Title: Tribological behaviour of Al6061/Gr/WC hybrid MMCs using multi-response optimisation

Authors: Gangadhara Rao Ponugoti; Ravi Kumar Mandava; Pandu Ranga Vundavilli

Addresses: Department of Mechanical Engineering, ACET, Kakinada, 533437, India ' Department of Mechanical Engineering, MANIT Bhopal, Bhopal, 462003, India ' School of Mechanical Sciences, IIT Bhubaneswar, Bhubaneswar, 752050, India

Abstract: The current investigation is motivated to examine the improvement in mechanical properties and tribological behaviour of Al6061/Gr/WC. Initially, the mechanical and tribological properties were evaluated after adding the reinforcement that is, graphite (Gr) at 3, 6, 9 and 12 wt.% compositions. Therefore, 9 wt.% of Gr generated superior properties than others. Consequently, the hybrid composites were fabricated by reinforcing tungsten carbide (WC) at 1, 2, 3 wt.% and Gr at 9 wt.%. Successful fabrication of the hybrid composites was confirmed through SEM examinations for microstructural characterisation. Further, the concept of design of experiments (DOEs) has been used to obtain the number of experiments. Later on, two nature inspired optimisation algorithm that invasive weed optimisation (IWO) and particle swarm optimisation (PSO) were implemented to determine the optimal wear properties and the results were compared with grey relational analysis (GRA) approach.

Keywords: wear loss; coefficient of friction; COF; invasive weed optimisation; IWO; particle swarm optimisation; PSO; grey relational analysis; GRA.

DOI: 10.1504/IJMMNO.2023.129930

International Journal of Mathematical Modelling and Numerical Optimisation, 2023 Vol.13 No.2, pp.123 - 146

Received: 29 Apr 2022
Accepted: 23 Jul 2022
Published online: 03 Apr 2023 *

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