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 language | English |
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Pages (from-to) | 58-69 |
Number of pages | 12 |
Journal | Procedia Engineering |
Volume | 184 |
DOIs | |
Publication status | Published - 2017 |
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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 journal › Article
}
TY - JOUR
T1 - Effect of Cutting Parameters on Surface Roughness in End Milling of AlSi/AlN Metal Matrix Composite
AU - Tomadi, S. H.
AU - A Ghani, Jaharah
AU - Che Haron, Che Hassan
AU - Ayu, H. Mas
AU - Daud, R.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
KW - AlSi/AlN Metal matrix composite
KW - ANOVA
KW - mathematical model
KW - optimum parameters
KW - Taguchi method
UR - http://www.scopus.com/inward/record.url?scp=85019692181&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85019692181&partnerID=8YFLogxK
U2 - 10.1016/j.proeng.2017.04.071
DO - 10.1016/j.proeng.2017.04.071
M3 - Article
AN - SCOPUS:85019692181
VL - 184
SP - 58
EP - 69
JO - Procedia Engineering
JF - Procedia Engineering
SN - 1877-7058
ER -