Date of Award


Publication Type

Master Thesis


Electrical and Computer Engineering




The gating and riser system design plays an important role in the quality and cost of a metal casting. Due to the lack of existing theoretical procedures to follow, the design process is carried out on a trial-and-error basis. The casting design optimization problem is characterized by multiple design variables, conflicting objectives, and a complex search space, making it unsuitable for sensitivity-based optimization. In this study, a formal optimization method using evolutionary techniques was developed to overcome such complexities. A framework for integrating the optimization procedure with numerical simulation for the design evaluation is presented. The comparison between a scalar and vector optimization approach was explored using the weighted-sum and multi-objective Genetic Algorithm methods. The proposed optimization framework was applied to the gating and riser system of a sand casting and the results were compared to a popular Design-of-Experiment (DOE) method. It showed that the multi-objective method gave better results and provided more flexibility in decision making.