Process Parameter Selection for Production of Stainless Steel 316L Using Efficient Multi-Objective Bayesian Optimization Algorithm

Additive manufacturing is a modern technique to produce parts with a complex geometry. However, the choice of the printing parameters is a time-consuming and costly process. In this study, the parameter optimization for the laser powder bed fusion process was investigated. Using state-of-the art mul...

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Veröffentlicht in:	Materials Jg. 16; H. 3; S. 1050
Hauptverfasser:	Chepiga, Timur, Zhilyaev, Petr, Ryabov, Alexander, Simonov, Alexey P., Dubinin, Oleg N., Firsov, Denis G., Kuzminova, Yulia O., Evlashin, Stanislav A.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 25.01.2023 MDPI
Schlagworte:	3D printing Algorithms Bayesian analysis Data points Gaussian process Hardness Lasers Mathematical models Mathematical optimization Mechanical properties Methods Multiple objective analysis Optimization Porosity Powder beds Powders Process parameters Production data Stainless steel Stainless steels Steel, Stainless powder bed fusion multi-objective optimization machine learning metal additive manufacturing printing parameters SS316L
ISSN:	1996-1944, 1996-1944
Online-Zugang:	Volltext
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