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<p>This study aims to optimize the ultrasonic machining (USM) parameters for friction stir welded (FSWed) AA6063 aluminum alloy to improve material removal efficiency and surface finish. The novelty lies in integrating ultrasonic machining with statistical modeling to analyze and enhance post-weld machining performance, which remains scarcely explored for AA6063 substrates. For the same, the study quantitatively investigates the effects of altering feed rate (F), spindle speed (S), and power percentage (P) on average material removal rate (MRR) and surface roughness through experimental trials. The microstructural analysis, hardness, impact, and tensile tests are conducted to facilitate comprehensive characterization. The results demonstrate that a greater feed rate often corresponds to an elevated average MRR, varying from 0.053 to 0.161 mm<sup>3</sup>/s under different experimental settings. The spindle speed indicates a complex association with average MRR, ranging from 0.056 to 0.124 mm<sup>3</sup>/s, whereas power percentage shows a marginal positive correlation, fluctuating between 40 and 60%. Surface roughness ranges from 0.701 to 1.905&#xa0;µm, demonstrating the influence of machining factors on surface finish quality. The findings highlight the significance of parameter optimization to attain optimal machining results, balancing material removal rate and surface finish quality in AA6063 samples following FSW, thereby offering useful insights for improving the manufacturing process.</p>

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Parametric Optimization and Microstructural Analysis of Ultrasonically Machined Friction Stir Welded Aluminum Alloy 6063

  • 期刊论文

  • 发表日期：

    2025年8月4日

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  • Vikrant Singh,
  • Sanidhya Kumar,
  • Mohit Vishnoi,
  • Ravi Shankar Thakur,
  • Sachin Jha,
  • Anuj Bansal,
  • N. Jeyaprakash,
  • Sundara Subramanian Karuppasamy

摘要

This study aims to optimize the ultrasonic machining (USM) parameters for friction stir welded (FSWed) AA6063 aluminum alloy to improve material removal efficiency and surface finish. The novelty lies in integrating ultrasonic machining with statistical modeling to analyze and enhance post-weld machining performance, which remains scarcely explored for AA6063 substrates. For the same, the study quantitatively investigates the effects of altering feed rate (F), spindle speed (S), and power percentage (P) on average material removal rate (MRR) and surface roughness through experimental trials. The microstructural analysis, hardness, impact, and tensile tests are conducted to facilitate comprehensive characterization. The results demonstrate that a greater feed rate often corresponds to an elevated average MRR, varying from 0.053 to 0.161 mm3/s under different experimental settings. The spindle speed indicates a complex association with average MRR, ranging from 0.056 to 0.124 mm3/s, whereas power percentage shows a marginal positive correlation, fluctuating between 40 and 60%. Surface roughness ranges from 0.701 to 1.905 µm, demonstrating the influence of machining factors on surface finish quality. The findings highlight the significance of parameter optimization to attain optimal machining results, balancing material removal rate and surface finish quality in AA6063 samples following FSW, thereby offering useful insights for improving the manufacturing process.