Multi-response optimization of reinforcement parameters of aluminum alloy composites by Taguchi method and grey relational analysis.

The present work describes the optimization of reinforcement parameters for hardness, thermal conductivity, and coefficient of thermal expansion while developing LM6 alloy/soda-lime glass particulate composite through Taguchi-based Grey Relational Analysis (GRA). Soda-lime glass particle weight % (1.5, 3.0 and 4.5 %), particle size (100, 150 and 300 μm) and pre-heat temperature (260, 380 and 500C) are varied accordingly to explore the effect of reinforcement parameters on LM6 alloy/soda-lime glass composite properties. Composites are developed through stir casting based on the L9 Taguchi orthogonal array approach. The properties such as hardness, thermal conductivity and oefficient of thermal expansion of developed composites are assessed. Signal to Noise Ratios (S/N ratios) are calculated and used for the optimization of parameters. GRA is employed for multi-response optimization to find the levels of parameters that affect the desirable properties of the composite. Thus, the reinforcement parameters are optimized for attaining the combined objectives of higher hardness, higher thermal conductivity and lower oefficient of thermal expansion values considered in this investigation. The analysis shows that 4.5 wt %, particle size of 200 μm and pre-heat temperature of 380C are optimal parameter levels. A confirmation test is carried out with the optimal parameter levels and the GRG value of 0.7778 is obtained. The GRG with the initial parameter settings is 0.4711, and the improvement of GRG is found to be 65.1 %. ANOVA is performed on GRG to find out significant parameters and the contribution of each parameter is identified. The wt.% of soda-lime glass is the most significant parameter and its contribution is 92.6 %.