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<p>Wire Arc Additive Manufacturing (WAAM) is a high-productivity technique for producing large metal components. Controlling bead geometry, microstructure, and mechanical properties remains challenging due to complex thermal cycles. In this study, ER70S-6 steel was deposited to investigate the combined effects of arc power and robot travel speed on bead geometry, hardness, wetting, and microstructural evolution. The microstructural analysis revealed refined acicular/Widmanstätten ferrite, a well-defined dilution zone with equiaxed grains, and a thin oxide layer enriched with Mn, Si, Al, and Fe. Porosity originated from oxide entrapment and gas retention. The response Surface Methodology (RSM) was used to model the process-response relationships and to identify the optimal parameters. Arc power was found to be the dominant factor, with robot travel speed contributing significantly. The optimized condition (2839&#xa0;W, 7.5&#xa0;mm/s) achieved a predicted hardness of 300 HV, an aspect ratio of 2.63, and a wetting angle of 60.8°, validated experimentally. The study demonstrates the predictive capability of RSM and provides guidelines for optimizing WAAM parameters for ER70S-6 steel components.</p>

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Experimental study and statistical modelling of wire arc additive manufacturing of ER70S-6

  • 期刊论文

  • 发表日期：

    2026年5月27日

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  • Mojtaba Karamimoghadam,
  • Mohammad Rezayat,
  • Nicola Contuzzi,
  • Mousa Javidani,
  • Antonio Mateo,
  • Giuseppe Casalino

摘要

Wire Arc Additive Manufacturing (WAAM) is a high-productivity technique for producing large metal components. Controlling bead geometry, microstructure, and mechanical properties remains challenging due to complex thermal cycles. In this study, ER70S-6 steel was deposited to investigate the combined effects of arc power and robot travel speed on bead geometry, hardness, wetting, and microstructural evolution. The microstructural analysis revealed refined acicular/Widmanstätten ferrite, a well-defined dilution zone with equiaxed grains, and a thin oxide layer enriched with Mn, Si, Al, and Fe. Porosity originated from oxide entrapment and gas retention. The response Surface Methodology (RSM) was used to model the process-response relationships and to identify the optimal parameters. Arc power was found to be the dominant factor, with robot travel speed contributing significantly. The optimized condition (2839 W, 7.5 mm/s) achieved a predicted hardness of 300 HV, an aspect ratio of 2.63, and a wetting angle of 60.8°, validated experimentally. The study demonstrates the predictive capability of RSM and provides guidelines for optimizing WAAM parameters for ER70S-6 steel components.