Multi response optimization on tribo-mechanical properties of CNTs/nSiC reinforced hybrid Al MMC through RSM approach

Abstract

Aluminum is a strong, lightweight, and wear-resistant material that can be strengthened further by alloying with MWCNTs and nano SiC particles. Various aerospace and automotive applications such as gas turbines, gearboxes, and brake parts require wear-tolerant materials with high strength and hardness. The carbon nanotubes (CNTs) unique mechanical and thermal properties found to be more suitable material for reinforcement. Also, CNTs possess a higher surface area, because of this the agglomeration tendency of the CNTs increases. Due to this agglomeration tendency of CNTs causes the CNTs to uneven distribution in the matrix metal affects the homogenous distribution of hardness and wear properties. Therefore, nSiC was used as a dispersion agent in Al6061 + CNTs composite. Reinforcement% of SiC varied from 0 to 10% and CNTs% of reinforcement was fixed at 1.5%. To find the optimum% of SiC reinforcement, the powder metallurgy and POD process parameters (Load, speed, and% of SiC reinforcement) correlated with the responses wear rate, hardness and surface roughness of the Nanohybrid MMCs. For this reason, a design of experiments is used to optimize the process parameters to achieve the desired objective. The indigenously fabricated hybrid nanocomposites were characterized by scanning electron microscopy equipped with EDS technique to study the wear surface of Nanohybrid MMCs. The optimum parameters were found Load at 2.00 kg, speed 200 rpm, 7.50% of SiC reinforcement results in wear rate of 20.50 µm/g with the hardness of 161.43 HV. Moreover, The L32 orthogonal array & Hierarchical clustering were established to understand and validate the relationship between the process parameters and responses of this investigation.

Keywords

• Carbon nanotubes
• Powder metallurgy
• Ball milling
• Response surface methodology