Improving 3D-printed high-impact polystyrene using fused filament fabrication via multi-objective optimisation

Nguyen, PQK; Zhang, YX; Zhang, Z; Yang, R

Improving 3D-printed high-impact polystyrene using fused filament fabrication via multi-objective optimisation

Nguyen, PQK Zhang, YX Zhang, Z Yang, R

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Publisher:: Emerald
Publication Type:: Journal Article
Citation:: Rapid Prototyping Journal, 2025, 31, (11), pp. 284-300
Issue Date:: 2025-12-15

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Field	Value	Language
dc.contributor.author	Nguyen, PQK
dc.contributor.author	Zhang, YX
dc.contributor.author	Zhang, Z
dc.contributor.author	Yang, R
dc.date.accessioned	2025-12-18T02:53:55Z
dc.date.available	2025-12-18T02:53:55Z
dc.date.issued	2025-12-15
dc.identifier.citation	Rapid Prototyping Journal, 2025, 31, (11), pp. 284-300
dc.identifier.issn	1355-2546
dc.identifier.issn	1758-7670
dc.identifier.uri	http://hdl.handle.net/10453/190979
dc.description.abstract	Purpose This study aims to improve mechanical strength and build time of Fused Filament Fabrication (FFF)-printed high-impact polystyrene (HIPS), considering five key controllable FFF process parameters including layer thickness, printing speed, number of contours, raster angle and infill density and their effects on mechanical performance of the HIPS. Design/methodology/approach This study develops a novel multistage material optimisation framework with a mixing experimental and theoretical analysis procedures for FFF of thermoplastic polymers. Artificial neuron network (ANN) is adopted for pattern recognition before the genetic algorithm (GA) and multi-criteria decision-making algorithm are applied for optimisation. Findings Optimised FFF-printing HIPS with rational balance between mechanical properties (tensile strength, flexural strength and impact strength) and build time were achieved. The infill density as the main contributor to the tensile strength and flexural strength, the raster angle as the main contributor to the impact strength while the layer thickness has the highest impact on the build time. ANN-GA method succeeds at achieving a reasonable balance of mechanical strength and build time. Originality/value User-friendly and innovative methodology are devised for developing highly accurate ANN-GA-TOPSIS models for multi-objective optimisation. Optimum settings for three-dimensional-printing HIPS with rational balance between mechanical properties (tensile strength, flexural strength and impact strength) and build time are achieved. The outcome of this research can be useful to achieve high-performance FFF-printed HIPS parts for automotive industries and medical fields with significantly reduced build time.
dc.language	en
dc.publisher	Emerald
dc.relation.ispartof	Rapid Prototyping Journal
dc.relation.isbasedon	10.1108/rpj-01-2025-0028
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0913 Mechanical Engineering
dc.subject.classification	Industrial Engineering & Automation
dc.subject.classification	4017 Mechanical engineering
dc.title	Improving 3D-printed high-impact polystyrene using fused filament fabrication via multi-objective optimisation
dc.type	Journal Article
utslib.citation.volume	31
utslib.for	0913 Mechanical Engineering
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	University of Technology Sydney/UTS Groups
pubs.organisational-group	University of Technology Sydney/UTS Groups/Centre for Advanced Manufacturing (CAM)
utslib.copyright.status	open_access	*
dc.rights.license	This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/
dc.date.updated	2025-12-18T02:53:54Z
pubs.issue	11
pubs.publication-status	Published online
pubs.volume	31
utslib.citation.issue	11

Abstract:

Purpose This study aims to improve mechanical strength and build time of Fused Filament Fabrication (FFF)-printed high-impact polystyrene (HIPS), considering five key controllable FFF process parameters including layer thickness, printing speed, number of contours, raster angle and infill density and their effects on mechanical performance of the HIPS. Design/methodology/approach This study develops a novel multistage material optimisation framework with a mixing experimental and theoretical analysis procedures for FFF of thermoplastic polymers. Artificial neuron network (ANN) is adopted for pattern recognition before the genetic algorithm (GA) and multi-criteria decision-making algorithm are applied for optimisation. Findings Optimised FFF-printing HIPS with rational balance between mechanical properties (tensile strength, flexural strength and impact strength) and build time were achieved. The infill density as the main contributor to the tensile strength and flexural strength, the raster angle as the main contributor to the impact strength while the layer thickness has the highest impact on the build time. ANN-GA method succeeds at achieving a reasonable balance of mechanical strength and build time. Originality/value User-friendly and innovative methodology are devised for developing highly accurate ANN-GA-TOPSIS models for multi-objective optimisation. Optimum settings for three-dimensional-printing HIPS with rational balance between mechanical properties (tensile strength, flexural strength and impact strength) and build time are achieved. The outcome of this research can be useful to achieve high-performance FFF-printed HIPS parts for automotive industries and medical fields with significantly reduced build time.

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http://hdl.handle.net/10453/190979