Multi-Objective Optimization of Bamboo-Filled Plastic Gears in Injection Moulding using Hybrid Optimization

Abstract

The growing demand for lightweight and eco-friendly components has led to increasing interest in replacing conventional metallic and glass-fiber-reinforced gears with sustainable plastic alternatives. However, injection-moulded plastic gears often suffer from poor dimensional stability, shrinkage, and insufficient mechanical strength, limiting their use in high-performance applications. To address these challenges, this research investigates the potential of using bamboo fillers as natural reinforcement in polypropylene-based plastic gears and optimizes the injection moulding process parameters to enhance product quality. A hybrid optimization framework integrating the Taguchi method, Grey Relational Analysis (GRA), and Principal Component Analysis (PCA) was employed to achieve multi-objective optimization targeting minimal shrinkage and maximal tensile strength. The results demonstrated that incorporating bamboo fillers significantly improved mechanical properties while maintaining acceptable processability. Although the inclusion of bamboo filler enhanced dimensional stability and stiffness, it also led to a moderate reduction in tensile strength at higher filler loadings due to weak interfacial bonding, indicating a trade-off between mechanical strength and sustainability benefits. The optimized processing conditions obtained from the hybrid approach yielded superior dimensional accuracy and strength compared to unoptimized settings. Overall, this study establishes bamboo as a promising sustainable filler material and demonstrates the effectiveness of hybrid optimization in improving the performance of injection-moulded plastic gears.