Measurement and optimization of atmospheric plasma sprayed CoMoCrSi coatings parameters on Ti-6Al-4V substrates affecting microstructural and properties using hybrid abductor induction mechanism

A hybrid artificial intelligence method (AIM) is used to optimize the atmospheric plasma spraying (APS) processing parameters for CoMoCrSi coatings deposited on Ti-6Al-4V substrates. In the proposed approach, the Taguchi design method is used to obtain an initial solution for the optimal set of APS parameters. The true optimal values of the spray distance, chamber pressure, current, argon gas flow rate and hydrogen gas flow rate are then obtained using an artificial neural network (ANN) and genetic algorithm (GA). The coatings deposited using the processing parameters determined using the Taguchi design method alone have a porosity of 8.5%. However, following the ANN/GA optimization procedure, the porosity reduces to just 5.6%. The XRD analysis results show that the as-sprayed coatings contain Cr₃Si phase as a result of the high-temperature plasma flame. In addition, it is shown that the structure of the Ti phase in the coating transforms from a α-Ti crystal structure (i.e., HCP) to a β-Ti crystal structure (i.e., BCC) during thermal treatment at temperatures to 1200 °C. Finally, it is shown that the hardness of the annealed coatings increases with both an increasing annealing time and an increasing annealing temperature. The higher hardness under higher temperature conditions is attributed to the precipitation of Cr₃Si phase. Overall, the coatings obtained in the present study using the optimal spray-coating parameters have a low porosity, a high hardness and a good thermal stability at high temperatures.