Research article

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

¹ Faculty of Mechanical Engineering, Le Quy Don Technical University, Hanoi, Vietnam
² Advanced Technology Center, Le Quy Don Technical University, Hanoi, Vietnam

* e-mail: vtle@lqdtu.edu.vn

Received: 9 January 2024
Accepted: 6 May 2024

Abstract

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 V_s, the laser power P_l, and the powder feed rate f_p), P_l 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. V_s exhibits the highest contribution to the models of the deposited track height h a contribution of 49.86%. On the other hand, f_p 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., V_s = 6 mm/s, P_l = 263.63 W, and f_p = 18 g/min) to build thin-walled structures in SS316L by LDMD.