Multi-objective optimization of electrochemical machining process parameters using a particle swarm optimization algorithm

The selection of optimum values of important process parameters of electrochemical machining processes such as the tool feed rate, electrolyte flow velocity, and applied voltage play a significant role in optimizing the measures of process performance. These performance measures generally include dimensional accuracy, tool life, material removal rate, and machining cost. In this paper, a particle swarm optimization algorithm is presented to find the optimal combination of process parameters for an electrochemical machining process. The objectives considered are dimensional accuracy, tool life, and the material removal rate Subjected to the constraints of temperature, choking, and passivity. Both single- and multi-objective optimization aspects are considered. The results of the proposed algorithm are compared with the previously published results obtained by using other optimization techniques.