EXPERIMENTAL INVESTIGATIONS 0N ELECTRIC DISCHARGE MACHINE USING DIFFERENT MATERIALS BY GREY THAGUCHI METHOD AND OPTIMISING BY MINITAB TOOL

Abstract

Going with the improvement of mechanical industry, the requests for combination materials having high hardness, sturdiness and effect opposition are increasing all things considered , such materials are hard to be machined by customary machining strategies. Consequently , non-conventional machining techniques including electrochemical machining ,ultrasonic machining ,electrical release machining (EDM) and so forth are connected to machine such hard to machine materials. Electric discharge machining is non traditional machining process utilized for machining hard and hard to machine materials.In this process a pulse discharge occurs in a small gap between the Working parts and electrodes and removing unnecessary material from the metal by melting and evaporating. In EDM, electronics and decorations are not connected to the process of removing electrical equipment and mechanism. which is converted into thermal energy through a series of subdued electrical discharge energy prevail between the cathode(work piece)and the anode (electrode) sinking in an insulating dielectric fluid. It is commonly used in mould, die making industry and in manufacturing of automotive, aerospace surgical components. The objective of the present work is to optimize the machining parameters for die sinking operation of EDM so as to achieve high material removal rate (MRR) and best surface roughness (SR). Three materials high carbon steel, mild steel and alluminium-6061 as work pieces and copper electrode of 10mm square shaped tool were used to carry out experiments by varying the input process parameters like discharge current (Ip) pulse on time (TON) and duty cycle. The output process parameters like MRR and SR will be determined for every experimental runs. By implementing the Taguchi L9 orthogonal array (OA) using commercial tool Minitab17 response to the variation of input parameters as an output was investigated with minimum no of experimental runs. Taguchi single objective optimization method was used to study the effect of individual input and output parameters for optimization both input and output parameters. The results this obtained from the above are given as inputs to Grey
Taguchi multi objective optimization technique so to determine the optimized cumulative parameters.