Prediction models and multi-objective optimization of the single deposited tracks in laser direct metal deposition of 316L stainless steel

被引:0
|
作者
Tat, Khoa Doan [1 ]
Le, Van Thao [2 ]
Van, Nguy Duong [1 ]
机构
[1] Le Quy Don Tech Univ, Fac Mech Engn, Hanoi, Vietnam
[2] Le Quy Don Tech Univ, Adv Technol Ctr, Hanoi, Vietnam
来源
MANUFACTURING REVIEW | 2024年 / 11卷
关键词
Laser direct metal deposition; 316L; optimization; GRA; TOPSIS; PSO; ENERGY DEPOSITION; MULTI-TRACK; POWDER;
D O I
10.1051/mfreview/2024012
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Laser direct metal deposition (LDMD) is a metal additive manufacturing process, which uses a laser source to melt metal powder and deposit the molten metal into the part layer-by-layer through a nozzle. With suitable process parameters and setting conditions, a component can be fabricated with a full density. In this process, the shape of single tracks is a key indicator, which directly prescribes the quality of the process and the fabricated component. To fabricate a complex component, especially that with thin-wall structures with free of defects, controlling the single tracks' geometry and the understanding on the effects of the process parameters are essential. Therefore, this article focuses on studying the effects of process variables on single tracks' attributes in the LDMD process of SS316L and identifying the optimum variables for the deposition of SS316L thin wall structures. The observed results indicated that, among the process parameters (the scanning speed Vs, the laser power Pl, and the powder feed rate fp), Pl exhibits the highest impact contribution to the models of the deposited track width w and the deposited track penetration p with a contribution of 71.83% and 87.68%, respectively. Vs exhibits the highest contribution to the models of the deposited track height h a contribution of 49.86%. On the other hand, fp shows an insignificant impact contribution to the w and p models. All the developed models feature a high prediction accuracy with the values of determination coefficients R2 of 97.89%, 97.08%, 99.11% for w, h, and p, respectively, indicating that they can be used to prediction w, h, and p with high confidence and precision levels. Moreover, the optimization results achieved by different methods (i.e., GRA, TOPSIS, and PSO+TOPSIS) demonstrated that the PSO and TOPSIS combination can be used to find out the most optimal process parameters (i.e., Vs = 6 mm/s, Pl = 263.63 W, and fp = 18 g/min) to build thin-walled structures in SS316L by LDMD.
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页数:15
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