A hybrid framework to estimate the surface state and fatigue performance of laser powder bed fusion materials after shot peening

Abstract

Despite the rapid growth of additive manufacturing (AM) technologies, AM parts usually present relatively poor surface quality in as-built condition. This necessitates the application of customized post surface treatments to efficiently enhance the surface quality and alleviate the adverse effects of high surface roughness and extremely irregular surface morphology on fatigue strength of AM metallic materials. In this paper, starting from an as-built AM surface, a detailed numerical model is developed to effectively estimate the surface morphology of laser powder bed fusion (LPBF) AlSi10Mg specimens after shot peening. The obtained results are then incorporated into two analytical approaches to evaluate the fatigue strength of different series. The accuracy of the model is validated by comparisons made with experimental data obtained considering as-built and shot peened specimens both before and after heat treatment. The results demonstrate that the proposed hybrid approach can serve as a powerful package not only to determine the beneficial contribution of shot peening on the surface morphology of AM material but also to provide an accurate and rather reliable approximation of their fatigue strength.