Sage Journals: Discover world-class research

Abstract

Additive manufacturing has been a revolution in the last decade and has led to a number of product innovations. Rapid prototyping (RP) has significantly reduced the product development cycle time and RP techniques are now replacing many conventional plastic processing techniques where production volume is not an issue. In order to ascertain the utility of additive manufacturing techniques for the development of fully functional parts, it’s important to establish the optimal set of process parameters for achieving maximum mechanical performance. In the current experimental investigation, the dogbone-shaped parts of acrylonitrile butadiene styrene (ABS) were fabricated by the fused deposition modeling (FDM) process. The process parameters were optimized for dogbone-shaped specimens fabricated by the FDM process. Among the parameters, it has been found that orientation and infill density are the most dominant factors affecting the tensile strength of FDM parts printed with ABS material.

Keywords

Additive manufacturing ANOVA design of experiment FDM tensile strength

Introduction

The competitive market has given birth to a new era of manufacturing called additive manufacturing (AM). Due to its advantages in terms of lesser lead time, part accuracy, good mechanical properties, and cost-effectiveness, this technology is proliferating into a versatile solution for fabricating a wide variety of parts. Manufacturing in the current scenario is changing rapidly from an era when the parts were handcrafted to automatic production with the use of computer-aided technology. In rapid prototyping, the material is added layer by layer, unlike in subtractive manufacturing processes, in which the parts are made by the removal of material in the form of chips. Rapid prototyping allows the manufacturer to reduce product lead time to market for new products and analyze the part before its final production. Bhatt et al.¹ reviewed the lower limb prosthetic devices, which are fabricated by AM processes, and suggested that the AM processes are user-centric and can cover all the user demands like a better fit, comfort, and stable gait rehabilitation in the prosthetic devices. In another study, it was observed that adding reinforcement material to Nylon-66 may increase the fatigue life and reduce the level of stress in the prosthesis.^{2, 3} Sood et al.⁴ analyzed the effect of various factors, viz., layer thickness, built orientation, raster angle, raster width, and air gap, on the compressive strength of the parts produced by fused deposition modeling (FDM)-based three-dimensional (3D) printers and concluded that the bond between layers should be strong enough to control the distortion. Low strength is due to the alignment of the built material in the direction of flow. The dimensional accuracy of the 3D-printed model is controlled by reducing the warpage, which was one of the major defects in the object. It was concluded that increasing layer thickness resulted in decreased warpage, but the stair-stepping error increased.^{5 –7} Kumar and Kumar⁸ investigated the surface roughness of the part produced by PolyJet technology and found that the orientation significantly affects roughness. Chiu et al.⁹ concluded that longer curing times lead to better dimensional accuracy. Nidagundi et al.¹⁰ optimized the process parameters using Taguchi’s L9 orthogonal array for four output parameters, namely, ultimate tensile strength, dimensional accuracy, surface roughness, and manufacturing time, by taking three input parameters (layer thickness, orientation angle, and fill angle). It was found that the 0° orientation and fill angle resulted in the best output responses.¹¹ Gay et al.¹² manufactured the flat parts using PolyJet technology and concluded that x-axis spacing and surface quality have an insignificant effect on the mechanical properties. Christiyan et al.¹³ observed that the lower layer thickness and printing speed resulted in maximum tensile and flexural strength.

In the current experimental endeavor, the performance of the FDM process has been compared at various combinations of process parameters. Various researchers have worked on process parameter optimization with limited input parameters. The FDM system has substantial parameters to be varied for making the component. Few recent FDM systems allow the use of multimaterial too. All individual parameters affect the output properties; therefore, it is required to study the number of parameters that affect the ultimate tensile strength, as presented in this paper. The Taguchi optimization method is used to identify the number of experiments with the required levels of factors. It is based on the concept of a robust design of experiments that can be performed under different conditions with the same factors. An analysis of variance (ANOVA) is used to find the critical factor from the given set of factors at different levels. Optimization is based on the signal-to-noise ratio with criteria based on the output, which usually depends on whether smaller is better, larger is better, or nominal is better.¹⁴ In this study, tensile strength was studied and analysis was carried out using larger is better. The effect of various parameters, that is, infill pattern, orientation, layer height, raster angle, infill density, wall thickness, wall speed, and infill speed, on the tensile strength of acrylonitrile butadiene styrene (ABS), has been statistically analyzed using Taguchi’s methodology.

Materials and methods

The dogbone-shaped specimens have been manufactured using the fused deposition technique. The ASTM D638 Type IV standard has been followed, as shown in Figure 1. ABS material has been used to fabricate specimens, and its material properties are listed in Table 1. The process parameters and their levels for the fabrication of dogbone-shaped specimens are listed in Table 2. As per the L18 orthogonal array, 18 samples were manufactured with different combinations of process parameters, and each sample was replicated three times to ensure the consistency of the experimental results. The infill pattern fills the interior geometry in a specific pattern, and it was varied as grid and lines, as shown in Figure 2(a) and (b). The orientations for printing the samples were taken in three ways, as shown in Figure 3. The raster angle for printing three orientations was taken as 0°, 45°, and 90°, as shown in Figure 4. All the printed samples with repetitions are shown in Figure 5.

Figure 1.

Schematic diagram of the dogbone-shaped specimen.

Table 1.

Material properties of acrylonitrile butadiene styrene.¹⁵

S. No.	Properties	Value
1	Tensile strength	40.12 MPa
2	Modulus of elasticity	2,532.31 MPa
3	Flexural modulus	2100 MPa
4	Izod notched impact	15.14 J/m
5	Elongation at break	50 %
6	Shore hardness	71.84 D

Table 2.

Process parameters and their levels.

S. No.	Factors	Level I	Level II	Level III
1	Infill pattern	Grid	Lines	–
2	Orientation	XY	YZ	XZ
3	Layer height	100 µm	150 µm	200 µm
4	Raster angle	0°	45°	90°
5	Infill density	50%	75%	100%
6	Wall thickness	0.4 mm	0.8 mm	1.2 mm
7	Wall speed	30 mm/s	35 mm/s	40 mm/s
8	Infill speed	60 mm/s	80 mm/s	100 mm/s

Dimension	Values	Dimension	Values
Overall length (LO)	115 mm	Distance between grips (D)	65 mm
Length of narrow section (L)	33 mm	Gage length (G)	25 mm
Radius of fillet (R)	14 mm	Outer radius (RO)	25 mm
Width of narrow section (W)	06 mm	Overall width (WO)	19 mm
Thickness (T)	04 mm

Figure 2.

Infill patterns.

Figure 3.

Orientations for printing the samples: (a) XY plane, (b) YZ plane, and (c) XZ plane.

Figure 4.

Raster angle in different orientation.

Figure 5.

Complete batch of the dogbone-shaped specimens.

Results and discussion

The dogbone specimens were tested on a universal testing machine with a suitable fixture. Each sample was tested under similar operating conditions at a crosshead speed of 1 mm/min. The tensile strength of the specimens manufactured with FDM technology varies for different orientations because of the bonding strength between the additive layers, as shown in Table 3. As the overall load is distributed between the layers, the strength of the specimen depends on the orientation of the printing.^{16, 17} The main effects plot for the means of eight different factors is shown in Figure 6. The process parameters, that is, infill pattern, wall thickness, and infill density, have a significant effect on the tensile strength. The raster angle and wall speed have an insignificant effect on the tensile strength of manufactured parts.^{18, 19} It has been observed that orientation and infill density had a statistically significant effect on the tensile strength of the manufactured parts, among all the other factors. From Figure 6, it can be seen that optimized parameters for ultimate tensile strength are the values for all the peak input parameters: infill pattern (lines), orientation (YZ), layer height (100 µm), raster angle (45º), infill density (100%), wall thickness (1.2 mm), wall speed (40 mm/s), and infill speed (60 mm/s).

Table 3.

Mean ultimate tensile strength of dogbone-shaped specimens.

Exp. No.	Infill pattern	Orientation	Layer height (µm)	Raster angle (°)	Infill density (%)	Wall thickness (mm)	Wall speed (mm/s)	Infill speed (mm/s)	Mean UTS (MPa)
1	Grid	x–y	100	0	50	0.4	30	60	18.95
2	Grid	x–y	150	45	75	0.8	35	80	23.74
3	Grid	x–y	200	90	100	1.2	40	100	37.79
4	Grid	y–z	100	0	75	0.8	40	100	23.70
5	Grid	y–z	150	45	100	1.2	30	60	44.24
6	Grid	y–z	200	90	50	0.4	35	80	12.36
7	Grid	x–z	100	45	50	1.2	35	100	14.99
8	Grid	x–z	150	90	75	0.4	40	60	12.98
9	Grid	x–z	200	0	100	0.8	30	80	20.83
10	Lines	x–y	100	90	100	0.8	35	60	40.96
11	Lines	x–y	150	0	50	1.2	40	80	25.55
12	Lines	x–y	200	45	75	0.4	30	100	24.38
13	Lines	y–z	100	45	100	0.4	40	80	43.34
14	Lines	y–z	150	90	50	0.8	30	100	20.91
15	Lines	y–z	200	0	75	1.2	35	60	29.36
16	Lines	x–z	100	90	75	1.2	30	80	13.18
17	Lines	x–z	150	0	100	0.4	35	100	17.25
18	Lines	x–z	200	45	50	0.8	40	60	08.33

Figure 6.

Main effects plot for means.

From Figure 6, it can be seen that infill density is majorly responsible for the strength of the parts, and less infill density leads to fragile tensile strength. Axial load is applied to the tensile test specimen; thus, orientation is crucial in the direction of the applied load. Wall thickness is another important parameter in FDM, and thicker walls provide better strength. Figure 7 shows the interaction effects of the eight different factors (infill pattern, orientation, layer height, raster angle, infill density, wall thickness, wall speed, and infill speed) on the tensile strength of dogbone-shaped specimens. Among these parameters, the infill density is the main influencing factor on the tensile strength of the fabricated parts.

Figure 7.

Parametric interaction plots for tensile strength.

Experiments have been designed as per the Taguchi L18 orthogonal array for establishing the optimal set of parametric combinations for maximizing the ultimate tensile strength of manufactured specimens. ANOVA has been used to find out the percentage contribution of each factor. Table 4 shows the percentage contribution of individual factors. This table provides the details of each factor contributing to the ultimate tensile strength of FDM parts with these eight parameters at different levels.

Table 4.

Analysis of variance for means.

Source	DOF	SS	MS	F-value	Percentage contribution (%)
Infill pattern	1	10.32	10.32	0.38	0.49
Orientation	2	805.25	402.63	14.87	38.62
Layer height	2	40.71	20.35	0.75	1.95
Raster angle	2	54.71	27.36	1.01	2.62
Infill density	2	961.78	480.89	17.76	46.13
Wall thickness	2	115.57	57.78	2.13	5.54
Wall speed	2	14.84	7.42	0.27	0.71
Infill speed	2	27.65	13.82	0.51	1.32
Error	2	54.15	27.08	–	2.60
Total	17	–	–	–	100%

The optimal combination of FDM process parameters (as listed in Table 5) is expected to result in the maximum value of the ultimate tensile strength of the manufactured parts. The experimental results have also been substantiated by the findings of Lopez and Ahmad 2020.²⁰

Table 5.

Optimum condition for maximum tensile strength.

Sl. No.	Factors	Optimum condition	Rank order
1	Infill pattern	Lines	8
2	Orientation	YZ plane	2
3	Layer height	100 µm	6
4	Raster angle	45⁰	4
5	Infill density	100%	1
6	Wall thickness	1.2 mm	3
7	Wall speed	40 mm/s	7
8	Infill speed	60 mm/s	5

Conclusions

The tensile test specimens have been manufactured using the FDM process. Maximum parameters were investigated to identify the optimized parameters for ultimate tensile strength. Taguchi’s experimental design approach has been adopted to plan the experiments. The combined effect of eight different process parameters has been investigated on the tensile behavior of the ABS specimens. It has been found that orientation and infill density have a statistically more significant effect on the tensile strength values. The maximum and minimum values of tensile strength with the proposed combinations were found to be 44.24 MPa (Experiment No. 5) and 8.33 MPa (Experiment No. 18). A confirmation experiment was also performed with the optimized combination and the tensile strength value was found to be 51.58 MPa. The input parameters have also been ranked according to their significance in defining the tensile performance of the FDM-based, dogbone-shaped specimens. Based on the values of the tensile strength achieved at the optimal combination of process parameters, it can be concluded that the FDM process can be used for the fabrication of a number of fully functional non-structural parts and components.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author received no financial support for the research, authorship and/or publication of this article.

ORCID iDs

Neel Kamal Gupta

Pawan Kumar Rakesh

References

Bhatt

, Joshi

, Rakesh

, and Godiyal

. Advances in additive manufacturing processes and their use for the fabrication of lower limb prosthetic devices. Expert Rev Med Dev 2023; 20(1): 17–27.

Bhatt

, Godiyal

, Joshi

and Rakesh

. “Design analysis and fatigue life prediction of an indigenously developed affordable knee prosthesis,” in Advances in engineering design , eds Rakesh

, Sharma

and Singh

(Singapore: Springer Nature), 2021.

Pugalendhi

, Ranganathan

and Chandrasekaran

Effect of process parameters on mechanical properties of VeroBlue material and their optimal selection in PolyJet technology. Int J Adv Manuf Technol 2020; 108: 1049 –1059.

Sood

, Ohdar

, Mahapatra

SS.

Experimental investigation and empirical modelling of FDM process for compressive strength improvement. J Adv Res 2012; 3: 81–90.

Torrado Perez

ART

, Roberson

, Wicker

RB.

Fracture surface analysis of 3D-printed tensile specimens of novel ABS-based materials. J Fail Anal Prev 2014; 14(3): 343–353.

Durgun

Ertan

Experimental investigation of FDM process for improvement of mechanical pr operties and production cost. Rapid Prototyp J 2014; 20(3): 228–235.

Raju

, Shekar

Venkateswarlu K and Drakashayani DN. Establishment of process model for rapid prototyping technique (Stereolithography) to enhance the part quality by Taguchi method. Procedia Technol 2014; 14: 380–389.

Kumar

. An experimental and theoretical investigation of surface roughness of poly-jet printed parts. Virtual Phys Prototyp 2015; 10(1): 23–34.

Chiu

, Chen

, Su

CH.

Optimization of process parameters for dimensional accuracy in an area-forming rapid prototyping system using the Taguchi method. Mod Phys Lett B 2015; 29: 1540011.

10.

Nidagundi

, Keshavamurthy

Prakash

CPS.

Studies on parametric optimisation for the fused deposition modelling process. Mater Today Proc 2015; 2(4-5): 1691–1699.

11.

Beltrán

, Carriles

, Álvarez

Blanco D and Rico JC. Characterization of factors influencing dimensional and geometric errors in PolyJet manufacturing of cylindrical features. Procedia Eng 2015; 132: 62–69.

12.

Gay

, Blanco

, Pelayo

Noriega A and Fernández P. Analysis of factors influencing the mechanical properties of flat PolyJet manufactured parts. Procedia Eng 2015; 132: 70–77.

13.

Christiyan

, Chandrasekhar

Venkateswarlu

. A study on the influence of process parameters on the mechanical properties of 3D printed ABS composite. IOP Conf Ser Mater Sci Eng 2016; 114: 012109.

14.

Yalçın

, Yüksel

, Aslantaş

Der O and Ercetin A. Optimization of micro-drilling of laminated Aluminum Composite Panel (Al–PE) using Taguchi orthogonal array design. Materials 2023; 16: 4528. https://doi.org/10.3390/ma16134528

15.

Vacha

Boruka

. Mechanical properties of acrylonitrile butadiene styrene thermoplastic polymer matrix with carbon nanotubes. Proceedings of the NANOCON, Oct 14th – 16th 2015, Brno, Czech Republic, EU , Brno: Tanger Ltd, 2015.

16.

Vishwas

Basavaraj

. Studies on optimizing process parameters of fused deposition modelling technology for ABS. Mater Today Proc 2017; 4: 10994–11003.

17.

Cazón

, Morer

Matey

. PolyJet technology for product prototyping: tensile strength and surface roughness properties. Proc Inst Mech Eng B J Eng Manuf 2014; 228(12): 1664–1675.

18.

Jihong

, Han

, Chuang

, Lu

, Shingqin

Weihong

. A review of topology optimisation for additive manufacturing: status and challenges. Chin J Aeronaut 2020; 34: 91–110. https://doi.org/10.1016/j.cja.2020.09.020.

19.

Brischetto

Torre

Tensile and compressive behaviour in the experimental tests for PLA specimens produced via fused deposition modelling technique. J Compos Sci 2020; 4: 140.

20.

Lopez

, Ahmad

Tensile mechanical behaviour of multi-polymer sandwich structures via fused deposition modelling. Polymers 2020; 12: 651.

Process parametric optimization of fused deposition modeling for manufacturing of acrylonitrile butadiene styrene parts