Development empirical-intelligent relationship between plasma spray parameters and coating performance of Yttria-Stabilized Zirconia

The present work deals with modeling coating characteristics of yttria-stabilized zirconia such as deposition efficiency, adhesion strength, surface roughness, and hardness in plasma spray process. Here, the process factors are input power, primary gas flow rate, stand-off distance, powder feed rate, and carrier gas flow rate. Firstly, a number of 32 experiments were conducted based on rotatable central composite design of experiments. Then, adaptive neuro-fuzzy inference system was used to correlate mapping relationships between plasma spray factors and mentioned coating properties. After examination of various network structures, results showed that the one with a number of two triangular membership function predicts the coating properties with the lowest root mean square error. Therefore, the developed model was used to determine the effect of plasma spray factors on mentioned characteristics according to graphs which were plotted through the proposed model.

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