Multi-objective optimization in turning of Al 7075-SiC composites using desirability analysis. (2022)

• Record Type: Journal Article
• Authors: Rao, Sadineni Rama; Mandava, Ravi Kumar; Rao, Veeravalli Rama Koteswara
• Is Part Of: Materials today. Volume 56:Part 3(2022)
• Page Start: 1281
• Page End: 1289
• Publication Date: 2022
• Subjects: Al 7075 alloy -- Desirability analysis -- Material removal rate -- SiC -- Surface roughness; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2021.11.256
• Languages: English
• ISSNs: 2214-7853

Abstract

Highlights: Cutting speed and depth of cut are the significant variables that effect both on MRR and SR in turning of the Al7075-SiC composites. With the addition of SiC ceramic particles to aluminium the MRR of the composites decreases and SR increases. Regression models for MRR and SR are developed and validated by ANOVA results. Multi-objective optimization is done with the help of desirability function analysis. The developed models are validated by a confirmation experiment and the maximum error between the predicted and observed data is 3.2%. Abstract: Al 7075 has potential applications in space, aircraft, marine, and automobile industries. So, the strength and wear resistance of the Al 7075 should be improved. Moreover, the strength and wear resistance can be improved by adding various ceramic particles, which are known as composites. Therefore, in the current research work, the reinforcements silicon carbide (SiC) ceramic particles with different wt.% (2, 4, and 6) are added with the matrix Al7075. Later, the mechanical properties like tensile strength and hardness of the fabricated composites are investigated. In addition to, the machinability (turning) characteristics of the fabricated Al7075-SiC composites are examined. Further, the response surface-based desirability function analysis is used to optimize the multi-objective like surface roughness (SR) and material removal rate (MRR). The results presented that the cutting speed and depth of cut contribute to maximizing the MRR and minimizing the SR of the developed composite. The optimal parameters for obtaining minimum SR and maximum MRR are cutting speed = 1500 RPM, feed = 0.15 mm/min depth of cut = 0.8 mm, and percentage of reinforcement = 3.24 wt%. Finally, regression models are developed and validated by confirmation experiments.