Abstract
The melt blending behaviour of natural fibre-reinforced thermoplastic composites plays a critical role in determining feedstock quality for extrusion-based manufacturing. This study evaluates the influence of screw speed and polyethylene glycol (PEG) loading on the melt flow index (MFI) and mixture blending time (MBT) of polylactic acid composites reinforced with wild almond fibre (WAF) (3-9 wt%) using response surface methodology (RSM). Central composite design (CCD) experiments were conducted to develop quadratic regression models and identify optimal processing conditions. Statistical analysis confirmed strong model significance, indicating high sensitivity of process parameters. The results reveal a transition from plasticizer-dominated viscosity control at low fibre loading to shear-driven dispersion at higher reinforcement levels. Under optimized conditions, MFI values reached approximately 27 g/10 min, while MBT was reduced, indicating improved processability. Numerical optimization showed high desirability, confirming convergence toward balanced processing conditions. The findings demonstrate the effectiveness of response surface modelling in capturing process-structure interactions and provide practical guidance for stable composite feedstock preparation for extrusion-based applications.
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