Design and Optimization of the Injection Molding Process of Glass Fiber Reinforced Polymeric Car Fender Using Computational Simulation

The increasing demand for lightweight and energy-efficient materials in the automotive industry has accelerated the adoption of fiber-reinforced polymer composites. This research presents the design and optimization of the injection molding process for glass fiber-reinforced polymer (GFRP) car fenders using computational simulation. The effects of various gate types and locations on key process parameters, including fiber orientation, volumetric shrinkage, shear rate, and fill time, were investigated using Finite Element Analysis (FEA), Autodesk Moldflow Insight 2024, and MATLAB-based Multi-Criteria Decision-Making (MCMD) techniques. Simulations were conducted across multiple configurations involving three, four, and five gates, with several variations in location. Among all, the four-gate configuration at Location 2 exhibited the most optimal performance. This location demonstrated the lowest shrinkage, stable and consistent fiber orientation, and a manageable shear rate, indicating superior dimensional accuracy and process stability. Fiber orientation was predicted using the Folgar-Tucker model, and the Tsai-Wu criterion was implemented to assess stress distribution without directly estimating mechanical strength. The results determine the crucial role of gate placement in influencing material behavior during molding and reducing common flaws. A simulation-driven method for optimizing injection molding settings is presented in this paper, enabling increased production efficiency, reduced trial-and-error, and improved quality control. The study presents a valuable approach for enhancing the production of GFRP car components by integrating process simulation and decision-making frameworks. These findings can inform future mold design strategies in the automotive sector, leading to improved quality control, reduced trial-and-error processes, and enhanced production efficiency.