Parameters Optimization of Auxiliary Gas Process for Double-Wire SS316L Stainless Steel Arc Additive Manufacturing

Abstract

Serious heat accumulation limits the further efficiency and application in additive manufacturing (AM). This study accordingly proposed a double-wire SS316L stainless steel arc AM with a two-direction auxiliary gas process to research the effect of three parameters, such as auxiliary gas nozzle angle, auxiliary gas flow rate and nozzle-to-substrate distance on depositions, then based on the Box–Behnken Design response surface, a regression equation between three parameters and the total score were established to optimized parameters by an evaluation system. The results showed that samples with nozzle angle of 30° had poor morphology but good properties, and increasing gas flow or decreasing distance would enhance the airflow strength and stiffness, then strongly stir the molten pool and resist the interference. Then a diverse combination of auxiliary process parameters had different influences on the morphology and properties, and an interactive effect on the comprehensive score. Ultimately the optimal auxiliary gas process parameters were 17.4°, 25 L/min and 10.44 mm, which not only bettered the morphology, but refined the grains and improved the properties due to the stirring and cooling effect of the auxiliary gas, which provides a feasible way for quality and efficiency improvements in arc additive manufacturing.

Fabrication of Multi-Walled Structure through Parametric Study of Bead Geometries of GMAW-Based WAAM Process of SS309L

“…By using orthogonal arrays of a BBD, multiple factors can be tested with minimal experimental runs [ 38 , 39 ]. This approach helps systematically identify the essential factors that affect product or process quality [ 40 ]. A BBD also gives the relationships between a response variable and multiple input variables, such as polynomial regression models, to identify optimal input conditions that maximize the response variable [ 41 , 42 ].…”

A Review of Process Optimization for Additive Manufacturing Based on Machine Learning

“…There are many research applying regression to find the relationship between process parameters and output qualities. Wu et al [63] proposed a double-wire SS316L stainless steel arc AM with a two-direction auxiliary gas process to improve efficiency in AM. The focus is on three parameters: auxiliary gas nozzle angle, auxiliary gas flow rate, and nozzle-to-substrate distance.…”

Preliminary Process and Microstructure Examination of Flux-Cored Wire Arc Additive Manufactured 18Ni-12Co-4Mo-Ti Maraging Steel

“…It is possible to use additives on unalloyed steels [28], low-alloy steels [20,29], mild steel [12] and high-strength low-alloy steels [30], yet an unfavourable phase can be obtained in the structure, as reported by Nemani et al [29] after WAAM, with the use of ER70S filler material. Austenitic stainless steels also qualify as trouble-free materials, which is proved by Xie et al [9], Yao et al [22] and Wu et al [23]. Roy et al [2] successfully made a part of AISI 410 martensitic stainless steel; similarly, Lervåg et al [10] for superduplex steel and Tain et al [31] for 10CrNi3MoV steel.…”

“…The use of additional treatments such as active cooling [17], on-line vortex cooling [18], ultrasonic vibration [19] and post heat treatment [5,20] is examined. The influence of interpass temperature/delay [21] or heat input [8,[22][23][24][25] is analyzed, in the context of distortion and deformations [26,27].…”