Sage Journals: Discover world-class research

Abstract

Additive manufacturing is becoming more and more significant for the production of engineering products. The global community of designers and manufacturers will undoubtedly benefit from identifying the process factors that could lead to superior mechanical behaviour. The incorporation of fibres and nanoparticles in polymer matrix is one of the most significant advancements in polymer fabrication. This study intends to investigate how the flexural behaviour of dissimilar polymer composites viz carbon fibre reinforced poly lactic acid (CF-PLA), carbon fibre reinforced poly ethylene terephthalate glycol (CF-PETG) and multi walled carbon nano tubes reinforced PLA (MWCNTs-PLA) are affected by process parameters viz nozzle diameter (0.2 mm, 0.4 mm, 0.6 mm), and infill pattern (triangular, honeycomb, rectilinear) through fused filament fabrication (FFF). Flexural testing was carried out on the fabricated specimens, and post to the testing, fractography has been carried out and statistical analysis of the observations is performed utilizing analysis of variance and Taguchi method. According to the observations, flexural strength of the polymer composite specimen increases with increase in nozzle diameter (ND). The flexural behaviour is also directly impacted with the variation of infill pattern (IP). Process parameter variations affect target factors differently depending on the fabricating material. For flexural behaviour, IP contributes 68.27% to CF-PLA, while ND contributes 88.96% to CF-PETG and 77.59% to MWCNTs-PLA. Overall, the highest flexural strength, 70.372 MPa, is exhibited by the specimen with ND 0.6 mm and rectilinear IP for MWCNTs-PLA as fabricating filament material. This study will aid researchers and designers in developing FFF-fabricated electrochemical energy storage devices with improved flexural behaviour of functional parts for a wide range of applications.

Keywords

Flexural behaviour fused filament fabrication polymer composites nozzle diameter infill pattern

Introduction

The cutting-edge technology known as additive manufacturing (AM) has revolutionized the manufacturing systems which paved the way for their domination in almost all type of industrial sectors. Contrary to subtractive manufacturing, Fused Filament Fabrication (FFF) is an AM process that uses minimal to no wasted material.^1–5 Additionally, it reduced the complexity of producing challenging component geometries. Not always the strongest combinations of strength attributes are available when transforming virtual models to goods. Products made with additives in particular are prone to faults caused by the manufacturing process, such as porosity, surface roughness, and geometric deviations from the intended dimensions.⁶ Another benefit of FFF process is that it has low maintenance costs, operates without supervision, allows for easy material swaps, and has interface-friendly temperatures. With FFF, a wide range of variables can be adjusted to affect the eventual characteristics of the finished object.^1,3,7,8 Layer thickness, build orientation, nozzle temperature, bed temperature raster angle, raster thickness, air void, nozzle diameter, infill density, and infill pattern are some of these variables which affect the mechanical characteristics of fabricated parts.^1,9–14

Several thermoplastic polymers, including poly lactic acid (PLA), acrylonitrile butadiene styrene (ABS), and polycarbonate (PC), are frequently utilized in FFF-process. The most popular material is PLA since it is readily available, biodegradable, and has very stable fabricating features that only need a few settings to be adjusted.^15–17 High mechanical strength, thermo-plasticity, and fabricability are only a few of PLA’s physical qualities that demonstrate its good biocompatibility.^16–19 However, their applicability in many applications is limited by their very stiff, brittle, slow crystallisation, and hydrolysis characteristics.²⁰ In order to make poly ethylene terephthalate glycol (PETG), a copolymer based on poly ethylene terephthalate (PET), secondary glycols are substituted for some of the ethylene glycol and joined along the copolymerizing agent’s backbone, resulting in an amorphous co-polyester with low levels of crystallinity.²¹ The incorporation of fibres and nanoparticles in polymer matrix is one of the most significant advancements in polymer fabrication.^22,23 PETG and PLA filament can be reinforced with materials including glass fibre, single walled carbon nanotubes, multi walled carbon nanotubes (MWCNTs), and carbon fibre (CF), to improve its mechanical, conductive and thermal behaviour.^{16,17,22,24–27} FFF-fabricated products' physical and mechanical qualities are greatly improved by carbonaceous reinforced polymer composites.^{17,22,24,28,29}

The infill pattern (IP) is one of the crucial factors in FFF process that determines how sturdy and long-lasting a construction will be.³⁰ The internal lattice or structure of FFF-fabricated items, known as the IP, is created based on the direction and pace of the filament deposition process. There are different kinds of infill patterns, including Hilbert curve, rectilinear, Archimedean chord, honeycomb, octagram spiral, and triangular.¹⁰ The strength of FFF-fabricated parts will vary depending on the infill pattern used. The raster layout and direction that influence the heat transmission between bonded layers are affected by infill patterns.^11,31 The choice of infill patterns will impact not just strength but also material utilisation and fabrication time. With the exception of small objects, the infill takes up more volume than the exterior shell and so becomes the predominant factor. Other key elements in FFF process that defines how extrusion and layer deposition will take place is the Nozzle Diameter (ND).³² It affects the layer height and rate of the filament deposition, which have a direct impact on the mechanical characteristics of FFF-fabricated structures. The mechanical strength of the final manufactured components increases with the efficiency of molecular fusion at bonded interlayers.³³ Since FFF-fabricated parts are typically created for prototyping, one of the main challenges is their endurance under repeated flexural load.^31,33 Numerous studies have been carried out to look at how the flexural characteristics are affected by the FFF process variables.^11,29,34

Kesavarma et al.⁷ reported that the infill pattern and infill percentage have a substantial influence on the flexural behaviour of the parts. Khan et al.¹⁰ demonstrated that, when compared to Hilbert curve, concentric and honeycomb patterns, the rectilinear infill pattern has the highest flexural performance. Lower layer height and 45° raster angle might increase flexural strength, according to Aworinde et al.,¹ fabrication at 0° raster angle is advised for wider raster width. The impact of nozzle temperature and fabricating speed on the mechanical characteristics of FFF-fabricated parts were thoroughly examined by Li et al.² Christiyan et al.⁹ found that as fabricating speed increases, component flexural strength falls as a result of the deboning of each layer. According to Saniman et al.,³⁵ the greatest flexural strain was produced by the honeycomb IP, whereas the best flexural strength was produced by the concentric IP. Ma et al.³¹ observed that the mechanical properties of a cubic structure produced through FFF process are significantly influenced by the material type, infill pattern, and density. According to Zandi et al.,³⁶ no interaction between the factors appears to be significant in determining the mechanical behaviour of the resulting specimens, with the layer height proving to be the most significant factor, followed by the nozzle diameter. This research shows that a higher nozzle diameter and a lower layer height produce a stronger bond between the layers, increasing the resistance of the additively made objects.³⁶

The Design of Experiments is a methodical action for analysing the influence of varying input parameters on a variety of response measures for the purpose of optimising those inputs.^12,37–41 By controlling characteristics and aspects related to a product’s design and development, scientists can utilise optimization to reduce the amount of change in a given product.^{12,37,40,42,43} The input parameters picked unquestionably have a big impact on how well a product performs in the end. Scientists frequently employ a variety of techniques to set up their experiments, including the Orthogonal Array of Taguchi.^44–46 To determine the supreme parameters, the experimental data is analysed. Additionally, the significant variables that have the significant impact on the study’s final outcome. It is also important to understand and compare how different carbonaceous polymer composites will respond to alteration in both ND and IP.

This study, therefore, compare the flexural properties of CF-PLA, CF-PETG, and MWCNTs-PLA composites, based on critical variables ND, and IP. The fracture surfaces are then examined using high-resolution microscopy to better understand failure causes. In order to investigate the relationship between the flexural strength and variation of process factors, The results of flexural tests are analysed with analysis of variance (ANOVA) and Taguchi method.

Material and methods

In FFF process, the nozzle extruded the fused filament material and could move parallel with respect to the horizontal build platform. The build platform offers the downward movement while placing a layer and the ability to traverse on to the succeeding layer once that layer is complete. Typical diameter for CFs employed in the creation of polymer composites are 6 μm and 210 μm in length, with an elastic modulus of around 232 GPa and a tensile strength of about 4.5 GPa. The 1.75 mm diameter filaments used in this experiment are CF-PLA (CF 20% by weight), CF-PETG (CF 20% by weight), and MWCNTs-PLA (MWCNTs 20% by weight). The results will improve our understanding of the material, which will be useful for future electrochemical energy storage systems. The Cubic3D CUB 5.5 FFF setup is utilised to shape the specimen. Software such as SOLIDWORKS 2019 and Simplify3D are employed to produce the ASTM D790 specimen (80 mm × 10 mm × 4 mm), Figure 1, with required FFF process parameters. For three-point flexural test, the 27 specimens are created utilising CF-PLA, CF-PETG, and MWCNTs-PLA with variations in the process parameters wiz ND (0.2 mm, 0.4 mm, and 0.6 mm) and IP (Triangular, Honeycomb, Rectilinear). Figure 2 illustrates the complete methodology of the present investigation. The selected infill patterns for experimental work are mentioned in Figure 3.

Figure 1.

ASTM D790 specimen (a) CAD Model (b) Fabricated specimen (c) Tested specimen.

Figure 2.

Methodology adopted for the current investigation.

Figure 3.

Selected infill patterns for experimental work.

The process variables that are classified as fixed and variable for specimens are shown in Table 1.

Table 1.

Process parameters of FFF-fabricated flexural test specimens.

Fixed process parameters			Variable process parameters
Parameter	Value	Unit	Parameter	Values	Unit
Liquefier temperature	220	°C	Nozzle diameter	0.2	mm
Bed temperature	60	°C		0.4	mm
Infill density	60	%		0.6	mm
Feed rate	40	mm/s	Infill pattern	Triangular	—
Layer height	0.15	mm		Honeycomb	—
Build orientation	XY	—		Rectilinear	—
External infill pattern	Concentric	—

An Instron 1195 with a 100 kN maximum capacity was used for the flexural testing with support span of 64 mm. It is a screw-driven machine. The schematic diagram of three-point flexural test is shown in Figure 4. The flexural test data for CF-PLA, CF-PETG, and MWCNTs-PLA specimens are shown in Table 2 along with variations in the process parameters. Analyses and comparisons are made regarding the impact of process parameters and fabrication materials. To analyse the failure morphology of the specimens for a particular filament material, specimens with maximum and minimum flexural strength are examined. In order to investigate the relationship between mechanical characteristics and altering process variables, the flexural test data is analysed using Taguchi method with ANOVA.

Figure 4.

Schematic diagram of three-point flexural test.

Table 2.

Flexural test results for FFF-fabricated specimens.

Specimen Code	Filament material	Nozzle diameter	Infill pattern	Flexural strength
Specimen Code	Filament material	(mm)	Infill pattern	(MPa)
A1	CF-PLA	0.20	Triangular	46.445
A2			Honeycomb	52.907
A3			Rectilinear	45.206
A4		0.40	Triangular	48.785
A5			Honeycomb	53.583
A6			Rectilinear	48.661
A7		0.60	Triangular	51.159
A8			Honeycomb	56.907
A9			Rectilinear	50.083
B1	CF-PETG	0.20	Triangular	45.869
B2			Honeycomb	50.661
B3			Rectilinear	46.528
B4		0.40	Triangular	53.756
B5			Honeycomb	54.657
B6			Rectilinear	51.581
B7		0.60	Triangular	65.228
B8			Honeycomb	63.721
B9			Rectilinear	58.649
C1	MWCNTs-PLA	0.20	Triangular	39.121
C2			Honeycomb	40.926
C3			Rectilinear	46.223
C4		0.40	Triangular	42.471
C5			Honeycomb	45.583
C6			Rectilinear	47.654
C7		0.60	Triangular	52.192
C8			Honeycomb	61.064
C9			Rectilinear	70.372

Result and discussion

A total of 27 specimens are examined, each representing a unique combination of the given process factors viz ND (0.2 mm, 0.4 mm, 0.6 mm) and IP (Triangular, Honeycomb, Rectilinear) using the CF-PLA, CF-PETG and MWCNTs-PLA as fabricating filament material, Table 2.

Effect of nozzle diameter

In this experiment three values of ND are utilized viz 0.2 mm, 0.4 mm and 0.6 mm. The potential layer height and, in turn, indirectly the fabricating speed are both determined by ND. In essence, it concerns how quickly and how much filament material can be extruded. In the below section, the comparison of flexural strength takes place at different NDs for a particular IP.

CF-PLA

Figure 5 depicts the stress versus strain curves for CF-PLA flexural test specimens at various IP. For triangular IP, the flexural strength achieved for specimen A1 is 46.445 MPa at ND 0.2 mm which is enhanced by 5.04% and 10.15% on increasing the ND to 0.4 mm (48.785 MPa, A4) and 0.6 mm (51.159 MPa, A7), respectively, Figure 5(a). For honeycomb IP, the flexural strength achieved for specimen A2 is 52.907 MPa at ND 0.2 mm which is increased by 1.28% and 7.56% on increasing the ND to 0.4 mm (53.583 MPa, A5) and 0.6 mm (56.907 MPa, A8), respectively, Figure 5(b). For rectilinear IP, the flexural strength achieved for specimen A3 is 45.206 MPa at ND 0.2 mm which is enhanced by 7.64% and 10.79% on increasing the ND to 0.4 mm (48.661 MPa, A6) and 0.6 mm (50.083 MPa, A9), respectively, Figure 5(c). The flexural behaviour of the CF-PLA specimens is enhanced on increasing the ND because it increases the bonding area between the adjacent rasters while other process parameters are maintained at constant value. Also, these strength values depend on delamination and separation of rasters during failure.

Figure 5.

Stress strain curves for CF-PLA specimens at different IP (a) Triangular (b) Honeycomb (c) Rectilinear.

CF-PETG

The stress strain curves for CF-PETG flexural test specimens at various IP are shown in Figure 6. The flexural strength for honeycomb IP is 50.661 MPa for specimen B2 at ND 0.2 mm, and it improved by 7.89% and 25.78% when the ND increased to 0.4 mm (54.657 MPa, B5) and 0.6 mm (63.721 MPa, B8), respectively, Figure 6(b). The flexural strength for rectilinear IP is 46.528 MPa for specimen B3 at ND 0.2 mm, and it enhanced by 10.86% and 26.05% when the ND increased to 0.4 mm (51.581 MPa, B6) and 0.6 mm (58.649 MPa, B9), respectively, Figure 6(c). Due to the poor raster-to-raster bonding, the flexural strength for triangular IP is less than honeycomb and rectilinear, 45.869 MPa for specimen B1 at ND 0.2 mm and it improved by 17.19% and 42.20% when the ND increased to 0.4 mm (53.756 MPa, B4) and 0.6 mm (65.228 MPa, B7), respectively, Figure 6(a). The increase in ND improves the CF-PETG specimens’ flexural strength because of high degree of fusion, with only a few well-distributed voids.

Figure 6.

Stress strain curves for CF-PETG specimens at different IP. (a) Triangular (b) Honeycomb (c) Rectilinear.

MWCNTs-PLA

The flexural strength achieved for specimen C3 is 46.223 MPa at ND 0.2 mm, and it improved by 3.10% and 52.24% on increasing the ND to 0.4 mm (47.654 MPa, C6) and 0.6 mm (70.372 MPa, C9), respectively for rectilinear IP, Figure 7(c). For triangular IP, due to weak connection between adjacent rasters, the flexural strength achieved for specimen C1 is 39.121 MPa at ND 0.2 mm, and it enhanced by 8.56% and 33.41% on increasing the ND to 0.4 mm (42.471 MPa, C4) and 0.6 mm (52.192 MPa, C7), respectively, Figure 7(a). The flexural strength achieved for specimen C2 is 40.926 MPa at ND 0.2 mm, and it improved by 11.38% and 49.21% on increasing the ND to 0.4 mm (45.853 MPa, C5) and 0.6 mm (61.064 MPa, C8), respectively for honeycomb IP, Figure 7(b). Since, it increases specific gravity of fabricated specimens with the increment in the ND while maintaining the other process variables constant, an increase in ND increases the flexural strength of the MWCNTs-PLA specimens. Figure 7 illustrates the stress-strain curves for MWCNTs-PLA flexural test specimens at various IP.

Figure 7.

Stress strain curves for MWCNTs-PLA specimens at different IP. (a) Triangular (b) Honeycomb (c) Rectilinear.

For a same value of the other process parameters, increasing the ND enhances the specimens' flexural strength. Weak horizontal linkages are created because of the narrow nozzle hole, which allows for the production of in-plane adjacent infill that barely touches. An increase in ND improves interlayer bonding by increasing pressure for a given height, leading to greater material deposition and narrower interlayer gaps and, in turn, greater specimen flexural strength. The findings demonstrate that, despite the lack of a linear association, larger nozzle hole diameters improved the flexural strength of the specimen.

Effect of infill pattern

The IP can be produced using a variety of geometries. IP is a noteworthy process variable in the FFF process. In the present work, three IPs viz triangular, honeycomb and rectilinear are employed. The comparison of flexural strength for a specific ND is done in the section below for various IPs.

CF-PLA

Since there is weak bonding of rasters, the flexural strength achieved for specimen A3 is 45.206 MPa for rectilinear IP and it improved by 17.04% and 2.74% on changing the IP to honeycomb (52.907 MPa, A2) and triangular (46.445 MPa, A1), respectively at ND 0.2 mm, Figure 8(a). Figure 8 depicts the stress strain curves for CF-PLA flexural test specimens for different ND. The specimen A6 exhibited the flexural strength of 48.661 MPa for rectilinear IP, and it enhanced by 0.25% and 10.11% on changing the IP to triangular (48.785 MPa, A4) and honeycomb (53.583 MPa, A5), respectively at ND 0.4 mm, Figure 8(b). The specimen A9 unveiled the flexural strength of 50.083 MPa for rectilinear IP, and it enhanced by 2.15% and 13.63% on changing the IP to triangular (51.159 MPa, A7) and honeycomb (56.907 MPa, A8), respectively at ND 0.6 mm, Figure 8(c). For CF-PLA specimens, the maximum flexural strength 56.907 MPa (A8) is achieved for honeycomb IP at ND 0.6 mm due to strong bonding between adjacent rasters and honeycomb IP’s hexagonal tiling offers comparatively higher flexural characteristics because its force distribution allows it to flow more fluently and less concentrate in the linkage chain. The minimum flexural strength 45.206 MPa (A3) is accomplished for rectilinear IP at ND 0.2 mm.

Figure 8.

Stress strain curves for CF-PLA specimens at different ND (a) 0.2 mm (b) 0.4 mm (c) 0.6 mm

CF-PETG

At ND 0.4 mm, the flexural strength achieved for specimen B6 is 51.581 MPa for rectilinear IP is enhanced by 5.96% and 4.22% on altering the IP to honeycomb (54.657 MPa, B5) and triangular (53.756 MPa, B4), respectively, Figure 9(b). At ND 0.6 mm, the flexural strength attained by specimen B9 is 58.649 MPa for rectilinear IP is enhanced by 11.22% and 8.65% on varying the IP to triangular (65.228 MPa, B7) and honeycomb (63.721 MPa, B8), respectively, Figure 9(c). For CF-PETG specimens, the lowest flexural strength 46.528 MPa (B3) achieved is for rectilinear IP at ND 0.2 mm and the highest flexural strength 65.228 MPa (B7) accomplished is for triangular IP at ND 0.6 mm. The stress strain curves for CF-PETG flexural test specimens at various ND are depicts in Figure 9. At ND 0.2 mm, the flexural strength of specimen B1 is 45.869 MPa for triangular IP with breaking and pullout of CFs, is heightened by 10.45% and 1.44% on altering the IP to honeycomb (50.661 MPa, B2) and rectilinear (46.528 MPa, B3), respectively, Figure 9(c).

Figure 9.

Stress strain curves for CF-PETG specimens at different ND. (a) 0.2 mm (b) 0.4 mm (c) 0.6 mm

MWCNTs-PLA

For MWCNTs-PLA specimens, the maximum flexural strength 70.372 MPa (C9) is accomplished for rectilinear IP at ND 0.6 mm and minimum flexural strength 45.206 MPa (C1) is attained for triangular IP at ND 0.2 mm. Figure 10 illustrates the stress-strain curves for MWCNTs-PLA flexural test specimens at various ND. The flexural strength for specimen C7 is 52.192 MPa with triangular IP and it improved by 17.00% and 34.83% when the IP modified to rectilinear (70.372 MPa, C9) and honeycomb (61.064 MPa, C8), respectively, at ND 0.6 mm, Figure 10(c). The flexural strength for specimen C1 is 39.121 MPa with triangular IP because of the ductile failure of the specimen and it enhanced by 4.61% and 18.15% when the IP modified to honeycomb (40.926 MPa, C2) and rectilinear (46.223 MPa, C3), respectively, at ND 0.2 mm, Figure 10(a). The flexural strength for specimen C4 is 42.471 MPa with triangular IP and it upgraded by 12.00% and 7.33% when the IP altered to rectilinear (47.654 MPa, C6) and honeycomb (45.583 MPa, C5), respectively, at ND 0.4 mm, Figure 10(b).

Figure 10.

Stress strain curves for MWCNTs-PLA specimens at different ND. (a) 0.2 mm (b) 0.4 mm (c) 0.6 mm.

For same value of the other process variables, the flexural behaviour of the specimens depicts variation with the alteration of the IP. These patterns have a direct effect on the flexural properties of the FFF-fabricated parts because there are differences in the deformation among IPs, presenting diverse responses associated with the different internal geometric structure of the patterns.

Failure morphology

Fractography is carried out to determine the failure cause using micrography of the deformed surface of the tested flexural specimen.

CF-PLA

Figure 11 illustrates the fracture surfaces of CF-PLA specimen with minimum (A3) and maximum (A8) flexural strength. For specimen A3, the deformation is due to weak raster bonding as well as delamination and separation of rasters resulting in minimum flexural strength for the CF-PLA specimens, Figure 11(a). It depicts the ductile failure of the specimen with the flexural strength of 45.206 MPa at ND 0.2 mm and rectilinear IP. But the specimen A8 exhibits the maximum flexural strength of 56.907 MPa at ND 0.6 mm and honeycomb IP. Specimen A8 depicts the strong raster to raster bonding but individual raster rupture is main cause for the distortion, Figure 11(b). It also exemplifies the ductile failure of the specimen during the flexural loading.

Figure 11.

Deformed surface for the CF-PLA specimens with minimum and maximum flexural strength (a) Specimen A3, (b) Specimen A8.

CF-PETG

The fracture surfaces of CF-PETG specimens with lowest (B1) and highest (B7) flexural strength are displayed in Figure 12. Specimen B1 depicts a flexural strength of 45.869 MPa at ND 0.2 mm and triangular IP. The weak raster-to-raster bonding, breaking of CFs, and CFs pullout is root for the brittle deformation of the specimen resulting in the lowest flexural strength for the CF-PETG specimens, Figure 12(a). However, the specimen B7 serves as an example of the CF-PETG specimen’s brittle failure with the highest flexural strength of 65.228 MPa at ND 0.6 mm and triangular IP. Strong raster-to-raster bonding, breaking of CFs, and CFs pullout is observed for Specimen B7 under flexural loading, Figure 12(b).

Figure 12.

Deformed surface for the CF-PETG specimens with minimum and maximum flexural strength (a) Specimen B1, (b) Specimen B7.

MWCNTs-PLA

The deformed surface of specimen C9 depicts the failure of individual rasters with breaking and pullout of MWCNTs, Figure 13(b). It also exhibits the ductile failure of the specimen during the flexural loading and also, exhibits the maximum flexural strength of 70.372 MPa at ND 0.6 mm and rectilinear IP. For specimen C1, the deformation is due to the weak raster bonding without individual raster failure resulting in minimum flexural strength for the CF-PLA specimens, Figure 13(a). It depicts the ductile failure of the specimen with the flexural strength of 39.121 MPa at ND 0.2 mm and triangular IP. Figure 13 illustrates the fracture surfaces of CF-PLA specimen with minimum (C1) and maximum (C9) flexural strength.

Figure 13.

Deformed surface for the MWCNTs-PLA specimens with minimum and maximum flexural strength (a) Specimen C1, (b) Specimen C9.

Figure 14 depicts the various voids exhibited by FFF-fabricated components. Inter-voids occur periodically as a result of raster spreading but the interfacial voids develop due to weak between neighbouring rasters.^47,48 The flexural behaviour of the fabricated specimens is affected by the presence of these voids, which can be reduced by adjusting the FFF process parameters appropriately. The size of voids is affected by several FFF parameters, such as infill pattern, layer thickness, nozzle diameter, air gap, build direction, infill percentage, and so on, and has an impact on the failure mechanism.

Figure 14.

Various kind of voids spotted in FFF-fabricated parts (a) Schematic diagram, (b) SEM image.

Figure 15 illustrates the dissimilar raster formation at different NDs. Due to change in ND, the raster width varied. At higher ND, the raster width is high resulting in higher tensile strength with a smaller number of voids and better raster to raster bonding, Figure 15(c). While, at lower ND, the raster width is lower resulting in low flexural strength due to more voids with separation and failure of individual rasters, Figure 15(a).

Figure 15.

Dissimilar raster formation at different NDs. (a) 0.2 mm (b) 0.4 mm, (c) 0.6 mm.

Analysis of variance

Using Taguchi’s L9 array DOE, Greater is better main effects plots for signal to noise ratios (SNRA) are produced by an ANOVA study of the process parameters with three levels each, namely IP which includes triangular (T), hexagonal (H) and rectilinear (R) pattern with the variation in ND viz 0.2 mm, 0.4 mm, and 0.6 mm over the target factor viz flexural strength of CF-PLA, CF-PETG, and MWCNTs-PLA specimens. The plots are illustrated in Figures 16, 17 and 18 for CF-PLA, CF-PETG, and MWCNTs-PLA, respectively. The MINITAB 21 programme is employed to analyse the experimental results.

Figure 16.

SNRA plots of the main effects of the process parameters on the flexural strength for CF-PLA.

Figure 17.

SNRA plots of the main effects of the process parameters on the flexural strength for CF-PETG.

Figure 18.

SNRA plots of the main effects of the process parameters on the flexural strength for MWCNTs- PLA.

CF-PLA

On the basis of the aforesaid rating, process elements that significantly affect the objective function may be found, and appropriate control actions may be taken. Figure 19 depicts the interaction plot to describe the behaviour of ND and IP for the flexural strength for CF-PLA specimens. Table 3 shows the % contributions of all two process parameters based on ANOVA. The p-value indicates that IP has the biggest influence on the flexural strength followed by ND for CF-PLA specimens. Flexural strength’s coefficient of determination (R²), which measures how much of the response’s overall variation is represented by the model’s components, is 97.71%.

Figure 19.

Interaction plots for the flexural strength for CF-PLA.

Table 3.

Analysis of variance for CF-PLA flexural strength.

Source	DF	Seq SS	Adj SS	Adj MS	F-value	p-value	Contribution
ND	2	0.9303	0.9303	0.4652	25.7700	0.0050	29.45%
IP	2	2.1570	2.1570	1.0785	59.7500	0.0010	68.27%
Residual error	4	0.0722	0.0722	0.0181			2.29%
Total	8	3.1595

S = 0.13, R ² = 97.71%, R ² (Adj) = 95.43%.

CF-PETG

Based on an ANOVA, Table 4 illustrates the % contributions of each of the two process parameters. For CF-PETG specimens, the p-value shows that IP has the greatest impact on flexural strength, followed by ND. Flexural strength has a coefficient of determination (R²) of 95.85%, which indicates how much of the entire alteration in the response is represented by the model’s elements. The flexural strength for CF-PETG specimens is represented by an interaction plot in Figure 20 that indicates how ND and IP respond.

Table 4.

Analysis of variance for CF-PETG flexural strength.

Source	DF	Seq SS	Adj SS	Adj MS	F-value	p-value	Contribution
ND	2	8.3899	8.3899	4.1950	42.8300	0.0020	88.96%
IP	2	0.6490	0.6490	0.3245	3.3100	0.1420	6.88%
Residual error	4	0.3918	0.3918	0.0979			4.15%
Total	8	9.4307

S = 0.31, R² = 95.85%, R² (Adj) = 91.69%.

Figure 20.

Interaction plots for the flexural strength for CF-PETG.

MWCNTs-PLA

The aforementioned rating can be used to determine process components that have a substantial influence on the target factor and identify the best course of action for control. Figure 21 illustrates the interaction plot to explain how ND and IP behaved in terms of flexural strength for MWCNTs-PLA specimens. Based on an ANOVA, Table 5 displays the % contributions of each of the two process parameters. For CF-PLA specimens, the p-value demonstrates that ND has the biggest influence on flexural strength, followed by IP. Flexural strength has a coefficient of determination (R²) of 96.61%, which specifies how much of the total variation in the response is represented by the model’s elements.

Figure 21.

Interaction plots for the flexural strength for MWCNTs-PLA.

Table 5.

Analysis of variance for MWCNTs-PLA flexural strength.

Source	DF	Seq SS	Adj SS	Adj MS	F-value	p-value	Contribution
ND	2	17.3273	17.3273	8.6636	45.7500	0.0020	77.59%
IP	2	4.2472	4.2472	2.1236	11.2200	0.0230	19.02%
Residual error	4	0.7574	0.7574	0.1894			3.39%
Total	8	22.3319

S = 0.44, R² = 96.61%, R² (Adj) = 93.22%.

The effect of variation in the process parameters, IP and ND, on the selected target factor, flexural strength, varies for each fabricating material. On analysing the effect of process factors on flexural strength, IP contributes 68.27% followed by ND for CF-PLA specimens, but for CF-PETG and MWCNTs-PLA specimens, the contribution of ND is 88.96% and 77.59%, respectively, trailed by IP. Therefore, the contribution of various factors differs from one filament material to the next; this may be because of the different types and distributions of reinforcing material in the polymer matrix.

Conclusion

The objective of this investigation was to comprehend and examine the flexural features of FFF-fabricated polymer composite materials CF-PLA, CF-PETG, and MWCNTs-PLA specimens in relation to variations in the selected process parameters - ND and IP. This study presents the appropriate material-parameter for higher flexural strength of the polymer composite specimens.

The results indicate that with the increment in ND, the specimens flexural strength increases. On augmenting ND from 0.2 mm to 0.6 mm, the maximum flexural strength enhancement achieved by CF-PETG specimens is 42.20% at triangular IP. For CF-PLA and MWCNTs-PLA specimens, the largest flexural strength improvement detected is 10.79% and 52.24%, respectively on increasing the ND from 0.2 mm to 0.6 mm at rectilinear IP.

The flexural properties of the parts fabricated through FFF process are directly impacted by IPs. For CF-PLA specimens, the highest flexural strength elevation observed is 17.04% on changing the IP from rectilinear to honeycomb at ND 0.2 mm. At ND 0.6 mm, for CF-PETG specimens, the greatest flexural strength improvement noticed is 11.22% on varying the IP from rectilinear to triangular, but for MWCNTs-PLA specimens, it upgraded by 34.83% when the IP modified from triangular to rectilinear.

Overall, the specimen with ND 0.6 mm and rectilinear IP for MWCNTs-PLA as the fabricating filament material exhibited the maximum flexural strength of 70.372 MPa due to the failure of individual rasters without separation including breaking and pullout of MWCNTs. Depending on the fabricating material, an alteration in a process parameter has diverse impact on the target factor. With all coefficients of determination values more than 95%, IP has the highest contribution of 68.27% for CF-PLA, but ND has the main contributions of 88.96% and 77.59% for CF-PETG and MWCNTs-PLA, respectively. In future, this research will assist the researcher and designers for creating the FFF-fabricated parts with better flexural behaviour of the functional parts for various applications.

Footnotes

Acknowledgements

The authors acknowledge the help from ACMS, IIT Kanpur, India for allowing to perform flexural testing. Support from FESEM lab, Department of Chemistry, DEI is highly appreciated for fractography analysis. We are also thankful to the grant received from AICTE (file no. 8-88/FDC/RPS (POLICY-1)/2019-20).

Declaration of conflicting interests

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

Funding

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

ORCID iDs

Akash Jain

Ankit Sahai

Rahul Swarup Sharma

References

Kehinde Aworinde

Oluropo Adeosun

Adekunle Oyawale

, et al. Parametric effects of fused deposition modelling on the mechanical properties of polylactide composites: a review. J Phys Conf Ser 2019; 1378: 022060. DOI: 10.1088/1742-6596/1378/2/022060

Liu

, et al. Mechanical performances of continuous carbon fiber reinforced PLA composites printed in vacuum. Compos Part B Eng 2021; 225: 109277. DOI: 10.1016/j.compositesb.2021.109277

Cabreira

Santana

RMC

. Effect of infill pattern in fused filament fabrication (FFF) 3D printing on materials performance. Rev Mater 2020; 25: 1–9. DOI: 10.1590/s1517-707620200003.1126

Sharma

Singhal

Gupta

. Innovative training framework for additive manufacturing ecosystem to accelerate adoption of three-dimensional printing technologies. 3D Print Addit Manuf 2018; 5: 170–179. DOI: 10.1089/3dp.2017.0003

Yadav

Singhal

Tyagi

, et al. Intensifying hands-on learning and experimentation of fused deposition modeling three-dimensional printers. Advances in Additive Manufacturing and Joining. Berlin, Germany: Springer, 2020, pp. 309–317. DOI: 10.1007/978-981-32-9433-2_27

Gebrehiwot

Espinosa Leal

Eickhoff

, et al. The influence of stiffener geometry on flexural properties of 3D printed polylactic acid (PLA) beams. Prog Addit Manuf 2021; 6: 71–81. DOI: 10.1007/s40964-020-00146-2

Kesavarma

Kong

Samykano

, et al. Bending properties of 3D printed coconut wood-PLA composite. IOP Conf Ser Mater Sci Eng 2020; 736: 052031. DOI: 10.1088/1757-899X/736/5/052031

Yadav

Angajala

Singhal

, et al. Evaluating mechanical strength of three dimensional printed PLA parts by free form fabrication. Mater Today Proc 2021; 46: 9498–9502. DOI: 10.1016/j.matpr.2020.03.557

Jaya Christiyan

Chandrasekhar

Venkateswarlu

. Flexural Properties of PLA components under various test condition manufactured by 3D printer. J Inst Eng Ser C 2018; 99: 363–367. DOI: 10.1007/s40032-016-0344-8

10.

Khan

Zakaria

Chong

, et al. Effect of infill on tensile and flexural strength of 3D printed PLA parts. IOP Conf Ser Mater Sci Eng 2018; 429: 012101. DOI: 10.1088/1757-899X/429/1/012101

11.

Chadha

Ul Haq

Raina

, et al. Effect of fused deposition modelling process parameters on mechanical properties of 3D printed parts. World J Eng 2019; 16: 550–559. DOI: 10.1108/WJE-09-2018-0329

12.

Heidari-Rarani

Ezati

Sadeghi

, et al. Optimization of FDM process parameters for tensile properties of polylactic acid specimens using Taguchi design of experiment method. J Thermoplast Compos Mater 2020; 35: 2435–2452. DOI: 10.1177/0892705720964560

13.

Yadav

Sahai

Sharma

.Experimental investigations for effects of raster orientation and infill design on mechanical properties in additive manufacturing by fused deposition modelling. Advances in Computational Methods in Manufacturing. Berlin, Germany: Springer, 2020, pp. 415–424. DOI: 10.1007/978-981-32-9072-3_36

14.

Priya

Naresh

Jayaganthan

, et al. A comparative study between in-house 3D printed and injection molded ABS and PLA polymers for low-frequency applications. Nanotechnology 2019; 6.

15.

Magri

A El

El Mabrouk

Vaudreuil

, et al. Mechanical properties of CF-reinforced PLA parts manufactured by fused deposition modeling. J Thermoplast Compos Mater 2021; 34: 581–595. DOI: 10.1177/0892705719847244

16.

Ristić

Miletić

Vukić

, et al. Characterization of electrospun poly(lactide) composites containing multiwalled carbon nanotubes. J Thermoplast Compos Mater 2021; 34: 695–706. DOI: 10.1177/0892705719857780

17.

Bajpai

Singh

Madaan

. Development and characterization of PLA-based green composites: A review. J Thermoplast Compos Mater 2014; 27: 52–81. DOI: 10.1177/0892705712439571

18.

Kaynak

Varsavas

. Performance comparison of the 3D-printed and injection-molded PLA and its elastomer blend and fiber composites. J Thermoplast Compos Mater 2019; 32: 501–520. DOI: 10.1177/0892705718772867

19.

Yadav

Sahai

Sharma

. Experimental studies on the mechanical behaviour of three-dimensional PLA printed parts by fused filament fabrication. J Inst Eng Ser D 2022, DOI: 10.1007/s40033-022-00403-4

20.

Mohapatra

Mohanty

Nayak

. Properties and characterization of biodegradable poly(lactic acid) (PLA)/poly(ethylene glycol) (PEG) and PLA/PEG/organoclay: a study of crystallization kinetics, rheology, and compostability. J Thermoplast Compos Mater 2016; 29: 443–463. DOI: 10.1177/0892705713518812

21.

Ajay Kumar

Khan

Mishra

. Effect of machine parameters on strength and hardness of FDM printed carbon fiber reinforced PETG thermoplastics. Mater Today Proc 2020; 27: 975–983. DOI: 10.1016/j.matpr.2020.01.291

22.

Mahesh

Joseph

Mahesh

, et al. Investigation on the mechanical properties of additively manufactured PETG composites reinforced with OMMT nanoclay and carbon fibers. Polym Compos 2021; 42: 2380–2395. DOI: 10.1002/pc.25985

23.

Ravi

Shiakolas

Welch

. Poly-L-lactic acid: pellets to fiber to fused filament fabricated scaffolds, and scaffold weight loss study. Addit Manuf 2017; 16: 167–176. DOI: 10.1016/j.addma.2017.06.002

24.

Shi

Xiao

Yang

, et al. Effects of physical aging on thermomechanical behaviors of poly(ethylene terephthalate)-glycol (PETG). Polym Technol Mater 2020; 59: 835–846. DOI: 10.1080/25740881.2019.1695273

25.

Kumar

Jamsarndorj

Jung

, et al. Vision-based human joint angular velocity estimation during squat and walking on a treadmill actions. Mater Today Proc 2021; 2021: 2186–2190. DOI: 10.1016/j.matpr.2020.10.078

26.

Calderón-Villajos

López

Peponi

, et al. 3D-printed self-healing composite polymer reinforced with carbon nanotubes. Mater Lett 2019; 249: 91–94. DOI: 10.1016/j.matlet.2019.04.069

27.

Cobos

Conejero

Fenollar

, et al. Influence of the addition of 0.5 and 1% in weight of multi-wall carbon nanotubes (MWCNTs) in poly-lactic acid (PLA) for 3D printing. Procedia Manuf 2019; 41: 875–881. DOI: 10.1016/j.promfg.2019.10.010

28.

Ferreira

Vale

Machado

, et al. Additive manufacturing of polyethylene terephthalate glycol/carbon fiber composites: an experimental study from filament to printed parts. Proceedings of the IMechE 2019; 233: 1866–1878. DOI: 10.1177/1464420718795197

29.

Yadav

Sahai

Sharma

. Flexural strength and surface profiling of carbon-based PLA parts by additive manufacturing. J Inst Eng Ser C 2021; 102: 921–931. DOI: 10.1007/s40032-021-00719-2

30.

Lubombo

Huneault

. Effect of infill patterns on the mechanical performance of lightweight 3D-printed cellular PLA parts. Mater Today Commun 2018; 17: 214–228. DOI: 10.1016/j.mtcomm.2018.09.017

31.

Rejab

MRM

Kumar

, et al. Effect of infill pattern, density and material type of 3D printed cubic structure under quasi-static loading. Proc Inst Mech Eng Part C J Mech Eng Sci 2021; 235: 4254–4272. DOI: 10.1177/0954406220971667

32.

Buj-Corral

Bagheri

Domínguez-Fernández

, et al. Influence of infill and nozzle diameter on porosity of FDM printed parts with rectilinear grid pattern. Procedia Manuf 2019; 41: 288–295. DOI: 10.1016/j.promfg.2019.09.011

33.

Baich

Manogharan

Marie

. Study of infill print design on production cost-time of 3D printed ABS parts. Int J Rapid Manuf 2015; 5: 308–319.

34.

Belouettar

Abbadi

Azari

, et al. Experimental investigation of static and fatigue behaviour of composites honeycomb materials using four point bending tests. Compos Struct 2009; 87: 265–273. DOI: 10.1016/j.compstruct.2008.01.015

35.

Nur Farhan Saniman

Reshid

Azhar Harimon

, et al. Flexural properties evaluation of additively manufactured components with various infill patterns. Int J Adv Sci Technol 2020; 29: 4646–4657.

36.

Zandi

Jerez-Mesa

Lluma-Fuentes

, et al. Experimental analysis of manufacturing parameters’ effect on the flexural properties of wood-PLA composite parts built through FFF. Int J Adv Manuf Technol 2020; 106: 3985–3998. DOI: 10.1007/s00170-019-04907-4

37.

Kam

İpekçi

Şengül

. Investigation of the effect of FDM process parameters on mechanical properties of 3D printed PA12 samples using Taguchi method. J Thermoplast Compos Mater 2021; 36: 307–325. DOI: 10.1177/08927057211006459

38.

Ahmad

Ishak

Mohammad Taha

, et al. Application of taguchi method to optimize the parameter of fused deposition modeling (FDM) using oil palm fiber reinforced thermoplastic composites. Polymers (Basel) 2022; 14: 2140. DOI: 10.3390/polym14112140

39.

İpekçi

Ekici

. Experimental and statistical analysis of robotic 3D printing process parameters for continuous fiber reinforced composites. J Compos Mater 2021; 55: 2645–2655. DOI: 10.1177/0021998321996425

40.

Taborda-Ríos

López-Botello

Zambrano-Robledo

, et al. Mechanical characterisation of a bamboo fibre/polylactic acid composite produced by fused deposition modelling. J Reinf Plast Compos 2020; 39: 932–944. DOI: 10.1177/0731684420938434

41.

Jain

Mishra

Dubey

, et al. Mechanical characteristics and failure morphology of FFF-printed poly lactic acid composites reinforced with carbon fibre, graphene and MWCNTs. J Thermoplast Compos Mater 2022; 089270572211330, DOI: 10.1177/08927057221133089

42.

Atakok

Kam

Koc

. Tensile, three-point bending and impact strength of 3D printed parts using PLA and recycled PLA filaments: a statistical investigation. J Mater Res Technol 2022; 18: 1542–1554. DOI: 10.1016/j.jmrt.2022.03.013

43.

Kumar

Singh

, et al. On investigations of thermal conductivity, circumferential compressive strength, and surface characterization of 3D-printed hybrid blended magnetostrictive PLA composite. J Thermoplast Compos Mater 2022; 35: 631–650. DOI: 10.1177/0892705720907651

44.

Singh

, et al. Investigations for tensile, compressive and morphological properties of 3D printed functional prototypes of PLA-PEKK-HAp-CS. J Thermoplast Compos Mater 2021; 34: 1408–1427. DOI: 10.1177/0892705719870595

45.

Singh

Kumar

, et al. On 3D-printed ZnO-reinforced PLA matrix composite: tensile, thermal, morphological and shape memory characteristics. J Thermoplast Compos Mater 2020; 35: 1510–1531. DOI: 10.1177/0892705720935961

46.

Maguluri

Suresh

Rao

. Assessing the effect of FDM processing parameters on mechanical properties of PLA parts using taguchi method. J Thermoplast Compos Mater 2021; 36: 1472–1488. DOI: 10.1177/08927057211053036

47.

Papon

Haque

. Tensile properties, void contents, dispersion and fracture behaviour of 3D printed carbon nanofiber reinforced composites. J Reinf Plast Compos 2018; 37: 381–395. DOI: 10.1177/0731684417750477

48.

Gupta

Shet

, et al. Microstructure and mechanical performance examination of 3D printed acrylonitrile butadiene styrene thermoplastic parts. Polym Eng Sci 2020; 60: 2770–2781. DOI: 10.1002/pen.25507

Comparing the flexural and morphological properties of dissimilar FFF-fabricated polymer composites

Abstract

Keywords

Introduction

Material and methods

Result and discussion

Effect of nozzle diameter

CF-PLA

CF-PETG

MWCNTs-PLA

Effect of infill pattern

CF-PLA

CF-PETG

MWCNTs-PLA

Failure morphology

CF-PLA

CF-PETG

MWCNTs-PLA

Analysis of variance

CF-PLA

CF-PETG

MWCNTs-PLA

Conclusion

Footnotes

Acknowledgements

Declaration of conflicting interests

Funding

ORCID iDs

References