Decision methodology of micro end-milling condition using tool catalog data-mining system

Hiroyuki Kodama, Koichi Okuda, Takuya Tsujimoto

研究成果

抄録

Data-mining methods were applied to support decisions about reasonable micro end-mill cutting conditions (cutting speed, feed rate, axial depth of cut and radius depth of cut). The aim of this research was to excavate new knowledge with the mining effect by applying the data mining process of hierarchical and non-hierarchical clustering methods to micro end-mill tool catalogs. Micro end-mill shape element of catalog data were focused on visually grouped end-mills, which meant the ratio of tool shape dimensions. With these process, principal component analysis was used to quantify the correlation degree between cutting conditions and tool shape parameters. End-milling condition decision equations were derived from response surface method using significant predictor variables consisting of tool shape parameters and workpiece mechanical properties. The catalog-mining system appeared to be effective for mining knowledge hidden in a large amount of catalog data related to tool shape and end-milling conditions. Therefore, it appears to be straightforward for unskilled engineers to visually determine micro end-milling conditions from the tool shape. Moreover, short-delivery manufacturing with less waste may be possible.

本文言語English
ホスト出版物のタイトルProceedings of the 16th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2016
出版社euspen
ISBN(電子版)9780956679086
出版ステータスPublished - 2016
外部発表はい
イベント16th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2016 - Nottingham
継続期間: 5月 30 20166月 3 2016

Other

Other16th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2016
国/地域United Kingdom
CityNottingham
Period5/30/166/3/16

ASJC Scopus subject areas

  • 材料科学一般
  • 環境工学
  • 機械工学
  • 産業および生産工学
  • 器械工学

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