首页|Optimization of hybrid manufacturing process combining forging and wire-arc additive manufactured Ti-6Al-4V through hot deformation characterization

Optimization of hybrid manufacturing process combining forging and wire-arc additive manufactured Ti-6Al-4V through hot deformation characterization

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  • NSTL
  • Elsevier
Recently, the hybrid method has been developed in which wire and arc additive manufacturing (WAAM) use to produce the near net shape preform for the single-step hot forging process. The hybrid method over-comes the defects and anisotropic properties of WAAM processed preform and produce the net shape of the component with better mechanical properties. This study investigates the hot deformation behavior and mechanical properties of WAAM Ti-6Al-4V alloy containing widmantatten microstructure (0.34 - 0.48 mu m) produced by the hybrid method. Hot deformation tests were conducted in the temperature range 700-1000 degrees C and strain rate range 0.01 s(-1) - 10 s(-1) up to the height reduction of 60%, using the thermal-mechanical simulator gleeble-380 0. The artificial neural network model (ANN) has been developed to correct the non-isothermal flow curve at finer intervals of experimental conditions. The microstructural studies were carried out at various regions using a developed processing map. The microstructures show an instability region at a high strain rate and lower temperature, associated with flow localization and lamellae kinking. At the same time, the high efficiency and stable regions are related to dynamic recrystallization in the temperature range 900-950 degrees C at a strain rate below 1 s-1. The self-deformation activation energy in the alpha + beta and beta phase regions was 308.7 kJ/mol and 493.2 kJ/mol, respectively. The forged sample at 920 degrees C and strain 0.6, 0.8, and 0.9 show high strength, elongation, and weak texture compared to the received and stress relieved sample. (C) 2021 Elsevier B.V. All rights reserved.

Wire and arc additive manufacturingTi-6Al-4VArtificial neural networkHot deformation behaviorDynamic recrystallizationTensile propertyDYNAMIC SOFTENING BEHAVIORTITANIUM-ALLOYMICROSTRUCTURAL EVOLUTIONMECHANICAL-PROPERTIESACTIVATION-ENERGYRESIDUAL-STRESSFLOW BEHAVIORSTRAIN-RATEMAPSRECRYSTALLIZATION

Maurya, A. K.、Yeom, Jong-Taek、Kang, Seung Won、Park, Chan Hee、Hong, Jae-Keun、Reddy, N. S.

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Korea Inst Mat Sci

Gyeongsang Natl Univ

2022

10.1016/j.jallcom.2021.162453

Journal of Alloys and Compounds

Journal of Alloys and Compounds

EISCI
ISSN：0925-8388
年,卷(期)：2022.894
  • 12
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