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dc.contributor.authorS., N. Najihah
dc.contributor.authorShayful Zamree, Abd Rahim
dc.contributor.authorS., M. Nasir
dc.contributor.authorMohd Sazli, Saad
dc.contributor.authorM., M. Rashidi
dc.contributor.authorMohd Fathullah, Ghazli @ Ghazali
dc.contributor.authorNik Noriman, Zulkepli
dc.date.accessioned2020-12-30T01:22:51Z
dc.date.available2020-12-30T01:22:51Z
dc.date.issued2016
dc.identifier.citationMATEC Web Conferences, vol.78, 2016, 12 pagesen_US
dc.identifier.issn2261-236X (online)
dc.identifier.urihttp://dspace.unimap.edu.my:80/xmlui/handle/123456789/69163
dc.descriptionLink to publisher's homepage at https://www.matec-conferences.org/en_US
dc.description.abstractInjection moulding is the most widely used processes in manufacturing plastic products. Since the quality of injection improves plastic parts are mostly influenced by process conditions, the method to determine the optimum process conditions becomes the key to improving the part quality. This paper presents a systematic methodology to analyse the shrinkage of the thick plate part during the injection moulding process. Genetic Algorithm (GA) method was proposed to optimise the process parameters that would result in optimal solutions of optimisation goals. Using the GA, the shrinkage of the thick plate part was improved by 39.1% in parallel direction and 17.21% in the normal direction of melt flow.en_US
dc.language.isoenen_US
dc.publisherEDP Sciencesen_US
dc.relation.ispartofseries2nd International Conference on Green Design and Manufacture 2016 (IConGDM 2016);
dc.subjectInjection mouldingen_US
dc.subjectGenetic Algorithm (GA)en_US
dc.titleAnalysis of shrinkage on thick plate part using genetic algorithmen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1051/matecconf/20167801083
dc.contributor.urlshayfull@unimap.edu.myen_US


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