Sage Journals: Discover world-class research

Abstract

Additive manufacturing (AM) processes are gaining widespread applications due to their ability to produce complex parts with reduced lead times. Fused deposition modeling (FDM), a promising AM process, demands precise control over its process parameters to optimize the performance. This article investigates the impact of FDM process parameters on dimensional accuracy of a microturbine impeller used in an organic rankine cycle (ORC). A full factorial design was employed to analyze the impact of FDM parameters including layer thickness, infill density, and infill angle. Dimensions of the impeller were measured using a coordinate measuring machine (CMM), and these experimental results were further used to establish the relationship between process parameters and dimensional accuracy. The adequacy of a developed predictive quadratic regression model was verified through analysis of variance (ANOVA). Individual and interaction effects of selected parameters were identified and discussed. The analysis revealed that layer thickness is significantly impacting the dimensional accuracy. Further, response surface methodology (RSM) was used to optimize the FDM process for enhanced dimensional accuracy. This study presents a significant method to enhance the adoption of the FDM process for manufacturing complex and functional parts.

Keywords

Functional polymers thermoplastics testing modeling optimization

Get full access to this article

View all access options for this article.

References

A review of materials, methods, applications and challenges. Compos Part B Eng 2018; 143: 172–196. DOI: 10.1016/j.compositesb.2018.02.012

Zhou

, Miller

, Vezza

, . Additive manufacturing: A comprehensive review. Sensors 2024; 24: 2668. DOI: 10.3390/s24092668

Kantaros

, Soulis

, Petrescu

FIT

, . Advanced composite materials utilized in FDM/FFF 3D printing manufacturing processes: The case of filled filaments. Mater 2023; 16: 6210. DOI: 10.3390/ma16186210

Sandanamsamy

, Harun

, Ishak

, . A comprehensive review on fused deposition modelling of polylactic acid. Prog Addit Manuf 2023; 8: 775–799. DOI: 10.1007/s40964-022-00356-w

Namvar

, Moloukzadeh

, Zolfagharian

, . Bio-inspired design, modeling, and 3D printing of lattice-based scale model scooter decks. Int J Adv Manuf Technol 2023; 126: 1–17. DOI: 10.1007/s00170-023-11185-8

Patel

and Taufik

Extrusion-based technology in additive manufacturing: A comprehensive review. Arab J Sci Eng 2024; 49: 1309–1342. DOI: 10.1007/s13369-022-07539-1

Brown

, Beer

and Conradie

Development of a stereolithography (STL) input and computer numerical control (CNC) output algorithm for an entry-level 3-D printer. South Afr J Ind Eng 2014; 25: 39–47. DOI: 10.7166/25-2-675

Mwema

and Akinlabi

Basics of fused deposition modelling (FDM). In: Fused deposition modeling: strategies for quality enhancement. 1st ed., 2020, pp. 1–15. DOI: 10.1007/978-3-030-48259-6_1

Sengsri

and Kaewunruen

Additive manufacturing meta-functional composites for engineered bridge bearings: A review. Constr Build Mater 2020; 262. DOI: 10.1016/j.conbuildmat.2020.120535

10.

Verma

, Awasthi

, Gupta

, . Fused deposition modeling of polyolefins: Challenges and opportunities. Macromol Mater Eng 2023; 308: 2200421. DOI: 10.1002/mame.202200421

11.

Gunaydin

and Türkmen

Common FDM 3D printing defects. In: Proceedings of the International Congress on 3D Printing (Additive Manufacturing) Technologies and Digital Industry, 2018; Antalya, Turkey, pp. 1–7.

12.

Hanon

, Zsidai

and Ma

Accuracy investigation of 3D printed PLA with various process parameters and different colors. Mater Today Proc 2021; 42(5): 3089–3096. DOI: 10.1016/j.matpr.2020.12.1246

13.

Singh

, Birru

and Singh

Optimizing the printing parameters for dimensional accuracy of distal femur bone by using Taguchi’s method. J Eng Appl Sci 2024; 71: 10. DOI: 10.1186/s44147-023-00338-x

14.

Grgić

, Karakašić

, Glavaš

, . Accuracy of FDM PLA polymer 3D printing technology based on tolerance fields. Processes 2023; 11: 2810. DOI: 10.3390/pr11102810

15.

Kačmarčik

, Spahic

, Varda

, . An investigation of geometrical accuracy of desktop 3D printers using CMM. IOP Conf Ser Mater Sci Eng 2018; 393: 012085. DOI:10.1088/1757-899X/393/1/012085

16.

Lieneke

, Denzer

, Adam

, . Dimensional tolerances for additive manufacturing: Experimental investigation for fused deposition modeling. Procedia CIRP 2016; 43: 286–291. DOI: 10.1016/j.procir.2016.02.361

17.

Ekinci

and Ehrmann

Influence of printing parameters on the dimensional accuracy of concave/convex objects in FDM printing. In: Proceedings of the 3rd International Electronic Conference on Applied Sciences , 2023, pp. 31–40. DOI: 10.3390/ASEC2022-13811

18.

Gorana

, Sahu

and Modi

Parameter optimization for dimensional accuracy of fused deposition modelling parts. Mater Today Proc 2023; 78: 640–646. DOI: 10.1016/j.matpr.2022.12.068

19.

Garg

, Rastogi

and Kumar

Process parameter optimization on the dimensional accuracy of additive manufacture Thermoplastic Polyurethane (TPU) using RSM. Mater Today Proc 2022; 62: 94–99. DOI: 10.1016/j.matpr.2022.02.309

20.

Mohamed

, Masood

and Bhowmik

Modeling, analysis, and optimization of dimensional accuracy of FDM-fabricated parts using definitive screening design and deep learning feedforward artificial neural network. Adv Manuf 2021; 9: 115–129. DOI: 10.1007/s40436-020-00336-9

21.

Sheoran

and Kumar

Fused deposition modeling process parameters optimization and effect on mechanical properties and part quality: Review and reflection on present research. Mater Today Proc 2020; 21: 1659–1672. DOI: 10.1016/j.matpr.2019.11.296

22.

McKee

, Kistenmacher

, Goerrissen

, . Synthesis, properties and applications of acrylonitrile–styrene–acrylate polymers. In:

Scheirs

, Scheirs

, Priddy

(eds) Modern styrenic polymers: polystyrenes and styrenic copolymers . 1st ed. Wiley, 2003. DOI: 10.1002/0470867213.ch16

23.

Kumar

, Sridhar

, Venkatraman

, . Polymer additive manufacturing of ASA structure: Influence of printing parameters on mechanical properties. Mater Today Proc 2021; 39: 1316–1319. DOI: 10.1016/j.matpr.2020.04.500

24.

Penumakala

, Santo

and Thomas

A critical review on the fused deposition modeling of thermoplastic polymer composites. Compos Part B Eng 2020; 201: 108336. DOI: 10.1016/j.compositesb.2020.108336

25.

Bharath

, Manjunatha

and Santhosh

Failure analysis and the optimal toughness design of sheep–wool reinforced epoxy composites. In: Failure analysis in biocomposites, fibre-reinforced composites and hybrid composites . Woodhead Publishing Series in Composites Science and Engineering, 2018, pp. 97–107. DOI: 10.1016/B978-0-08-102293-1.00005-X

26.

Mohamed

Optimization of fused deposition modeling process parameters: A review of current research and future prospects. Adv Manuf 2015; 3: 42–52.

Analyzing and optimizing fused deposition modeling parameters for dimensional accuracy of microturbine impellers

Abstract

Keywords

Get full access to this article

References