Siti Haryani, Tomadi and J. A., Ghani and C. H., Che Haron and Mas Ayu, Hassan and Rosdi, Daud (2017) Effect of Cutting Parameters on Surface Roughness in End Milling of AlSi/AlN Metal Matrix Composite. Procedia Engineering, 184. pp. 58-69. ISSN 1877-7058. (Published)
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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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | AlSi/AlN Metal matrix composite; Taguchi method; ANOVA; mathematical model; optimum parameters |
| Subjects: | T Technology > TJ Mechanical engineering and machinery |
| Faculty/Division: | Faculty of Mechanical Engineering |
| Depositing User: | Noorul Farina Arifin |
| Date Deposited: | 17 May 2017 05:36 |
| Last Modified: | 31 Jan 2018 00:12 |
| URI: | http://umpir.ump.edu.my/id/eprint/17711 |
| Download Statistic: | View Download Statistics |
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