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AI approaches: Recent studies on shrinkage optimisation in injection moulding process
In producing plastic products, injection moulding was well known for its manufacturing process. The quality of the plastic product depends on a certain processing parameter, and defects may occur when the processing parameters are wrongly set up. The purpose of this paper is to review the techniques...
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Main Authors: | , , , |
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Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Get full text |
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Summary: | In producing plastic products, injection moulding was well known for its manufacturing process. The quality of the plastic product depends on a certain processing parameter, and defects may occur when the processing parameters are wrongly set up. The purpose of this paper is to review the techniques related to the optimisation in injection moulding process of the shrinkage defect. One of the two categories of optimisation approach are non-classical approach (Artificial Intelligence (AI) techniques) is reviewed by focusing on the shrinkage defects in optimising the injection moulding process from year 2012 until year 2016 (2017 instead). The result of review indicates that Artificial Neural Network (ANN) categorized as non-classical approach AI approach is considered as the most used by researchers for optimisation process besides shows good performance for optimisation of the injection moulding process. |
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ISSN: | 0094-243X 1551-7616 |
DOI: | 10.1063/1.5066793 |