Intelligent Modeling and Optimization of ECM Process Parameters

Electrochemical machining (ECM) is an unconventional process used for the machining of hard materials and metal matrix composites. In the present work, the artificial neural network trained with back-propagation algorithm is used for correlating the interactive and high-order influences of various machining parameters on the predominant machining factors. The operators' requirements cannot be satisfied by the machining parameters provided by ECM machine tool builders. The process parameters are then optimized using weighted sum particle swarm optimization. The fitness function for optimization is obtained from the developed model.