A theoretical assessment of surface defect machining and hot machining of nanocrystalline silicon carbide

Saurav Goel, Waleed Bin Rashid, Xichun Luo, Anupam Agrawal, V. K. Jain

Research output: Contribution to journalArticle

23 Citations (Scopus)

Abstract

In this paper, a newly proposed machining method named "surface defect machining" (SDM) was explored for machining of nanocrystalline beta silicon carbide (3C-SiC) at 300 K using MD simulation. The results were compared with isothermal high temperature machining at 1200 K under the same machining parameters, emulating ductile mode micro laser assisted machining (μ-LAM) and with conventional cutting at 300 K. In the SDM simulation, surface defects were generated on the top of the (010) surface of the 3C-SiC work piece prior to cutting, and the workpiece was then cut along the ⟨100⟩ direction using a single point diamond cutting tool at a cutting speed of 10 m/s. Cutting forces, subsurface deformation layer depth, temperature in the shear zone, shear plane angle and friction coefficient were used to characterize the response of the workpiece. Simulation results showed that SDM provides a unique advantage of decreased shear plane angle which eases the shearing action. This in turn causes an increased value of average coefficient of friction in contrast to the isothermal cutting (carried at 1200 K) and normal cutting (carried at 300 K). The increase of friction coefficient, however, was found to aid the cutting action of the tool due to an intermittent dropping in the cutting forces, lowering stresses on the cutting tool and reduced operational temperature. Analysis shows that the introduction of surface defects prior to conventional machining can be a viable choice for machining a wide range of ceramics, hard steels and composites compared to hot machining.
LanguageEnglish
Article number021015
Number of pages12
JournalJournal of Manufacturing Science and Engineering
Volume136
Issue number2
DOIs
Publication statusPublished - 10 Feb 2014

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Nanocrystalline silicon
Surface defects
Silicon carbide
Machining
Friction
Diamond cutting tools
Cutting tools
Laser modes
Shearing
Temperature

Keywords

  • surface defect machining
  • MD simulation
  • nanometric cutting
  • beta silicon carbide

Cite this

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abstract = "In this paper, a newly proposed machining method named {"}surface defect machining{"} (SDM) was explored for machining of nanocrystalline beta silicon carbide (3C-SiC) at 300 K using MD simulation. The results were compared with isothermal high temperature machining at 1200 K under the same machining parameters, emulating ductile mode micro laser assisted machining (μ-LAM) and with conventional cutting at 300 K. In the SDM simulation, surface defects were generated on the top of the (010) surface of the 3C-SiC work piece prior to cutting, and the workpiece was then cut along the ⟨100⟩ direction using a single point diamond cutting tool at a cutting speed of 10 m/s. Cutting forces, subsurface deformation layer depth, temperature in the shear zone, shear plane angle and friction coefficient were used to characterize the response of the workpiece. Simulation results showed that SDM provides a unique advantage of decreased shear plane angle which eases the shearing action. This in turn causes an increased value of average coefficient of friction in contrast to the isothermal cutting (carried at 1200 K) and normal cutting (carried at 300 K). The increase of friction coefficient, however, was found to aid the cutting action of the tool due to an intermittent dropping in the cutting forces, lowering stresses on the cutting tool and reduced operational temperature. Analysis shows that the introduction of surface defects prior to conventional machining can be a viable choice for machining a wide range of ceramics, hard steels and composites compared to hot machining.",
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A theoretical assessment of surface defect machining and hot machining of nanocrystalline silicon carbide. / Goel, Saurav; Bin Rashid, Waleed; Luo, Xichun; Agrawal, Anupam; Jain, V. K. .

In: Journal of Manufacturing Science and Engineering, Vol. 136, No. 2, 021015, 10.02.2014.

Research output: Contribution to journalArticle

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