Optimization of Micro Electrochemical Machining of Inconel 625 using Taguchi based Grey Relational Analysis

Abstract

Material removal rate (MRR) is an important feature of microelectrochemical machining (ECM). The process is based on chemical reactions. The rate of machining depends upon atomic weight, the current density, electrolyte and the time of machining. To know the effects of MRR on Inconel 625, experiments have been conducted by considering different parameters using of stainless steel electrodes. In this present investigation, optimization is based on Taguchi approach with a grey relational analysis (GRA). The experimental runs have been planned using Taguchi’s principle with three input machining variables such as electrolyte concentration, voltage and feed rate. Besides the MRR, the surface roughness and overcut was included as performance measures in this investigation. ANOVA were involved to investigate the influence of process parameters on performance characteristics during machining. The outcome of this analysis shows that the voltage is the predominant factor for the desired performance characteristics and also optimum parameters are identified. The regression models are developed to be used as predictive tools. The confirmation test was conducted to validate the results achieved by GRA approach. This research work is help the industrialist for selecting parameters to attain desired outputs.