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A Study of the Factors Influencing Generated Surface Roughness of Down
-
facing Surfaces in Selective Laser Melting
WCMNM
2018
Amal Charles1*, Ahmed Elkaseer1, 2, Tobias Müller1, Lore Thijs3, Maika Torge4,5, Veit
Hagenmeyer1, Steffen Scholz1,5
1 Institute for Automation and applied Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany
2 Faculty of Engineering, Port Said University, Port Said, Egypt
3 Direct Metal Printing Engineering, 3D Systems, Leuven, Belgium
4Institute for Applied Materials Applied Materials Physics, Karlsruhe Institute of Technology,Karlsruhe, Germany
5Karlsruhe Nano Micro Facility, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
*Corresponding author. Tel.: +49 721 608-25851, E-mail address: amal.charles@kit.edu
Abstract
Additive manufacturing provides a number of benefits in terms of a large freedom to design complex parts and
reduced lead-times while globally reducing the size of supply chains as it brings all production processes under one
roof. However, AM lags far behind conventional manufacturing in terms of surface quality. This proves a hindrance
for many companies to invest in AM. The aim of this work is to investigate the effect of varying process parameters
on the resultant roughness of the down-facing surfaces. The results indicate that the Sz parameter provides greater
insight into the quality of down-facing surfaces than the Sa parameter. It is also found that the interaction between
parameters are of greatest significance on the obtainable surface roughness, though their effects vary greatly
depending on the applied levels. This behaviour is mainly attributed to the difference in energy absorbed by the
powder, however further investigation is still warranted.
Keywords: Additive Manufacturing, Selective Laser Melting, Surface Roughness, Design of Experiments, Ti6Al4V
1. Introduction
Since the advent of the first Additive Manufacturing
(AM) technique, the Stereolithography process by 3D
Systems in 1987, additive manufacturing has been
under continuous and rapid development to meet
growing industrial demands. Formerly, it was mainly
used as a prototyping technique for pre-production,
testing and analysis. However, different additive
manufacturing techniques, recently emerged, play a
significant role in modern industries [1, 2].
This is principally because additive manufacturing
has shown high potential to produce 3D intricate
geometries with short lead-times at relatively low cost.
This helps strengthen supply chain and boosts its
profitability and flexibly [3]. Presently, AM has been
successfully exploited in electronic, aerospace and
biomedical industry where highly specialised and
customisable components are required [4-6].
Especially, Selective Laser Melting (SLM) technique
makes great strides in the field of metal AM. This is
especially achievable with the commercial emergence
of Titanium and Nickel based super alloys that have
exceptional material properties [6, 7].
The SLM process is a powder bed additive
manufacturing technique using a laser as a power
source. The interaction between the laser and the
metal powder causes the powder to selectively melt
according to the desired slices. Once one layer is
scanned, the platform is moved down by the height of
this layer and another layer of powder is applied on top
of the formerly built layer. This process of melting and
bonding layers together continues successively until
the desired part is built.
The non-melted powder remains in the build
chamber and it provides support to the part being built.
This non-melted powder can be subsequently
removed after the build and sieved; it can therefore be
reused in successive builds [8].
Though noticeable progress has been made, there
has been some challenging issues still need
addressing to allow AM and SLM to be among the
mainstream manufacturing processes. Especially,
limited precision of the fabricated products and the
repeatability of the processes are considered a
technological barrier to the maturation of additive
manufacturing techniques [9]. In particular, AM parts
are often built with high surface roughness which
necessitates some post processing steps to refine the
resultant roughness and makes it suitable for a wide
range of engineering applications. These post-
processing steps are rather expensive and time
consuming.
Fig. 1. The Staircase effect, up-facing and down-facing surfaces in AM
parts
The SLM process exhibits the so-called staircase
effect in both up-facing and down-facing surfaces as
depicted in Fig.1. This staircase effect contributes to
the increased roughness of these surfaces. Down-
facing surfaces, especially ones that are at an angle
less than 45 degree, with respect to the build platform,
show very high roughness. This is mainly attributed to
the formation of dross and spatter due to the high laser
absorptivity of powders compared to the solid metal in
the bulk of the part as can be seen on Fig. 2. The
surface topology of parts produced by SLM are highly
dependent on their orientation. This is why, in order to
produce parts with good surface quality, down-facing
surfaces with angles less than 45° are usually avoided
World Congress on Micro and Nano Manufacturing
Edited by
Joˇ
sko Valentinˇ
ciˇ
c, Martin Byung-Guk Jun, Kuniaki Dohda, and Stefan Dimov
Copyright c
2018 WCMNM 2018 Organisers ::
Published by
Research Publishing Singapore
ISBN: 978-981-11-2728-1 :: doi:10.3850/978-981-11-2728-1 57 327
328
Joˇ
sko Valentinˇ
ciˇ
c, Martin Byung-Guk Jun, Kuniaki Dohda, and Stefan Dimov (Eds.)
by reorienting the part. Otherwise, there is a need for
the building of support structures. However, this in turn
results in the increase of process steps, especially the
removal of the support could exhibit defects such as
burr formation leading to even higher roughness [10].
Fig. 2. (a) A depiction of overheated zone above loose powder and (b) the
resulting dross formation in the final part
There has been some research attempts made in
trying to correlate process parameters with surface
quality of parts, however little research has been
devoted to characterise the surface roughness of
down-facing surfaces. In this context, this work
focusses on investigating and correlating the effects of
different build parameters on the surface roughness of
down-facing surfaces, when the build parameters are
only varied within the plane of the down-facing surface
and its immediately adjacent volume.
2. Experiments
2.1. Parameters
The parameters selected for this research work
were the laser power, scan speed and scan spacing.
The parameters were varied only for the down-facing
surfaces of the build as seen in Fig. 3. The remainder
of the part was built using the standard build
parameters, as recommended by 3D Systems, for a 60
micron layer thickness. The different levels of the
parameter settings after rounding off can be seen in
Table 1.
Fig. 3. Illustration of areas printed with down-facing parameters
Table 1. Selected parameters and their levels
Value
Laser
Power
Scan
Speed
Scan
Spacing
-1
50
200
50
- .59...
90
465
60
0
150
850
75
0.593
210
1235
90
1
250
1500
100
2.2. Design of Experiments
Central Composite method was used to design the
experimental trials. This model was used as the limits
for the factor settings. A portion of the Design of
Experiments used to fabricate the test pieces can be
seen in Table 2.
Table 2. Design of Experiments
Trial Laser
Power(W)
Scan
Speed(mm/s)
Scan
Spacing(µm)
1
90
465
60
2
90
465
90
3
90
1235
60
4
90
1235
90
5
210
465
60
6
210
465
90
7
210
1235
60
8
210
1235
90
9
50
850
75
10
250
850
75
2.3. Test piece
The test piece was designed to enable
measuring the roughness of the down-facing surfaces.
Consequently, the test pieces were designed to have
a down-facing surface area of 10mm*20mm, a depth
of 20mm and with overhang inclinations of 45°, 35°
and 25° as seen in Fig.4.
Fig. 4. Depiction of CAD models with 45°, 35° and 25° overhangs from left
to right, respectively
2.4. Additive manufacturing
The test pieces were designed using CAD
Software and were directly imported into 3DXpert2
software for the slicing, positioning and pre-processing
of the build files. 3D Systems ProX® DMP 320
machines was used to perform the printing. The parts
were heat treated before removal from the build
platform in order to prevent warpage.
2.5. Measurements
An FRT MicroProf 100 profilometer was used for
the measurement of the surface roughness. The
samples were subject to ultrasonic cleaning with water
in order to detach any loose powder on the surface
prior to measurement. The topography of a square of
1mmX1mm dimension was scanned on the down
surfaces of all samples. This scanned topography was
then used to generate the various areal and line
roughness parameters.
3. Results and discussion
A careful visual examination was conducted for all
samples to characterize the visual appearance of the
down-facing surfaces. Test pieces were visually
looked over to detect the presence of bright spots that
could indicate spots of large spatter or dross presence,
as shown in Fig. 5.
Fig. 5. Visual examination shows significant variations in roughness for
the different test pieces
the World Congress on Micro and Nano Manufacturing
329
3.1. Surface roughness
The results presented herein are for test pieces
with an overhang angle of 45°.
3.1.1 Laser power and Scan Speed
Figure 6 presents the results of measured surface
roughness in terms of Ra, Rz and Rq, for different scan
speeds and laser power.
Fig. 5 Roughness measurements (a) Ra, (b) Rz and (c) Rq
An analysis of the graphs shown in fig 6, indicates
that at the lower scan speed, increasing the laser
power does not have a significant effect on the
roughness parameters observed. However, at the
higher speed, all roughness parameters show higher
values at both levels of power and also shows a
greater degree of difference for different power levels.
3.1.2 Laser power and scan spacing
Figure 7 presents the results of generated surface
roughness in terms of Ra, Rz and Rq, for different scan
spacing and laser power.
Fig. 6 Roughness measurements (a) Ra, (b) Rz and (c) Rq
The results of the roughness parameters,
illustrated in Fig 7, show that at the lower laser power
of 90W there is only a miniscule increase in roughness
parameters when scan spacing is increased. On the
other hand, at the power of 210W, a stark decrease in
roughness was observed when using the larger scan
spacing of 90 µm.
3.1.3 Scan speed and scan spacing
Figure 7 presents the results of generated surface
roughness in terms of Ra, Rz and Rq, for different scan
spacing and scan speeds.
Fig. 7 Roughness measurements (a) Ra, (b) Rz and (c) Rq
10
12
14
16
18
20
465 mm/s 1235 mm/s
Ra (µm)
Scan Speed (mm/s)
Laser
power
90W
Laser
power
210W
a
60
70
80
90
100
110
465 mm/s 1235 mm/s
Rz (µm)
Scan Speed (mm/s)
Laser
power
90W
Laser
power
210W
b
15
20
25
30
465 mm/s 1235 mm/s
Rq (µm)
Scan Speed (mm/s)
Laser
power
210W
Laser
power
90W
c
10
12
14
16
18
60 µm 90 µm
Ra (µm)
Scan spacing (µm)
Laser
power
90W
Laser
power
210W
a
60
70
80
90
100
60 µm 90 µm
Rz (µm)
Scan spacing (µm)
Laser
power
90W
Laser
power
210W
b
14
16
18
20
22
60 µm 90 µm
Rq (µm)
Scan spacing (µm)
Laser
power
90W
Laser
power
210 W
c
12
14
16
18
20
60 µm 90 µm
Ra (µm)
Scan spacing (µm)
Scan
speed
465
mm/s
Scan
speed
1235
mm/s
a
60
70
80
90
100
110
60 µm 90 µm
Rz (µm)
Scan spacing (µm)
Scan
Speed
465
mm/s
Scan
speed
1235
mm/s
b
16
21
26
60 µm 90 µm
Rq (µm)
Scan spacing (µm)
Scan
speed
465
mm/s
Scan
speed
1235
mm/s
c
330
Joˇ
sko Valentinˇ
ciˇ
c, Martin Byung-Guk Jun, Kuniaki Dohda, and Stefan Dimov (Eds.)
From the results presented in Fig 8, it is clear that
increasing the scan spacing results in the decrease of
roughness values. This is true for both the high and
low values of scan speed tested.
3.1.4 Areal surface texture
Figure 9 depicts the measured Sa and Sz values
for all the test pieces. It is clear that the Sa values over
the whole square does not exhibit drastic changes
across all the tested sample but on the other hand the
Sz values exhibit significant deviations though they
have similar Sa values.
Fig. 8 Graph depicting Sz value as line and Sa as dotted line
Fig 10 shows 3D topographies of two surfaces that
measured with similar Sa values but display very
different surface qualities. The variations in the Sz
parameter can be attributed to the disturbance of the
surface due to the presence of partially melted powder
as well as dross formation that results in high peaks
and low valleys resulting in non-uniformity.
Fig 11, depicts a microscope image of surfaces built
with the same scan speed but with 90W and 210W
power respectively. This increase in roughness can be
attributed to the increased presence of partially melted
powder and large peaks due to dross formation.
Though not presented herein, the same was found to
be the reason for the decrease in roughness when
increasing scan spacing.
Fig. 9 (a) 3D surface topography of test piece 7 and (b) test piece 8
Fig. 10 (a) Optical microscope image of test piece 3 built with 90W and (b)
test piece 7 built with 210W laser power
4. Conclusions
This paper has reported an experimental
investigation into the effect of SLM process
parameters and the generated surface quality of the
down-facing surfaces of printed parts. The results
show that Sz parameter provides greater insight into
the surface quality than the Sa parameter due to the
non-uniformity of the surface. The presence of partially
melted powder and dross formation is the major cause
of surface defects within the down-facing surfaces.
Results clearly indicate that for down-facing
regions, increasing scan spacing results in lower
roughness values, while a higher scan speed
increases surface roughness.
As for the laser power, it shows different
degrees of effect on the surface quality, at low scan
speeds, a high laser power shows a miniscule
decrease in roughness values compared to a lower
laser power. However, it is also clear that only looking
at the roughness does not provide reliable information
on dross. Dimensional accuracy tests are required as
larger energy inputs cause bigger melt pools to form,
this can cause large dross but with less measured
roughness as the larger interconnected melt pools will
cause a uniform dross, which cannot be detected just
be measuring roughness.
Though relationships begin to arise between
parameters, the non-linear behavior and the complex
interactions between process parameters add to its
unpredictability. Which makes this process a prime
candidate for process modelling and optimization.
Acknowledgements
This work was done in the H2020-MSCA-
ITN-2016 project PAM2, Precision Additive Metal
Manufacturing, which is funded by The EU Framework
Programme for Research and Innovation - Grant
Agreement No 721383. In addition, the support by the
Karlsruhe Nano Micro Facility (KNMF-LMP,
http://www.knmf.kit.edu/) a Helmholtz research
infrastructure at KIT, is gratefully acknowledged.
References
[1] D.R. Eyers et al.,6 Industrial Additive
Manufacturing: A manufacturing systems
+!,-+!.%0!6 *(+/.!,- %) ) /-.,1 92: 208-
218.
!,() 5-D printing: The new industrial
revolution, Business Horizons, 2012; 55: 155-162.
[3] ,)- 5 ,%).%)# ./,%)# !$)*'*#16
IFAC Proceedings, 2013; 46; 468-472.
',! !. ' 5Selective laser melting of high
aspect ratio 3D nickel4titanium structures two way
trained for MEMS applications6 Int J Mech Mater,
2008; 4:2.
[5] P. Rochus et al. 5New applications of rapid
prototyping and rapid manufacturing (RP/RM)
technologies for space instrumentation6 .
Astronaut, 2007; 61: 1-6
[6] N. Guo et al.5Additive manufacturing: technology,
applica.%*)- ) ,!-!,$ )!! -6 ,. of Mech Eng,
2013; 8; 215-243.
[7*/,!'' !. ' 5.!,%'- "*, %.%0!
()/"./,%)#6 ))'- 4 Manufacturing
technology, 2017, 66: 659-681.
$%&- !. '6 -./ 1 *" .$! (%,*-.,/./,'
evaluation during selective laser melting of Ti-6Al-6
Acta Materialia, 2010; 58:3303-3312
))) !. ' 5 A Review on Status of
Research in Metal Additive Manufacturing, In;
Advances in 3D Printing & Additive Manufacturing
Technologies, D.I Wimpenny et al., Springer, 2017;95
[10] A. Triantaphyllou et al., 5/,"! texture
measurement for additive ()/"./,%)#6 Surf.
Topogr.; Metrol. Prop, 2015; 3; 024002
0
50
100
150
200
250
300
1 2 3 4 5 6 7 8 9 10
Surface texture (µm)
Test piece No.
Sa
Sz
a
a
b
b
