Multi-response optimization of process parameter in fused deposition modelling by response surface methodology
This paper reported on the effect of ambient temperature, layer thickness, and part angle on the surface roughness and dimensional accuracy. The response surface methodology (RSM) was employed by using historical data in the experiment to determine the significant factors and their interactions on t...
Saved in:
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP)
2019
|
Online Access: | http://eprints.utem.edu.my/id/eprint/24788/2/MULTI-RESPONSE%20OPTIMIZATION%20OF%20PROCESS%20PARAMETER%20IN%20FUSED%20DEPOSITION%20MODELLING%20BY%20RESPONSE%20SURFACE%20METHODOLOGY.PDF http://eprints.utem.edu.my/id/eprint/24788/ https://www.ijrte.org/wp-content/uploads/papers/v8i3/C4152098319.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.utem.eprints.24788 |
---|---|
record_format |
eprints |
spelling |
my.utem.eprints.247882022-05-12T11:49:17Z http://eprints.utem.edu.my/id/eprint/24788/ Multi-response optimization of process parameter in fused deposition modelling by response surface methodology Kasim, Mohd Shahir Harun, Nurul Hatiqah Mohd Shahim, Mohammad Shah All Hafiz W. Mohamad, W Noor Fatihah This paper reported on the effect of ambient temperature, layer thickness, and part angle on the surface roughness and dimensional accuracy. The response surface methodology (RSM) was employed by using historical data in the experiment to determine the significant factors and their interactions on the fused deposition modelling (FDM) performance. Three controllable variables namely ambient temperature (30 °C, 45 °C, 60 °C), layer thickness (0.178 mm, 0.267 mm, 0.356 mm) and part angle (22.5°, 45°, 67.5°) have been studied. A total of 29 numbers of experiments had been conducted, including two replications at the center point. The results showed that all the parameter variables have significant effects on the part surface roughness and dimensional accuracy. Layer thickness is the most dominant factors affecting surface roughness. Meanwhile, the ambient temperature was the most dominant in determining part dimensional accuracy. The responses of various factors had been illustrated in the cross-sectional sample analysis. The optimum parameter required for minimum surface roughness and dimensional accuracy was at ambient temperature 30 °C, layer thickness 0.18 mm and part angle 67.38°. The optimization has produced maximum productivity with RaH 3.21 µm, RaV 11.78 µm, and RaS 12.79 µm. Meanwhile, dimensional accuracy height eror 3.21%, width error 3.70% and angle 0.38° Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP) 2019-09 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/24788/2/MULTI-RESPONSE%20OPTIMIZATION%20OF%20PROCESS%20PARAMETER%20IN%20FUSED%20DEPOSITION%20MODELLING%20BY%20RESPONSE%20SURFACE%20METHODOLOGY.PDF Kasim, Mohd Shahir and Harun, Nurul Hatiqah and Mohd Shahim, Mohammad Shah All Hafiz and W. Mohamad, W Noor Fatihah (2019) Multi-response optimization of process parameter in fused deposition modelling by response surface methodology. International Journal Of Recent Technology And Engineering (IJRTE), 8 (3). pp. 327-338. ISSN 2277-3878 https://www.ijrte.org/wp-content/uploads/papers/v8i3/C4152098319.pdf 10.35940/ijrte.C4152.098319 |
institution |
Universiti Teknikal Malaysia Melaka |
building |
UTEM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknikal Malaysia Melaka |
content_source |
UTEM Institutional Repository |
url_provider |
http://eprints.utem.edu.my/ |
language |
English |
description |
This paper reported on the effect of ambient temperature, layer thickness, and part angle on the surface roughness and dimensional accuracy. The response surface methodology (RSM) was employed by using historical data in the experiment to determine the significant factors and their interactions on the fused deposition modelling (FDM) performance. Three controllable variables namely ambient temperature (30 °C, 45 °C, 60 °C), layer thickness (0.178 mm,
0.267 mm, 0.356 mm) and part angle (22.5°, 45°, 67.5°) have been studied. A total of 29 numbers of experiments had been conducted, including two replications at the center point. The results showed that all the parameter variables have significant effects on the part surface roughness and dimensional accuracy. Layer thickness is the most dominant factors affecting surface roughness. Meanwhile, the ambient temperature was the most dominant in determining part dimensional accuracy. The responses of various factors had been illustrated in the cross-sectional sample analysis. The optimum parameter required for minimum surface roughness and dimensional accuracy was at ambient temperature 30 °C, layer thickness 0.18 mm and part angle 67.38°. The optimization has produced maximum productivity with RaH 3.21 µm, RaV 11.78 µm, and RaS 12.79 µm. Meanwhile, dimensional accuracy height eror 3.21%, width error 3.70% and angle 0.38° |
format |
Article |
author |
Kasim, Mohd Shahir Harun, Nurul Hatiqah Mohd Shahim, Mohammad Shah All Hafiz W. Mohamad, W Noor Fatihah |
spellingShingle |
Kasim, Mohd Shahir Harun, Nurul Hatiqah Mohd Shahim, Mohammad Shah All Hafiz W. Mohamad, W Noor Fatihah Multi-response optimization of process parameter in fused deposition modelling by response surface methodology |
author_facet |
Kasim, Mohd Shahir Harun, Nurul Hatiqah Mohd Shahim, Mohammad Shah All Hafiz W. Mohamad, W Noor Fatihah |
author_sort |
Kasim, Mohd Shahir |
title |
Multi-response optimization of process parameter in fused deposition modelling by response surface methodology |
title_short |
Multi-response optimization of process parameter in fused deposition modelling by response surface methodology |
title_full |
Multi-response optimization of process parameter in fused deposition modelling by response surface methodology |
title_fullStr |
Multi-response optimization of process parameter in fused deposition modelling by response surface methodology |
title_full_unstemmed |
Multi-response optimization of process parameter in fused deposition modelling by response surface methodology |
title_sort |
multi-response optimization of process parameter in fused deposition modelling by response surface methodology |
publisher |
Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP) |
publishDate |
2019 |
url |
http://eprints.utem.edu.my/id/eprint/24788/2/MULTI-RESPONSE%20OPTIMIZATION%20OF%20PROCESS%20PARAMETER%20IN%20FUSED%20DEPOSITION%20MODELLING%20BY%20RESPONSE%20SURFACE%20METHODOLOGY.PDF http://eprints.utem.edu.my/id/eprint/24788/ https://www.ijrte.org/wp-content/uploads/papers/v8i3/C4152098319.pdf |
_version_ |
1732948780503793664 |
score |
13.160551 |