Abstract
Current paper comprises the inter-relationship between second-order regression modeling and genetic algorithm (GA)-based optimization of air plasma deposited with improved thermal barrier coating (TBC) systems structures. For developing the regression model, experiments were performed as per [Formula: see text] orthogonal array, and models were established by MINITAB software. The regression models have been found satisfactory for predicting the responses at 99% confidence level. GA optimization showed a 14.86% improvement in hardness and a 15.99% reduction in roughness. The optimal level of air plasma spraying (APS) parameters was obtained as 8 number of spraying layers, 70[Formula: see text]V of accelerating voltage, 600[Formula: see text]A of Arc current, 30[Formula: see text]mm/s of travel speed, 100[Formula: see text]mm of spray distance, 25[Formula: see text]g/min of powder feed rate, 4[Formula: see text]J/min of carrier gas flow rate, and 55[Formula: see text]L/min of primary gas flow rate for maximum hardness and minimum roughness.
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