## 1 Introduction
The kerf width showed an exponential increase with increase in pulse-on time. The pulse-off time showed a directly opposite phenomenon when compared to pulse-on time. The increase in gap voltage showed a decrease in the kerf width as well as the surface roughness. Using multiresponse optimisation, the optimum values were identified--while keeping the input parameters--as 6.11 us as pulse-on time, 6.52 us as pulse-off time and 67.8 V as gap voltage. [PERSON] et al. [26] worked on the optimisation of the EDM of the Al6061 composite with 8% SiC. The work applied response surface methodology (RSM) for the mathematical model, and the Box-Behnken Design (BBD) approach was employed for the experimental design. The input parameters employed were current, pulse-on time and duty cycle. The work evaluated the material removal rate (MRR), electrode wear rate (EWR) and surface roughness of the machined specimen. The variation in MRR was dominated by the current. The variation in EWR was dominated by pulse-on time and the surface roughness was dominated by current as well as pulse-on time. The optimum parameters for MRR were identified to be 8 A peak current, 183.84 msec \(\rm T_{on}\) and 8.67 duty cycle using the theory of desirability. [PERSON] et al. [27] carried out a comprehensive review on the recent trends in the machining of aluminum-based metal matrix composites in the recent scenario. The review covered the importance of EDM in the machining of difficult-to-machine composites of aluminum and identified the need for the prediction of the output parameters of an EDM process based on material properties and the input parameters. [PERSON] et al. [28] worked on the optimisation of major and minor process parameters in obtaining the MRR, EWR and \(\rm R_{a}\) for Al6061-6% \(\rm B_{t}C\) metal matrix composites (MMC). Extensive work was carried out with the input parameters as current, spark-on time, spark-off time, pulse-on time, gap voltage, duty factor and flushing pressure. The work used RSM to optimise the parameters. The MRR showed the output value at the error level of 0.167%, the surface roughness showed an error rate of 2.31% and the electrode wear rate showed an error in the range of 9.31% with the experimental value. [PERSON] et al. [29] worked on the machining of Al6061-7.5% SiC composite in high-speed wire EDM. The work aimed at optimizing the kerf width, surface roughness and cutting rate based on the input parameters of current, voltage and pulse-on time. The voltage was identified to be the dominating factor for surface roughness. Current was identified to be the dominating factor for kerf width and the pulse-on time was the dominating factor in cutting rate. A better surface finish was achieved with lower current and voltage. The Scanning Electron Microscope (SEM) images revealed that narrow craters are produced when the machining is carried out at lower voltage and current. RSM was used to predict the error levels in the corner accuracy as well as the cutting orientations. The model was able to predict the values within 5% error. [PERSON] and [PERSON] [30]worked on EDM machining of Al6061 composite reinforced with SiC and graphite. The work was carried out with the input parameters, current, pulse-on time, pulse-off time and gap voltage and the output parameter was set as MRR. The work identified that voltage has very low significance in the MRR of the material. It was also identified that the current and pulse-on time are the major contributors to the MRR. Increased pulse-off time reduced the MRR. [PERSON] et al. [31] carried out an optimisation study of the Al/SiC composites using the nondominated sorting genetic algorithm, which is a multiresponse algorithm for identifying the optimum MRR and Ra of the composite. Since both output parameters are contrasting, the work chose a multiresponse algorithm to optimise both the parameters.