Experimental verification of end-milling condition decision support system using data-mining for difficult-to-cut materials

Hiroyuki Kodama, Toshiki Hirogaki, Eiichi Aoyama, Keiji Ogawa, Koichi Okuda

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

4 Citations (Scopus)

Abstract

Data-mining methods using hierarchical and non-hierarchical clustering are proposed, which could help manufacturing engineers determine guidelines for deciding end-milling conditions. We have constructed a novel system that uses clustering techniques and tool catalog data to support the determination of end-milling conditions for different types of recent difficult-to-cut materials. In the present report, we especially focus on the cutting speed to estimate the performance of this system. A comparison with the conditions recommended by famous tool makers in Japan, reveals that our proposed system can be used to determine the cutting speeds for various difficult-to-cut materials. That is, milling experiments using a square end mill under two sets of end-milling conditions (conditions derived from the end-milling condition decision support system and conditions suggested by expert engineers) for difficult-to-cut materials (austenite stainless steel; JIS SUS310) showed that the catalog mining method is effective for deriving guidelines for deciding end-milling conditions at the beginning of the manufacturing stage.

Original languageEnglish
Title of host publicationAdvances in Abrasive Technology XVII
PublisherTrans Tech Publications Ltd
Pages334-339
Number of pages6
Volume1017
ISBN (Electronic)9783038352211
DOIs
Publication statusPublished - 2014
Externally publishedYes
Event17th International Symposium on Advances in Abrasive Technology, ISAAT 2014 - Kailua, United States
Duration: Sep 22 2014Sep 25 2014

Publication series

NameAdvanced Materials Research
Volume1017
ISSN (Print)1022-6680
ISSN (Electronic)1662-8985

Other

Other17th International Symposium on Advances in Abrasive Technology, ISAAT 2014
CountryUnited States
CityKailua
Period9/22/149/25/14

Fingerprint

Decision support systems
Data mining
Engineers
Austenite
Stainless steel
Experiments

Keywords

  • Catalog data
  • Cutting speed
  • Data mining
  • Difficult-to-cut materials
  • End-milling
  • Hierarchical and non-hierarchical clustering
  • Response surface method

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Kodama, H., Hirogaki, T., Aoyama, E., Ogawa, K., & Okuda, K. (2014). Experimental verification of end-milling condition decision support system using data-mining for difficult-to-cut materials. In Advances in Abrasive Technology XVII (Vol. 1017, pp. 334-339). (Advanced Materials Research; Vol. 1017). Trans Tech Publications Ltd. https://doi.org/10.4028/www.scientific.net/AMR.1017.334

Experimental verification of end-milling condition decision support system using data-mining for difficult-to-cut materials. / Kodama, Hiroyuki; Hirogaki, Toshiki; Aoyama, Eiichi; Ogawa, Keiji; Okuda, Koichi.

Advances in Abrasive Technology XVII. Vol. 1017 Trans Tech Publications Ltd, 2014. p. 334-339 (Advanced Materials Research; Vol. 1017).

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

Kodama, H, Hirogaki, T, Aoyama, E, Ogawa, K & Okuda, K 2014, Experimental verification of end-milling condition decision support system using data-mining for difficult-to-cut materials. in Advances in Abrasive Technology XVII. vol. 1017, Advanced Materials Research, vol. 1017, Trans Tech Publications Ltd, pp. 334-339, 17th International Symposium on Advances in Abrasive Technology, ISAAT 2014, Kailua, United States, 9/22/14. https://doi.org/10.4028/www.scientific.net/AMR.1017.334
Kodama H, Hirogaki T, Aoyama E, Ogawa K, Okuda K. Experimental verification of end-milling condition decision support system using data-mining for difficult-to-cut materials. In Advances in Abrasive Technology XVII. Vol. 1017. Trans Tech Publications Ltd. 2014. p. 334-339. (Advanced Materials Research). https://doi.org/10.4028/www.scientific.net/AMR.1017.334
Kodama, Hiroyuki ; Hirogaki, Toshiki ; Aoyama, Eiichi ; Ogawa, Keiji ; Okuda, Koichi. / Experimental verification of end-milling condition decision support system using data-mining for difficult-to-cut materials. Advances in Abrasive Technology XVII. Vol. 1017 Trans Tech Publications Ltd, 2014. pp. 334-339 (Advanced Materials Research).
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