Optimization of age hardening behaviour of AA2024 hybrid composite reinforced with red mud and fly ash through RSM

Abstract

Hybrid AA2024 Metal Matrix composite find explicit application, so important factors like Hardness, lightweight is considered and hybrid composite was synthesized by stir casting route. In this investigation, the effects of age hardening on Hardness of AA2024 reinforced with industrial wastes is measured by using a Vickers hardness test and the influence of different process parameters are studied using Design Expert. A Response Surface Methodology is an effective technique used to observe the impact of age hardening parameters and their interconnection on surface hardness of the prepared hybrid AA2024 composite. A mathematical model was created to optimize the weight percentage of reinforcement and artificial ageing process parameters for maximum Hardness. Adequacy and lack of fit of the developed model were checked using the Analysis of variance Technique. Hardness is taken as the response and optimum parameters are obtained by using the quadratic model. Based on the results, it can be perceived that the weight percentage of Red mud, ageing temperature and ageing time has shown a notable effect on the response. For a specifically optimized parameter, the hardness is improved and it was observed that ageing temperature is the most influencing factor based on the RSM. The optimized parameters for the desired response are Ageing Temperature is 198.87ᵒC, Ageing time is 6.82884 hours, and Red mud wt % is 4.2865 respectively. A confirmation test is carried out with the optimized parameters experimentally and its error is less than the 5 % which shows good results with RSM. Surface morphological studies are carried for the optimized Age Hardened hybrid composite and it showed the uniform distribution of reinforcements in the matrix. Because of the increased hardness, these hybrid composite would perceive real time applications like Orthopaedic braces, aircraft structures and manufacturing crew machine products.