Journal of Basic and Applied Research International

The industry's usage of machining has been restricted by a lack of knowledge and understanding about important input parameters and the machinability of materials, which makes it difficult to fulfill the necessary criteria for material removal rate, surface roughness, tool wear, and many other issues. This paper examines the Performance evaluation of Aluminum alloy 356 cow-horn composite as a turning machining material using response surface methodology. A356/cow horn particles (CHp) composite from Ochieze, 2017, was used as a raw material and the composite composition by mass is 90% Aluminum alloy and 10% cow-horn reinforcement. The molten composite was made more wettable by adding 2% weight of magnesium powder. The addition of magnesium powder reduced the interface energy of the matrix reinforcement and raised the composite's surface energy, which in turn decreased its surface tension. The Response Surface Methodology was utilized to create the experiment's design. After optimization, several significant models are shown with a probability value of less than 0.05. The findings of the analyzed result show that the suggested mathematical models obtained from the data can accurately portray the performance within the limitations of the components under discussion. The investigation demonstrates that, as opposed to depth of cut, cutting speed considerably impacts surface roughness and tool wear rate. Ra and TWR are not significantly affected by the depth of cut. Numerical optimization was used to identify combinations of process parameters that will give the best response. Adjusting the feed rate, depth of cut, and cutting speed to 900 rpm, 0.25 rev/mm, and 1.5 mm achieve the optimal composite turning process at a surface roughness of 160.256 mm, material removal rate of 15.4011 mm3/min, and tool wear of 0.000362687 mg/mm respectively.