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Machining parameter optimisation of an aluminium hybrid metal matrix composite by statistical modelling

Publication Type : Journal Article

Publisher : Journal of Industrial Lubrication and Tribology

Source : Journal of Industrial Lubrication and Tribology, Volume 65, Number 6, p.425-435 (2013)

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Keywords : Alumina, Aluminum, Aluminum alloys, Analysis of variance (ANOVA), Atmospheric temperature, Cutting, Design, Design and Development, Design/methodology/approach, Hybrid metal matrix composites, Machinery, Machining centers, Machining parameter optimisation, Mass scale productions, Mechanical properties, Metallic matrix composites, Metals, Optimization, Quality characteristic, Reinforcement, Surface properties, Surface properties of materials, Surface roughness, Taguchi parameter design, Tensile strength

Campus : Coimbatore

School : School of Engineering

Department : Mechanical Engineering

Verified : Yes

Year : 2013

Abstract : pPurpose - The objective of this research is focused on the design of a new hybrid composite as well as to analyse the optimum turning conditions to minimise the surface roughness and work piece surface temperature, thereby increasing the productivity. Design/methodology/approach - Mechanical properties such as hardness and tensile strength of Al-Si10Mg alloy reinforced with 3, 6 and 9?wt.% of alumina along with 3?wt.% of graphite prepared by stir casting method have been evaluated. The present study addresses the machinability parameter optimisation of Al alloy-9 per cent alumina-3 per centgraphite. Experiments were conducted based on the Taguchi parameter design by varying the feed (0.1, 0.15 and 0.2?mm/rev), cutting speed (200, 250 and 300?m/min) and depth of cut (0.5, 1.0 and 1.5?mm). The results were then analysed using analysis of variance (ANOVA). Findings - Mechanical properties of the hybrid composite increases with reinforcement content. The surface roughness decreases with increasing cutting speed and conversely increases with increasing feed and depth of cut. The work piece surface temperature increases as cutting speed, feed and depth of cut increases. The ANOVA result reveals that feed plays a major role in minimising both surface roughness and surface temperature of work piece. The cutting speed and depth of cut follow feed in the order of importance, respectively. Research limitations/implications - The vibration of the machine tool is a factor which may contribute to poor quality characteristics. This factor has not taken been into account in this analysis since major vibrations in the machine are induced due to the machining process. Practical implications - Design and development of new hybrid metal matrix composites (HMMCs) with a detailed analysis on machining conditions. The findings could help in the production of composite with a higher degree of surface finish. This will enable the adoption of HMMCs as industrial product for mass scale production. Originality/value - Good quality characteristics were achieved using optimum machining conditions arrived using a statistical modelling. Copyright © 2013 Emerald Group Publishing Limited. All rights reserved./p

Cite this Research Publication : Dr. Radhika N, Subramaniam, Rb, and Senapathi, S. Ba, “Machining parameter optimisation of an aluminium hybrid metal matrix composite by statistical modelling”, Journal of Industrial Lubrication and Tribology, vol. 65, pp. 425-435, 2013.

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