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...

Full description

Saved in:
Bibliographic Details
Main Authors: Kasim, Mohd Shahir, Harun, Nurul Hatiqah, Mohd Shahim, Mohammad Shah All Hafiz, W. Mohamad, W Noor Fatihah
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