Optimizing tensile strength of PLA-Lignin Bio-composites using machine learning approaches
It is imperative to accurately estimate the final performance of composite parts during the initial design phase of the manufacturing process. In generating sustainable bio composites with superior mechanical properties such as tensile strength, the combination of fillers and plasticizers, as well a...
Saved in:
Main Authors: | , , , , , , , |
---|---|
Format: | Conference or Workshop Item |
Language: | English English |
Published: |
Springer
2023
|
Subjects: | |
Online Access: | http://irep.iium.edu.my/104852/2/104852_Optimizing%20tensile%20strength.pdf http://irep.iium.edu.my/104852/7/104852_Optimizing%20tensile%20strength_SCOPUS.pdf http://irep.iium.edu.my/104852/ https://link.springer.com/chapter/10.1007/978-981-19-9509-5_58 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Universiti Islam Antarabangsa Malaysia |
Language: | English English |
id |
my.iium.irep.104852 |
---|---|
record_format |
dspace |
spelling |
my.iium.irep.1048522023-07-17T02:04:18Z http://irep.iium.edu.my/104852/ Optimizing tensile strength of PLA-Lignin Bio-composites using machine learning approaches Manshor, Mohd Romainor Kamarulzaman, Amjad Fakhri Anuar, Hazleen Toha @ Tohara, Siti Fauziah Ali, Fathilah Sukindar, Nor Aiman Suhr, Jonghwan Haris, Nursyam Dzuha TS195 Packaging It is imperative to accurately estimate the final performance of composite parts during the initial design phase of the manufacturing process. In generating sustainable bio composites with superior mechanical properties such as tensile strength, the combination of fillers and plasticizers, as well as their concentration in the mixture, are always deemed crucial. In order to reduce the number of experimental runs and their associated costs and timescales, statistical optimization of the core design elements has become increasingly important. The filler and plasticizer concentrations of extruded bio composites were adjusted in this study utilizing both statistical (analysis of variance (ANOVA) and response surface methodology (RSM)) and machine learning (Multilayer Perceptron (MLP)) approaches. Initial ANOVA results indicated that lignin, epoxidized palm oil (EPO), and their respective combinations were the most influential factors in enhancing the durability of lignin/polylactic acid (PLA) bio composites. In this work, RSM and MLP were used to model and predict the data in order to maximize the various solutions and establish the nonlinear relationship between the concentration of lignin and EPO. Springer 2023-05-14 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/104852/2/104852_Optimizing%20tensile%20strength.pdf application/pdf en http://irep.iium.edu.my/104852/7/104852_Optimizing%20tensile%20strength_SCOPUS.pdf Manshor, Mohd Romainor and Kamarulzaman, Amjad Fakhri and Anuar, Hazleen and Toha @ Tohara, Siti Fauziah and Ali, Fathilah and Sukindar, Nor Aiman and Suhr, Jonghwan and Haris, Nursyam Dzuha (2023) Optimizing tensile strength of PLA-Lignin Bio-composites using machine learning approaches. In: 5th International Conference on Advances in Manufacturing and Materials Engineering, 9th - 10th August 2022, Kuala Lumpur, Malaysia. https://link.springer.com/chapter/10.1007/978-981-19-9509-5_58 10.1007/978-981-19-9509-5_58 |
institution |
Universiti Islam Antarabangsa Malaysia |
building |
IIUM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
International Islamic University Malaysia |
content_source |
IIUM Repository (IREP) |
url_provider |
http://irep.iium.edu.my/ |
language |
English English |
topic |
TS195 Packaging |
spellingShingle |
TS195 Packaging Manshor, Mohd Romainor Kamarulzaman, Amjad Fakhri Anuar, Hazleen Toha @ Tohara, Siti Fauziah Ali, Fathilah Sukindar, Nor Aiman Suhr, Jonghwan Haris, Nursyam Dzuha Optimizing tensile strength of PLA-Lignin Bio-composites using machine learning approaches |
description |
It is imperative to accurately estimate the final performance of composite parts during the initial design phase of the manufacturing process. In generating sustainable bio composites with superior mechanical properties such as tensile strength, the combination of fillers and plasticizers, as well as their concentration in the mixture, are always deemed crucial. In order to reduce the number of experimental runs and their associated costs and timescales, statistical optimization of the core design elements has become increasingly important. The filler and plasticizer concentrations of extruded bio composites were adjusted in this study utilizing both statistical (analysis of variance (ANOVA) and response surface methodology (RSM)) and machine learning (Multilayer Perceptron (MLP)) approaches. Initial ANOVA results indicated that lignin, epoxidized palm oil (EPO), and their respective combinations were the most influential factors in enhancing the durability of lignin/polylactic acid (PLA) bio composites. In this work, RSM and MLP were used to model and predict the data in order to maximize the various solutions and establish the nonlinear relationship between the concentration of lignin and EPO. |
format |
Conference or Workshop Item |
author |
Manshor, Mohd Romainor Kamarulzaman, Amjad Fakhri Anuar, Hazleen Toha @ Tohara, Siti Fauziah Ali, Fathilah Sukindar, Nor Aiman Suhr, Jonghwan Haris, Nursyam Dzuha |
author_facet |
Manshor, Mohd Romainor Kamarulzaman, Amjad Fakhri Anuar, Hazleen Toha @ Tohara, Siti Fauziah Ali, Fathilah Sukindar, Nor Aiman Suhr, Jonghwan Haris, Nursyam Dzuha |
author_sort |
Manshor, Mohd Romainor |
title |
Optimizing tensile strength of PLA-Lignin Bio-composites using
machine learning approaches |
title_short |
Optimizing tensile strength of PLA-Lignin Bio-composites using
machine learning approaches |
title_full |
Optimizing tensile strength of PLA-Lignin Bio-composites using
machine learning approaches |
title_fullStr |
Optimizing tensile strength of PLA-Lignin Bio-composites using
machine learning approaches |
title_full_unstemmed |
Optimizing tensile strength of PLA-Lignin Bio-composites using
machine learning approaches |
title_sort |
optimizing tensile strength of pla-lignin bio-composites using
machine learning approaches |
publisher |
Springer |
publishDate |
2023 |
url |
http://irep.iium.edu.my/104852/2/104852_Optimizing%20tensile%20strength.pdf http://irep.iium.edu.my/104852/7/104852_Optimizing%20tensile%20strength_SCOPUS.pdf http://irep.iium.edu.my/104852/ https://link.springer.com/chapter/10.1007/978-981-19-9509-5_58 |
_version_ |
1772810673784356864 |