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    Thick plate part using genetic algorithm methodology

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    Abstract,Acknowledgement.pdf (165.1Kb)
    Introduction.pdf (255.1Kb)
    Literature Review.pdf (1.733Mb)
    Methodology.pdf (635.2Kb)
    Results and Discussion.pdf (524.9Kb)
    Conclusion and Recommendation.pdf (120.7Kb)
    Refference and Appendics.pdf (717.4Kb)
    Date
    2016-06
    Author
    Syed Mohd Azlan, Syed Othman
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    Abstract
    This study focuses on the optimisation of the injection moulding parameters to maximise the strength on the moulded parts produced using Autodesk Moldflow Insight (AMI) 2012. The strength of the moulded parts moulded using Acrylonitrile-Butadiene- Styrene (ABS) has been analysed. Mould temperature, melt temperature, packing pressure and packing time were selected as a set of processing parameter. Design Expert software (V7.0.0) was used as a medium to analyse and optimise the strength on the thick plate part. The polynomial model obtained using Design of Experiment (DOE) was integrated with the Response Surface Methodology (RSM) and Centre Composite Design (CCD) in this study. A predictive RSM was interfaced with an effective Genetic Algorithm (GA) to determine an optimum value of processing parameters with the highest strength. As a result, the strength of the moulded parts has been improved 2.2% after optimisation.
    URI
    http://dspace.unimap.edu.my:80/xmlui/handle/123456789/69922
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    • School of Manufacturing Engineering (FYP) [338]

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