In this study, machine learning models are proposed to predict the Vickers hardness of AlSi10Mg alloys fabricated by laser powder bed fusion (LPBF). A total of 113 utilizable datasets were collected from the literature. The hyperparameters of the machine-learning models were adjusted to select an accurate predictive model. The random forest regression (RFR) model showed the best performance compared to support vector regression, artificial neural networks, and k-nearest neighbors. The variable importance and prediction mechanisms of the RFR were discussed by Shapley additive explanation (SHAP). Aging time had the greatest influence on the Vickers hardness, followed by solution time, solution temperature, layer thickness, scan speed, power, aging temperature, average particle size, and hatching distance. Detailed prediction mechanisms for RFR are analyzed using SHAP dependence plots.

1. 서 론
2. 해석 모델 구축
3. 결과 및 고찰
4. 결 론
Acknowledgements

• 전준협(전북대학교 신소재공학부, 한국생산기술연구원 탄소경량소재응용그룹) | Junhyub Jeon (Department of Metallurgical Engineering, Jeonbuk National University, Jeonju 54896, Republic of Korea, Jeonbuk Regional Division, Korea Institute of Industrial Technology, Gimje 54325, Republic of Korea)
• 서남혁(전북대학교 신소재공학부, 한국생산기술연구원 탄소경량소재응용그룹) | Namhyuk Seo (Department of Metallurgical Engineering, Jeonbuk National University, Jeonju 54896, Republic of Korea, Jeonbuk Regional Division, Korea Institute of Industrial Technology, Gimje 54325, Republic of Korea)
• 김민수(한국생산기술연구원 탄소경량소재응용그룹) | Min-Su Kim (Jeonbuk Regional Division, Korea Institute of Industrial Technology, Gimje 54325, Republic of Korea)
• 손승배(전북대학교 신소재공학부) | Seung Bae Son (Department of Metallurgical Engineering, Jeonbuk National University, Jeonju 54896, Republic of Korea)
• 정재길(전북대학교 신소재공학부) | Jae-Gil Jung (Department of Metallurgical Engineering, Jeonbuk National University, Jeonju 54896, Republic of Korea)
• 이석재(전북대학교 신소재공학부) | Seok-Jae Lee (Department of Metallurgical Engineering, Jeonbuk National University, Jeonju 54896, Republic of Korea) Corresponding Author