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In-Situ Distortion Prediction in Metal Additive Manufacturing Considering Boundary Conditions

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Abstract

Undesired distortion often occurs in metal additive manufacturing due to the high temperature gradient resulting from repeated thermal cycles. A good understanding and fast predictions of in-situ distortion are essential to achieve high dimensional accuracy and prevent delamination or failure of build parts. Experimental investigations and numerical methods have been employed to study the in-situ distortion. However, the complex measurement systems and high computational cost limit their applications. An analytical modeling method with closed-form solutions is proposed in this paper to predict the in-situ distortion of laser cladding process without using iteration-based numerical calculations. The effects of build edges and geometry are considered, which include thermal convection and radiation at boundaries. Heat input and heat sink solutions modified from the point moving heat source model are added together to predict the temperature profile of the build and substrate. The die-substrate assembly model is used to calculate the deflection during the manufacturing process. Alloy 625 is selected to test the predictive accuracy and computational efficiency of the presented analytical model. The predicted results are close to the experimental data of in-situ distortion in literature. The computational time is less than 30 s. The good predictive accuracy and low computational cost make the presented method a promising approach to study the full-field temperature and distortion of a geometrically complex part.

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Acknowledgements

The authors would like to acknowledge the financial support from The Boeing Company.

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  1. George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 801 Ferst Drive, Atlanta, GA, 30332-0405, USA

    Wenjia Wang, Jinqiang Ning & Steven Y. Liang

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  1. Wenjia Wang
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Correspondence to Wenjia Wang or Steven Y. Liang.

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Wang, W., Ning, J. & Liang, S.Y. In-Situ Distortion Prediction in Metal Additive Manufacturing Considering Boundary Conditions. Int. J. Precis. Eng. Manuf. 22, 909–917 (2021). https://doi.org/10.1007/s12541-021-00496-z

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