Assessment of Aluminum Alloy 6351 Eggshell Reinforced Composite in Dry Turning Using Response Surface Methodology
S. C. Nwoziri
Department of Mechanical Engineering, University of Calabar, Nigeria.
Bethel Mba *
Department of Mechanical Engineering, Michael Okpara University of Agriculture Umudike, Nigeria.
Franklin Onwuka
Department of Mechanical Engineering, Federal University of Nigeria Nsukka, Nigeria.
E. B. Agbonko
Department of Mechanical Engineering, University of Calabar, Nigeria.
Uchenna Alozie
Department of Mechanical Engineering, Federal Polytechnic Nekede, Nigeria.
Clifford Omonini
Department of Mechanical and Aerospace Engineering, Nazarbayev University Astana, Kazakhstan.
G. A Ogban-Ekpe
Department of Mechanical Engineering, University of Calabar, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
Lack of knowledge and comprehension of critical input parameters and material machinability has limited the industry's use of machining, making it challenging to meet requirements for machining responses and numerous other problems. This study uses response surface methods to evaluate Aluminum Alloy 6351 Eggshell Reinforced Composite as a turning machining material. The material removal rate (MRR), cutting force (Fc), and surface roughness (Ra) of the samples were examined. The mass percentage of the composite is 15% egg shell reinforcement and 85% aluminum alloy. Cutting force (Fc), surface roughness (Ra), and material removal rate (MRR) ANOVA tables show that several models have significant probability values (P-values) less than 0.05. Numerical optimization was used to identify combinations of process parameters that will give the best response of cutting force (Fc), surface roughness (Ra), and material removal rate (MRR). The Cutting force (Fc), surface roughness (Ra), and material removal rate (MRR) can all be predicted using the regression equation model that was created. The only input variable that significantly affects the cutting force is cutting speed.
The three-input variable studied has a significant effect on surface roughness (Ra) and material removal rate (MRR).
The optimization result obtained indicates that the optimal response for turning an aluminum alloy 6351 eggshell reinforced composite is 1.39676µm, 101.333N, and 2016.77mm3/min for surface roughness (Ra), cutting force (Fc), and material removal rate (MRR), respectively. This is achieved when the input variables of cutting speed (Vc), feed rate (Fr), and depth of cut (Dc), which are 589.479 rpm, 0.205976 mm/min, and 0.315524 mm, respectively, are used.
Keywords: Numerical optimization, regression equation, material removal rate, surface roughness, cutting force