dc.contributor.author | S., N. Najihah | |
dc.contributor.author | Shayful Zamree, Abd Rahim | |
dc.contributor.author | S., M. Nasir | |
dc.contributor.author | Mohd Sazli, Saad | |
dc.contributor.author | M., M. Rashidi | |
dc.contributor.author | Mohd Fathullah, Ghazli @ Ghazali | |
dc.contributor.author | Nik Noriman, Zulkepli | |
dc.date.accessioned | 2020-12-30T01:22:51Z | |
dc.date.available | 2020-12-30T01:22:51Z | |
dc.date.issued | 2016 | |
dc.identifier.citation | MATEC Web Conferences, vol.78, 2016, 12 pages | en_US |
dc.identifier.issn | 2261-236X (online) | |
dc.identifier.uri | http://dspace.unimap.edu.my:80/xmlui/handle/123456789/69163 | |
dc.description | Link to publisher's homepage at https://www.matec-conferences.org/ | en_US |
dc.description.abstract | Injection 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.iso | en | en_US |
dc.publisher | EDP Sciences | en_US |
dc.relation.ispartofseries | 2nd International Conference on Green Design and Manufacture 2016 (IConGDM 2016); | |
dc.subject | Injection moulding | en_US |
dc.subject | Genetic Algorithm (GA) | en_US |
dc.title | Analysis of shrinkage on thick plate part using genetic algorithm | en_US |
dc.type | Article | en_US |
dc.identifier.doi | https://doi.org/10.1051/matecconf/20167801083 | |
dc.contributor.url | shayfull@unimap.edu.my | en_US |