Statistical approach optimizing slant feed grinding

Keita Shimada, Pay Jun Liew, Tianfeng Zhou, Jiwang Yan, Tsunemoto Kuriyagawa

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Micro-grinding is one of the methods to create submillimeter-structures, and it has been applied to many processes such as finishing of internal surface of fuel injector valves and dental technique. Micro-grinding has recently been required to improve ground surface roughness. Slant feed grinding is a machining method to improve finished surfaces, but the mechanism of improving ground surface roughness of slant feed grinding has not been completely clarified yet. This paper proposed a theoretical method for calculating ground surface roughness of slant feed grinding by using a statistical approach. This method can clarify the mechanism, and it can also optimize conditions of slant feed grinding. A self-developed micro-grinding device was then employed to confirm the calculation method experimentally, and the experimental results agreed with the theoretical calculation.

Original languageEnglish
Pages (from-to)898-907
Number of pages10
JournalJournal of Advanced Mechanical Design, Systems and Manufacturing
Volume6
Issue number6
DOIs
Publication statusPublished - 2012
Externally publishedYes

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Surface roughness
Machining

Keywords

  • Ground surface roughness
  • Micro-grinding
  • Slant feed grinding
  • Statistical calculation

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Mechanical Engineering

Cite this

Statistical approach optimizing slant feed grinding. / Shimada, Keita; Liew, Pay Jun; Zhou, Tianfeng; Yan, Jiwang; Kuriyagawa, Tsunemoto.

In: Journal of Advanced Mechanical Design, Systems and Manufacturing, Vol. 6, No. 6, 2012, p. 898-907.

Research output: Contribution to journalArticle

Shimada, Keita ; Liew, Pay Jun ; Zhou, Tianfeng ; Yan, Jiwang ; Kuriyagawa, Tsunemoto. / Statistical approach optimizing slant feed grinding. In: Journal of Advanced Mechanical Design, Systems and Manufacturing. 2012 ; Vol. 6, No. 6. pp. 898-907.
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