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<p>This study aims to enhance the cutting performance of PCBN (polycrystalline cubic boron nitride) tools with negative chamfered micro-textures during dry machining of gray cast iron (HT250), addressing challenges associated with high cutting forces and elevated temperatures. The underlying principle is that topologically optimized micro-texture geometries can regulate friction and heat transfer at the tool–workpiece interface, thereby reducing resistance, improving thermal dissipation, and enhancing machining stability. Response surface methodology (RSM) was employed to evaluate the effects of edge distance, scaling factor, and texture depth on the average main cutting force and cutting temperature. All three parameters had significant influence, with the interaction between edge distance and scaling factor being most critical. The analysis shows that proper parameter adjustment reduces friction and pressure on the rake face, lowering cutting force, temperature, and surface roughness. The optimal texture configuration was identified as an edge distance of 105&#xa0;μm, a scaling factor of 0.97, and a depth of 50&#xa0;μm. Cutting tests using laser-fabricated textured tools showed prediction errors of 2.9% for cutting force and 3.4% for temperature, confirming the accuracy and practical applicability of the developed model.</p>

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Response Surface-Based Optimization and Experimental Validation of Micro-Texture Parameters for Negative Chamfered PCBN Cutting Tools

  • 期刊论文

  • 发表日期：

    2025年9月30日

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  • Ziwei Jiang,
  • Guangfeng Shi,
  • Jiye Liu,
  • Siwei Meng,
  • Deshi Kong

摘要

This study aims to enhance the cutting performance of PCBN (polycrystalline cubic boron nitride) tools with negative chamfered micro-textures during dry machining of gray cast iron (HT250), addressing challenges associated with high cutting forces and elevated temperatures. The underlying principle is that topologically optimized micro-texture geometries can regulate friction and heat transfer at the tool–workpiece interface, thereby reducing resistance, improving thermal dissipation, and enhancing machining stability. Response surface methodology (RSM) was employed to evaluate the effects of edge distance, scaling factor, and texture depth on the average main cutting force and cutting temperature. All three parameters had significant influence, with the interaction between edge distance and scaling factor being most critical. The analysis shows that proper parameter adjustment reduces friction and pressure on the rake face, lowering cutting force, temperature, and surface roughness. The optimal texture configuration was identified as an edge distance of 105 μm, a scaling factor of 0.97, and a depth of 50 μm. Cutting tests using laser-fabricated textured tools showed prediction errors of 2.9% for cutting force and 3.4% for temperature, confirming the accuracy and practical applicability of the developed model.