Analysis of Shrinkage on Thick Plate Part using Genetic Algorithm

Najihah, S.N.; Shayfull, Z.; Nasir, S. M.; Saad, Mohd Sazli; Rashidi, M. M.; Fathullah, M.; Noriman, N. Z.

doi:10.1051/matecconf/20167801083

Cited by 42 publications

(5 citation statements)

References 17 publications

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“…The shrinkage on the thick plate part was minimised at 14.41% for the normal direction and 42.48% for the parallel direction. Besides, Najihah et al [30] also do the same experiment as previous literature with the same material but an addition of optimisation method known as Genetic Algorithm (GA) and the RSM. The shrinkage at the thick plate part was improved.…”

Section: Optimization Of the Injection Molding Process By Response Surface Methodology (Rsm)mentioning

confidence: 99%

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Overview of the Injection Moulding Optimisation for Shrinkage Defect

et al. 2018

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The injection moulding process in manufacturing plastic material has become a worldwide used for more than 100 years. The used can be seen everywhere instead of became a daily used product. The complexity of the process makes it difficult to handle but the big production makes it possible to happen. The entire process not just involve the difficult cycling process, but the involvement of the materials which pertaining many types of characteristic which considered to. Every big production need a quality production product with suitable cost and time efficiency. Eventhough, alongside the process, many defects can be detected by the physically seen marks. Many people especially from the expert’s field are trying to minimise as much as they can to reduce the defects so that the residual cost can be minimise. One of the way to overcome the problems is by simulation before the real product is being produce. The simulation is made by two classes of types which classical and non-classical method. Either both of the method gave good result but it still not reaches a perfect solution. In this study, the optimisation method of non-classical and classical are used to minimise the shrinkage defects at the thick plate part.

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Section: Optimization Of the Injection Molding Process By Response Surface Methodology (Rsm)mentioning

confidence: 99%

“…Lastly, Najihah et al, [30] use Genetic Algorithm (GA) to reduce the shrinkage at the thick plate part. The plastic material used was ABS, and the parameter used was packing time, packing pressure, melt temperature and mould temperature.…”

Section: A Comparison From the Previous Studymentioning

confidence: 99%

Overview of the Injection Moulding Optimisation for Shrinkage Defect

et al. 2018

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“…The GA agents (which are chromosomes) will be created randomly in the solution space after each variable has been set. In this study, population size, number of generations, crossover probability and mutation probability have been set to 50, 23, 0.40 and 0.01 respectively [ 25 ]. Furthermore, the bit number for each variable has been set.…”

Section: Genetic Algorithmmentioning

confidence: 99%

“…The fitness of chromosomes was a criterion for chromosomes selection. The best chromosomes would be able to survive and generate new generation as mentioned in the Darwin Theory [ 25 , 26 ].…”

Section: Genetic Algorithmmentioning

confidence: 99%

Warpage Optimisation on the Moulded Part with Straight Drilled and Conformal Cooling Channels Using Response Surface Methodology (RSM), Glowworm Swarm Optimisation (GSO) and Genetic Algorithm (GA) Optimisation Approaches

et al. 2021

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It is quite challenging to control both quality and productivity of products produced using injection molding process. Although many previous researchers have used different types of optimisation approaches to obtain the best configuration of parameters setting to control the quality of the molded part, optimisation approaches in maximising the performance of cooling channels to enhance the process productivity by decreasing the mould cycle time remain lacking. In this study, optimisation approaches namely Response Surface Methodology (RSM), Genetic Algorithm (GA) and Glowworm Swarm Optimisation (GSO) were employed on front panel housing moulded using Acrylonitrile Butadiene Styrene (ABS). Each optimisation method was analysed for both straight drilled and Milled Groove Square Shape (MGSS) conformal cooling channel moulds. Results from experimental works showed that, the performance of MGSS conformal cooling channels could be enhanced by employing the optimisation approach. Therefore, this research provides useful scientific knowledge and an alternative solution for the plastic injection moulding industry to improve the quality of moulded parts in terms of deformation using the proposed optimisation approaches in the used of conformal cooling channels mould.

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“…At the same time, we expanded the possibilities of calculating the shrinkage of a plastic product, which distinguishes our work from research [13], [14]. But we also took into account the main parameters of the effect on shrinkage, which was considered in [14].…”

Section: To Determine Thementioning

confidence: 99%

Tools for the Production of Plastic Products

Ahmad*,

Mustafa,

Belova

et al. 2019

IJITEE

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The paper discusses the types of system elements of mold parts. The calculation method of design data tooling which can be used at design of injection mold is offered. This method gives the chance to provide the necessary accuracy of casting. Distinctive feature of the offered method is modification of the formalized shrinkage material description of a molding detail. The offered calculation method of design data tooling allows increasing the accuracy of the received plastic product because are considered: absolute and relative volume shrinkage; relative actual linear shrinkage of material; alleged linear shrinkage

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Analysis of Shrinkage on Thick Plate Part using Genetic Algorithm

Cited by 42 publications

References 17 publications

Overview of the Injection Moulding Optimisation for Shrinkage Defect

Overview of the Injection Moulding Optimisation for Shrinkage Defect

Warpage Optimisation on the Moulded Part with Straight Drilled and Conformal Cooling Channels Using Response Surface Methodology (RSM), Glowworm Swarm Optimisation (GSO) and Genetic Algorithm (GA) Optimisation Approaches

Tools for the Production of Plastic Products

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