Hybrid FEM-Taguchi-CBQPSO optimization of A356 sand casting gating to minimize defects

This study presents a novel hybrid simulation-optimization framework to minimize defects in sand castings of aluminum A356 alloy for textile machinery components. The methodology integrates Finite Element Method (FEM) simulations in ProCAST with the Taguchi method and a Chaotic Binary Quantum Particle Swarm Optimization (CBQPSO) algorithm to systematically design the gating system. The Taguchi method efficiently screened initial parameters, which were then optimized globally by the CBQPSO algorithm using FEM-derived defect metrics. A response surface methodology (RSM) model validated the results and provided a predictive tool. Applied to a case study at Bahirdar Textile Foundry, the approach yielded an optimized gating design with a tapered sprue, dual runners, and four ingates. This design achieved substantial improvements: a 68.14% reduction in filling time, a 50.56% decrease in solidification time, and a 20.20% lower oxide ratio. FEM analysis confirmed enhanced thermal balance, superior directional solidification, reduced shrinkage porosity, and more stable flow dynamics. The research demonstrates the efficacy of integrating FEM with intelligent algorithms for multi-objective casting optimization, offering a robust, data-driven pathway for high-integrity castings that contributes to the digital automation and sustainable goals of Industry 4.0 in foundry operations.