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<p>Bone milling represents a technically demanding and clinically sensitive procedure integral to neurosurgical and spinal interventions, particularly in the context of lumbar disc decompression. The thermomechanical stresses incurred during this operation pose substantial risks to adjacent neurovascular and osseous tissues, and surface topography, especially roughness, is widely considered to influence subsequent healing and tissue integration. This investigation employed Response Surface Methodology (RSM) via Minitab to rigorously evaluate the compounded effects of four machining parameters: rotational speed, feed rate, depth of cut, and tool diameter on thermal generation, milling force, and surface microgeometry. The results of the multi-response optimization show that the optimal values for thermal generation (29.8770 C°), cutting force (0.1570 N), and surface roughness (1.1016µm) were all achieved under the same set of milling parameters: a spindle speed of 4000 rpm, a feed rate of 20 mm/min, a depth of cut of 0.1 mm, and a tool diameter of 8 mm, across the cutting direction. The results suggest that the findings could be applied to robotic bone milling surgeries, providing doctors with a limited set of parameters to ensure precision and minimize thermal and mechanical disruptions.</p>

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Integrated Multivariate Optimization of Bone Milling Parameters for Minimizing Iatrogenic Trauma and Enhancing Osteogenic Potential

  • 期刊论文

  • 发表日期：

    2026年5月27日

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  • Ali Akhondi,
  • Vahid Tahmasbi,
  • Mahdi Qasemi

摘要

Bone milling represents a technically demanding and clinically sensitive procedure integral to neurosurgical and spinal interventions, particularly in the context of lumbar disc decompression. The thermomechanical stresses incurred during this operation pose substantial risks to adjacent neurovascular and osseous tissues, and surface topography, especially roughness, is widely considered to influence subsequent healing and tissue integration. This investigation employed Response Surface Methodology (RSM) via Minitab to rigorously evaluate the compounded effects of four machining parameters: rotational speed, feed rate, depth of cut, and tool diameter on thermal generation, milling force, and surface microgeometry. The results of the multi-response optimization show that the optimal values for thermal generation (29.8770 C°), cutting force (0.1570 N), and surface roughness (1.1016µm) were all achieved under the same set of milling parameters: a spindle speed of 4000 rpm, a feed rate of 20 mm/min, a depth of cut of 0.1 mm, and a tool diameter of 8 mm, across the cutting direction. The results suggest that the findings could be applied to robotic bone milling surgeries, providing doctors with a limited set of parameters to ensure precision and minimize thermal and mechanical disruptions.