Design of injection nozzle in direct metal deposition (DMD) manufacturing of thin-walled structures based on 3D models

Abstract

The direct metal deposition (DMD) process is one of the metal-based additive manufacturing techniques available today. In this study, an injection nozzle design methodology is proposed based on the finite element modeling of substrate temperature and powder distribution. The design methodology is applied to the deposition of Ti-6Al-4V powder in building thin-walled structures, which is also applicable to solid parts. The objective is to explore and find the designs of injection nozzle shape that maximize the powder usage and minimize laser energy needs, later defined as powder catchment and laser energy efficiencies. The laser heating of substrate model and the particle-laden gas flow model are utilized. First, a proper set of process parameters is chosen to model the melt pool shape on the substrate that can build a thin-walled structure of certain width. Then, the powder distribution is explored by testing various injection nozzle shape parameters based on the solutions of a particle-laden injection turbulent flow. A neural network is built in order to explore the variations of objective functions due to the design variables. The first output of the neural network predicts the particle concentration in flight. The second output evaluates the powder catchment efficiency. The process efficiency is defined as the product of the two outputs. After validating the neural network, multiple sets of injection nozzle geometric parameters are provided to map their process efficiencies. With the methodology proposed, the injection nozzle can be designed to maximize the process efficiency.