Parameter Optimization of Sandcasting of Silumin (Aa6061) Using Genetic Algorithm

Abstract

Automobile and engine components are often sand cast during manufacture because of its simplicity in operation. Manufacturing processes and conditions were appropriately carried out by developing a Design of Experiment platform to effect a fair randomization of the various experimental runs. Taguchi Orthogonal array was used to develop a layout for the sand casting experiment. Multiple linear Regression technique was used to develop mathematical models for the 3 responses-fatigue strength, wear rate and hardness. The Weighted Average method was applied in ascribing criteria weights. The single composite objective function generated was inputted into the Genetic algorithm tool box which yielded optimal levels for the four cases adopted.  Case 4 which is the maximum importance for fatigue strength had its optimal conditions to be 749.99^oC, 49.999Hz, 30.01seconds and 265.35mm² for pouring temperature, vibration frequency, vibration time and runner size respectively. Validation test conducted showed that the values obtained from the actual experiment were similar to that yielded by the predictive models.

Keywords: Sand casting , Optimization,  Genetic algorithm and Taguchi design

DOI: 10.7176/IEL/13-1-06

Publication date: April 28^th 2023