Dynamic Simulation of Arc Additive Manufacturing Process for Defect Identification

Arc Additive Manufacturing (AAM) is a cuttingedge technology for producing complex metal components with high precision and efficiency. This study introduces a dynamic fluid simulation method to optimize AAM path planning and identify defects before actual production. Leveraging the open-source Blender software and the Affine Particle-In-Cell (APIC) algorithm, the simulation models the weld material’s behavior, including cooling and solidification, to enhance the accuracy of deposition outcomes. The method assesses the impact of process parameters and path design on weld morphology, ensuring that path defects are highlighted. By digitalizing path codes, the simulation synchronizes with CNC machine movements, providing a virtual representation of the entire deposition process. Comparing these simulations with experimental results validates the visual accuracy of the process, showcasing the potential of digital intelligence in advancing AAM technology.