Optimizing cold spray process parameters for AA2024/Al <sub>2</sub> O <sub>3</sub> coatings to minimize wear loss via response surface methodology and particle swarm optimization
Ashokkumar Mohankumar, D. Thirumalaikumarasamy, Vignesh Packkirisamy
Abstract
The primary obstacle in cold spraying (CS) is choosing the optimum set of spray parameters to implement in order to attain the desired coating properties. To find the optimum set of spray parameters for CSed AA2024/Al2O3 cermet coating on AZ31Mg alloy, the response surface methodology (RSM) and particle swarm optimization (PSO) techniques were utilized. In order to create an interaction among the process variables temperature (TEMP), nozzle spray distance (NSD), and powder delivery rate (PDR) and with the deposit properties (wear loss), So in this study, an experimental test was planned, conducted, executed, and empirical relationships were developed by creating a three-factor, five-level central composite rotatable design matrix (CCRDM) through RSM approaches to predict the wear loss of CSed cermet coatings. The established empirical relationship was optimized through PSO. The RSM was compared with the optimized value found by PSO. As a result, the optimized parameters of TEMP of 550 °C, the NSD of 15 mm, and a PDR of 25 gpm resulted in a minimum wear loss of 2.52 mg through the RSM. On the other hand, the optimized value obtained using particle swarm optimization for the response wear loss is 2.421 mg with a TEMP of 550.634 °C, an NSD of 15.534 mm, and a PDR of 25.645 gpm. When CS coating parameters are optimized using RSM and PSO, PSO produces more precise results than RSM. From the ANOVA findings, TEMP was determined to be the most influential parameter, followed by NSD and PDR.