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<p>This research investigates the tribological performance of a Cu–AlCoCrCuFe high-entropy alloy (HEA) surface composite fabricated through the Friction Stir Processing (FSP) technique. A Box–Behnken design, integrated with Response Surface Methodology (RSM), was employed to systematically evaluate the effects of four key control parameters—HEA volume percentage, applied load, sliding velocity, and sliding distance—on two critical tribological responses: wear rate and coefficient of friction (COF). Analysis of Variance (ANOVA) revealed that all four factors significantly affect both responses, with applied load exerting the strongest influence on COF, while HEA volume had the most pronounced effect on minimizing wear rate. With <i>R</i><sup>2</sup> values of 0.9792 for wear rate and 0.9780 for COF, the resultant RSM models demonstrated excellent prediction accuracy. Multi-objective numerical optimization identified the optimal parameter combination as 10.09 N applied load, 11.99% HEA volume, 1429.48&#xa0;m sliding distance, and 0.5428&#xa0;m/s sliding velocity. Under these optimized conditions, the predicted wear rate and COF were 2.32 × 10<sup>−3</sup> mm<sup>3</sup>/Nm and 0.708, respectively. Experimental validation of the optimized parameters demonstrated excellent agreement with model predictions, showing deviations of only 4.91% for wear rate and 1.56% for COF. Microstructural characterization revealed significant grain refinement and increased hardness with inclusion of higher HEA content, attributed to Hall–Petch and Orowan strengthening mechanisms. These enhancements directly contributed to a transition in the wear mechanism from severe to mild abrasive wear.</p>

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Designing for Durability: Multi-objective RSM Optimization of Dry Sliding Wear in Cu–HEA Surface Composites

  • 期刊论文

  • 发表日期：

    2025年12月22日

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  • C. Krishnaraj,
  • S. Kannan,
  • S. Seenivasan,
  • M. Jegadeeswaran,
  • L. Suriyaprakash,
  • C. Jeevakarunya,
  • A. Saiyathibrahim

摘要

This research investigates the tribological performance of a Cu–AlCoCrCuFe high-entropy alloy (HEA) surface composite fabricated through the Friction Stir Processing (FSP) technique. A Box–Behnken design, integrated with Response Surface Methodology (RSM), was employed to systematically evaluate the effects of four key control parameters—HEA volume percentage, applied load, sliding velocity, and sliding distance—on two critical tribological responses: wear rate and coefficient of friction (COF). Analysis of Variance (ANOVA) revealed that all four factors significantly affect both responses, with applied load exerting the strongest influence on COF, while HEA volume had the most pronounced effect on minimizing wear rate. With R2 values of 0.9792 for wear rate and 0.9780 for COF, the resultant RSM models demonstrated excellent prediction accuracy. Multi-objective numerical optimization identified the optimal parameter combination as 10.09 N applied load, 11.99% HEA volume, 1429.48 m sliding distance, and 0.5428 m/s sliding velocity. Under these optimized conditions, the predicted wear rate and COF were 2.32 × 10−3 mm3/Nm and 0.708, respectively. Experimental validation of the optimized parameters demonstrated excellent agreement with model predictions, showing deviations of only 4.91% for wear rate and 1.56% for COF. Microstructural characterization revealed significant grain refinement and increased hardness with inclusion of higher HEA content, attributed to Hall–Petch and Orowan strengthening mechanisms. These enhancements directly contributed to a transition in the wear mechanism from severe to mild abrasive wear.