Sensoy, Abdullah TahirColak, MuratKaymaz, IrfanDispinar, Derya2024-10-042024-10-0420202193-567X2191-4281https://doi.org/10.1007/s13369-020-04922-8http://hdl.handle.net/20.500.12403/3409This study aimed to determine the optimal casting parameters for the maximum fluidity of A356 alloy. Gravity die cast method was used. For this purpose, central composite design (CCD) was performed. The input parameters and their limits for the trial design were selected as pre-heating temperature (100-400 degrees C), casting temperature (680-760 degrees C), and cross-sectional thickness (1-10 mm). Using the CCD-based simulation results of the feed distance, a highly correlated full-quadratic regression equation was obtained with the highestR(2)(0.99), which then was used as the objective function for the particle swarm optimization (PSO) process. The highest value of the response parameter, flow distance, reached up to 491.19 mm when the input parameters were selected as 400 degrees C, 760 degrees C and 10 mm, respectively. The sensitivity analysis has shown that the most effective parameter on the fluidity is the cross-sectional thickness. The response surface method (RSM)-based optimization results have been also validated using the PSO method. Although the higher temperatures have been found to result in better fluidity, there may be some drawbacks to working at higher temperatures such as energy cost and mould life. To determine the optimum input parameters, the RSM model suggested in this study can be modified for any type of casting process. Moreover, especially for a complex-shaped part, the manufacturer can be advised regarding operating conditions such as pre-heating and casting temperatures.eninfo:eu-repo/semantics/closedAccessCentral composite design (CCD)Response surface method (RSM)Particle swarm optimizationFluidityCasting parametersInvestigating the Optimum Model Parameters for Casting Process of A356 Alloy: A Cross-validation Using Response Surface Method and Particle Swarm OptimizationArticle45119759976810.1007/s13369-020-04922-82-s2.0-85090774566Q1WOS:000568828200001Q3