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February 26, 20260 citations

深層学習を用いたレーザー撥液加工法の最適化

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広石広夢 石村蓮後蓮 後藤昌山昌樹 山口

Key Points

  • This research aims to optimize laser processing conditions for creating waffle structures that exhibit excellent water-repellent properties.
  • Proposed a helical processing method for laser beam scanning in concentric circles.
  • Conducted experiments using aluminum alloy as the workpiece.
  • Varying laser processing conditions resulted in a dataset of 3,000 entries.
  • Developed an optimization model using deep learning for processing conditions.
  • Identified optimal processing conditions satisfying depth/pitch ratio of ≥ 0.5 for maintaining water-repellent performance under disturbances.

Abstract

本研究では，撥液性能に優れた形状の一つとされるマイクロメートル領域のワッフル構造を，超短パルスレーザーで加工する渦巻加工法を提案する。これは，ワッフル構造の中心から同心円状かつ2次元方向にレーザービームを走査し，正方形領域をくり抜く方法である。実験では，アルミ合金を被加工材とし，レーザー加工条件を変化させ 3,000 データを取得した。深層学習による加工条件の最適化モデルを構築したところ，外乱に対して撥水性能を維持するのに適した深さ/ピッチ比 ≧ 0.5 を満足する加工条件を同定できた。

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Cite This Study

石村 et al. (2025) studied this question.

synapsesocial.com/papers/699fe38b95ddcd3a253e782dhttps://doi.org/10.1299/jsmedmc.2025.124
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