Grey fuzzy optimization of ultrasonic-assisted EDM process parameters for deburring CFRP composites

The reduction of burr formation during machining of carbon fiber reinforced plastic composite is of great concern in many applications. This novel work presents the deburring of CFRP using ultrasonic-assisted electrical discharge machining. An L18 array varying the input parameters, such as capacitance, pulse-on time, and ultrasonic voltage, was selected to assess the output performances like tool wear rate and burr removal rate. Multi-objective optimization was performed by the grey fuzzy logic method and the optimum input parameter was predicted based on the results of grey fuzzy reasoning grade. The significance of the process parameters on TWR and BRR were also analyzed using analysis of variance. The experimental results show that a capacitance of 10,000 pF, TON of 200 µs, and VUS of 150 V were the optimal input parameters to simultaneously minimize TWR and maximize BRR. The burr free exit side walls were observed by scanning electron microscopic image during machining at the optimum condition. However, the vaporization of the resin near the hole surface is unavoidable which is due to the electro-thermal effect of EDM process. The capacitance (63.58%), TON (29.17%), and VUS (2.76%) were found to be the factors most affecting the combined output responses. Finally, the verification of the results shows an overall improvement of 7.14% on TWR, 19.88% on BRR, and 1.3% on GFRG.