Effect of Cutting Parameters on Surface Roughness in End Milling of AlSi/AlN Metal Matrix Composite

S. H. Tomadi, Jaharah A Ghani, Che Hassan Che Haron, H. Mas Ayu, R. Daud

Research output: Contribution to journalArticle

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Abstract

This paper presents the effects of cutting parameters and the corresponding prediction model on the surface roughness in the machining of AlSi/AlN metal matrix composite (MMC). This new composite material was fabricated by reinforcing smaller sizes of AlN particles at volume fractions of 10%, 15% and 20% with AlSi alloy. The machining experiments involved of uncoated carbide tool and PVD TiAlN coated carbide and conducted at different cutting parameters of cutting speed (240-400m/min), feed rate (0.3-0.5mm/tooth) and depth of cut (0.3-0.5mm) under dry cutting conditions. Taguchi's L18 orthogonal arrays approach was performed to determine the optimum cutting parameters using a signal-to-noise (S/N) ratio according to the stipulation of the smaller-the-better. The test results revealed that the type of cutting tool is the most significant factor contributing to the surface roughness of the machined material. A mathematical model of surface roughness has been developed using regression analysis as a function of all parameters with an average error of 10% can be observed between the predicted and experimental values. Furthermore, the optimum cutting parameters was predicted; A1 (uncoated carbide), B2 (cutting speed: 320m/min), C2 (feed rate: 0.4mm/tooth), D2 (axial depth: 0.4mm) and E1 (10% reinforcement) and validation experiment showed the reliable results.

Original languageEnglish
Pages (from-to)58-69
Number of pages12
JournalProcedia Engineering
Volume184
DOIs
Publication statusPublished - 2017

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Milling (machining)
Surface roughness
Composite materials
Metals
Carbides
Machining
Carbide tools
Physical vapor deposition
Cutting tools
Regression analysis
Volume fraction
Signal to noise ratio
Reinforcement
Experiments
Mathematical models

Keywords

  • AlSi/AlN Metal matrix composite
  • ANOVA
  • mathematical model
  • optimum parameters
  • Taguchi method

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Effect of Cutting Parameters on Surface Roughness in End Milling of AlSi/AlN Metal Matrix Composite. / Tomadi, S. H.; A Ghani, Jaharah; Che Haron, Che Hassan; Ayu, H. Mas; Daud, R.

In: Procedia Engineering, Vol. 184, 2017, p. 58-69.

Research output: Contribution to journalArticle

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abstract = "This paper presents the effects of cutting parameters and the corresponding prediction model on the surface roughness in the machining of AlSi/AlN metal matrix composite (MMC). This new composite material was fabricated by reinforcing smaller sizes of AlN particles at volume fractions of 10{\%}, 15{\%} and 20{\%} with AlSi alloy. The machining experiments involved of uncoated carbide tool and PVD TiAlN coated carbide and conducted at different cutting parameters of cutting speed (240-400m/min), feed rate (0.3-0.5mm/tooth) and depth of cut (0.3-0.5mm) under dry cutting conditions. Taguchi's L18 orthogonal arrays approach was performed to determine the optimum cutting parameters using a signal-to-noise (S/N) ratio according to the stipulation of the smaller-the-better. The test results revealed that the type of cutting tool is the most significant factor contributing to the surface roughness of the machined material. A mathematical model of surface roughness has been developed using regression analysis as a function of all parameters with an average error of 10{\%} can be observed between the predicted and experimental values. Furthermore, the optimum cutting parameters was predicted; A1 (uncoated carbide), B2 (cutting speed: 320m/min), C2 (feed rate: 0.4mm/tooth), D2 (axial depth: 0.4mm) and E1 (10{\%} reinforcement) and validation experiment showed the reliable results.",
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