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<p>Wire and Arc Additive Manufacturing (WAAM), particularly Gas Metal Arc Welding (GMAW)-based WAAM, has attracted increasing attention for repair-oriented applications because of its high deposition rate, cost efficiency, and suitability for restoring metallic components. However, excessive deposition can increase machining allowance and material waste during secondary finishing, thereby reducing the overall efficiency of the repair process. This study investigates the effects of voltage, wire feed rate, and CO₂ shielding-gas flow rate on material waste in semi-automatic GMAW-based WAAM using Response Surface Methodology (RSM) with a Box–Behnken Design. Experimental results were analyzed using Analysis of Variance (ANOVA) to determine the significance of the main, interaction, and quadratic effects. The final quadratic model showed high predictive accuracy, with a coefficient of determination (R²) of 0.9978. Voltage was identified as the dominant factor affecting material waste, while wire feed rate influenced the response mainly through interaction and nonlinear effects. CO₂ flow rate showed a comparatively minor direct effect within the investigated range but contributed through interaction with wire feed rate. Desirability-based optimization identified an optimal parameter combination of voltage setting = 3.62, wire feed rate setting = 3.61, and CO₂ flow rate = 12.05&#xa0;L/min, giving a predicted material waste of 310.39&#xa0;g. Confirmation tests showed low prediction errors, demonstrating the reliability of the model within the studied process window. The optimized parameters were further applied to repair trials on a tool-holder body and a slot-cutting insert. The repaired components restored their original dimensional requirements and were assessed through functional testing, material-waste evaluation, porosity analysis, Vickers microhardness mapping, and heat-affected zone assessment. The results indicate that the optimized GMAW-based WAAM parameters provide a practical material-efficiency window for reducing post-machining waste while supporting preliminary repair quality in component-restoration applications.</p>

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Optimization of process parameters for wire arc additive manufacturing for repair-based applications using response surface methodology

  • 期刊论文

  • 发表日期：

    2026年7月22日

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  • Muhamad Syakir Mohd Zin,
  • Zammeri Abd Rahman,
  • W. Noor Fatihah W. Mohamad,
  • Mohd Sobri Hamid,
  • Rodianah Alias,
  • Muhd Zamree Zakaria,
  • Zulkifli Abd Rahman,
  • Kharudin Ali,
  • Madihah Maharof

摘要

Wire and Arc Additive Manufacturing (WAAM), particularly Gas Metal Arc Welding (GMAW)-based WAAM, has attracted increasing attention for repair-oriented applications because of its high deposition rate, cost efficiency, and suitability for restoring metallic components. However, excessive deposition can increase machining allowance and material waste during secondary finishing, thereby reducing the overall efficiency of the repair process. This study investigates the effects of voltage, wire feed rate, and CO₂ shielding-gas flow rate on material waste in semi-automatic GMAW-based WAAM using Response Surface Methodology (RSM) with a Box–Behnken Design. Experimental results were analyzed using Analysis of Variance (ANOVA) to determine the significance of the main, interaction, and quadratic effects. The final quadratic model showed high predictive accuracy, with a coefficient of determination (R²) of 0.9978. Voltage was identified as the dominant factor affecting material waste, while wire feed rate influenced the response mainly through interaction and nonlinear effects. CO₂ flow rate showed a comparatively minor direct effect within the investigated range but contributed through interaction with wire feed rate. Desirability-based optimization identified an optimal parameter combination of voltage setting = 3.62, wire feed rate setting = 3.61, and CO₂ flow rate = 12.05 L/min, giving a predicted material waste of 310.39 g. Confirmation tests showed low prediction errors, demonstrating the reliability of the model within the studied process window. The optimized parameters were further applied to repair trials on a tool-holder body and a slot-cutting insert. The repaired components restored their original dimensional requirements and were assessed through functional testing, material-waste evaluation, porosity analysis, Vickers microhardness mapping, and heat-affected zone assessment. The results indicate that the optimized GMAW-based WAAM parameters provide a practical material-efficiency window for reducing post-machining waste while supporting preliminary repair quality in component-restoration applications.