Experimental investigation on improving the deposition rate of gas metal arc-based additive manufacturing by auxiliary wire feeding method

Han, Qing; Gao, Jia Qi; Han, Changle; Zhang, Guangjun; Li, Yongzhe

doi:10.1007/s40194-020-00994-0

Cited by 15 publications

(2 citation statements)

References 18 publications

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“…In recent years, a few studies using CWGMA in WAAM have reported it as a process with increased productivity, reduced energy input, and other benefits in several materials such as mild steels [17][18][19], stainless steels [20], and aluminium alloys [21].…”

Section: Introductionmentioning

confidence: 99%

Process Control Methods in Cold Wire Gas Metal Arc Additive Manufacturing

Bento

Wang

Ding

et al. 2023

Metals

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Cold wire gas metal arc (CWGMA) additive manufacturing (AM) is more productive and beneficial than the common electric arc processes currently used in wire arc additive manufacturing (WAAM). Adding a non-energised wire to the gas metal arc (GMA) system makes it possible to overcome a process limitation and decouple the energy input from the material feed rate. Two novel process control methods were proposed, namely, arc power and travel speed control, which can keep the required geometry accuracy in WAAM through a broad range of thermal conditions. The reinforcement area of the bead is kept constant with accurate control over the height and width while still reducing the energy input to the substrate; decreasing penetration depth, remelting, and the heat-affected zone (HAZ); and reaching a dilution lower than 10%. This work also presents improved productivity compared to all the other single-arc energy-based processes with a demonstrator part built using 9.57 kg h−1 with CWGMA AM.

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Section: Introductionmentioning

confidence: 99%

Process Control Methods in Cold Wire Gas Metal Arc Additive Manufacturing

Bento

Wang

Ding

et al. 2023

Metals

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“…Han et. al [6] studied the Gas Metal Arc (GMA) Additive manufacturing (AM) of Al 2325 material. This study proposed a unique strategy to increase the deposition rate without affecting the mechanical characteristics and bead geometrics due to high heat input.…”

Section: Introductionmentioning

confidence: 99%

Parametric Modeling for Optimization of Deposition Rate in Wire Arc Additive Manufacturing of AISI 410 Stainless Steel Using Bead-on-Plate Specimens

Pradeep Kumar,

Arun Prakash,

Kanmani

et al. 2023

MSF

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The deposition rate is a critical parameter that has a significant influence in Wire Arc Additive Manufacturing (WAAM) of critical aerospace components made of AISI 410 Stainless steel. In this work, Taguchi parametric modeling for wire arc additive manufacturing is carried out using the input parameters of the welding current (WC), the travel speed of the nozzle (TSN), and the distance between the nozzle and the workpiece (DNW). Each factor is varied at 3 levels and the experiments are carried out based on Taguchi L9 orthogonal array. The response variable considered is the deposition rate (DR). Based on the results from experiments, the optimal combination of process parameters obtained is 140 A of welding current, 3mm/s of the travel speed of the nozzle, and 15 mm of distance between the nozzle and workpiece. The optimum deposition rate achieved is 8.545 g/s. The percentage of contribution of various factors is found to be TSN at 43.65% and WC at 16.6% and DNW at 4.9%.

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Enhanced curve-fitting model of the bead section profile and the corresponding overlapping model for twin-electrode gas tungsten arc–based additive manufacturing

Han

Dong³

et al. 2021

Int J Adv Manuf Technol

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Experimental investigation on improving the deposition rate of gas metal arc-based additive manufacturing by auxiliary wire feeding method

Cited by 15 publications

References 18 publications

Process Control Methods in Cold Wire Gas Metal Arc Additive Manufacturing

Process Control Methods in Cold Wire Gas Metal Arc Additive Manufacturing

Parametric Modeling for Optimization of Deposition Rate in Wire Arc Additive Manufacturing of AISI 410 Stainless Steel Using Bead-on-Plate Specimens

Enhanced curve-fitting model of the bead section profile and the corresponding overlapping model for twin-electrode gas tungsten arc–based additive manufacturing

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