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.
Tomadi, S. H., Ghani, J. A., Haron, C. H. C., Ayu, H. M., & Daud, R. (2017). Effect of Cutting Parameters on Surface Roughness in End Milling of AlSi/AlN Metal Matrix Composite. In Procedia Engineering (Vol. 184, pp. 58–69). Elsevier Ltd. https://doi.org/10.1016/j.proeng.2017.04.071