Optimization of technological parameters for cold spraying using the response surface method

Abstract

Cold spray technology can obtain coatings in a solid state, which is suitable for deposition protective and restorative coatings. Currently, most of the research in cold spraying is based on a single-factor analysis to explore the law. However, the interaction effect of multiple factors is more scientific. In this study, the response surface method (RSM) was used to optimize the technological parameters of cold spraying. A multi-factor and multi-level quadratic regression model was established for gas temperature, pressure, and particle diameter of outlet velocity, and the process parameters were optimized. The results showed that the gas temperature, particle diameter, and gas pressure have significant effects under a single factor. Also, under the interaction of multiple factors, the P-value of the quadratic regression model was less than 1·10–4 , and the R2 of the model was 0.9626, indicating that the curve fitting is good and the model has good credibility. The interaction between gas pressure and gas temperature is significant, while the interaction between gas temperature and powder diameter, gas pressure, and powder diameter are insignificant. Moreover, the parameter error between the optimized parameters through response surface analysis and the actual numerical simulation is 0.76 %, indicating high accuracy.