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A METROLOGY HORROR STORY: THE ADDITIVE SURFACE
Richard Leach, Adam Thompson, Nicola Senin
Manufacturing Metrology Team, Faculty of Engineering, University of Nottingham,
NG7 2RD, Nottingham, UK
Keywords: surface metrology, additive
manufacturing, selective laser melting.
Additive manufacturing (AM) includes several
technologies, where parts are fabricated from 3D
model data by adding material in a layer by layer
manner . Due to the increased freedom of
design offered by AM processes, complex and
intricate geometries can be manufactured in a
near net-shape fashion. However, without
significant post-processing, AM technologies
have not typically been capable of achieving the
design requirements of many function-critical
parts, often failing in their ability to attain the
desired structural integrity, mechanical properties
or geometric accuracy required by the designer,
in comparison to the properties expected from a
conventionally manufactured counterpart [2,3].
Surface topography investigation is widely
recognised as a fundamental tool for
improvement of process-related knowledge .
Qualitative and quantitative assessment of
topographic formations can help to shed light on
the physics involved in the surface fabrication
process, thus facilitating the identification of how
process and material parameters influence the
structural, mechanical and geometrical properties
of the manufactured part.
This paper focuses on the topography of the
surfaces produced using selective laser melting
(SLM) of metals; a process which belongs to the
powder-bed fusion family of AM technologies
(see  for details). During the SLM process,
several physical interactions take place between
the laser, the powder bed and the layers
underneath, and it is such interactions that must
be fully investigated and understood, in order to
improve the SLM process. The typical surface
features encountered on an SLM layer, and
representative of the manufacturing process
fingerprint, are summarised in figure 1. The weld
tracks are the most evident features, appearing
as ridge-like formations indicating the path
followed by the processing laser while traversing
the powder bed. Smaller-scale ripples on the
weld tracks are formed as a result of the cyclical
process of liquefaction and solidification of the
melt pool as the laser moves across the surface
. Unmelted powder particles typically appear
as small, randomly distributed sphere-like
protrusions . Larger, similarly sphere-like,
formations are usually an indication of spatter, i.e.
the ejection of molten droplets from the melt pool,
that solidify in mid-air and adhere to the area
surrounding the weld track . Surface recesses
are indicative of multiple phenomena: localised
discontinuities of the weld tracks due to balling
effects, incomplete welding between adjacent
tracks and micro-scale porosity due to gas
FIGURE 1. Topographic features relevant to
investigation of the manufacturing process
fingerprint, as they appear on a layer of an SLM
All of the above topographic formations present
significant measurement and characterisation
challenges: high slopes, undercuts and step-like
transitions are frequent, as well as significant
changes of optical properties within the field of
view; for example, because of the presence of
highly reflective and opaque regions, and/or more
varied and more uniform colour patterns . AM
surfaces have freeform geometry, and are a
combination of structured surface texture with
random features – a veritable horror story for
metrology. In this paper, we will summarise our
work in trying to establish an infrastructure for
measurement and characterisation of SLM
surfaces. This study is part of a wider
investigation, in which we intend to rigorously
examine additive surfaces for the purpose of
designing future measurement strategies.
A portion of the top surface of an SLM artefact
was selected as representative of the typical
features encountered on a metallic surface
produced by SLM. The region of interest (ROI) is
a square of approximately (2 × 2) mm in size,
taken from the top surface of a (20 × 20 × 20) mm
cube artefact, manufactured from Ti6Al4V using
a Renishaw AM250 SLM machine from a CAD
model of a cube with nominally flat faces. The
size of the ROI ensures that the field of view
(FOV) is adequately representative of the
topographical formations expected to be found on
the top surface, in order to demonstrate the
relevant measurement challenges.
The following commercial instruments,
measurement technologies, measurement
setups and types of returned datasets were
considered. Philips XL30 scanning electron
microscopy (SEM): at 61× magnification in
secondary electron mode; 2D intensity image.
Keyence VHX-5000 digital optical microscopy
(DOM): ; 100× to 1000× variable objective at
200× (FOV 3.05 mm × 2.28 mm) with focus
stacking (FS); 2D colour map. Alicona
InfiniteFocus G5 focus variation microscopy
(FVM): 20× objective lens (NA 0.40, FOV 0.81
mm × 0.81 mm, lateral resolution 3 μm) with FS,
stitching of multiple images performed in the
Alicona software; height map and colour map.
Olympus LEXT OLS4100 confocal microscopy
(CM): 20× objective lens (NA 0.6, FOV 0.64 mm
× 0.64 mm), stitching of multiple images
performed in the Olympus software; height map.
Zygo NewView 8300 coherence scanning
interferometry (CSI): 20× objective at 1× zoom
(NA 0.40, FOV 0.42 mm × 0.42 mm), stitching of
multiple images performed in the Zygo software;
height map. Nikon MCT 225 X-ray computed
tomography (XCT) : geometric magnification of
44.1×, voxel size of 4.53 µm, 3142 X-ray
projections with two frames per projection, tube
voltage of 145 kV and current of 66 µA, 0.25 mm
copper pre-filter; triangulated mesh. Data were
reconstructed in the Nikon CT-Pro software,
using a second order beam hardening correction.
Surfaces were determined in VGStudio MAX 2.2
, using the maximum gradient method .
Colour maps, height maps and triangulated
meshes were examined as acquired by the
various measurement technologies. Colour maps
are calibrated images where pixels are mapped
to (x,y) coordinates. Height maps are maps
whose pixels contain height information. Height
maps are intrinsically limited to 2.5D data (i.e. no
undercuts or vertical surfaces), while triangulated
meshes are not (i.e. they are “full 3D” geometric
models). Currently, however, triangulated
meshes must be resampled into height maps in
order for texture parameters (such as those
defined by ISO 25178-2 ) to be computed.
The investigation focused specifically on how
challenging topographic formations are
processed by the various measurement
solutions, analysing in particular the features
discussed above that typically make SLM
surfaces problematic to measure.
The raw data were analysed in the surface
metrology software MountainsMap by DigitalSurf
. Areal topographies were levelled by least-
squares mean plane subtraction using a common
reference region, and truncated to homogenise
colour scales in height maps. Datasets were
manually aligned via visual inspection of
topographic formations, and small areas were
extracted for feature comparison.
Investigation of optical images (see figure 2)
highlights the difficulties experienced when
utilising reflected light in measurements. While
amplifying smaller-scale features, (e.g. weld track
ripples), using reflected light can lead to bright,
highly saturated regions corresponding to the
most exposed parts of the topography, strongly
contrasted with the darker, deep recesses. This
is a typical issue with optical imaging and
measurement of SLM surfaces: higher intensity
incident light is needed to illuminate recesses, but
increases the chances of saturation in more
reflective regions, with the consequent loss of
topographic detail. This issue is in stark contrast
to the output of SEM imaging, where it is
generally easier to obtain clearer images overall.
Both optical and SEM images are characterised
by artefacts specific to each measurement
technology, which the expert eye must recognise
when visually inspecting the result. Multiple
reflections, projected shadows and optical
chromatic/geometric aberrations are common for
optical imaging; while charging artefacts, smears
and bright and dark halos are typical of SEM
imaging . For optical imaging, a surface can
look considerably different if imaged through
coaxial or ring light, polarised or non-polarised
light, monochromatic or polychromatic light, and
if processed with different detector settings
(saturation, contrast, etc.). Analogously, SEM
imaging is affected by multiple parameters, such
as electron beam energy and detector sensitivity.
Investigation of close-up views of height maps
and images obtained via different measurement
solutions (see figure 3), highlights some of the
features which are most challenging to measure
for each measurement solution. The large recess
in the bottom left quadrant is particularly
interesting, as the returned information varies
substantially between measurements. The
protruded singularities are also of interest, as
they result in a range of different measurement
artefacts depending on the technology used to
acquire the specific dataset. Figure 3b and figure
3e highlight the presence of an exogenous
particle removed during stylus measurement also
performed on this sample as part of a wider study
(data shown in figure 3a, figure 3c, figure 3d and
figure 3f were taken after the stylus
measurement). Figure 3a also highlights the
presence of the scratch left by the stylus, which is
barely perceptible in the CSI data (figure 3d).
FIGURE 2. Colour and intensity maps: a) DOM; b) FVM; c) SEM.
FIGURE 3. Topography details (field of view approximately 0.3 mm × 0.3 mm) captured with different
measurement solutions; a) DOM; b) SEM; c) CM; d) CSI; e) FVM; f) XCT.
DISCUSSION AND CONCLUSIONS
Some interesting considerations can be drawn
from the available data. Firstly, when an opinion
needs to be reached about the topography of a
SLM surface, it is intrinsically unadvisable to rely
on any measurement result taken individually.
Experimental findings demonstrate that no single
measurement technology or setup is optimal for
the measurement of all notable features that need
investigation. Secondly, no measurement
technology or setup amongst those compared
can be considered “higher class” than the others
and thus act as reference; in other words, there is
no “truth” to rely upon. Incorporation of traceable
stylus measurement may be able to provide this
reference, but alignment of stylus profiles to 2.5D
height maps is non-trivial.
The work presented in this paper highlights the
main challenges in measurement of metal
additive surfaces, through visual comparison of
measurements made using a variety of
technologies. It is clear from the measurements
made during this initial phase that the features
present on these surfaces are represented in
substantially different ways by each instrument,
and, therefore, that individual measurements
may not always be able to provide the information
required. Substantial further work is, therefore,
required in quantification of these differences, as
well as in extension to a wider array of metal and
polymer AM surfaces.
The authors would like to thank Dr Peter de Groot
and Dr Jack DiSciacca from Zygo Engineering for
their assistance in the acquisition of CSI data.
A.T. and R.K.L. would like to thank EPSRC
(Grants EP/M008983/1 and EP/L01534X/1) and
3TRPD Ltd. for funding this work. N.S. and R.K.L.
would also like to thank the EC-FP7-PEOPLE-
MC METROSURF for supporting this work. The
authors would like to thank DigitalSurf for
providing the MountainsMap software.
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