On fabrication of acrylonitrile butadiene styrene-zirconium oxide composite feedstock for 3D printing-based rapid tooling applications

Abstract

The 3D-printed rapid tools are being used in finishing operations such as drilling, milling, broaching, roller burnishing, and other finishing operations that need anti-wear plastic composite materials. Zirconium oxide (ZrO₂) is one of the ceramic materials which is highly appreciated due to its anti-wear properties. This study aims to develop the ZrO₂ ceramic particles reinforced acrylonitrile butadiene styrene (ABS) thermoplastic composite feedstock filaments for 3D printing of rapid tools. In the first stage, the multiple numbers (as per Taguchi L₉ orthogonal array (OA)) of ABS-ZrO₂ feedstock filaments were developed by varying the loading of ZrO2 in ABS matrix (2 wt.%, 4 wt.%, and 6 wt.%), processing temperature (200, 205 and 210°C), and rotation speed of screw (4, 6 and 8 RPM). The optimum setting obtained for manufacturing ABS-ZrO₂ composite feedstock filaments is the combination of 2% ZrO2 loading, 205°C processing temperature, and 6 RPM screw speed. In the next stage, fused filament fabrication (FFF) based 3D printing has been used to prepare the rapid tools. The wear test performed for 3D printed ABS-ZrO₂ composites rapid tools shows only .62% weight loss which is lower as compared to virgin ABS (.91% weight loss). The results of the study are supported by fracture analysis, morphology, and mechanical properties.

Keywords

Fused filament fabrication wear test tensile test hardness reinforcement feedstock filament

Introduction

Additive Manufacturing (AM) is a rapidly emerging technology for 3D structure fabrication by using a layer-by-layer deposition process of filament form or powdered molten material.¹ Several advantages of AM include (a) easy manufacturing of intricate geometrical shapes, (b) shorter manufacturing lead times (c) ability to prepare lattice structures within the desired part to reduce its weight, (d) less energy consumption (e) less waste material, and cheap cost.² Moreover, additively manufactured composites exclude the process of coating workpieces and can produce near-to-net shape materials which do not require machining in manufacturing a cutting tool, where microhardness and abrasion resistance are desired properties.³

In the field of AM, fused deposition modeling (FDM) also called FFF is one of the low-cost 3D printing processes that has been used in every area of applications.⁴ The process of FDM requires thermoplastic fibers, which are heated and then expelled, layer by layer, to fabricate a 3D product.⁵ There are two types of material utilized in FDM plastics; firstly, the modeling material that comprises the finished object, and secondly, the support material that acts as scaffolding to provide support to the object during its printing.⁶ FDM-processed thermoplastics, such as polylactic acid (PLA) and ABS, are the most used polymer in this regard,⁷ However, the parts developed by FDM have great applications in rapid prototyping, but the inadequate physical properties restrict their practical applications.⁸ Therefore, various varieties of alternate FDM filament materials have been developed to improve the physical properties of the final part and reduce its running cost which leads to enhancement in the scope of this technique. In this regard, ceramics has attracted the researcher’s attention due to their unique applications, such as wear-resistance applications, in electronic devices, high-performance vehicles, and next-generation aircraft, benefiting from their chemical stability, high hardness, and functional properties.^9–11 However, modern computer numeric control (CNC) based manufacturing has high efficiency in machining ceramic-based products, the process faces some restrictions for the fabrication of ceramics with intricate shapes.¹² Regarding FDM, the fabrication of novel FDM materials based on ceramics or metals is a tedious task because of the requirement of specific properties (size, mechanical and rheological characteristics) of filament used in the FDM system.¹³

A general approach used to enhance the characteristics of FDM parts comprises using polymers with good properties (such as liquid crystalline polymers and poly-aryl-ether-ketone) and mixing the filler material or ceramic powder within the neat polymers.¹⁴ For this purpose, FFF is most widely used for component fabrication beyond commercial material usage. This is due to the comparatively simple printer setup and low cost of the printer. In this direction, prepared feedstock filaments for the FDM 3D printer by mixing PLA at different carbon nanotubes (CNT) weight percentages and observed that the application of 5% CNTs enhanced Young’s modulus by 30%, but reduced the tensile strength and overall toughness of the FDM parts.¹⁵ Further, a lot of polyamide-based composites have been also designed to manufacture products for tribological applications. The previous researchers achieved excellent mechanical, physical, and tribological characteristics by using ultra-high molecular weight polyethylene (UHMWPE) for the implementation to produce parts for friction units by additive manufacturing.¹⁶ Recently, some researchers used ceramic-and polymer granulates as the feedstock for AM of ZrO₂ ceramics by FDM.¹⁷ To manufacture ZrO₂-based products, the FFF process has been used to create a Low-density polyethylene (LDPE) and wax binder system.¹⁸ It was demonstrated that a 50% of volume ZrO₂ feedstock loaded with low melt viscosity values is appropriate for FFF printing. Till now, different ceramic-like mullite,¹⁹ Silicon tetrachloride or tetrachlorosilane (Si₃N₄),²⁰ and ZrO₂²¹ were prepared by using filaments as feedstock. There is still a need of identifying the tribological properties of FDM-printed ABS-ZrO₂ composite parts for fabricating new formulations for 3D printing.

A lot of recent studies have focused on ABS-ZrO₂ composites because of their improved mechanical, thermal, and electrical characteristics.²² However, problems still exist in establishing the best interfacial adhesion and dispersion between ABS and ZrO₂ nanoparticles. Electrical conductivity can be affected, mechanical strength can be decreased, and thermal stability can be negatively impacted by poor interfacial bonding.²³ It was investigated Several approaches to overcome these problems, including surface modification of ZrO₂ nanoparticles, compatibilizer inclusions, and enhanced processing methods. For ABS-ZrO₂ composites to reach their full potential, it is still necessary to achieve a homogenous dispersion, create a strong interfacial contact, and balance the characteristics of ABS and ZrO₂.²⁴ Further studies are necessary to advance their development and widen their applications. Lots of reinforcements added in the ABS for thermoplastic composite feedstock filament preparation are extensive. To improve the mechanical characteristics of ABS-based composites, researchers have looked at the insertion of different reinforcements such as carbon fibers, glass fibers, nanofillers, and nanoparticles.^25,26 Enhancing strength, stiffness, toughness, and thermal stability are the goals of these reinforcements. Achieving homogeneous dispersion of reinforcements within the ABS matrix, preserving good interfacial adhesion between the matrix and reinforcements, optimizing processing parameters, and addressing potential problems like filament breakage or nozzle clogging during 3D printing are obstacles that researchers must overcome.^27,28 The development of high-performance ABS-based composite filaments for diverse applications must successfully overcome these obstacles. ABS is known for its toughness and impact resistance, while ZrO₂ possesses high hardness and excellent wear resistance.²⁹ The combination of ABS and ZrO₂ in the composite material can enhance wear properties due to their complementary characteristics, resulting in improved durability and reduced wear. Based on previous literature, observed that rpm and temperature are the most important factors for feedstock filament fabrications.³⁰

Based on the literature review, it has been observed that several research works is performed for enhancing the hardness of polymers by adding different fillers or metallic powder in different thermoplastic polymers. But hitherto, very less has been reported on the reinforcement of ZrO₂ in ABS polymers using an extrusion process which may be used for rapid tooling applications. In this study, the mechanical, physical, morphological, and wear properties of fabricated composite feedstock filaments have been investigated using a Taguchi L₉ (3^∧3) OA. Further, the tribological properties have been investigated on the 3D printed ABS-ZrO₂ composite structures as the rapid tools.

Materials and Method

In this research work, ZrO₂ particles (particles size (20–50 μm)) (Shiva Chemical, Ludhiana, India) have been reinforced with ABS thermoplastic (Procured from Batra Polymers, Ludhiana, India) using an extrusion process. A single screw extrusion system (Manufacturer; Felfil, Italy, maximum temperature: 300°C) was used for the preparation of composite feedstock filaments. Based upon the literature review, three main input factors (compositions of ABS + ZrO₂, extrusion temperature, and screw speed (in RPM)) have been selected which are shown in Table 1 with their three different levels. Based on the pilot experimentations, it was observed that 8 wt. % ZrO2 was loaded in ABS without affecting the dimensional and flow properties. However, on the mechanical properties concerns, the maximum loading of 6% ZrO₂ in ABS was selected. Three different compositions of ABS + ZrO₂ have been selected (98 + 2; 96 + 4 and 94 + 6) according to their weight percentage whereas temperature has been varied between 200 to 210°C, and RPM is selected as 4, 6, and 8 setups (Table 1). The parameters and their levels have been judicially selected as per the observations made during pilot experimentation. It has been noticed that beyond selected levels, the dimensions of the filaments were not uniform.

Table 1.

Selected factors with their different levels.

Factors	Level 1	Level 2	Level 3
Compositions (ABS + ZrO₂) (by wt. %)	98 + 2	96 + 4	94 + 6
Temperature (in °C)	200	205	210
RPM	4	6	8

Based on Table 1, Taguchi L9 (3^∧3) OA has been selected for fabrication of the design of experimentation (DOE). According to Taguchi L9, an OA total of nine experiments has been designed which is shown in Table 2.

Table 2.

Selected factors with their different levels.

Experiment run no	Compositions (ABS + ZrO₂) (by wt. %)	Temperature (in °C)	Screw rotational speed (RPM)
1	98 + 2	200	4
2	98 + 2	205	6
3	98 + 2	210	8
4	96 + 4	200	6
5	96 + 4	205	8
6	96 + 4	210	4
7	94 + 6	200	8
8	94 + 6	205	4
9	94 + 6	210	6

Based on Tables 1 and 2, a total of nine sets of feedstock filaments have been prepared using a single screw extruder which is shown in Figure 1.

Figure 1.

Feedstock filament fabrication process of ABS-ZrO₂ composite using an extrusion process.

Experimentation

Feedstock fabrication

ABS thermoplastic polymers (in granules form) (dia: 1.5–2 mm) have been reinforced with ZrO₂, (99% pure powder (Make: Indian Platinum Private Limited, India)) (max. limit up to 300°C). Initially, ZrO₂ particles have been mechanically mixed with ABS thermoplastic polymer. In the next stage, nine different sets of feedstock filaments have been fabricated with a diameter range of 1.75 mm ± .10 mm using a single screw extruder according to Table 2. In Figure 2, 9 different types of fabricated reinforced feedstock filaments have been shown.

Figure 2.

ABS-ZrO₂-based fabricated feedstock filaments using a single screw extruder.

Tensile Testing

Tensile testing has been carried out on a universal tensile tester (UTT) (Make; Shanta Engineering, Pune, India; maximum capacity: 5000N) with a strain rate of 20 mm/min after the fabrication of feedstock filaments (Figure 3). The procedure of ASTM D638 has been followed for the tensile testing of composite feedstock filaments, as there is no ASTM standard is available for filament testing.

Figure 3.

Working procedure of UTT for ABS-ZrO₂ composite feedstock filaments.

3D printing and wear analysis

After tensile testing, optimization has been performed using Minitab statistical software (Version 17.00) for obtaining the best setting of each important factor for the fabrication of feedstock filament that has better mechanical strength. After optimization of process parameters, scanning electron microscope (SEM) and optical analysis were performed on the best and worst samples according to tensile strength.

To 3D print cylindrical pins for wear testing and examine the wear-resistant properties of the chosen material composition in contrast to commercial ABS material, the manufactured feedstock filaments were fed into a FFF printer. Pin-on-disc parameters were set for 0.42 m/s sliding velocity, an 80 mm track diameter, a 50 N applied load, and a 10-min of testing period for a single pin at 100 rpm disc speed. Lastly, wear test analysis was performed on ABS thermoplastic polymer-based virgin pins and reinforced pins with ZrO₂.

Multifactor optimization

A multifactor optimization process was applied to tensile results (Young’s modulus, strength at peak, and Modulus of toughness) using Minitab statistical software (Version 19.00) for obtaining the best settings. By providing equal weights of each component of the tensile result best setting for the fabrication of composite feedstock filaments has been determined.

Morphological Analysis

Morphological (optical and SEM) analysis has been performed after tensile testing on all the fabricated composite feedstock filaments as per Table 2. To investigate the fracture of feedstock filaments, an optical photomicroscope (Model No. SMZ745T; Manufacturer: Nikon) was used. The surface roughness was measured using “Gwyddion software version 2.60”. After optical and tensile testing of all the samples, SEM analysis has been performed on the best and worst samples based on tensile strength. The SEM was utilized to examine the reinforcement of Zr with ABS thermoplastic polymers. Furthermore, energy-dispersive X-ray spectroscopy (EDS) was done on the fractured part of feedstock filaments on only the best and worst samples to determine the actual reason for feedstock filament strength. The SEM and EDS tests were carried out under a vacuum with the SEM system (Make: Jeol: IT500) and a 15V power source. The microstructure of the fabrics was photographed at magnifications of ×100 and ×200. When studying fractured parts of feedstock filaments, EDS can provide information about the distribution of elements and the presence of impurities or foreign materials within the material. EDS may also guide material design, process optimization, and quality control efforts to enhance performance and reliability.

XRD Analysis

XRD Analysis of virgin ABS, Zr, and their composite was analyzed using an “X-ray diffractometer” (Model No.: D8 ADVANCE ECO; Make: Bruker Scientific Instruments, Billerica, Massachusetts, USA). For this experimentation, the small size of materials is placed in a sample holder with a plain surface area and positioned in the center of the XRD machine where an x-ray is deposited on the sample and reflected on the other side. By using “DIFFRAC Measurement Center” (Version V7.3.1), software data were recorded and saved in .brml, and .raw file format and were analyzed using “DIFFRAC.WIZARD” software with the following measuring conditions. The Cu-alpha radiation source was operated at 40 kV/25 mA. k-β filter was used to eliminate the interference peak. The diffraction pattern appeared in the 2θ range from 5° to 90° with a scan speed of 3°/min and a scan step of .04°. The divergence and anti-scatter slits were .600 mm and 5.100 mm, respectively (See Table 3).

Table 3.

Detailed measurement parameters of XRD setup.

Serial no	Factors	Specifications
01	Scan type	Coupled two-theta/theta
02	Anode	Cu
03	Divergence slit	.600 mm
04	Scan mode	Continuous PSD fast
05	Start	05°
06	End	90°
07	Scan speed	3°/min
08	Step size	.04°
09	Temperature	22°C
10	Generator mA	25.0 mA
11	Generator kV	40.0 kV
12	Slit mode	Fixed
13	Anti-scatter slit	5.100

Results and discussion

Mechanical properties

After filament extrusion (for selection of the composition of materials) at a predefined level of process variables, feedstock filament wire has been prepared as per Taguchi L9 (3^3) OA. The results for the different output parameters (Young’s modulus, Peak Strength, and Modulus of Toughness) along with signal-to-noise ratio (SNRA) is shown in Table 4. As per the results of the tensile testing, the best filament is sample 2 (based on Peak strength) and the worst filament is sample 7. Accordingly, further investigations have been made on sample two and sample seven for SEM, EDS, and wear analysis.

Table 4.

Results output of tensile strength with their SNRA.

Experiment run no	Young’s modulus (in MPa)	Peak strength (in MPa)	Modulus of toughness (in MPa)	SNRA for young’s modulus	SNRA for strength at peak	SNRA for modulus of toughness
1	304.76	19.20	.62	12.78	25.67	−4.15
2	289.52	24.32	1.02	12.33	27.72	.17
3	262.82	20.50	.80	11.49	26.23	−1.93
4	281.52	18.58	1.73	12.09	25.38	4.76
5	116.55	20.28	1.67	04.43	26.14	4.45
6	212.00	12.72	.36	09.62	22.09	−8.87
7	199.47	11.37	.31	09.10	21.11	−10.17
8	241.00	14.46	.41	10.74	23.20	−7.74
9	197.00	11.82	.35	08.99	21.45	−9.12

According to Table 4, it has been observed that experiment run no. 01 is the maximum value of Young’s Modulus whereas experiment run no. 2 and 4 are the maximum value of peak strength and Modulus of Toughness respectively. Table 4 shows the different output results of the tensile strength of composite feedstock filaments along with their SNRA. The stress versus strain diagram is shown in Figure 4 of all the feedstock filaments that have been fabricated according to Table 2 during tensile testing.

Figure 4.

Stress versus strain diagram of fabricated feedstock filaments tensile testing.

Peak Strength

Figure 5 shows the main effects plot for SNRA of peak strength output parameter (for larger the better type case). As per the calculation of SNRA, it was predicted that the best setting for maximum peak strength is a combination of 98 + 2 (ABS + ZrO₂) weight composition, 205°C of barrel temperature, and 6 RPM of a single screw extruder.

Figure 5.

Main effects plot for SNRA of peak strength.

Table 5 shows the response table for SNRA for larger is the better type for peak strength.

Table 5.

Response table for SNRA of peak strength (larger is better).

Level	Compositions (ABS + ZrO2)	Temperature	RPM
1	26.54	24.05	23.65
2	24.54	25.69	24.85
3	21.92	23.26	24.50
Delta	4.62	2.43	1.20
Rank	1	2	3

As shown in Table 6, the residual error was 5.55%. It shows that the model has a higher degree of accuracy. Further, it has been observed that compositions (ABS + ZrO2) were the most significant parameter contributing 69.61%. Respectively, the temperature and rotational speed of the barrel screw were less significant which contributes 19.92% and 4.92%. Finally, the calculated value for peak strength is 26.36 MPa, which is close to the experimentally observed value. For this ANOVA analysis, confidence levels are taken as 95%.

Table 6.

Results output analysis of variance for SNRA.

Source	DF	Seq SS	Adj SS	Adj MS	F	p	% age contribution
Compositions (ABS + ZrO₂)	2	32.154	32.154	16.077	12.55	.074	69.61
Temperature	2	9.202	9.202	4.601	3.59	.218	19.92
RPM	2	2.272	2.272	1.136	.89	.530	04.92
Residual error	2	2.562	2.562	1.281			05.55
Total	8	46.191

For single optimization, the following formula was used:

η_{o p t} = C + (C_{A 1} - C) + (C_{B 2} - C) + (C_{C 2} - C)

Where, C is the overall mean of SNRA, C_A1, C_B2, _and C_C2 are the mean of SNRA data for the composition of materials, barrel temperature, and, rpm of the rotating screw at levels 1, 2, and 2 respectively.

The overall mean SNRA (C) was calculated as per Table 4.

C = 24.33

Now,

C_{A 1} = 26.54, C_{B 2} = 25.69, a n d C_{C 2} = 24.85 (f r o m t h e r e s p o n s e t a b l e o f S N R A)

From here,

η_{o p t} = 24.33 + (26.54 - 24.33) + (25.69 - 24.33) + (24.85 - 24.33)

η_{o p t} = 28.42 d b

N o w, y_{{o p t}^{2}} = {(10)}^{η_{o p t} / 10} (F o r, l a r g e r b e t t e r t y p e s)

y_{{o p t}^{2}} = {(10)}^{28.42 / 10}

y_{o p t} = 26.36 M P a

Here, the optimum value of peak strength has been obtained 26.36 MPa on the predicted setting of extrusion. On the predicted setting, the experimentation was conducted again to check the accuracy of the optimization process. The experimental value was obtained 25.10 MPa which is close to the calculated value.

Young’s modulus and modulus of toughness

Similar to peak strength, optimization was also performed for Young’s modulus and Modulus of toughness. The main effects plot for SN ratios for Young’s Modulus and Modulus of Toughness (larger is the better type case) are shown in Figure 6. As per the results of Young’s Modulus, the combination of 98 + 2 (ABS + ZrO₂) weight composition ratio, working temperature of 200°C and 6 RPM single screw extruder is the optimized setting. Similarly, the modulus of toughness was optimized with a combination of 96 + 4 (ABS + ZrO₂) weight composition, 205°C working and 6 RPM of a single screw extruder.

Figure 6.

Main effects plot for SNRA of young’s modulus and modulus of toughness. (a) Main effects plot for SNRA of young’s modulus (b) main effects plot for SNRA of modulus of toughness.

Multifactor Optimizations

Multifactor optimization was employed in tensile testing to enhance the understanding and characterization of material behavior under complex loading conditions. By applying multi-factor optimization, the optimal combination of these factors would yield the desired mechanical properties, such as peak strength, Young’s modulus and modulus of toughness. This approach allows for a more comprehensive analysis of the material’s response, enabling the development of robust and efficient design criteria for various applications. By considering multifactor optimization all the factors of tensile testing are included with equal weightage. For better-optimized results; multifactor optimization analysis has been performed on all the components of tensile testing (Young’s modulus, peak strength, and modulus of toughness) shown in Table 4. Based upon multi-factor optimization predicted setting and composite desirability are shown in Figure 7. Based upon Table 7 and Figure 7 it has been shown that the best-predicted settings for fabrication of feedstock filaments with the 98% of ABS and 2% of ZrO₂ compositions and working temperature for fabrication of feedstock filaments at 205°C and rotational speed of rotating speed of screw in the barrel at 6 no. of setup with composite desirability ‘.9308’ of the proposed model.

Figure 7.

Multi-factor optimization plot of tensile test for composite feedstock filaments.

Table 7.

Results output ANOVA for SNRA.

Solution	Compositions (ABS + ZrO₂)	Temperature	RPM	Fit SNRA for modulus of toughness	Fit SNRA for young’s modulus	Fit SNRA for peak strength	Composite desirability
1	98 + 2	205	6	2.8399	49.0565	28.4116	.9308

Composite desirability analysis provides a systematic and quantitative approach to decision-making by considering multiple criteria simultaneously. The composite desirability is very close to one which shows the degree of accuracy is very high for this multifactor optimization analysis. The maximum achievable composite desirability depends on various factors, such as the specific criteria and goals of the process but in this research work, it goes up to 1. Factors that can decrease the value of the desirability function include limitations in resources, technical constraints, and conflicting objectives.

Morphological analysis

After mechanical testing, the morphological analysis was performed on all the fabricated feedstock filament samples using an optical microscope at ×50 magnification power (Figure 8). According to Figure 8, it was observed that ZrO₂ particles were uniformly reinforced in all the fabricated feedstock filaments. It was also noticed that sample no. 1 to sample no. 5 is denser in all sector whereas sample six to sample nine are less dense which also support the tensile strength results of the composite feedstock filaments.

Figure 8.

Optical image of a fractured sample of the tensile sample at ×100 magnifications. (a) 1 (b) 2 (c) 3 (d) 4 (e) 5 (f) 6 (g) 7 (h) 8 (i) 9.

For a detailed analysis of the fractured surface of all the feedstock filaments, 3D rendering analysis, and surface roughness analysis have been performed that as shown in Figure 9. Surface roughness testing is performed on fractured parts of feedstock filaments to analyze the quality of the fracture surface. It provides valuable information about the material’s strength, structural integrity, and manufacturing process. Higher surface roughness can introduce stress concentration points, leading to reduced tensile strength. However, an optimal level of roughness can enhance interlayer bonding, increasing tensile strength. Factors such as material composition, extrusion parameters, and post-processing techniques also influence the final tensile strength.

Figure 9.

3D rendering image and surface roughness image of fractured part of feedstock filaments.

According to Figure 9 (3D rendering image), it was observed that surface roughness is not much uneven and it varies from 4.67 μm to 8.77 μm which is acceptable for the fabrication of feedstock filaments. Based on Figure 9, It is observed that surface roughness is less in sample no. 2 (4.67 μm), which also supports the tensile strength of the sample.

After optical analysis, for better internal structure and details SEM and EDS analysis was performed on best and worst according to tensile testing that is shown in Figure 10.

Figure 10.

SEM image and EDS analysis of best and worst feedstock filaments. (a) SEM image of best feedstock filament at ×100 (b) SEM image of worst feedstock filament at ×100 (c) EDS analysis of best feedstock filament (d) EDS analysis of worst feedstock filament.

According to Figure 10(a) and (b) it was observed that small particles of ZrO₂ are properly reinforced in ABS thermoplastic polymer. Small particles of ZrO₂ are highlighted with a black circle in Figure 10(a) and (b) that have been taken at ×100 magnification. Further EDS analysis has been done on the best and worst samples to observe the distribution of ZrO₂ in ABS-based feedstock filaments. According to EDS analysis, it is observed that 1.49% Zr is present in the best composite feedstock filaments according to weight percentage, whereas only .10% Zr is present in the worst sample according to tensile testing. EDS analysis supports the tensile test results because more amount of ZrO₂ is present in the best sample (experiment run no. 2) as compared to the worst sample (experiment run no. 7).

Some other properties such as crystallinity and amorphous percentage are present in fabricated composite feedstock filament as compared to virgin ABS thermoplastic polymers and ZrO₂. XRD graphs of virgin ABS, ZrO_2, and fabricated feedstock filament (sample no. 2) are shown in Figure 11.

Figure 11.

XRD plots of virgin ABS, ZrO_2, and composite feedstock filament.

According to Figure 11, it was observed that virgin ABS thermoplastic polymers are a very less peak (only 1) and are very close to a flat surface indicating the crystallinity of the materials is very low which is also mentioned in Table 8. According to the XRD plot of ZrO₂ powder, it has been observed that there are lots of sharp peaks present between 25° to 90° showing that higher crystallinity percentage (see Table 8). Finally, it was observed that from XRD plots of composite materials of ABS and ZrO₂ powder higher peaks as compared to ABS and lower no. of peaks and also fewer sharp peaks as compared to ZrO₂ powder, which indicates a medium percentage of crystallinity (see Table 8).

Table 8.

Crystallinity and amorphous percentage using XRD.

Materials	Crystallinity (in % age)	Amorphous (in %age)
ABS polymer	17.60	82.40
ZrO₂	69.60	30.40
Composite (ABS + ZrO₂)	34.70	65.30

Based on Table 8, It has been observed that the crystallinity value of ABS polymer is near 17.60%, ZrO₂ powder is near 69.60% and composite materials are 34.70%. This result shows that reinforcement of ZrO₂ powder into ABS thermoplastic polymers increases the crystallinity value of composite materials that’s why the hardness of the materials is improved. In this research work degree of crystallinity was obtained from XRD analysis. The degree of crystallinity is determined by comparing the intensity of the diffracted X-rays from the crystalline regions to those from the non-crystalline or amorphous regions in the sample. By quantifying the ratio of crystalline to non-crystalline components, the degree of crystallinity can be obtained. Crystallinity has a significant impact on its physical characteristics. A polymer’s chains are more regularly aligned the more crystalline whereas more irregularity in alignment is more amorphous. Hardness and density rise as crystallinity increases.

Wear Analysis

Due to the reinforcement of ZrO₂ in ABS thermoplastic materials tensile strength was increased, so further wear test was performed on virgin ABS, best and worst sample pins. The wear track graphs of all three samples were tracked on emery paper as shown in Figure 12. According to Figure 12, it was observed that in the ABS wear track graph density of ABS polymers is more whereas the density of the best sample is less as compared to both, which is also reflected in Table 9. Table 9 shows the weight loss of all the samples (virgin ABS, best and worst sample) during wear test analysis.

Figure 12.

Wear track graph of ABS polymer, best and worst sample composite materials.

Table 9.

Wear test analysis data of virgin ABS, best and worst sample.

Sr No	Sample name	Initial weight (in gm)	Final weight (in gm)	Weight loss (in gm)	%age weight loss, %
1	Virgin ABS	1.8724	1.8554	.0170	.91
2	Best sample	1.9543	1.9422	.0121	.62
3	Worst sample	1.9456	1.9297	.0159	.82

According to Table 9, it was observed that the maximum weight loss during wear test analysis in virgin ABS (.0170 gm) and minimum weight loss in the best sample according to tensile testing (.0121 gm) which supports the tensile testing results. Based on Tables 4 and 9, it was observed that sample no. 2 is the best as per tensile and wear test, this is due to the better mixing of ZrO₂ in ABS thermoplastic polymers. So, for manufacturing wear-based products, it should be manufactured at the composition of 2% ZrO₂ in ABS thermoplastic polymers at the barrel temperature of 205°C at the rotational speed of the barrel of a single screw extruder setting 6.

Conclusions

In this research work, ZrO₂ powder was reinforced in ABS thermoplastic polymers using an extrusion process for the enhancement of wear properties in composite materials. Different tests (tensile testing, morphological testing, XRD, and wear test analysis) were performed, and the following result has been obtained.

• Based on tensile testing and multi-factor optimization, it was concluded that fabricated composite feedstock samples of ABS and ZrO₂ powder are best with the composition of 98% ABS and 2% ZrO₂ at 205°C barrel temperature at 6 no. of RPM.

• Based on SEM and XRD analysis, it was concluded that ZrO₂ powder is equally distributed in fabricated composite feedstock filaments through SEM analysis. According to XRD analysis, it has concluded that the crystallinity value of composite feedstock filament is increased as compared to virgin ABS which shows better hardness.

• Lastly, according to wear test analysis, it was observed that in sample no. 2 wear losses are minimum as compared to virgin ABS, and the worst sample that supports the tensile testing results and shows the improvement of hardness properties in fabricated materials.

Footnotes

Acknowledgements

The authors are highly thankful to the Center for Manufacturing Research, GNDEC, Ludhiana, and University Center for Research and Development, Chandigarh University for technical/financial assistance.

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

Nishant Ranjan

Rashi Tyagi

Ranvijay Kumar

References

Gardan

. Additive manufacturing technologies: state of the art and trends. Addit Manuf 2017; 19: 149–168.

Yao

Wang

. Improved surface of additive manufactured products by coating. J Manuf Process 2016; 24: 212–216.

Prakash

Nancharaih

Rao

. Additive manufacturing techniques in manufacturing-an overview. Mat Today: Proc 2018; 5(2): 3873–3882.

Mustapha

Metwalli

. A review of fused deposition modelling for 3D printing of smart polymeric materials and composites. Eur Polym J 2021; 156: 110591.

Valino

Dizon

Espera

Jr , et al. Advances in 3D printing of thermoplastic polymer composites and nanocomposites. Prog Polym Sci 2019; 98: 101162.

Wang

. A critical review of the use of 3-D printing in the construction industry. Autom 2016; 68: 21–31.

Manoj

Bhuyan

Banik

, et al. Review on particle emissions during fused deposition modeling of acrylonitrile butadiene styrene and polylactic acid polymers. Mat Today: Proc 2021; 44: 1375–1383.

Chohan

Singh

. Pre and post processing techniques to improve surface characteristics of FDM parts: a state of art review and future applications. Rapid Prototyp J 2017; 23(3): 495–513.

Rathod

Kumar

Jain

. Polymer and ceramic nanocomposites for aerospace applications. Appl Nanosci 2017; 7(8): 519–548.

10.

Safavi

Walsh

. Electrodeposited Co-P alloy and composite coatings: a review of progress towards replacement of conventional hard chromium deposits. Surf Coat Technol 2021; 422: 127564.

11.

Srinivasan

Kunjiappan

Palanisamy

. A brief review of carbon nanotube reinforced metal matrix composites for aerospace and defense applications. Int Nano Lett 2021; 11(4): 321–345.

12.

Feldhausen

Heinrich

Saleeby

, et al. Review of computer-aided manufacturing (CAM) strategies for hybrid directed energy deposition. Addit Manuf 2022; 56: 102900. In Press DOI: 10.1016/j.addma.2022.102900

13.

Singh

Fraternali

. Development of in-house composite wire based feed stock filaments of fused deposition modelling for wear-resistant materials and structures. Compos B Eng 2016; 98: 244–249.

14.

Padhan

Marathe

Bijwe

. Tribology of poly (etherketone) composites based on nano-particles of solid lubricants. Compos B Eng 2020; 201: 108323.

15.

Patanwala

Hong

Vora

, et al. The microstructure and mechanical properties of 3D printed carbon nanotube‐polylactic acid composites. Polym Compos 2018; 39(S2): 1060–1071.

16.

Dontsov

Panin

Buslovich

, et al. Taguchi optimization of parameters for feedstock fabrication and FDM manufacturing of wear-resistant UHMWPE-based composites. Materials 2020; 13(12): 2718.

17.

Shen

Xiong

, et al. Fused deposition fabrication of high-quality zirconia ceramics using granular feedstock. Ceram Int 2021; 47(24): 34352–34360.

18.

Notzel

Eickhoff

Pfeifer

, et al. Printing of zirconia parts via fused filament fabrication. Materials 2021; 14(19): 5467.

19.

Gorjan

Tonello

Sebastian

, et al. Fused deposition modeling of mullite structures from a preceramic polymer and γ-alumina. J Eur Ceram Soc 2019; 39(7): 2463–2471.

20.

Gonzalez-Gutierrez

Cano

Schuschnigg

, et al. Additive manufacturing of metallic and ceramic components by the material extrusion of highly-filled polymers: a review and future perspectives. Materials 2018; 11(5): 840.

21.

Cano

Lube

Huber

, et al. Influence of the infill orientation on the properties of zirconia parts produced by fused filament fabrication. Materials 2020; 13(14): 3158.

22.

Huang

Chen

, et al. Multifunctional graphene-based nano-additives toward high-performance polymer nanocomposites with enhanced mechanical, thermal, flame retardancy and smoke suppressive properties. J Chem Eng 2021; 410(410): 127590.

23.

Carneiro

Covas

Reis

, et al. The effect of processing conditions on the characteristics of electrically conductive thermoplastic composites. J Thermoplast 2012; 25(5): 607–629.

24.

Sezer

Eren

. FDM 3D printing of MWCNT re-inforced ABS nano-composite parts with enhanced mechanical and electrical properties. J Manuf Process 2019; 37: 339–347.

25.

Farajian

Alipanahi

Mahboubkhah

. Analyses of mechanical properties and morphological behavior of additively manufactured ABS polymer, ABS/PBT blend, and ABS/PBT/CNT nanocomposite parts. J Thermoplast 2022; 36: 2390–2411. In-press.

26.

Singh

Kumar

, et al. On 3D-printed ZnO-reinforced PLA matrix composite: tensile, thermal, morphological and shape memory characteristics. J Thermoplast 2022; 35(10): 1510–1531.

27.

Singh

Kumar

Ranjan

. Sustainability of recycled ABS and PA6 by banana fiber reinforcement: thermal, mechanical and morphological properties. J Inst Eng India Ser C 2019; 100: 351–360.

28.

Singh

Parija

Verma

, et al. Assessment of psychological distress pattern & its correlates among people receiving COVID-19 vaccination during the COVID-19 pandemic: a cross-sectional study. Indian J Med Res 2022; 156(3): 674–680.

29.

Singh

Kumar

Tiwari

, et al. On secondary recycling of ZrO2-reinforced HDPE filament prepared from domestic waste for possible 3-D printing of bearings. J Thermoplast 2021; 34(9): 1254–1272.

30.

Yadav

Rohru

Babbar

, et al. Fused filament fabrication: a state-of-the-art review of the technology, materials, properties and defects. Int J Interact 2022; 24: 1–23.