Experimental investigations, empirical modeling and multi objective optimization of performance characteristics for ECDD with pressurized feeding method - Singh, Tarlochan; Rathore, Ranjeet Singh; Dvivedi, Akshay (Measurement : journal of the International Measurement Confederation, 2020)
[Display omitted] •Empirical models were developed to establish the relation between input process parameters and performance characteristics.•The outcomes manifested by the predictive models are in good agreement with experimental results as it exhibits an average error less than 5%.•The underlying process mechanism for ECDD with the pressurized feeding system has also been explored.•Effect of process parameters on response characteristics has also discussed.•Genetic algorithm (GA) was used to perform the multi objective optimization. Electrochemical discharge drilling (ECDD) is a hybrid micromachining process that can be used to drill micro holes on all kind of materials, irrespective of their mechanical and electrical properties. In ECDD, the continual penetration of tool electrode having electrochemical discharge (ECD) energy along the work material generates the holes. The relative movements between tool electrode and work material controls the energy penetration rate, and subsequently effects the performance characteristics. Therefore, the effect of process parameters associated with feeding motion and ECD energy are important to investigate simultaneously with respect to the performance characteristics. In the current study, a Buckingham’s dimensional method was used to determine the relation between input process parameters (that includes simultaneous interaction of ECD energy based parameters and feeding motion based parameters) and performance characteristics. The material removal rate (MRR) and hole overcut (HOC) were considered as the performance characteristics. MRR and HOC symbolize the productivity and accuracy of the process, respectively. During predictive modeling, the constant terms and coefficients were estimated from the non-linear experimental data. The outcomes manifested by the predictive models are in good agreement with the experimental results. The underlying process mechanism for ECDD with the pressurized feeding system has been explored by considering the simulation results as an evidences. Microscopic images of machined holes and discharge characteristics were used to develop the fundamental background of ECDD process mechanism with pressurized feeding method. Additionally, genetic algorithm (GA) was used to perform the multi objective optimization of ECDD process.