On the effect of loading and printing parameters that influence the fatigue behavior of laser powder-bed fusion additively manufactured steels
Ali Alhajeri,
Oluwatobi Aremu,
Mosa Almutahhar,
Mohammed Yousif,
Jafar Albinmousa,
Usman Ali
Affiliations
Ali Alhajeri
Department of Mechanical Engineering, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia
Oluwatobi Aremu
Department of Mechanical Engineering, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia
Mosa Almutahhar
Department of Mechanical Engineering, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia
Mohammed Yousif
Department of Mechanical Engineering, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia
Jafar Albinmousa
Department of Mechanical Engineering, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia; Interdisciplinary Research Center on Advanced Materials, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia
Usman Ali
Department of Mechanical Engineering, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia; Interdisciplinary Research Center on Advanced Materials, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia; K.A. CARE Energy Research & Innovation Center at Dhahran, Saudi Arabia; Corresponding author. Department of Mechanical Engineering, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia.
The aim of this paper is to investigate the factors (build orientation, sample conditions, and R-ratio) that affect the cyclic response of laser powder-bed fusion stainless steel 316L and 17-4 PH parts. Initially, the data set was analyzed to confirm the normality assumption. The significant and insignificant factors that affect the fatigue life were identified using analysis of variance (ANOVA). Main effects for different sample conditions were also analyzed. Process and reproducibility assessment were performed to study the effect of process factors. Combining fatigue data sets was recommended as the best approach to accurately predict the fatigue behavior of LPBF 316L and 17-4 PH parts. Finally, the effect of sample conditions on fatigue life was quantified. The highest fatigue life was achieved with Machined-Polished surfaces.
