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

Hiroyuki Kodama, Koichi Okuda, Takuya Tsujimoto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of the 16th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2016
Publishereuspen
ISBN (Electronic)9780956679086
Publication statusPublished - 2016
Externally publishedYes
Event16th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2016 - Nottingham, United Kingdom
Duration: May 30 2016Jun 3 2016

Other

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

Keywords

  • Data-mining
  • Hierarchical and non- hierarchical clustering
  • Micro end-mill
  • Tool catalog data

ASJC Scopus subject areas

  • Materials Science(all)
  • Environmental Engineering
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Instrumentation

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  • Cite this

    Kodama, H., Okuda, K., & Tsujimoto, T. (2016). Decision methodology of micro end-milling condition using tool catalog data-mining system. In Proceedings of the 16th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2016 euspen.