論文

査読有り
2018年

CAM操作者の意図を考慮したエンドミル加工用自動工程設計システム

日本機械学会論文集
  • 西田 勇
  • ,
  • 平井 大志
  • ,
  • 佐藤 隆太
  • ,
  • 白瀬 敬一

84
860
開始ページ
17
終了ページ
00563-17-00563
記述言語
日本語
掲載種別
研究論文(国際会議プロシーディングス)
DOI
10.1299/transjsme.17-00563
出版者・発行元
一般社団法人 日本機械学会

<p>In this study, an automatic process planning system for end-milling operation is proposed, in which CAM operator's intention for process planning is considered. In the previous process planning systems, the machining sequence is calculated geometrically, based on the Total Removal Volume (TRV) and the machining region split from TRV. However, it remains difficult to determine the best machining sequence from the large number of the calculated machining sequences. The previous process planning systems also do not consider CAM operator's intention in the determination of the appropriate machining sequence. First, our new process planning system stores the priority of machining feature and the geometrical properties of the selected machining region when a CAM operator decides the machining sequence. After storing the priority of machining feature and the geometrical properties, the appropriate machining sequence can be automatically determined by referring this information. CAM operator's intention, which is involved implicitly in the stored geometrical properties of the machining region, can be applied to decide machining sequence. A case study was conducted to show the effectiveness of our new proposed process planning system. In the case study, user-specific machining sequences were automatically determined based on the implicit relation among the geometrical properties of the machining region and the individual CAM operator's intention.</p>

リンク情報
DOI
https://doi.org/10.1299/transjsme.17-00563
CiNii Articles
http://ci.nii.ac.jp/naid/130006726325
Scopus
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85084944836&origin=inward
Scopus Citedby
https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85084944836&origin=inward
ID情報
  • DOI : 10.1299/transjsme.17-00563
  • CiNii Articles ID : 130006726325
  • SCOPUS ID : 85084944836

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