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<p>Nickel-based alloys are well-known as one of the difficult-to-cut materials. Particularly during finish cutting, the issue is not only the tool wear rate but also the meeting surface roughness (SR) requirements under unavoidable tool wear conditions. The challenge intensifies when machining large workpieces because tool changes are not recommended to maintain surface smoothness. Therefore, optimizing the tool life while considering SR as a constraint is crucial. This study addresses this issue using Bayesian optimization, an efficient data-driven approach that can autonomously identify optimal machining conditions with minimal input data. In addition, this study investigated the mechanism behind optimized machining conditions. The results revealed that SR does not always progress linearly with tool-flank wear length. A suitable region of cutting conditions was defined to maintain the desired SR, even as the tool flank wear increased within an allowable range (0.3&#xa0;mm). In this case, the wear mechanism is initiated with a smooth abrasive wear, followed by adhesive wear.</p>

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Tool life optimization in finish cutting of Inconel 718 with surface roughness constraint: from machine learning to proof of mechanism

  • 期刊论文

  • 发表日期：

    2025年10月29日

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  • Jonny Herwan,
  • Ichiro Ogura,
  • Takashi Murakami,
  • Takashi Misaka,
  • Yoshiyuki Furukawa,
  • Kiwamu Ashida

摘要

Nickel-based alloys are well-known as one of the difficult-to-cut materials. Particularly during finish cutting, the issue is not only the tool wear rate but also the meeting surface roughness (SR) requirements under unavoidable tool wear conditions. The challenge intensifies when machining large workpieces because tool changes are not recommended to maintain surface smoothness. Therefore, optimizing the tool life while considering SR as a constraint is crucial. This study addresses this issue using Bayesian optimization, an efficient data-driven approach that can autonomously identify optimal machining conditions with minimal input data. In addition, this study investigated the mechanism behind optimized machining conditions. The results revealed that SR does not always progress linearly with tool-flank wear length. A suitable region of cutting conditions was defined to maintain the desired SR, even as the tool flank wear increased within an allowable range (0.3 mm). In this case, the wear mechanism is initiated with a smooth abrasive wear, followed by adhesive wear.