Modelling and Optimization of Electrostatic Discharge Machining Parameters Using Genetic Algorithm

Abstract

Electrostatic Discharge is a phenomenon that results from separating two dissimilar solid surfaces that were in contact. It results from the transfer of electrons from one surface to the other. Hence, one of the surfaces is positively charged, while the other surface becomes negatively charged. This phenomenon takes place during single point diamond turning of contact lenses polymers such as ONSI-56. Since higher electrostatic discharge adversely affects surface roughness, there is need to optimize electrostatic discharge machining parameters. The aim of this study is to develop an electrostatic discharge model and optimize the electrostatic discharge machining parameters during single point diamond turning of ONSI-56. Multiple regression has been utilized for model development and Genetic Algorithm (GA) has been used to optimize the model parameters. The GA toolbox in MATLAB is used for optimization in this study. In this study, cutting speed, depth of cut and feed rate are the model variables, while electrostatic discharge is the response variable. The regression model’s effectiveness has been evaluated by the R2 value method. The model has an R2 value of 88.29%, indicating that there is a strong collective significant effect among the control and response variables. Additionally, the results indicated that cutting speed and feed rate are the most significant predictors, while depth of cut is a slightly less significant predictor. The optimization process yields the following optimal values for cutting speed, feed rate, depth of cut and ESD, respectively: 200 rpm, 12 mm/min, 10 µm and 1,28 kV. An assessment of population size against objective function execution time has revealed that a population size of 500 has the shortest execution time of 14.23 seconds. The results have revealed that the optimization technique (GA) is efficient in ESD process optimization during single point diamond turning of ONSI-56.