Simple method to construct process maps for additive manufacturing using a support vector machine

Kenta Aoyagi, Hao Wang, Hideki Sudo, Akihiko Chiba

研究成果: Article査読

65 被引用数 (Scopus)

抄録

We propose a simple method to construct a process map for additive manufacturing using a support vector machine. By observing the surface of the built parts and classifying them into two classes (good or bad), this method enables a process map to be constructed in order to predict a process condition that is effective at fabricating a part with low pore density. This proposed method is demonstrated in a biomedical CoCr alloy system. We show that the proposed method is effective at reducing the number of experiments necessary to tailor an optimized process condition. This study also shows that the value of a decision function in a support vector machine has a physical meaning (at least in the proposed method) and is a semi-quantitative guideline for porosity density of parts fabricated by additive manufacturing.

本文言語English
ページ(範囲)353-362
ページ数10
ジャーナルAdditive Manufacturing
27
DOI
出版ステータスPublished - 2019 5月

ASJC Scopus subject areas

  • 生体医工学
  • 材料科学(全般)
  • 工学(その他)
  • 産業および生産工学

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