Multiobjective optimization of electric discharge machining of an Al–SiCp composite using the Taguchi–PCA method as well as the firefly and cuckoo search algorithms

Electric discharge machining (EDM) processes are extensively used in industries to machine materials and geometries that complex not machinable by conventional methods. In our study, we focused on identifying the optimal process parameters for EDM during of an aluminum alloy 6061 (matrix) –10% silicon carbide (particle) composite. The novel aspect this work is use a copper electrode with different (circular, triangular, square) machining, together input variables such as current density (A) well pulse on- off-timing (T T off ). We L 27 (3 13 ) Taguchi orthogonal array experimental layout responses measured were recast layer thickness (RCT), tool wear rate (TWR), material removal (MRR). Taguchi’s approach signal-to-noise (S:N) ratio was integrated principal component analysis (PCA) multicriterion optimization. Also, nature inspired cuckoo search (CS) firefly (FA) algorithms identify conditions predict outputs maximum MRR minimum TWR RCT. From S:N + PC analyses, identified were: circle (12 A, 65 μs, 2 μs); triangle 95 6 square 8 μs). Under all conditions, influence most significant. Metallurgical examination conducted through micrographs machined surface clearly supported predicted results. optimized appropriate automobile aerospace obtain holes specific good integrity reduced tools.