Investigation of the surface roughness of rocks sawn by diamond sawblades


AYDIN G., KARAKURT İ., AYDINER K.

INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES, vol.61, pp.171-182, 2013 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 61
  • Publication Date: 2013
  • Doi Number: 10.1016/j.ijrmms.2013.03.002
  • Journal Name: INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.171-182
  • Keywords: Diamond sawblades, Rock, Surface roughness, Statistical analysis, WEAR, STONE, TOOLS, PERFORMANCE, MODEL
  • Karadeniz Technical University Affiliated: Yes

Abstract

Surface roughness (SR) is a measure of the technological quality of a product and a factor that greatly influences manufacturing costs. The current study presents an experimental study on the SR of granitic rocks sawn by the diamond sawblades. Effects of the operating variables on the SR are determined and the SR is correlated with the rock properties. Morphologies of the wearing surfaces of rocks and the roughness profiles of the measurements are also investigated. Moreover, models are developed depending on both the operating variables and the rock properties for the estimation of the SR. Results show that the SR increases with the increase of the peripheral speed, the traverse speed, and the cutting depth, while it decreases with the increase of the flow rate of cooling fluid. The peripheral speed and the traverse speed are determined as the significant operating variables affecting the SR. Additionally, rather than the mechanical properties of the rock, the mineralogical properties are determined as mainly responsible for the SR. Among the mineralogical properties, mean grain size of rock is ranked first in governing the SR. The chipping craters, scratching grooves and fractures on the rock surface are determined as the characteristics of the diamond sawblade cutting. Furthermore, the modeling results reveal that the developed models have high potential for the estimation of the SR. (C) 2013 Elsevier Ltd. All rights reserved.