Prediction of Process Parameters for Powder Bed Fusion Using Electron Beam

Abstract: The Powder Bed Fusion using Electron Beam (PBF-EB) process is a highly complex additive manufacturing process. There are a very limited number of materials that have been used successfully, which limits the applications of the process, despite its well-documented advantages over conventional manufacturing. However, the development of new materials is hindered due to a lack of understanding of the fundamental phenomena in the process. The goal of this work has been to develop a model that is able to predict the process parameters that will lead to the manufacture of a fully dense component.   The model is based on 1285 empirical datasets of process parameters and the physical properties of the printed materials. Nine different materials were included in the data. By inputting a pre-defined set of process parameters and materials properties the model will output the beam power at which it is predicted a dense component may be manufactured. This novel approach will shorten the development of new process parameters by providing a first approximation of suitable parameters to iterate from. A tool steel powder supplied by Uddeholms AB was printed, using parameters proposed by the model. Two sets of pre-defined process parameters were used with several beam velocities and resulted in a number of correct predictions.   This model is a first step in predicting process parameters and presents a simple, transparent and new method of obtaining the process window for novel materials in Powder Bed Fusion using Electron Beam.