Characterization, Prediction, and Optimization of Dry Sliding Wear Behaviour of Al6061/WC Composites
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ORIGINAL ARTICLE
Characterization, Prediction, and Optimization of Dry Sliding Wear Behaviour of Al6061/WC Composites Thella Babu Rao1
•
Gangadhara Rao Ponugoti2
Received: 17 August 2020 / Accepted: 7 October 2020 Ó The Indian Institute of Metals - IIM 2020
Abstract This investigation deals with an experimental analysis done on dry sliding wear behaviour of aluminium matrix composites reinforced with WC (tungsten carbide) particles. The composites were processed through powder metallurgy (P/M) technique with the addition of various fractions of WC particles. Results of scanning electron microscope (SEM) examinations and XRD analysis showed better dispersion of the reinforced particles and good matrix–reinforcement interface integrity. The results of dry sliding wear tests conducted on composite samples were analysed for varied conditions of WC volume fraction and sliding distance. The wear properties of composites were significantly affected by the variation of the WC volume percentage (5–25%). Smother wear tracks and closely spaced grooves on the composite pin worn surfaces were found for higher volume fraction WC particles. The postulated regression models for prediction of wear behaviour approximate their experimental values with an estimated error from 1.97 to 6.56%. The derived optimal wear properties to improve the sliding wear performance of the composites through a novel hybrid (GRA integrated TLBO) multi-response optimization approach are in a
& Thella Babu Rao [email protected] Gangadhara Rao Ponugoti [email protected] 1
Department of Mechanical Engineering, National Institute of Technology Andhra Pradesh, West Godavari Dist., Tadepalligudem, Andhra Pradesh 534 101, India
2
Department of Mechanical Engineering, Aditya College of Engineering & Technology, Surampalem, East Godavari Dist., Andhra Pradesh 533 437, India
closer correlation with the experimentally measured values. Also, wear performance predicted values through hybrid multi-response optimization are closer to their validation experimental results compared with the predicted values through TLBO and GRA approaches. The derived optimal set of wear properties are 1.921 mm3/m wear rate and 0.292 coefficient of friction at 15 vol% of WC, 10 N applied load, 775 m sliding distance, and 1 m/s sliding velocity. The surfaces of the composite samples tested at the derived set of optimal wear behavioural parameters were also examined through SEM and analysed. Keywords Al6061/WC MMCs Scanning electron microscopy Interfacial integrity Wear rate and coefficient of friction Multi-objective optimization Grey relational analysis Teacher–learner-based optimization Hybrid GRA–TLBO approach
1 Introduction Today, the development of advanced materials holding high strength, lightweight, and excellent wear characteristics becomes prominent for high-performance aerospace, automobile and industrial components. The interest in metal matrix composites (MMCs) research is considerably growing in the recent advanced materials research du
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