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Modèles géométriques avec defauts pour la fabrication additive

Abstract : The intricate error sources within different stages of the Additive Manufacturing (AM) process have brought about major issues regarding the dimensional and geometrical accuracy of the manufactured product. Therefore, effective modeling of the geometric deviations is critical for AM. The Skin Model Shapes (SMS) paradigm offers a comprehensive framework aiming at addressing the deviation modeling problem at different stages of product lifecycle, and is thus a promising solution for deviation modeling in AM. In this thesis, considering the layer-wise characteristic of AM, a new SMS framework is proposed which characterizes the deviations in AM with in-plane and out-of-plane perspectives. The modeling of in-plane deviation aims at capturing the variability of the 2D shape of each layer. A shape transformation perspective is proposed which maps the variational effects of deviation sources into affine transformations of the nominal shape. With this assumption, a parametric deviation model is established based on the Polar Coordinate System which manages to capture deviation patterns regardless of the shape complexity. This model is further enhanced with a statistical learning capability to simultaneously learn from deviation data of multiple shapes and improve the performance on all shapes.Out-of-plane deviation is defined as the deformation of layer in the build direction. A layer-level investigation of out-of-plane deviation is conducted with a data-driven method. Based on the deviation data collected from a number of Finite Element simulations, two modal analysis methods, Discrete Cosine Transform (DCT) and Statistical Shape Analysis (SSA), are adopted to identify the most significant deviation modes in the layer-wise data. The effect of part and process parameters on the identified modes is further characterized with a Gaussian Process (GP) model. The discussed methods are finally used to obtain high-fidelity SMSs of AM products by deforming the nominal layer contours with predicted deviations and rebuilding the complete non-ideal surface model from the deformed contours. A toolbox is developed in the MATLAB environment to demonstrate the effectiveness of the proposed methods.
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Submitted on : Tuesday, December 3, 2019 - 1:01:48 AM
Last modification on : Monday, February 15, 2021 - 10:50:40 AM
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  • HAL Id : tel-02390292, version 1



Zuowei Zhu. Modèles géométriques avec defauts pour la fabrication additive. Génie mécanique [physics.class-ph]. Université Paris-Saclay, 2019. Français. ⟨NNT : 2019SACLN021⟩. ⟨tel-02390292⟩



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