Journal of Additive Manufacturing Technologies
Vol 1 No 3 (2021): J AM Tech
https://doi.org/10.18416/JAMTECH.2111592

Articles, ID 592

Comparison of finite element and empirical model prediction of surface residual stress in inconel 718 parts fabricated by laser powder bed fusion additive manufacturing

Main Article Content

Mert Kaya (Marmara University), Nedim Sunay , Yusuf Kaynak 

Abstract

Inconel 718 parts produced by Laser Powder Bed Fusion (LPBF) generally have excessive residual stresses (RS) due to the extreme temperature gradients and high cooling rates that occur during production. These stresses can damage the mechanical properties and fatigue life of parts. Therefore, RS are one of the main reasons that hinder the widespread use of the LPBF process. The main purpose of this study is to predict the RS that may occur by finite element modeling and empirical approach of the production process in order to minimize the RS and distortions that occur during production. According to the simulation and theoretical calculation results, it has been observed that the RS in the build direction are generally large tensile stresses in the upper and lower regions and compressive stresses in a large middle region in between. One of the most important parameters that determine the residual stress magnitude is the scanning speed, which affects the energy density. The change in energy density due to constant laser power and increasing laser speed alters the amount of residual stress in the parts.  This paper illustrates that when fabricating components with lower energy density leads to an increase of tensile residual stress, however, increasing energy density with altering process parameters results in reduced tensile residual stress.

Article Details

How to Cite

Kaya, M., Sunay, N., & Kaynak, Y. . (2021). Comparison of finite element and empirical model prediction of surface residual stress in inconel 718 parts fabricated by laser powder bed fusion additive manufacturing. Journal of Additive Manufacturing Technologies, 1(3), 592. https://doi.org/10.18416/JAMTECH.2111592