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

Click here for a simple search.
[feed] Atom [feed] RSS 1.0 [feed] RSS 2.0

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

Available under License Creative Commons Attribution Non-commercial No Derivatives.


Official URL: https://doi.org/10.1016/j.proeng.2017.04.071


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
Divisions:Faculty of Mechanical Engineering
ID Code:17711
Deposited By: Noorul Farina Arifin
Deposited On:17 May 2017 13:36
Last Modified:31 Jan 2018 08:12

Repository Staff Only: item control page








An Institutional Repository is an online focus for collecting, preserving, and disseminating any University publication in the digital form for the intellectual sharing.
The UMP Institutional Repository (UMP IR) provides access of University publication such as journal article, conference paper, research paper, thesis and dissertations.

Any Enquiries

Please email or call Knowledge Management staff:-

Pn. Noorul Farina (09-424 5605) OR
Cik Ratna Wilis Haryati (09-424 5612)

Any correspondence concerning this specific repository should be sent to umplibrary@ump.edu.my