Machining parameters optimization on the die casting process of magnesium alloy using the grey-based fuzzy algorithm

The present investigation focuses on finding the optimal machining parameters' setting for the die casting process of magnesium alloy using the grey-based fuzzy algorithm. This proposed algorithm, coupling the grey relational analysis with the fuzzy logic, obtains a grey-fuzzy reasoning grade to evaluate the multiple performance characteristics according to the grey relational coefficient of each performance characteristic. One of the real case studies performed in the die casting process, thin-walled cover components of liquid crystal display (LCD) panel, verifies that the proposed optimum procedure is feasible and effective. The casting density, warpage and flow mark of finished product are adopted to evaluate the machiniablity performances. Various die casting parameters, such as the die temperature, the pressure of injection, the plunger velocity (first and second stage) and the filling time are explored in the experiment. The table of orthogonal array is used in the experimental design. The response table, response graph and analysis of variance (ANOVA) are used to find the optimal setting and the influence of machining parameters on the multiple performance characteristics. Under the circumstances of the optimal machining parameters, the confirmation tests indicate the effectiveness of the proposed algorithm. Experimental results have shown that the required performance characteristics in the die casting process have great improvements by using this proposed algorithm.