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: Hatta, N. M., Zain, A. M., Shayfull, Z., Sallehuddin, R.
Format: Conference Proceeding
Language:English
Subjects:
Artificial intelligence
Artificial neural networks
Defects
Injection molding
Optimization
Process parameters
Rapid prototyping
Shrinkage
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Zain, A. M.
Shayfull, Z.
Sallehuddin, R.
description 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.
doi_str_mv 10.1063/1.5066793
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subjects Artificial intelligence
Artificial neural networks
Defects
Injection molding
Optimization
Process parameters
Rapid prototyping
Shrinkage
title AI approaches: Recent studies on shrinkage optimisation in injection moulding process
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