Comparative study of the performance of coated and uncoated silicon nitride (Si3N4) ceramics when machining EN-GJL-250 cast iron using the RSM method and 2D and 3D roughness functional parameters

  • A. LaouissiEmail author
  • M. A. Yallese
  • A. Belbah
  • A. Khellaf
  • A. Haddad
Technical Paper


This paper presents a comparative study of both the surface roughness (Ra and Rz) and the tangential cutting force (Fz) achieved during the machining of EN-GJL-250 cast iron by uncoated and coated silicon nitride ceramics (Si3N4). Experimental tests were planned according to a L27 Taguchi design. Both the surfaces of response (RSM) and analysis of variance (ANOVA) methods were applied to determine and classify the cutting parameters affecting the surface roughness and cutting forces and for deriving the mathematical models to be used in the optimization stage when implementing the desirability function. Moreover, in order to localize the surface defects in the machined profiles, 2D and 3D topographic analysis based on the Abbott–Firestone curve was employed. The results obtained show that the surface roughness is largely influenced by both the feed rate and the cutting speed, while the depth of cut is the factor that most influenced the cutting force followed by the feed rate. Furthermore, the coated ceramic tool demonstrates a better surface quality and lower cutting force than those obtained by uncoated ceramic. The 3D topographic analysis indicates the generated surfaces as constituted by numerous interrupted ridges. The wear tests show that the CC1690 ceramics are more efficient than the CC6090 ceramics in terms of cutting force, surface roughness and wear resistance.


ANOVA Surface roughness Cutting force 3D topography Ceramic tools Optimization 

List of symbols


Cutting speed (m/min)


Depth of cut (mm)


Feed rate (mm/rev)


Tangential cutting force (N)


Response surface methodology


Rockwell hardness


Analysis of variance


The sum of square


Mean of squares sum


Degrees of freedom


Objective function

Cont. %

Contribution ratio (%)


Coefficient of determination (%)


Arithmetic mean roughness (μm)


Mean roughness depth (μm)


Core roughness depth (μm)


Reduced peak height (μm)


Reduced valley depth (μm)


Material volume above the upper core surface (%)


Void volume under the lower core surface (%)


Core roughness depth of the surface (µm)


Reduced peak height of the surface (µm)


Reduced valley depth of the surface (µm)


Material portion level that separates the high peaks from the surface roughness (%)


Material portion level that separates the deepest valleys from the surface roughness (%)


Flank wear (µm)


Peak material volume (ml/m2)


Core material volume (ml/m2)



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Copyright information

© The Brazilian Society of Mechanical Sciences and Engineering 2019

Authors and Affiliations

  1. 1.Département de Génie Mécanique, Laboratoire de Mécanique Appliquée des Nouveaux Matériaux (LMANM)Université 8 Mai 1945GuelmaAlgeria
  2. 2.Département de Génie Mécanique, Laboratoire Mécanique et Structure (LMS)Université 8 Mai 1945GuelmaAlgeria

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