Grey relational analysis optimization of input parameters for electrochemical discharge drilling of silicon carbide by gunmetal tool electrode

Abstract

The electrochemical discharge machining process (ECDM) is a hybrid advanced technology integrated with electrochemical and electro-discharge processes has used for the manufacturing of non-conducting along with conducting materials. The silicon carbide is non-conducting material which has widely used in various fields such as automobile, aviation, medical, nuclear reactor, and missile. The machining of silicon carbide is a challenging task by using non-conventional along with conventional machining processes due to its physical properties. The current research work shows the machining of Silicon carbide material by using fabricated ECDM machine setup with gunmetal tool material. The Taguchi L27 orthogonal array technique is applied for experimental work. The grey relational analysis optimization is applied for the investigation of optimum input factors for better output responses. The input process factors like electrolyte concentration, applied voltage, and rotation of tool and outcome results such as machined depth and the diameter of hole were checked after drilling of silicon carbide material. The experimental results indicate the electrolyte concentration is the leading factor for diameter of hole and depth of machined hole subsequent to voltage and tool rotation.