Abstract
This study focuses on the optimisation of the injection moulding parameters to maximise the strength ofmoulded parts using a simulation software. The moulded parts were injected with Acrylonitrile- Butadiene-Styrene (ABS) whereas mould temperature, melt temperature, packing pressure and packing time were selected as variable process parameters. The polynomial model obtained using Design of Experiment (DOE) was integrated with the Response Surface Methodology (RSM) and Centre Composite Design (CCD). The RSM was supported with Genetic Algorithm (GA) to anticipate the optimum value of processing parameters with the highest strength. It was found that strength of the parts can be improved 2.2% using the methodology reported herein.
Highlights
Injection moulding is among the most important polymer processing methods to produce plastic parts [1]
Processing parameters such as melt temperature, mould temperature, packing pressure and packing time are the main factors affecting the quality of the plastic parts produced by the injection moulding process [2,3,4,5,6,7]
An efficient optimisation method using Genetic Algorithm (GA) and Response Surface Methodology (RSM) was useed to estimate an optimal solution of injection moulding process in order to maximise the strength on the thick plate part
Summary
Injection moulding is among the most important polymer processing methods to produce plastic parts [1]. Among the defects are warpage, shrinkage, and weld line which influence the cosmetic quality on the surface as well as on the strength of the part. Processing parameters such as melt temperature, mould temperature, packing pressure and packing time are the main factors affecting the quality of the plastic parts produced by the injection moulding process [2,3,4,5,6,7]. The results showed that the proposed method can be applied to optimise the processing parameters in solving the trade-off between consumption of energy (clamping force) and the quality of the product (warpage) produced
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