Rapid Mold Manufacturing by 3D Printing Incorporating SLA Technology and Improved PSO Algorithm

The traditional mold manufacturing process is difficult to meet the requirements of modern production due to high cost and long cycle time. To improve the speed of mold manufacturing, the study proposes a rapid mold manufacturing method for 3D printing based on stereolithography appearance technology and an improved particle swarm algorithm. First, the study optimizes the efficiency and accuracy of light-curing 3D printing using an STL file reading algorithm. Then the particle swarm algorithm is applied to optimize each sub-path to ensure that the motion trajectory of the print head is more efficient, and finally, the research method is tested for performance. The test results indicated that the convergence curve of the study algorithm’s fitness decreased gradually as the iterations incremented. The suggested algorithm’s adaptation value, which was 2.045, was at its lowest when there were roughly 74 iterations in the study algorithm. In the small-scale Gr48TSP issue solving, the research algorithm’s running time was the shortest, at 7 s. In the large-scale PCB3038TSP problem solution, the study algorithm’s execution duration was approximately 420 s. The actual application test results revealed that the maximum warpage deformation of samples A, B, C, D, E, and F were 1.793, 1.797, 1.839, 1.815, 1.826, 1.814, and 1.816, respectively. The warp deformation values of the six sample molds were all within the qualified range, which meets the basic qualification standards. It can be seen that the research proposes a 3D printing rapid mold manufacturing method, which can effectively solve the bottleneck problem of traditional mold manufacturing in path planning, while also improving the efficiency and quality of mold manufacturing, and has important theoretical significance and practical application value. Additionally, it can increase mold manufacturing’s productivity and quality, which has significant theoretical and practical application value.