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Warpage Optimisation Using Recycled Polycar-bonates (PC) on Front Panel Housing
Many studies have been done using recycled waste materials to minimise environmental problems. It is a great opportunity to explore mechanical recycling and the use of recycled and virgin blend as a material to produce new products with minimum defects. In this study, appropriate processing paramete...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7999641/ https://www.ncbi.nlm.nih.gov/pubmed/33804036 http://dx.doi.org/10.3390/ma14061416 |
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author | Tamizi, Nur Aisyah Miza Ahmad Rahim, Shayfull Zamree Abd Abdellah, Abdellah El-hadj Abdullah, Mohd Mustafa Al Bakri Nabiałek, Marcin Wysłocki, Jerzy J. Jeż, Bartłomiej Palutkiewicz, Paweł Rahman, Rozyanty Abdul Saad, Mohd Nasir Mat Ghazli, Mohd Fathullah |
author_facet | Tamizi, Nur Aisyah Miza Ahmad Rahim, Shayfull Zamree Abd Abdellah, Abdellah El-hadj Abdullah, Mohd Mustafa Al Bakri Nabiałek, Marcin Wysłocki, Jerzy J. Jeż, Bartłomiej Palutkiewicz, Paweł Rahman, Rozyanty Abdul Saad, Mohd Nasir Mat Ghazli, Mohd Fathullah |
author_sort | Tamizi, Nur Aisyah Miza Ahmad |
collection | PubMed |
description | Many studies have been done using recycled waste materials to minimise environmental problems. It is a great opportunity to explore mechanical recycling and the use of recycled and virgin blend as a material to produce new products with minimum defects. In this study, appropriate processing parameters were considered to mould the front panel housing part using R0% (virgin), R30% (30% virgin: 70% recycled), R40% (40% virgin: 60% recycled) and R50% (50% virgin: 50% recycled) of Polycarbonate (PC). The manufacturing ability and quality during preliminary stage can be predicted through simulation analysis using Autodesk Moldflow Insight 2012 software. The recommended processing parameters and values of warpage in x and y directions can also be obtained using this software. No value of warpage was obtained from simulation studies for x direction on the front panel housing. Therefore, this study only focused on reducing the warpage in the y direction. Response Surface Methodology (RSM) and Genetic Algorithm (GA) optimisation methods were used to find the optimal processing parameters. As the results, the optimal ratio of recycled PC material was found to be R30%, followed by R40% and R50% materials using RSM and GA methods as compared to the average value of warpage on the moulded part using R0%. The most influential processing parameter that contributed to warpage defect was packing pressure for all materials used in this study. |
format | Online Article Text |
id | pubmed-7999641 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-79996412021-03-28 Warpage Optimisation Using Recycled Polycar-bonates (PC) on Front Panel Housing Tamizi, Nur Aisyah Miza Ahmad Rahim, Shayfull Zamree Abd Abdellah, Abdellah El-hadj Abdullah, Mohd Mustafa Al Bakri Nabiałek, Marcin Wysłocki, Jerzy J. Jeż, Bartłomiej Palutkiewicz, Paweł Rahman, Rozyanty Abdul Saad, Mohd Nasir Mat Ghazli, Mohd Fathullah Materials (Basel) Article Many studies have been done using recycled waste materials to minimise environmental problems. It is a great opportunity to explore mechanical recycling and the use of recycled and virgin blend as a material to produce new products with minimum defects. In this study, appropriate processing parameters were considered to mould the front panel housing part using R0% (virgin), R30% (30% virgin: 70% recycled), R40% (40% virgin: 60% recycled) and R50% (50% virgin: 50% recycled) of Polycarbonate (PC). The manufacturing ability and quality during preliminary stage can be predicted through simulation analysis using Autodesk Moldflow Insight 2012 software. The recommended processing parameters and values of warpage in x and y directions can also be obtained using this software. No value of warpage was obtained from simulation studies for x direction on the front panel housing. Therefore, this study only focused on reducing the warpage in the y direction. Response Surface Methodology (RSM) and Genetic Algorithm (GA) optimisation methods were used to find the optimal processing parameters. As the results, the optimal ratio of recycled PC material was found to be R30%, followed by R40% and R50% materials using RSM and GA methods as compared to the average value of warpage on the moulded part using R0%. The most influential processing parameter that contributed to warpage defect was packing pressure for all materials used in this study. MDPI 2021-03-15 /pmc/articles/PMC7999641/ /pubmed/33804036 http://dx.doi.org/10.3390/ma14061416 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Tamizi, Nur Aisyah Miza Ahmad Rahim, Shayfull Zamree Abd Abdellah, Abdellah El-hadj Abdullah, Mohd Mustafa Al Bakri Nabiałek, Marcin Wysłocki, Jerzy J. Jeż, Bartłomiej Palutkiewicz, Paweł Rahman, Rozyanty Abdul Saad, Mohd Nasir Mat Ghazli, Mohd Fathullah Warpage Optimisation Using Recycled Polycar-bonates (PC) on Front Panel Housing |
title | Warpage Optimisation Using Recycled Polycar-bonates (PC) on Front Panel Housing |
title_full | Warpage Optimisation Using Recycled Polycar-bonates (PC) on Front Panel Housing |
title_fullStr | Warpage Optimisation Using Recycled Polycar-bonates (PC) on Front Panel Housing |
title_full_unstemmed | Warpage Optimisation Using Recycled Polycar-bonates (PC) on Front Panel Housing |
title_short | Warpage Optimisation Using Recycled Polycar-bonates (PC) on Front Panel Housing |
title_sort | warpage optimisation using recycled polycar-bonates (pc) on front panel housing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7999641/ https://www.ncbi.nlm.nih.gov/pubmed/33804036 http://dx.doi.org/10.3390/ma14061416 |
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