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<p>As a novel precision machining technique for roller surfaces, double-disc straight-groove (DDSG) grinding encounters challenges arising from the high friction coefficient and limited wear resistance of the lower grinding disk. Based on the DDSG mechanism, a static analytical model is established to elucidate the interrelation between the friction coefficients of the upper and lower disks. Microtextures with varied geometrical parameters—including surface density (A), depth (h), and angle (θ)—were fabricated on a cemented carbide disk. A three-factor, three-level orthogonal experimental design combined with friction–wear testing was employed to evaluate their effects on the friction coefficient, material removal rate, and surface roughness. The multi-objective optimization problem was converted into a single-objective form through the q-rung orthopair fuzzy set (q-ROFS) framework. The results demonstrate that the optimal microtexture configuration effectively reduces the friction coefficient, enhances surface finish, and improves material removal efficiency. The proposed q-ROFS-based optimization approach exhibits superior robustness and, for the first time, integrates fuzzy decision-making with DDSG grinding. By coupling a theoretical friction–rotation model with multi-objective fuzzy optimization, this study provides new insights and a systematic framework for improving the tribological performance and design reliability of precision grinding disks.</p>

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Optimized design of microtexture parameters in double-disc straight-groove grinding using a multi-objective fuzzy decision approach

  • 期刊论文

  • 发表日期：

    2026年7月2日

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  • Jierui Wang,
  • Yuhong Du,
  • Xiaofan Deng,
  • Yanzhi Hao,
  • Xinlong Li

摘要

As a novel precision machining technique for roller surfaces, double-disc straight-groove (DDSG) grinding encounters challenges arising from the high friction coefficient and limited wear resistance of the lower grinding disk. Based on the DDSG mechanism, a static analytical model is established to elucidate the interrelation between the friction coefficients of the upper and lower disks. Microtextures with varied geometrical parameters—including surface density (A), depth (h), and angle (θ)—were fabricated on a cemented carbide disk. A three-factor, three-level orthogonal experimental design combined with friction–wear testing was employed to evaluate their effects on the friction coefficient, material removal rate, and surface roughness. The multi-objective optimization problem was converted into a single-objective form through the q-rung orthopair fuzzy set (q-ROFS) framework. The results demonstrate that the optimal microtexture configuration effectively reduces the friction coefficient, enhances surface finish, and improves material removal efficiency. The proposed q-ROFS-based optimization approach exhibits superior robustness and, for the first time, integrates fuzzy decision-making with DDSG grinding. By coupling a theoretical friction–rotation model with multi-objective fuzzy optimization, this study provides new insights and a systematic framework for improving the tribological performance and design reliability of precision grinding disks.