Optimization of process parameters for multi-feature structural size fusing deposition based on random walk sparrow search algorithm
In the fused deposition molding process,the printing parameters have an important impact on the accuracy of the molded specimens.In order to improve the overall dimensional accuracy,the random walk sparrow algorithm is employed to obtain the optimal experimental scheme.Firstly,the orthogonal test of four factors and four levels is designed with the delamination thickness,heating temperature,print-ing speed,and filling rate of melt deposition molding as the experimental variables.Subsequently,the Taguchi-grey correlation method is used to process experimental data,with the relative error of the differ-ent characteristic structure sizes of the sample as the optimization object.Finally,the passed Random walk sparrow algorithm is utilized to calculate the optimal parameter scheme.The results indicate that the sam-ple formed by the optimized process parameters has a 20％increase in the comprehensive dimensional accu-racy compared with those obtained using Taguchi-gray correlation method,with a 27％increase in the gray correlation value.
fused deposition modelingTaguchi methodgrey correlation methodrandom walk sparrow search algorithm
万方数据
维普
