Multi-Response Optimization of Process Parameter in Fused Deposition Modelling by Response Surface Methodology
Mohd Shahir Kasim1, Nurul Hatiqah Harun2, Mohammad Shah All Hafiz3, Saiful Bahri Mohamed4, W Noor Fatihah W. Mohamad5

1Mohd Shahir Kasim*1, Advanced Manufacturing Centre, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia, and Fakulti Kejuruteraan Pembuatan, Universiti Teknikal Malaysia, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia.
2Nurul Hatiqah Harun, Fakulti Kejuruteraan Pembuatan, Universiti Teknikal Malaysia, Hang Tuah Jaya,  Durian Tunggal, Melaka, Malaysia.
3Mohammad Shah All Hafiz, Advanced Manufacturing Centre, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia, and Fakulti Kejuruteraan Pembuatan, Universiti Teknikal Malaysia, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia.
4Saiful Bahri Mohamed*2, Fakulti Reka Bentuk Inovatif dan Teknologi, Universiti Sultan Zainal Abidin, Kampung Gong Badak, 21300 Kuala Terengganu, Terengganu, Malaysia.
5W Noor Fatihah W. Mohamad, Fakulti Kejuruteraan Pembuatan, Universiti Teknikal Malaysia, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia and Fakulti Reka Bentuk Inovatif dan Teknologi, Universiti Sultan Zainal Abidin, Kampung Gong Badak, 21300 Kuala Terengganu, Terengganu, Malaysia.

Manuscript received on 5 August 2019. | Revised Manuscript received on 10 August 2019. | Manuscript published on 30 September 2019. | PP: 327-338 | Volume-8 Issue-3 September 2019 | Retrieval Number: C3876098319/19©BEIESP  | DOI: 10.35940/ijrte.C4152.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: TThis 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°.
Keywords: Rapid Prototyping, Fused Deposition Modelling, Optimization, Response Surface Methodology
Scope of the Article: