Macroscale modeling plays an essential role in simulating additive manufacturing (AM) processes. However, models at such scales often pay computational time in output accuracy. Therefore, they cannot forecast local quality issues like lack of fusion or surface roughness. For these reasons, this kind of model is never used for process optimization, as it is supposed to work with optimized parameters. In this work, a more accurate but still simple three-dimensional (3D) model is developed to estimate potential faulty process conditions that may cause quality issues or even process failure during the electron beam melting (EBM) process. The model is multilayer, and modeling strategies are developed to have fast and accurate responses. A material state variable allows for the molten material to be represented. That information is used to analyze process quality issues in terms of a lack of fusion and lateral surface roughness. A quiet element approach is implemented to limit the number of elements during the calculation, as well as to simulate the material addition layer by layer. The new material is activated according to a predefined temperature that considers the heat-affected zone. Heat transfer analysis accuracy is comparatively demonstrated with a more accurate literature model. Then, a multilayer simulation validates the model capability in predicting the roughness of a manufactured Ti6Al4V sample. The model capability in predicting a lack of fusion is verified under a critical process condition.
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