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    Analysis of shrinkage on thick plate part using genetic algorithm

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    Abstract,Acknowledgement.pdf (171.2Kb)
    Introduction.pdf (70.86Kb)
    Literature Review.pdf (1.331Mb)
    Methodology.pdf (410.5Kb)
    Results and Discussion.pdf (1.054Mb)
    Conclusion and Recommendation.pdf (120.8Kb)
    Refference and Appendics.pdf (774.0Kb)
    Date
    2016-05
    Author
    Siti Noor Najihah, Mohd Nasir
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    Abstract
    Injection moulding process has been widely used to produce plastic products with various shapes for high productivity and high volume products with low cost. However there are several defect which can influence the quality of the moulded part. The most common defect is shrinkage. Shrinkage causing contractions on moulded part. It is very difficult to eliminate the shrinkage problem perfectly but it can be reduced. To overcome this problem, Genetic Algorithm (GA) is used. Most of researchers use GA method to find the shrinkage especially for thin part but hardly to found researches that use GA method for optimising a thick plate part. A thick plate part different with the thin plate part not only the thickness but also the weight of the part. This study aims to determine the appropriate injection moulding parameters by simulation of Autodesk Moldflow Insight 2012 for experimental works, determine the significant parameters that affected the shrinkage of the thick plate part in the injection moulding process and determining an optimum shrinkage on the thick plate parts by using GA method. This study is involving simulation, optimisation and experimental work. Using GA, the shrinkage value of thick plate part in parallel direction is improved by 39.1% and the shrinkage in normal direction is improved by 17.2% through simulation. Meanwhile, the shrinkage value in both parallel and normal direction is improved by 7.1% and 13.1%, respectively through experimental. Validation conducted gives the shrinkage in both parallel and normal direction improved by 8.4% and 18.5% through simulation and the shrinkage in both parallel and normal direction improved by 14.5% and 7% through experimental.
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    http://dspace.unimap.edu.my:80/xmlui/handle/123456789/69910
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