Multi-objective parametric optimization of Green sand moulding properties using genetic algorithm

Green sand moulding has been practiced for the production of casting over the last several years through the development of different moulding sand tests, control graphs and established correlations between the physical properties and variable factors that influences sand mixture. Although, the past investigations were helpful in identifying the variable factors, the optimum formulation of sand mixture composition is remaining to be a critical problem for the foundry man. In view of its development in the field of green sand moulding technology, experiments have been conducted by varying clay content, moisture content, amount of coal dust and the mulling time. For each sand mixture, the moulding properties such as Green Compression Strength and Permeability were measured. Taguchi Method is used to study the effect of independent variables to develop predictive models. It is desired to obtain optimal process parameters that maximize Green Compressive strength and permeability. It is difficult to obtain a combination of green sand moulding parameters that satisfy both the objectives in a single solution. Therefore, in this paper, it is proposed to explore the optimization technique to generate the set of optimum solutions using multi-objective genetic algorithm over a wide range of moulding parameters.