Multi Response Optimization of Process Parameters In Wedm Machining Of D2 Steel Using Grey Fuzzy Technique

Abstract

With the increasing demand of good quality products and services, a large number of newlinenew materials have been developed from the last two decades. The industries need those newlinematerials which not only have good strength but also should operate in adverse conditions. newlineTitanium and its alloys, nickel and its alloys, carbides, ceramics, glasses and steels and its newlinealloys etc. find wide applications in automobile, aerospace, machine tool and medical newlineindustries. The conventional machining sometimes finds it difficult to machine these newlinematerials to required surface finish and accuracy. So to overcome these problems, non newlineconventional machining techniques have been developed where the tool and the work piece newlinedoes not come in contact like in conventional machining but use different forms of energy to newlineremove the material. The Wire Electrical Discharge Machining (WEDM) is one of the non newlineconventional machining processes employed for the machining of complicated contours in newlinethe work piece. newlineIn the present work, the machining of D2 Steel is carried out using different wire newlineelectrodes, i.e., brass wire, zinc coated copper wire and annealed copper wire. The input newlineparameters taken are Pulse ON time, Pulse OFF time, Spark Voltage, Peak Current, Wire newlineFeed and Wire Tension. The output parameters considered are Material Removal Rate newline(MRR), Tool Wear Rate (TWR), Surface Roughness (SR) and Kerf Width. A set of 27 newlineexperiments are conducted using each wire according to Taguchi s concept. The experimental newlinevalues are modelled using Fuzzy Logic Approach (Mamdani Approach). The input newlineparameters and the output parameters are expressed using linear membership function and the newlinerelationships are established using if then statements called as Fuzzy Rules. It is found that newlinethe Fuzzy modelled values are in agreement to the experimental values with more than 90 per newlinecent accuracy. newlineA hybrid Grey Fuzzy Logic technique is used for the multi response optimization of newlinethe machining parameters. In this technique, the Grey Fuzzy Relational Grade (GFRG) valu