Multi-objective optimisation of dry sliding wear control parameters for stir casted AA7075- TiO2 composites using Taguchi-Grey relational approach-Reference-Cited by-同舟云学术

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Multi-objective optimisation of dry sliding wear control parameters for stir casted AA7075- TiO2 composites using Taguchi-Grey relational approach

Published:2020-09-06 Issue: Volume: Page:1-10
ISSN:1448-4846
Container-title:Australian Journal of Mechanical Engineering
language:en
Short-container-title:Australian Journal of Mechanical Engineering

Author:

S.V Alagarsamy¹,M Ravichandran²,M Meignanamoorthy³

Affiliation:

1. Department of Mechanical Engineering, Mahath Amma Institute of Engineering and Technology, Pudukkottai, India

2. Department of Mechanical Engineering, K.Ramakrishnan College of Engineering, Tiruchirappalli, India

3. Department of Mechanical Engineering, Mother Terasa College of Engineering and Technology, Pudukkottai, India

Publisher

Informa UK Limited

Subject

Mechanical Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/14484846.2020.1815997

Reference32 articles.

1. Synthesis, microstructure and properties of TiO2 reinforced AA7075 matrix composites via stir casting route

2. Optimization of friction and wear behaviour of Al–Si 3 N 4 nano composite and Al–Gr–Si 3 N 4 hybrid composite under dry sliding conditions

3. Study of mechanical and tribological behaviour of Al/SiC/ZrO2 hybrid composites fabricated through powder metallurgy technique

4. Optimization of Tribological Performance of Al-6061T6-15% SiCp-15% Al<sub>2</sub>O<sub>3</sub> Hybrid Metal Matrix Composites Using Taguchi Method & Grey Relational Analysis

5. Experimental investigation on mechanical behaviour, modelling and optimization of wear parameters of B4C and graphite reinforced aluminium hybrid composites

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1. Synthesis, mechanical and tribological behaviours of boron nitride reinforced AA7075 composites produced by stir casting technique;Surface Topography: Metrology and Properties;2024-05-31

2. Multi-Objective Optimization of Tribological Characteristics for Aluminum Composite Using Taguchi Grey and TOPSIS Approaches;Lubricants;2024-05-10

3. Optimized deep learning regression assisted wear rate analysis of Cu–AlCoCrCuFe HEA composite;AIP Advances;2024-05-01

4. Insitu synthesis of Al– MgAl2O4 composites and parametric optimization of tribological characteristics;Heliyon;2024-02

5. Current status on manufacturing routes to produce metal matrix composites: State-of-the-art;Heliyon;2023-02

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