Scholarlink

<p>Laser-assisted turning (LAT) is an effective machining approach for improving the machinability of hard and abrasive metal matrix composites by reducing cutting resistance through localized thermal softening. In this study, LAT is adopted to address the challenges associated with conventional machining of AA7178 aluminum alloy reinforced with 3 wt.% SiC nanoparticles, which typically exhibits high cutting forces, rapid tool wear, and poor surface finish. Turning experiments were conducted on a CNC laser-assisted setup using an uncoated tungsten carbide tool. The effects of cutting speed, feed rate, depth of cut, and laser power on surface roughness and cutting force were systematically investigated using a Taguchi L27 orthogonal array. Analysis of variance (ANOVA) revealed that laser power is the most influential parameter affecting surface roughness, contributing 39.14% to the total variation, while cutting speed predominantly governs cutting force reduction with a contribution of 45.15%. Under optimized machining conditions (cutting speed of 180&#xa0;m/min, feed rate of 0.15&#xa0;mm/rev, depth of cut of 0.25&#xa0;mm, and laser power of 500 W), surface roughness and cutting force were reduced to 2.18&#xa0;µm and 63.45 N, respectively. Multi-response optimization using Grey Relational Analysis identified the optimal parameter combination that balances both responses. The results confirm that laser-assisted turning significantly enhances machinability by improving surface quality, reducing cutting forces, and minimizing tool wear, demonstrating its suitability for precision machining of nanoparticle-reinforced aluminum matrix composites.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Correlation of Process Parameters with Machinability Responses in a Novel Laser-Assisted Machining Process of SiC/AA7178 Nanocomposites

  • 期刊论文

  • 发表日期：

    2026年2月18日

查看全文
  • Nikhil Bharat,
  • P. S. C. Bose

摘要

Laser-assisted turning (LAT) is an effective machining approach for improving the machinability of hard and abrasive metal matrix composites by reducing cutting resistance through localized thermal softening. In this study, LAT is adopted to address the challenges associated with conventional machining of AA7178 aluminum alloy reinforced with 3 wt.% SiC nanoparticles, which typically exhibits high cutting forces, rapid tool wear, and poor surface finish. Turning experiments were conducted on a CNC laser-assisted setup using an uncoated tungsten carbide tool. The effects of cutting speed, feed rate, depth of cut, and laser power on surface roughness and cutting force were systematically investigated using a Taguchi L27 orthogonal array. Analysis of variance (ANOVA) revealed that laser power is the most influential parameter affecting surface roughness, contributing 39.14% to the total variation, while cutting speed predominantly governs cutting force reduction with a contribution of 45.15%. Under optimized machining conditions (cutting speed of 180 m/min, feed rate of 0.15 mm/rev, depth of cut of 0.25 mm, and laser power of 500 W), surface roughness and cutting force were reduced to 2.18 µm and 63.45 N, respectively. Multi-response optimization using Grey Relational Analysis identified the optimal parameter combination that balances both responses. The results confirm that laser-assisted turning significantly enhances machinability by improving surface quality, reducing cutting forces, and minimizing tool wear, demonstrating its suitability for precision machining of nanoparticle-reinforced aluminum matrix composites.