592
Views
52
CrossRef citations to date
0
Altmetric
Original Articles

Evaluation of New Vegetable-Based Cutting Fluids on Thrust Force and Surface Roughness in Drilling of AISI 304 Using Taguchi Method

, , , &
Pages 1136-1146 | Received 20 Aug 2010, Accepted 19 Oct 2010, Published online: 18 Aug 2011
 

Abstract

This study focused on both formulation of vegetable-based cutting fluids (VBCFs) and machining with these cutting fluids. For this purpose, characterizations of chemical and physical analyses of these formulated cutting fluids were carried out. Performances of five cutting fluids, three VBCFs developed from crude and refined sunflower oils, and two commercial types, were investigated for thrust force and surface roughness during drilling of AISI 304 with HSS-E tool. Spindle speed, feed rate and drilling depth were considered as machining parameters. L9 orthogonal array was used for the experiment plan. Results were evaluated using regression analysis and ANOVA.

ACKNOWLEDGMENT

The authors thank TUBITAK for supporting this project (Project No. 107M164).

Notes

4 Homogeneous, not separated, stable emulsion.

3 Near to homogeneous.

2 Partially phase separated, cream at surface.

1 Completely phase separated.

SS: Sum of squares.

MS: Mean square.

DF: Degree of freedom.

SS: Sum of squares.

MS: Mean square.

DF: Degree of freedom.

SS: Sum of squares.

MS: Mean square.

DF: Degree of freedom.

SS: Sum of squares.

MS: Mean square.

DF: Degree of freedom.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 561.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.