Tribological Behavior of AA7075 Reinforced with Ag and ZrO2 Composites

Author:

Mahesha C. R.1,R Suprabha1,Sree Jayan M. Mahaveer2,Kulkarni Shilpa3,Sharma Aman4,Al-Ammar Essam A.5,Mohammed S. M. A. K.6,Subbiah Ram7,Alemayehu Agonafir8ORCID

Affiliation:

1. Department of Industrial Engineering & Management, Dr. Ambedkar Institute of Technology, Bangalore 560056, Karnataka, India

2. Department of Mathematics, Indra Ganesan College of Engineering, Tiruchirapalli 620012, Tamil Nadu, India

3. Department of Physics, Shri Ramdeobaba College of Engineering and Management, Nagpur 440013, Maharashtra, India

4. Department of Mechanical Engineering, GLA University, Mathura, UP 281406, India

5. Department of Electrical Engineering, College of Engineering, King Saud University, 800 Riyadh 11421, Saudi Arabia

6. Department of Mechanical and Industrial Engineering, Ryerson University, Toronto M5B 2K3, ON, Canada

7. Department of Mechanical Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, Telangana 500090, India

8. Department of Mechanical Engineering, Mizan Tepi University, Mizan Teferi, Ethiopia

Abstract

In this study, an AA7075 composite material with a varying weight percentage of silver and zirconium oxide reinforcement is examined in terms of its properties. Reinforcement quantities ranging from 0, 4, 8, 12, and 16 wt % were combined with the matrix using the in-situ technique of stir casting in the field. Tensile, mechanical hardness, and compressive strength were assessed in accordance with the standard. The X-ray diffraction and EDS were utilized to analyze AA7075 composites for the distribution and dispersion of particles. Different input parameters such as load (N), composites (wt %), and velocity (m/s) were used to evaluate wear resistance when using the pin-on-disc method. The wear rate (mm/m) was estimated for every weight percent of reinforced mass loss (g). Optimization methods such as Taguchi and analysis of variance were used to determine the AA7075’s optimal processing parameters and composites that were the most significant. In order to identify the best genetic algorithm results, theoretical and experimental results were evaluated.

Funder

King Saud University

Publisher

Hindawi Limited

Subject

General Engineering,General Materials Science

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