Influence of Computational Grid and Deposit Volume on Residual Stress and Distortion Prediction Accuracy for Additive Manufacturing Modeling

Introduction

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Powder Bed Additive Manufacturing offers unique advantages in terms of cost, lot size and manufacturability of complex products. The energy used however leads to distortions during the process. The distortion of single layers can be comparable with the powder layer thickness. The contact between the coater blade and the deposited material could terminate the build process. Furthermore, accumulated residual stresses can lead to deviations of the final shape from the design. This work focusses on the accuracy of quick residual stress and distortion models that will both provide layer by layer distortion data as well as the final work piece residual stress and shape. The residual stress and distortion models are implemented in an ICME platform that takes powder size distribution as well as the heat source powder interaction into account. Lower scale models are briefly introduced and data required for the residual stress analysis are documented prior to the analysis of some large components assessing manufacturability and final work piece shape.

Link to the original article can be found here: https://link.springer.com/chapter/10.1007/978-3-319-57864-4_34

Authors

O. Desmaison, P.-A. Pires, G. Levesque, A. Peralta, S. Sundarraj, A. Makinde, V. Jagdale and M. Megahed,
Influence of Computational Grid and Deposit Volume on Residual Stress and Distortion Prediction Accuracy for Additive Manufacturing Modeling,
Proceedings of the 4th World Congress on Integrated Computational Materials Engineering (ICME 2017, May 21-25, 2017, Ypsilanti, Michigan, USA. DOI 10.1007/978-3-319-57864-4_34

Keywords

Metal additive manufacturing, Powder bed, Process modeling, Residual stress, Distortion

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