Performance of assessment model for Injection moulding parameters
In order to manufacture a better quality of plastic product, the best injection moulding parameters have to be identified. Therefore, this research studies the performance of assessment model for injection moulding parameters using Taguchi and ANOVA method. The objective of this research is to ident...
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Main Authors: | , , , , |
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Format: | Conference or Workshop Item |
Language: | English |
Published: |
Springer, Singapore
2022
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Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/35400/1/Faiz2.pdf http://umpir.ump.edu.my/id/eprint/35400/ https://doi.org/10.1007/978-981-19-2890-1_6 https://doi.org/10.1007/978-981-19-2890-1_6 |
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Summary: | In order to manufacture a better quality of plastic product, the best injection moulding parameters have to be identified. Therefore, this research studies the performance of assessment model for injection moulding parameters using Taguchi and ANOVA method. The objective of this research is to identify the best injection moulding parameters in producing plastic pallets in term of compressive strength when subjected to a constant load. Melting temperature, charging speed and holding pressure and polypropylene material were chosen as the parameters to study their effect on compressive strength. According to the results obtained, the melting temperature of 230 °C, charging speed of 93 rpm and holding pressure of 25 MPa were found to be the best combination of injection moulding parameters to fabricate the better performance of plastic pallet which give the maximum ultimate load with 6376.7 kg. Based on the statistical ANOVA analysis results, the most significant parameter affecting the compressive strength of plastic pallet is melting temperature, which is indicated by the percentage contribution of P = 63.67%, followed by holding pressure with 21.79%. Charging speed is the least significant parameter with 2.96%. To conclude that, Taguchi and ANOVA method show that melting temperature is the most significant parameter in order to get the best compressive strength. |
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