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

• Published in: Industrial lubrication and tribology 2013-01, Vol.65 (6), p.425-435
• Main Authors: Radhika, N., Subramaniam, R., Babudeva senapathi, S.
• Format: Article
• Language: English
• Subjects: Alumina; Aluminum base alloys; Aluminum oxide; Analysis of variance; Composite materials; Cutting parameters; Cutting speed; Design engineering; Design parameters; Design techniques; Engineering; Friction; Graphite; Heat; Hybrid composites; Machinability; Machine tools; Machining; Mathematical models; Mechanical engineering; Mechanical properties; Metal matrix composites; Metals; Modelling; Optimization; Research methodology; Statistical models; Studies; Surface finish; Surface roughness; Surface temperature; Tensile strength; Turning (machining); Variance analysis; Wear resistance; Workpieces
• ISSN: 0036-8792; 1758-5775
• DOI: 10.1108/ILT-01-2011-0008

Purpose – 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.