Abstract
Shot peening (SP) process is performed on AA2024-T3 alloy to improve its fatigue strength, flexural strength and surface hardness. Response surface method (RSM) is used for designing the experiments. Experiments are conducted and the regression equations are framed using the Design Expert software. RSM based second order regression equations are used as input to Particle swarm optimisation (PSO) algorithm. PSO algorithm is used to find the best combination of shot peening process parameters, namely, peening pressure and peening distance for maximizing the responses. Validation of the solutions obtained from PSO is done by performing shot peening process with nickel balls. The results of mechanical properties of AA2024-T3 are found close to the predicted values obtained from PSO algorithm.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
