The Direct Metal Deposition (DMD) process is one of the most important metal based additive manufacturing techniques available today. In this study, a print head design optimization methodology is proposed based on the finite element modeling of powder distribution and substrate temperature distribution. The design methodology is applied to the deposition of Ti-6Al-4V powder in building thin-walled (≈ 0.7 mm) structures, which is also applicable to solid parts. The design objective is to find the optimal design of the injection nozzle shape that can maximize the powder usage and minimize laser energy needs, later defined as powder and laser energy efficiencies. A neural network is built to investigate the nozzle shape parameters based on the results from the 3D powder flow model. With the methodology proposed in this study, the optimal injection nozzle design can be found.

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