Özet:

The focus of this study is on the modeling and optimisation of percentage elongation and average deflection using injection moulded high density polyethylene-Sawdust composite. The HDPE material and sawdust were mixed together to form a homogenous mixture with various percentage composition by volume as obtained by the central composite design (CCD). The response surface methodology (RSM) and artificial neural networks (ANN) were used to determine the effect of the interaction of temperature and percentage by volume of material on the mechanical properties of the produced HDPE-sawdust composite. Models were developed for predicting the mechanical properties percentage elongation and average deflection) for the produced composites. The models were validated using coefficient of determination (R2). The coefficient of determination (R2) obtained ranged from 0.9213 (92.13%) to 0.981 (98.10%) which indicates a good fit was achieved between the model and experimental results. The optimization results for HDPE-Sawdust composites shows that the percentage elongation and average deflection were minmized with values of 90.98% and 2.46cm obtained at barrel temperature of 164.64 oC and polymer level of 68.54%.

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