276 is a difficult to machine superalloy and comprehensively employed in various engineering fields such as nuclear applications, aerospace and gas turbines. Hastealloy C-276 having better strength and poor thermal conductivity makes them difficult to machine materials which results in reduced life of the cutting tool and poor machinability by conventional methods of material removal. Advanced metal removal methods have evolved to accomplish those kind of needs and appealed to be an opposite alternative approach to traditional machining. Electro Discharge Machining (EDM) is considered as one of the nontraditional metal removal process which is especially adopted for machining of hard to machine materials. In this present investigation Spark Erosion Machining has been employed for machining of Haste Alloy C-276 with copper electrode by using Taguchi’s experimental design approach. Applied current (A), pulse on time (TON) and pulse off time (TOFF) were considered as the input process variables and the performance of spark erosion machining has been assessed by considering the performance measures such as material removal rate, surface roughness, overcut, form and orientation tolerance errors. The significance of process variables were analyzed by Analysis of Variance (ANOVA). Multi objective optimization has been performed by desirability function analysis to obtain better machining performance. In addition DFA based Adaptive Neuro Fuzzy Inference System (ANFIS) have been evolved to optimize the desired performance characteristics.