Analysis of Strength on Thick Plate Part using Genetic Algorithm Optimisation Method
1 School of Manufacturing Engineering, Universiti Malaysia Perlis, Kampus Tetap Pauh Putra, 02600 Arau, Perlis, Malaysia
2 Green Design and Manufacture Research Group, Center of Excellence Geopolymer and Green Technology (CEGeoGTech), Universiti Malaysia Perlis, 01000 Kangar, Perlis, Malaysia
3 Centre For Diploma Studies, Universiti Malaysia Perlis, Malaysia
4 Faculty of Mechanical Engineering, Universiti Malaysia Pahang, 26600 Pekan, Pahang, Malaysia
* Corresponding author: firstname.lastname@example.org
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.
© The Authors, published by EDP Sciences, 2016
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