Fused deposition modeling (FDM) or three-dimensional (3D) printing are becoming ubiquitous today because it allows the fabrication of 3D products directly from computer-aided design software. The quality of 3D parts is influenced by several parameters that need to be carefully tuned to obtain a high-quality final product. The surface finish of the finished parts is one of the major factors to consider because it affects both the dimensional accuracy and the functionality of the piece. Thus, the present study focuses on improving the surface finish of parts produced by FDM by manipulating different parameters such as layer height, raster angle, extruder temperature, printing speed, and percent infill. Polylactic acid was used for this study, which is a material present in filament form, and was extruded using a newly developed 3D printer; the Taguchi’s 35 design-of-experiment method was used to design the experiment. The results indicate that raster angle, extruder temperature, and layer thickness are the most influential process parameters of the surface quality of the final product

Baharudin, B.T Hang Tuah

Jaafar, Che Nor Aiza

Mohd Ariffin, Mohd Kharul Anuar

Shah Ismail, Mohd Idris

Sukindar, Nor Aiman

Universiti Teknologi MARA Institutional Repository

Journal of Mechanical Engineering                                         Vol. SI 3 (1), 33-43, 2017 
___________________ 
ISSN 1823- 5514, eISSN 2550-164X                              Received for review: 2016-07-22 
© 2017 Faculty of Mechanical Engineering,                        Accepted for publication: 2017-03-03 
Universiti Teknologi MARA (UiTM), Malaysia.                                         Published: 2017-07-15 
Optimization of the Parameters for 
Surface Quality of the Open-source 
3D Printing 
 
 
Nor Aiman Sukindar 
Mechanical Department of Politeknik Kuching, Sarawak, 
KM 22 Jalan Matang, 93050 Kuching, Sarawak, Malaysia 
 
Mohd Kharul Anuar Mohd Ariffin 
 B.T Hang Tuah Baharudin 
Che Nor Aiza Jaafar 
Mohd Idris Shah Ismail 
Department of Mechanical and Manufacturing, Universiti Putra Malaysia, 
43400 Serdang, Selangor, Malaysia 
 
  
ABSTRACT 
 
Fused deposition modeling (FDM) or three-dimensional (3D) printing are 
becoming ubiquitous today because it allows the fabrication of 3D products 
directly from computer-aided design software. The quality of 3D parts is 
influenced by several parameters that need to be carefully tuned to obtain a 
high-quality final product. The surface finish of the finished parts is one of 
the major factors to consider because it affects both the dimensional 
accuracy and the functionality of the piece. Thus, the present study focuses 
on improving the surface finish of parts produced by FDM by manipulating 
different parameters such as layer height, raster angle, extruder 
temperature, printing speed, and percent infill. Polylactic acid was used for 
this study, which is a material present in filament form, and was extruded 
using a newly developed 3D printer; the Taguchi’s 35 design-of-experiment 
method  was used to design the experiment. The results indicate that raster 
angle, extruder temperature, and layer thickness are the most influential 
process parameters of the surface quality of the final product. 
 
 
Introduction 
 
Fused deposition modeling (FDM), also known as additive manufacturing 
(AM), has significantly improved since it was patented by Crump [1] in 
N. A. Sukindar et al. 
 
 
34 
 
 
1992. The idea of FDM is quite simple: a three-dimensional (3D) object is 
constructed from a melted material that is deposited layer by layer and 
allowed to solidify [2]. Acrylonitrile butadiene styrene and polylactic acid 
(PLA) are the most common materials used in FDM. Since the original patent 
expired a few years ago, a variety of software and hardware designs for FDM 
have become available on the market. Because of its low cost, the demand for 
FDM technology is increasing. In 1996, Stratasys introduced the Genisys 
machine, which uses the inkjet printing mechanism. In the same year, Z 
Corp. also launched its Z402 3D printer. Other companies commercializing 
this technology include Beijing Yinhua Laser Rapid Prototypes Making & 
Mould Technology Co., Ltd. and BPM Technology [3]. However, Stratasys 
dominates the FDM market with a 41.5% share of all systems in 2010, 
making it the biggest manufacturer of AM technology [4]. 
The development of low-cost 3D printing began in 2004 with an open-
source 3D printing project called RepRap (replicating rapid prototyping). 
Since then, several 3D printers have become available on the market for as 
little as $5000 [5]. However, the performance of such low-cost 3D printers 
remains questionable; many research and development have been done to 
improve this situation. For example, Melenka [6] evaluated the dimensional 
accuracy of parts made with the MakerbotBot Replicator 2 desktop 3D 
printer; the results demonstrated that settings need to be carefully monitored 
if a consistent geometry is required. In addition, research on how process 
parameters affect parts made from PLA materials shows that different 
process parameters (e.g., infill orientation or the number of shells) 
significantly impact the mechanical performance of the material [7]. 
Surface finish is a vital quality of the finished part because it directly 
affects the dimensional accuracy and, therefore, the functionality of finished 
parts. Previous research applied Taguchi method governing process 
parameters with three levels and orthogonal array of L9, which manipulating 
several process parameters, including print speed, layer height, and 
percentage infills  to investigate which parameters that most affect the quality 
of surface finish [8]. The present research investigates the surface finish of 
parts made of PLA materials using Taguchi method by varying the process 
parameters of layer height, raster angle, extruder temperature, printing speed, 
and percentage infill. All process parameters are analyzed to find, which are 
the most influential for optimizing the printing process. 
 
Experimental Setup 
 
Sample Preparation 
The experiment was conducted by using a newly developed three-axis 3D 
printer with a more accurate lead screw specifically designed for this research 
Optimization Of The Parameters for Surface Quality 
 
35 
 
 
as shown in Figure 1. The open-source software Repetier-Host, which is 
freely available online, was used for this work. 
 
 
 
Figure 1: Three-axis 3D printer 
 
A sample was designed by using Autodesk Inventor (Autodesk, USA) and 
comprised a 20 × 20 × 5 mm3 rectangular cuboid (refer Figure 2) converted 
into standard triangular language (STL) format. Various process parameters 
were fixed throughout the experiment at the values given in Table 1. 
 
Table 1: Parameters held constant throughout the experiment 
 
 
 
 
 
 
 
 
 
 
Figure 2: Specimen used for surface-roughness test 
 
Parameters Description 
Nozzle diameter 0.3 mm 
Shell thickness 1.2 mm 
Bead temperature 45°C 
N. A. Sukindar et al. 
 
 
36 
 
 
Materials and Method 
White PLA with a diameter of 1.75 mm was used. The specimen was 
fabricated with all parameter combinations considered by using Taguchi’s 35 
design-of-experiment method with an orthogonal array of L27 was  
implemented in Minitab 16.0 software (Minitab, USA), which gave a total of 
27 experiments. The parameters were varied as shown in Table 2. 
 
Table 2: Five parameters varied for measuring surface roughness 
 
 
 
Surface-roughness Measurements 
To measure the surface roughness, we used a Perthometer S2 PGK (Mahr, 
Germany) surface analyzer as shown in Figure 3. To ensure consistent data, 
three readings were taken, each at three different spots on the sample surface.  
 
. 
 
Figure 3: Surface analyzer for measuring surface roughness (Perthometer S2 
PGK) 
 
Results and Discussion 
 
A total of 27 3D samples were printed with all five parameters varied as 
indicated in Table 2. The arithmetic average of the roughness profile (Ra) of 
Layer 
thickness 
(mm) 
Raster 
angle 
(degrees) 
Percentage 
infill (%) 
Liquefier 
temperatur
e (°C) 
Printing 
speed 
(mm/s) 
0.2 90 20 200 60 
0.3 70 60 230 80 
0.4 45 100 260 100 
Optimization Of The Parameters for Surface Quality 
 
37 
 
 
all the samples was measured and recorded for later analysis. Figure 4 shows 
the raster variation of the printed parts. 
 
 
 
Figure 4: Samples made with raster angle (from left to right) 45°, 70°, and 
90° 
 
Analysis of variance 
Figures 5(a) and 5(b) show a normal probability plot and residual versus fit, 
respectively. These show a normal distribution plot and random scatter of the 
residual, the latter of which shows a non pattern about the zero. Figure 5(c) 
shows residual versus order and shows that the assumption of randomly 
scattered data is satisfied. 
 
 
             (a)          (b) 
 
45403530252015
10
5
0
-5
-10
Fitted Value
R
e
s
id
u
a
l
Versus Fits
(response is Surface Rouhgness (Ra))
N. A. Sukindar et al. 
 
 
38 
 
 
2624222018161412108642
10
5
0
-5
-10
Observation Order
R
e
s
id
u
a
l
Versus Order
(response is Surface Rouhgness (Ra))
 
  
(c) 
 
Figure 5: (a) Normal probability plot; (b) Residual versus fits; (c) Residual 
versus order 
 
Figure 6 shows the mean function of all the process parameters 
involved in this study. Meanwhile, Table 3 shows the result of analysis of 
variance and the result show that the raster angle is a dominant parameter (p-
value = 0.000) for determining surface roughness, which is consistent with 
previous results [9, 10]. The parameter “liquefier temperature” is also 
significant for the surface roughness (p-value = 0.003), and the liquefier 
temperature of 200°C gives the highest Ra. The liquefier temperature must be 
carefully monitored to determine the optimum temperature for printing. The 
effect of printing temperature was observed by imaging with a scanning 
electron microscope (Hitachi SU1510, Japan). If the temperature is too low, 
the bonding between each layer is affected and the surface finish is rough [cf. 
Figures 7(a) and 7(b)]. In addition, the road width of each layer becomes 
inconsistent if the liquefier does not sufficiently heat the filament. However, 
if the temperature is much higher than it should be, the road width causes 
expansion, as shown in Figures 7(c) and7(d), and this phenomenon affects 
the accuracy of the final product. Based on this analysis, 230°C is the 
optimum temperature because it gives the lowest Ra as shown Figure 8(a). 
The layer thickness also shows a significant impact on surface roughness (p-
value = 0.003) which also consistent with the previous result [11]. Table 4 
shows the S/N ratio values for the experiment by factor level. The result 
found that the raster angle (B) is the main contribution affecting the surface 
roughness followed by liquefier temperature (D), layer thickness (A), 
printing speed (E), and percentage infill (C).  
 
 
 
Optimization Of The Parameters for Surface Quality 
 
39 
 
 
Table 3: Results of analysis of variance 
 
Source DF Seq SS 
Adj 
SS 
Adj 
MS 
F 
p-
value 
Layer Thickness 
(mm) (A) 
2 426.58   426.58   213.29    8.26   0.003 
Raster Angle 
(degree) (B) 
2 668.33   668.33   334.17 12.95   0.000 
Percentage Infill 
(C) 
2 27.63    27.63    13.82    0.54 0.596 
Liquefier 
Temperature 
(Celcius) (D) 
2 453.93   453.93   226.96    8.79   0.003 
Printing Speed 
(mm/s) (E) 
2 43.37 43.37 21.69 0.84 0.450 
Error 16 412.94 412.94 25.81   
Total 26 2032.78     
 
321
30.0
27.5
25.0
22.5
20.0
321 321
321
30.0
27.5
25.0
22.5
20.0
321
A
M
e
a
n
 o
f 
M
e
a
n
s
B C
D E
Main Effects Plot for Means
Data Means
 
Figure 6: (A) Mean as a function of layer thickness; (B) Mean as a function 
of raster angle; (C) Mean as a function of percentage infill; (D) Mean as a 
function of extruder temperature; (E) mean as a function of printing speed 
N. A. Sukindar et al. 
 
 
40 
 
 
 
 
Figure 7: Finished parts made at different temperatures 
 
Table 4: S/N ratio values for the experiment by factor level 
                          
The other parameters, including printing speed and percentage infill, 
do not significantly affect the surface roughness, which is consistent with 
previous results [11]. The p-value for printing speed and percent infill is 
0.450 and 0.596 respectively. 
 
Optimum parameters 
Based on our analysis, the optimum parameters include a raster angle of 90° 
to optimize the surface finish. This factor is statistically dominant, as seen 
from the results presented in Table 3. Figure 9 shows that the optimum 
Level A B C D E 
1 21.35 19.36 23.97 30.66 26.56 
2 23.97 25.20 26.33 20.67 23.61 
3 30.78 31.54 25.81 24.78 25.94 
Delta 9.43 12.18 2.36 9.99 2.94 
Rank 3 1 5 2 4 
Optimization Of The Parameters for Surface Quality 
 
41 
 
 
extruder temperature is 230°C, but a more accurate evaluation may be 
obtained by varying the temperature from 210°C to 250°C. Layer thickness 
should be set to a low value to obtain a smoother surface finish; in this case, 
we used 0.2 mm. However, surface finish also depends upon the nozzle; 
different nozzles have different tip diameters and die angles, and these factors 
affect the stability and the accuracy of the extrusion process. Another 
research has addressed the stability of the extrusion process by analyzing the 
die angle of the material being extruded [12]. 
 
0.4
10
0.3
20
30
40
200
220 0.2240
260
Surface Rouhgness (Ra)
Layer Thickness (mm)
Extruder Temperature (Celcious)
Surface Plot of Surface Rouhgnes vs Layer Thickness , Extruder Tempera
 
 
Figure 9: 3D surface plot of surface roughness as a function of layer 
thickness and extruder temperature 
 
Parts with a fine finish are obtained by tuning the factors mentioned above, 
which leads to the finish shown by scanning electron microscopy in Figure 9. 
 
 
 
Figure 10: Scanning electron microscopy image of fine finish obtained with 
optimum parameters 
N. A. Sukindar et al. 
 
 
42 
 
 
Conclusion 
 
All parameters of the 3D printing process were analyzed to obtain optimum 
results. Based on our analysis, the raster angle, extruder temperature and 
layer thickness exert the strongest influence on the surface roughness of the 
final pieces. The other two parameters which are printing speed, and 
percentage infill not significantly affect the surface roughness. Finally, tuning 
the right parameters will have fine and smooth surface finish. 
 
Acknowledgements 
 
The authors express their appreciation for the MyBrain 15 scholarship and 
Fundamental Research Grant under the Ministry of Higher Education 
Malaysia FRGS/1/2015/TK03/UPM/02/3 under vote number 5524728. 
 
References 
 
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[3] Wohlers, T. and Gornet, T., “History of additive manufacturing 
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Optimization of the Parameters for Surface Quality of the Open-source 3D Printing / Nor Aiman Sukindar...[et al.]

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Optimization of the Parameters for Surface Quality of the Open-source 3D Printing / Nor Aiman Sukindar...[et al.]

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