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feature METROLOGY
Don Braggins,
UK Industrial Vision Association
INDUSTRIAL VISION
AND MICRO MANUFACTURING
MAIN IMAGE: Figure 4. Effects on an image of varying the angle of incident
illumination, courtesy of STEMMER IMAGING.
M
achine vision is now a well-established tool on the
production line for making critical dimensional
measurements as part of the quality control process in both
high volume and low volume manufacturing, and provides a real
return on investment. Quantifiable measurements that can be
obtained from an image include distances, angles, centre of
mass, area and circular fit, to name but a few. Industrial vision
measurements can also be directly linked into statistical process
control (SPC) methods to improve product quality, reduce
wastage, improve productivity and streamline the process.
The speed and accuracy of current industrial vision systems
means that in many applications 100% inspection can be carried
out, and each and every product or component can be
measured. By feeding these data into the SPC system, not only
can trends be identified earlier, but random and sudden defects
can also be identified, which is not possible using more traditional
sampling methods for SPC data acquisition. The challenge for
using industrial vision in micro manufacturing is being able to
make measurements at the required scale in a production line
environment. As with any measurement system, the key factors of
accuracy, precision and repeatability are of vital importance in
machine vision systems.
Accuracy is an indication of how close the actual measurement is
to true value. Precision is the number of digits to which the
measurement can be read. Repeatability shows the closeness of
a number of repeated measurements. This is illustrated in Figure
1, where it can be seen that a group of measurements could have
poor accuracy and poor repeatability, or good repeatability but
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feature METROLOGY
Fifth Anniversary of the
Calibration Laboratory for Laser
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Figure 3.
Telecentric imaging, courtesy of STEMMER IMAGING.
poor accuracy, or good accuracy but
poor repeatability, as well as the
desired combination of good
accuracy and good repeatability.
Precision is generally limited by the
repeatability and accuracy
characteristics.
Figure 1.
Measurement accuracy and repeatability,
courtesy of STEMMER IMAGING.
Figure 2.
Fundamental Imaging parameters,
courtesy of National Instruments.
Factors affecting accuracy and
repeatability in machine vision
A number of factors affect accuracy
and repeatability in machine vision
systems, including the camera, optics,
illumination, object positioning and
measurement algorithms.
Fundamental imaging parameters are
field of view, working distance,
resolution, depth of field and sensor
size (Figure 2). Measurements are
only as good as the information that
can be extracted from the image, and
image quality is dependent on
resolution, contrast, depth of field,
perspective and distortion. Resolution
is the amount of object detail
reproduced by the imaging system
and contrast is the difference between
the object and background greyscale
values. Machine vision measuring
systems specify accuracy and
repeatability in terms of physical units,
such as microns, provided that the
image field-of-view (the dimensions of
the area seen by the camera) and the
number of elements in the camera’s
image sensor are known and fixed.
This calibration procedure defines the
measurement dimension for each
individual pixel in the camera sensor
and is dependent not only on the
number of pixels in the sensor, but on
the quality of the lens used as well.
For micro manufacturing applications,
even with optimised lens/sensor
combinations, the measurement
dimension of the individual pixel may
still be too large for the measurements
required, however, measurement
algorithms which use interpolation and
fitting techniques to allow
measurements to be made to a
fraction of a pixel can be used to
improve the measurement range.
There is a wide choice of sensor
resolutions available allowing the most
appropriate choice for the dimensions
being measured, however the lenses
used in the optical system are also of
critical importance. A perfect lens
would fully reproduce an image from
an object with absolutely no
degradation. However sharpness,
contrast, illumination, spectral
transmission and distortion all affect
the ability of a lens to reproduce an
image. A lens can only resolve so
much detail in terms of spatial
frequency — the finer the image detail
passing through the lens, the harder it
is for the lens to reproduce a good
image; the image becomes less
distinguishable.
Another consideration is the
performance of the lens across the
entire field of view. For some lenses,
the resolution capability deteriorates
the further away from the centre axis,
which is an important consideration if
the resolution is required across the
entire image or alternatively means
that the object must be accurately
positioned in the centre of the field of
view. Depending on the size of the
object and the distance to the
camera, there may also be issues with
depth of field or off-axis distortion.
Telecentric imaging
A telecentric lens is a compound lens
used in machine vision systems to
eliminate dimensional and geometric
variations of images within a range of
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feature METROLOGY
Figure 5.
Inspection of solar cell
manufacture, courtesy of
STEMMER IMAGING.
different distances from the lens and across the whole field of
view, by collimating the light entering the lens. Telecentric lenses
have the same magnification at all distances. An object-space
telecentric lens creates images of the same size for objects at any
distance and has constant angle of view across the entire field of
view. An object that is too close or too far from the lens may still
be out of focus, but the resulting blurred image will be the same
size as the correctly-focused image would be.
This makes them ideal for metrology applications, especially in
the automotive and electronics industries, for high accuracy
measurement of parts with complicated three-dimensional
shapes. Figure 3 shows an image of a thick drilled block using a
conventional lens and telecentric lens. The conventional lens
shows the walls of the holes, making measurement of the
diameters difficult. With the telecentric lens, the walls are not seen
and the diameters can readily be measured.
Off-axis imaging
In many applications it is not possible to position the imaging
system so that it is mounted perpendicular to the object being
measured. If the imaging system has to be mounted off-axis, then
distortion and foreshortening effects can result and these must be
corrected in order to ensure accurate measurements.
Illumination
Machine vision illumination controls how the object appears to the
camera. Adequate illumination can often make the difference
between a system that works reliably and one that does not. After
all, if the appropriate image is not presented to the camera for
measurement, considerations of accuracy and repeatability
become largely irrelevant. At the most basic level, there must be
‘enough’ light so that the camera can acquire a good image.
Beyond this, it is almost always necessary to use the orientation,
geometry or colour of light to highlight relevant details or minimise
the appearance of unhelpful parts of the image, such as glare.
Probably the most important factor that governs how the image
appears is the angle at which the light falls on the object (Figure
4). For example, light approaching an object from a low angle will
tend to create highlights on raised edges. Choosing the
appropriate wavelength of illumination can play a major role in
revealing or masking specific features on the object, while the
‘quality’ of the light describes whether the light is diffuse or not.
Lighting control is also important. For example, the light can be
strobed or pulsed, the intensity can be raised or lowered or, in a
more complex set-up, different lighting scenarios can be
preprogrammed using a lighting controller.
Speed
Another important factor to be considered is that of speed. Once
all of the dimensional measurement criteria have been met, the
system needs to be able to make the measurements at the
appropriate speed for the production line. In addition to the ability
to acquire and process the images at the appropriate rate, it also
means that the imaging system needs to be interfaced into the
production line, with camera triggers linked into product delivery
system, and if necessary into a reject mechanism to allow ‘out of
spec’ components to be removed.
Real world measurements
Three practical examples of the use of industrial vision systems in
micro manufacturing applications are illustrated here. The first is
the use of a vision system in the manufacture of solar cells.
ECKELMANN AG, located in Wiesbaden, Germany, has
developed a vision system based on line scan cameras for laser
edge detection as part of the edge isolation process in solar cell
manufacture (Figure 5). It was designed for the ASYS Group
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(Dornstadt, Germany), a leading manufacturer of handling
systems, process machines and special machines for the
electronic and solar industries, and is fully integrated to provide
feedback control to the production process. Edge isolation
provides electrical separation between the active front side of a
solar cell and the rear side. A laser cuts a small groove along the
cell edges, the depth of the groove depending on the cell doping.
The difficulty lies in positioning the groove as close as possible to
the outer contour of the cell in order to maximise the active
surface and thus the efficiency. The edge isolation control system
features a line scan camera with 4096 pixels, optics and
customised LED illumination supplied by STEMMER IMAGING.
The image processing system measures the outer contours of the
cell and feeds them back to the control system of the laser
equipped with a deflection mirror to provide an active feedback
system. If the edge damage is within tolerance levels the laser will
ignore it and proceed with the cutting process. Image acquisition
and analysis take place in just 800 ms and the resolution of the
system makes it possible to ensure that the distance to the edge
during laser cutting is below 100 µm. The calibration and
qualification of the laser and camera have been automated so the
system can easily be commissioned or recalibrated after
maintenance work.
The second application uses vision to help with handling
components in the micro assembly and testing industry. Since
these components are tiny, almost weightless, and highly
sensitive to electrostatic charge, inspecting and sorting them
ready for assembly can be a painstaking task. Vision has been
incorporated into a system that combines the functions of
feeding, orientation and inspection of parts. IMS (Almelo, The
Netherlands) develops and builds high-tech production
equipment for the high-precision, electronics and medical
industry. Working together with the University of Twente
(Enschede, The Netherlands) and Bosch Rexroth (Lorh am Main,
Germany), they developed the Vision Inspection Feeding System
feature METROLOGY
(ProVIS), a multi-purpose, modular system for the supply and
recognition, inspection, handling and placing of parts.
Recognition and inspection, ProVIS (Figure 6) uses two separate
cameras, one for recognition, and another for inspection.
The Matrox Imaging Library software development kit performs all
the product recognition and inspection tasks. To use the system,
a technician calibrates the ProVIS with a part that is within
tolerance to create what’s known as the Golden Template. Then
the camera takes pictures of the parts on the inspection stage.
Finally, specific processing modules analyse the parts. First the
Geometric Model Finder (GMF) module locates the parts in the
image, so the Metrology module can measure the features of
each part. The results, both good and bad parts, are displayed on
the monitor. Parts that pass inspection can be used for assembly;
parts that cannot be recognised are most likely lying on their
sides or too close to another part, so they are re-fed into the
system by a vibratory tray. If the inspection shows a part to be out
of tolerance, the system tags it; if the system is feeding parts for
assembly, the non-conforming parts will be kept out of the
assembly step.
The system can also be programmed to find surface defects. The
Metrology module figures prominently in the solution, and is used
for finding dimensions and checking tolerances, complex
operations that are processing-intensive. With the appropriate
optical system the measurement results are accurate to
+/- 0.01 mm. Without appropriate lighting, the camera is unable
to produce usable images.
The ProVIS features a dome with blue light above the tray where
the products are fed to the system. The inspection of the parts’
dimensions, the fundamental task of the system, is backlit. The
right combination of illumination and zoom lenses provides the
accuracy needed for such tiny parts. As with most assembly
applications time is important, and all the visual inspections and
data processing has to be completed within the allowed cycle
Figure 6.
ProVIS inspection system,
courtesy of Matrox Imaging.
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feature METROLOGY
Figure 7.
Inspection of SMDs, courtesy of Cognex UK.
time, typically 1 to 5 seconds, depending on
the complexity of the inspection operation.
The final application also makes use of
another machine vision capability — that of
optical character recognition to ensure that the
correct batch number is marked on a product.
At Micro Crystal in Switzerland, a smart
camera from Cognex is used to inspect the
packaging of ceramic surface-mounted
devices (SMDs) which contain the quartz
oscillator used in watches and mobile phones.
A smart camera is one in which the image
processing is carried out within the camera
itself, rather than transferring the image to a
PC for processing.
These SMDs are sold on rolls of polyester tape
in quantities up to 16,000. SMD packages can
be as small as 2 x 1.2 mm. The company has
been using an Optical Tape End-Controller on
this production line. Similar to a film-cutting
table, the roll of uninspected SMD tape is
guided over a worktable where the smart
camera performs an automatic optical
inspection (Figure 7).
The inspection process checks the following
criteria:
52 cmm 3/7 www.micromanu.com
• That there is an SMD in the package.
• That the position of the SMD is correct.
• That the batch number is present on the
ceramic housing of the SMD and that it can
be read perfectly.
The image processing is achieved using
pattern-matching technology which locates
objects reliably even if they are of different
sizes, differently aligned, if their appearance is
poor or even if they are partly covered. By
analysing the geometrical information, it is able
to determine the position of the object clearly.
LED lighting is used to give the optimum
illumination to ensure reliable detection of the
laser marked batch numbers, even though
they are not always sharply contoured.
According to the packaging specifications of
Micro Crystal, the gold contact surfaces of the
ceramic housing must always be on the side
facing away from the camera, and so they
should be invisible to the vision system. If the
smart camera detects fluctuations in
brightness triggered by the gold areas on the
grey ceramic surface, the Optical Tape EndController sounds the alarm. The faulty section
is then moved to a pre-determined processing
point and removed by hand.
About the UKIVA
The UKIVA is a Special
Interest Group of the PPMA
(Processing & Packaging
Machinery Association), and
its prime objective is
promoting the use of vision
by manufacturing industry.
The Association’s members
are involved in the supply of
vision systems and
components for use in a
wide range of industrial
imaging applications.
Thanks are due to UKIVA
members Cognex UK
(www.cognex.co.uk), Matrox
Imaging (www.matrox.com),
National Instruments
(www.ni.com) and
STEMMER IMAGING
(www.stemmerimaging.co.uk) for their
contributions to this article.
www.ukiva.org