Machine Vision 2021/22 - Machine Vision Key Technology for Automation Solutions Applications - Products - Suppliers - VDMA Verlag
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Machine Vision Key Technology for Automation Solutions Machine Vision 2021/22 Applications – Products – Suppliers
CONTENTS 01
Contents
Contents
02 Machine vision –
when machines see and comprehend
04 The future of industrial production
06 From product quality to quality of life
13 The right solution for every job
13 Diverse systems
14 The most important trends
16 Standards for machine vision
17 Ensuring your vision project is a success
18 OPC Machine Vision
20 Company profiles
48 Index of members
53 Imprint
02 MACHINE VISION
Machine vision –
when machines see and comprehend
Cameras generate images that are automatically Safe production, reliable products
analyzed by software. Machine vision systems
perform quality tests, guide machines, control Machine vision guarantees safety – in
your production process as well as in the
processes, identify components, read codes and
end product.
deliver valuable data for optimizing production.
Machine Vision is constantly capturing new
fields of application – also beyond the arena Sustainability
of manufacturing – always striving for higher
Smooth material flow, considerate use of energy
quality, efficiency and product safety.
and resources – machine vision makes it possi-
ble. At an early stage in the production process
faulty parts are detected and sorted out before
they are processed further. It prevents prevents
10 reasons to use defective components and a high reject rate of
products.
machine vision
Stable and optimised processes
100% quality check for
maximum product quality Recognizing trends and irregularities in pro
duction processes early on – machine vision
Producing quality non-stop, 24 hours a day, paves the way for realizing the smart factory of
7 days a week – expensive product recalls, the future.
product liability claims and image loss can be
avoided.
High savings potential
Higher productivity Machine vision systems lower your costs. They
and competitiveness often pay off after only a few months.
Modern production is automated. Machine
vision enables manufacturing companies to Flexibility
remain competitive, to prevent an exodus of
key technologies, to generate qualified jobs, Modern vision systems are flexible, able to
and to capture new markets. Not just since learn and to adapt. This is ensured by self-
Covid-19 has it become clear that production is training and standardised interfaces software.
increasingly carried out where consumption “Plug and play” – this is what the machine
takes place, not least because of rising environ- vision industry is working on. Even batch size 1
mental and transport costs. Production becomes becomes feasible.
competitive through the use of machine vision.
The outsourcing of production to low-wage
countries can be avoided. User-friendliness
Specific programming skills were perhaps
previously required. Ease-of-use and seamless
integration into the production process have
been commonplace for a long time now.
MACHINE VISION 03
Ergonomic workplaces Machine vision – a growth market
Checking tasks are often monotonous and tiring The machine vision industry in Germany and
for the eyes. Sometimes they are too complex for Europe has been reporting high growth numbers
the human brain. Monotonous and dull tasks are and record sales figures for years. Between 2013
accomplished by a „seeing machine“ – machine and 2019, sales in the German industry grew by
vision systems support workers, ensure a perfect an average of 9% per year. In 2020, sales declined
human-machine interaction resulting in a due to the COVID-19 pandemic. But far from
more advanced and safe workplace. being as drastic as in other industries.
The reason for the boom: Equipped with machine
A technology serving people vision systems, machines and robots are learning
to “see”. Within the global race towards greater
With and for humans, ensuring security, higher automation, this key technology is not just found
quality, and safety in and outside the factories in traditional industrial sectors, but is conquering
worldwide. Optimising traffic flows, the perfect brand new areas too. Improved quality, greater
swing in golf, training of medical doctors, check- reliability, increased safety and cost-effectiveness
ing moles, waste separation and recycling – all are benefits that are just as crucial in non-manu-
benefit from machine vision! facturing contexts as in the realm of industrial
production.
www.seeing-machines.eu
Machines with eyes wide open
You want to know more about machine
vision? Then take a look at the VDMA
multi-media report about „seeing
machines“.
04 MACHINE VISION
The future of industrial production
The factory of the future will be designed From inspection to optimization
to yield maximum benefit from the lowest
possible consumption of material and energy. Many machine vision systems today are more
than pure inspection systems, as they make it pos-
Interconnected and more flexible production
sible to recognize trends in production processes
processes will pave the way for new business early on. Thus quality control is evolving into pro-
models. All devices will be able to communicate duction optimization, which allows to flexibly
directly with each other and thus create true react in the intermediate stages of production, for
interoperability. example by implementing warning thresholds in
the software for the classification of error types,
sizes, dimensions and many other inspection crite-
Strict quality specifications are commonplace ria. This allows to detect at a very early stage any
today. Random quality checks are increasingly changes that are slowly creeping in. The documen-
replaced by a 100% quality control approach. tation of characteristics that are relevant for qual-
Each and every stage of production becomes ity, helps uncover the cause of an occurring error.
subject to comprehensive documentation and The identified error can then be effectively
traceability, especially when the product is safety- avoided. Should errors occur nonetheless, it is
critical. This is economically feasible thanks to increasingly possible to implement automated
machine vision systems that undertake infallible rework of the faulty workpiece.
quality checks along the production cycle. Expen-
sive product recalls, product liability claims and
image loss can be avoided. The Industrial Internet of Things,
Industry 4.0 and Machine Learning
Global competition is becoming fiercer: only
those production facilities that are among the Machines, production resources and products
leaders in terms of productivity and costs will are increasingly directly communicating with
be able to survive. Machine vision plays a key role each other and are interconnected; starting with
in this because it offers solutions suited to meet the customer’s order to quality control, from
the challenges of the future. the shop floor to the board room. The resulting
MACHINE VISION 05
data convergence will open up entirely new Interoperability, connectivity and standards
intelligent production options in which all are key factors
objects influence and control each other by
means of autonomous data and information Interoperability and the ability to interconnect
exchange. The “Smart Factory” resulting from are key factors when it comes to implementing
this will follow a completely new production Industry 4.0. But standards are crucial: Infor
paradigm: Products are identifiable, can be mation networks between companies and
localised at any time and know their history, straightforward integration of different value
their current state as well as possible options on chains are only possible if all those involved
their way to finalisation. C
ustomized one-off agree on standards. They define the mechanisms
products, manufactured fast and efficiently, of cooperation and the information to be
will thus become reality. Moreover, artificial exchanged. Like many players, VDMA supports
intelligence, especially machine learning, will the communication architecture OPC Unified
further optimize production. Deep learning Architecture. Currently around 30 branch specific
algorithms continue to improve the performance OPC UA companion specifications are being
of machine vision systems, allow for intuitive developed within VDMA, all of which work in
“teaching” of inspection tasks, help find anoma- cooperation with each other in order to ensure
lies and enable predictive maintenance. seamless interoperability with each other in the
near future.
Machine Vision: In September 2019, Part 1 of the OPC UA for
key technology for Industry 4.0 Machine Vision Companion Specification (in
short OPC Machine Vision) was published (Part 1:
Machine vision is the trailblazer and key tech Control, configuration, management, recipe
nology for these interconnected production management, result management). Part 2 is
processes. No other component is able today currently being developed. The industry agrees
to gather and interpret as much data as which information, data, functions and services
machine vision systems. The idea is to verify are to be integrated into a production network
and process what has been “seen” and transmit and mapped in OPC UA. The aim is an easy
the results to the systems of the value chain in connection and straightforward integration
every phase of production. This is not only about of machine vision systems into production con-
finding out whether a part is good or insuffi- trol and IT s ystems.
cient but about triggering intelligent actions.
Machine vision is perfectly suited to do this OPC Machine Vision describes the interface
because it is the “seeing element”. Increasingly, between machine vision systems and other
autonomous guided vehicles (AGV) and autono- systems in an automation scenario. Previously,
mous mobile robots (AMR) are roaming in the the system integrator had to develop proprietary
factory floor to transport things to the right interfaces for each machine vision application.
place at the right time. Machine vision provides The working group has now defined a uniform
them with the sensory capabilities to navigate interface that will significantly simplify the
intelligently and safely in areas with constant entire integration process in the future. Stand-
movement of people. A new concept using many ardised integration of machine vision with all
mobile robots is the so-called “matrix produc- its possibilities will advance it from a mere
tion”. It consists of robot cells that are connected inspector to a true production optimizer.
by mobile robots which bring tools and work-
pieces where they are needed – seemingly
guided by an invisible hand, but in reality guided
by machine vision and AI.
06 MACHINE VISION
From product quality to quality of life
In industrial production, machine vision An acoustic camera makes sounds visible
displays the qualities of a genuine all-rounder.
Moreover it has proven itself in many other Integrated into the image processing software,
an acoustic camera can be used to determine
fields of application beyond the factory.
and visualize not only the presence, but also the
Improved quality, greater reliability, increased exact location of an error source. Data obtained
safety and cost-effectiveness are benefits that in this way can be used to draw precise conclu-
are just as crucial in non-manufacturing contexts sions about problems in the manufacturing pro-
as in the realm of industrial production. cess or to generate detailed repair instructions.
An acoustic camera is used, for example, to check
plug connections. In addition to the visual appear-
Are all pins in the right place? ance of a plug connection, the noise that occurs
during the assembly process and its location can
This question is often only clarified when all help to assess whether it has been executed cor-
the parts are assembled. But this is often too rectly. In many cases, the mounting position is
late and could lead to defective products, for not ideally visible or not visible at all for a stable
example. evaluation by purely optical means during the
process. Especially in cases like these, the signal
With the help of machine vision, it can be offers a variety of additional evaluation options
determined in a matter of millisecons whether to ensure the quality of the plugging process.
the pins will fit into the PCB’s hole pattern.
Source: NeuroCheck GmbH
For this purpose, a high-precision image of the
circuit board is created. This considerably simpli-
fies the testing process for the pin inspection of
connector assembly lines, as faulty connectors Absolutely in-line with correlation-free
are sorted out before assembly. Good, because metrology
who would want a smartphone that does not
work reliably? In-line measuring systems in the automotive
industry monitor the production process and
Source: senswork GmbH provide production plant operators with trends
regarding process stability and quality.
MACHINE VISION 07
With high-precision and fast 3D sensors, fea- Surface inspection
tures such as bolts, holes and edges can be
measured directly in the line in milliseconds. The In industrial production and quality assurance,
sensors enable the inspection of the quality-rel- surfaces often have to be inspected, either dur-
evant features required for inline process control ing production or in random samples of the fin-
in production. As a result of the new tracking ished product. Various 3D sensors, such as laser
technology, which records the sensor position on scanners and SfS sensors working according to
the robot arm with high accuracy regardless of the “shape-from-shading” principle, are used for
temperature influences, metrological tasks can this purpose. Three main areas of application
be performed in a cell in the production line in can be distinguished:
addition to process monitoring. Thus, time-con-
suming correlation measurements with coordi- • Form test: In a 3D image of the surface,
nate measuring machines in a dedicated meas- eviations from the shape, outer contours, and
d
uring room are no longer necessary. This means often also flatness must be checked.
that reliable, traceable measurement and test Identification of defects: This is about finding
data are available from the first component pro- and evaluating local defects. These can be
duced during production start-up. In addition, scratches, bulges, blowholes, burrs, and bursts,
the new tracked and traceable in-line measure- etc.
ment technology offers the potential to shift Roughness test: Surfaces always show a
periodically occurring metrological measure- more or less pronounced roughness. Depend-
ment tasks into the line, which contributes both ing on the application, a maximum roughness
to a significant acceleration of responsiveness is permissible, or a defined roughness is
due to the greatly increased measurement fre- required.
quency and to an increase in the efficiency of
production processes. This results in a much This technology is used in many applications:
higher measuring frequency for quality assur- from surface testing of aluminium, checking the
ance and much higher accuracy for process con- roughness of textured lacquer samples during
trol. production, to testing Braille characters, or even
measuring wrinkles after washing processes.
Source:
Carl Zeiss Automated Inspection GmbH Source: in-situ GmbH
08 MACHINE VISION
Weld visualization using 3D-welding helmet ture of the visitors is checked with the help of a
contactless thermometer. Anyone who has an
For many years welding helmets have protected appointment receives safety, hygiene and data
welders´ eyes at the cost of visibility and produc- protection instructions and has to agree to them
tivity. While worker safety is paramount, this before the appointment. The robot informs the
reduction in capacity represents one of the big- host about the visit and motivates the visitor to
gest limitations to productivity in the field. To disinfect their hands in the waiting area.
achieve better results, the Xtreme Dynamic Range
(XDR) technology is introduced for creating the Source: Pi4_robotics GmbH
revolutionary 3D-welding helmet that enables
operators to examine their work in real time. The
helmet equipped with XDR acquires and synthe-
sizes images as a stereo camera unit. As a result, Lenses enable high-precision adjustment of
welders can weld more reliably due to the ability positioning tasks
to view weld beads, items being welded and the
working environment simultaneously. In the electronic assembly process, or in the
space shuttle boom arm: highest precision is
Source: XIMEA GmbH needed. The perfect solution to meet high preci-
sion requirements of positioning tools are large
format lenses with a resolution of up to 100 line
pairs per millimetre (lp/mm) and an excellent
Concierge robots optical stability over the image field, be it on
earth or in space.
Concierge robots protect your employees and
customers from risks, especially in times of Die-Attach is a lead-free process for bonding
COVID-19. They greet guests politely and profes- silicon chips to the pad or die cavity of the
sionally. They are reliable and always in a good support structure of microelectromechanical
mood. A cloud-based appointment manage- systems (MEMS). Special pick-and-place tools
ment system informs the robot which visitors are required to retrieve the die mount from
are currently expected. The identity of the visi- the wafer tape and position it on the adhesive.
tors is confirmed with facial recognition and a A critical point in production comes when
comparison with their identity card data and the adhesive needle must hit a target on the
passport photo. In addition, the body tempera- substrate within 0.3 µm. Depending on the
MACHINE VISION 09
machine, the distance from one target to Returning bottles in the supermarket
another can be up to 40 mm. The perfect solu-
tion to meet the precise requirements of posi- Modern reverse vending systems, which are
tioning tools in die-attach machines are large mainly used in food retailing, nowadays work with
format lenses with a very high resolution and high-performance camera systems for the recogni-
an excellent optical stability over the image tion of barcodes and security features. Within one
field. Equipped with a beam splitter, the coaxial second, up to 1,000 images from a total of six
illumination option provides uniform illumina- cameras are generated, evaluated and compared
tion in all RGB channels without reflections from with a database of more than 35,000 data records.
the highly reflective substrate. Lenses without Such a high data processing rate enables an input
beam splitter can be used with ring lights for speed of empty containers of up to two metres per
incident brightfield illumination. second. Thanks to specially matched LED lighting
elements, even very small and low-contrast bar-
Source: Jos. Schneider Optische Werke GmbH codes can be reliably detected and evaluated. In
addition, the camera-based continuous object
tracking system can be used to monitor any posi-
tion modifactions or withdrawings of the bottles.
Gripping into the box? child’s play! An attempt to defraud by pulling out already
deposited bottles or goods – also known as the
What is simple for an infant can be a difficult thread trick – can thus be effectively prevented.
task for a robot. The complex “reach into the
box” with the help of optical sensors is consid- Source: Diebold Nixdorf Technologies GmbH
ered a particularly complex challenge in auto-
mation.
Process stability and high performance, even at Apples or pears?
top speeds - this challenge has been worked on Clearly recognized thanks to 3D vision and AI
for years. Machine vision technology is not only
used for the “ gripping”, but also for optimised Conventional image processing methods some-
robot path calculation and the process-safe times face great challenges if they are to reliably
multi-pick function. detect variants of an object or product that differ
from one another in shape and color. This is
Source: ISRA VISION AG often the case when recognizing and sorting10 MACHINE VISION
imaged scene. The shape information replaces
the color information of a 2D RGB image, which
in turn significantly simplifies the recognition
and d ifferentiation of differently colored fruits
and enables additional applications, such as
the exact positioning and measurement of the
recognized objects.
Source: BASLER AG
Modern approach to farming
using depth cameras
Depth cameras have proven themselves
extremely effective in vertical farming and auto-
mated harvesting solutions. The information
they provide can be used to monitor plant
growth and health. Harvesting machines can
better understand their surroundings and navi-
gate efficiently. They are able to locate fruit on a
plant, assess its ripeness and pick it, all without
damaging the plant. Adding a 2D RGB sensor to
provide colour information further augments
the captured 3D data, e.g. to better assess a
plant’s health or the ripeness of the fruit. The
visible spectrum and 3D data are used for agri-
cultural machinery navigation systems, to avoid
plants and other obstacles.
Source: FRAMOS GmbH
fruits, for example. With the help of trained neu-
ral networks and 3D image processing, not only
can different types of fruits be precisely recog- Stone collector 4.0
nized and distinguished from one another, but
also different varieties of a species, such as green Finding and removing field stones automatically
apples from red ones. is possible thanks to image processing.
How does it work? First, a drone conducts a survey using advanced
A deep learning-based vision system uses 3D sensors, GPS, and trained neural networks using
data as raw material. This system delivers high- computer vision to accurately map rocks’ loca-
resolution 3D images with nearly millimeter tions and sizes. Then there is a hydraulically
precision. A grayscale image as an intensity controlled implement mounted on a front-end
image is supplemented by distance measure- loader. A human then drives the tractor on the
ments for each individual pixel using time-of- optimized route provided by the map, and the
flight measurements of light pulses in the near computer vision on the implement automati-
infrared range. The resulting 3D point cloud cally identifies the rock and pulls it into the
provides additional information about the tractor bucket.MACHINE VISION 11
The core components of both systems (drone
and tractor) are robust cameras whose high-
resolution images are used in three areas: for
accurate training of the neural networks, for
identification of the stones on the aerial photo-
graphs and for real-time recognition of the field
stones on the robot arm, which picks them up
from the field.
Source: LUCID Vision Labs GmbH
Sensor fusion and artificial intelligence
for the safe mobility of the future
How will we travel or transport our goods
tomorrow? The answer is as simple as it is
complex: autonomous, without drivers or pilots.
The machines will decide, not humans. What
sounds like a utopia is already in parts reality Recycling –
today. no problem thanks to Hyperspectral Imaging
In addition to public acceptance, safety will Applications in the recycling industry are becom-
be the key to success. This can only be achieved ing more and more demanding. Not only a suit-
if various sensors that are intelligently fused able data acquisition and data processing is
together support the decision algorithms of required, but also powerful data analysis and
artificial intelligence. Whether for cars, delivery data evaluation.
robots, air cabs or drones. High-performance
industrial cameras are just as important as Color cameras can only process information in
lidar lasers or radars. Due to their individual the visible light band. Hyperspectral imaging in
capabilities, they guarantee a safe flight, even the near infrared range offers the degree of clas-
under varying weather. Vehicles that have sification accuracy required for many recycling
limited on-board sensor technology can be tasks by directly measuring the chemical molec-
upgraded by customized hardware and software ular composition by means of light absorption
solutions, e.g. as a retrofit, and automated safely (spectroscopy). Thus different materials can be
and efficiently. This not only enables drones to measured exactly according to their chemical
fly autonomously, but also to perform real-time compositions in real time.
operations. For example, centimeter-precise 3D
maps can be generated, or GPS-free localization Due to a combination of a powerful real-time
and exact environment recognition can be embedded vision system in the relevant wave-
enabled. Automated inspection and monitoring length range and a real-time analysis software
missions are already reality and enable high- equipped with a user-friendly interface, the
precision data evaluation in real time today. degree of classification accuracy necessary for
such applications can be achieved.
Source: Allied Vision Technologies GmbH /
Spleenlab GmbH Source: EVK DI Kerschaggl GmbH12 MACHINE VISION
Safe train rides – Frequent malpositions and external influences
thanks to image processing are detected and evaluated in order to implement
preventive maintenance measures – not only on
When a train drives into the maintenance hall, the train but also on the railroad track.
camera gates automatically inspect the train.
Thereby any damage or deterioration of the roof, The system “learns” to understand correlations
side and underfloor structure is being detected. better and better the more data is collected. This
Using different imaging methods, it is possible to saves valuable time and ensures that mainte-
carry out inspections which the human eye can- nance can be planned precisely. From the selec-
not perform. All findings are carefully docu- tion of components to the exact time of ordering
mented - within minutes. An analysis tool links and an optimised stockkeeping of spare parts.
the recorded data of the maintenance process
with other collected information. External param- Source: PSI Technics GmbH
eters can also be included, such as weather con-
ditions, travelled distances or velocities.
Based on Big Data and Machine Learning, this Success in the saddle
huge data can be exploited to its full potential.
Safety-relevant components and their diagnoses Cycling is a popular sport. Under exertion, how-
can be classified together so that correlations ever, it exposes the body to considerable stress.
become clear and conclusions can be drawn as to Pain, especially in the back, knees and hips, is
when parts need to be replaced. common among competitive athletes.
A bike-fitting system with a camera and suitable
analysing software helps professional and ama-
teur athletes to position themselves optimally on
the bike. This prevents incorrect postures, mini-
mizes the risks of injuries, prevents pains and
maximizes athletic success.
For analysis, the bicycle is fixed in a roller trainer.
A camera records this set in a two-dimensional
X-Y axis. While the cyclist pedals with different
intensity and in different positions, the camera
records the sequence of movements. Changes in
the joint angles are recorded in high quality and
at high frequency (60 frames per second), pre-
cisely and without any distortion. A motion anal-
ysis software measures the direct effects on the
respective mechanical parameters of the cyclist,
i.e. influence of force, movement and pedalling
technique.
Source:
IDS Imaging Development Systems GmbHMACHINE VISION 13
The right solution for every job
The VDMA Sourcing Service helps you Choose between three comfortable search
identifying the right partner for your machine strategies:
vision application – no matter whether
you need components, complete systems
• Search by type of product
(systems, components, services)
or services.
• Search by type of application (e.g. surface
inspection, robot vision, identification)
• Search by type of customer industry
www.vdma.org/visionfinder
Diverse systems
Some machine vision systems are so compact you can hold them in the palm of your hand. Sometimes, they are
integrated vision systems that work intelligently directly from devices and enable them to see and understand.
Others could fill a whole room.
• Application-specific vision systems are turnkey • Smart cameras (intelligent cameras) are
systems for a specific application such as c omplete vision systems that include software
the inspection of flat glass or wafers. They are for image analysis, all contained within the
usually PC-based and offer high-performance. compact housing of the camera itself. They can
be programmed flexibly to carry out different
• Configurable vision systems are usually types of tasks.
C-based as well. Unlike application-specific
P
systems they are more versatile in their use. • Vision sensors are also complete vision systems
End users can often implement a range of within a single compact housing. In contrast to
applications via a graphical user interface. smart cameras, they are made for one specific
type of application, e. g. code reading.
System integrators, with their high level of sector- and application-specific know- Making use of versatile components, solutions can quickly be developed to
how, offer made-to-measure solutions. tackle a wide range of tasks.14 MACHINE VISION
Reaching into the box - child‘s play! Robot Vision
What is simple for an infant can be a difficult task for a robot. But with machine Machine vision delivers sharp eyes for industrial robots and teaches them
vision, the „reach into the box“ works! to do see and understand. Robot Vision is an important trend, also in robotics.
3D technology is being used here.
The most important trends
Machine vision is developing rapidly, creating Performance
ever greater benefits for users.
The efficiency of machine vision systems is rapidly
increasing, thanks to higher-definition cameras,
steadily increasing processor p
erformance as well
The third dimension as multi-core processor technology, state-of-the-
art software and standardised interfaces. Ever
With machine vision becoming three-dimen- more rapid inspection speeds and accuracies are
sional, many tasks can be accomplished in a thus achieved at comparable costs.
cost-effective way – from the precise inspection
of adhesive beading or welded seams and auto-
mated gripping of unsorted items in boxes Colour
through to non-contact precision measuring
of formed sheet metal parts in the production In many applications, colour recognition is of
cycle. great advantage. For example, different models
or components can be identified or sorted, and
quality checks can be conducted on the basis of
Standardisation colour. Colour recognition has now become a
standard routine for which numerous machine
Standardised interfaces facilitate the integration vision solutions are available.
of individual machine vision components
into an overall workable system. This reduces
the amount of effort required and makes
the machine vision solution efficient and
inexpensive.MACHINE VISION 15
User-friendliness Embedded Vision
Whereas in the past experts were needed to Embedded Vision enables image processing on
implement machine vision solutions, today many compact, high-performance, and low-energy
adaptations can be carried out without any great computing platforms. They can be integrated
prior knowledge, thanks to intuitive configura- in areas of limited space or small devices. This
tion options and ergonomic software user inter- technology thus opens up many new fields of
faces. application which so far could be covered neither
by PC-based nor by intelligent machine vision
systems.
Hyperspectral Imaging
Hyperspectral cameras or sensors take several Machine Learning
images of a scene in different wavelength
ranges. Combined, the images provide a greater Machine learning is an important area of artifi-
depth of information. This technology is used in cial intelligence. Computer programs based on
areas and applications whenever ingredients or machine learning use algorithms to find solu-
substances need to be identified and discerned, tions to new problems. The artificial system rec-
and are not recognizable through a standard ognizes patterns in the learning data it receives.
color or monochrome picture. For instance, in the Deep Learning enables the classification of
food or wood industry, in recycling, mining or images with a better classification rate than with
agriculture. previous methods. The user does not have to
explicitly program the different error classes, i.e.
you just “show” the deep-learning algorithm
images and it learns from them.
Would you have seen the scratch?
Modern vision systems detect
errors that the human eye tends
to overlook or classify as irrelevant.
As the example of the saxophone
shows, such faults would be per-
ceived as annoying when touching
or playing the scratched key.16 MACHINE VISION
Standards for machine vision
Standards facilitate use of machine vision and integration of individual components into a complete
system with optimum functionality. They cut down on development time and investment costs and
also accelerate time-to-market. And, the number of standards is growing steadily.
You will find an overview of existing globally accepted
machine vision interface standards in the brochure
“Guide to Understanding Machine Vision Standards”
which can be downloaded under
www.vdma.org/vision
About G3 – Global Coordination of Machine Twice a year, technical experts meet in so called
Vision Standardization „International Vision Standards Meetings“ for
joint work and coordination according to a rotat-
In 2009, member supported trade associations ing system alternating between Asia, America
from Asia, Europe and the USA began a coopera- and Europe. Existing G3 standards are: GenICam,
tive initiative to coordinate the development of EMVA 1288, GigE Vision, CoaXPress, Camera Link,
vision standards and founded the so called “G3” Camera Link HS, USB3 Vision and VDI/VDE/VDMA
initiative. The aim of G3 is to develop globally 2632 and OPC Machine Vision. The newest
adopted vision standards and hence to avoid G3-standardisation projects are emVision and the
overlapping or duplication of efforts. Open Optics Camera Interface.MACHINE VISION 17
Ensuring your vision project is a success
Part 3: Acceptance test of
classifying machine vision systems
For measuring (non-classifying) machine vision
systems, quantitative capability analysis is
already well established. Measurement uncer-
tainty is usually employed as an indicator.
Until now, on the other hand, there have been
no corresponding and accepted qualification
indicators for classifying machine-vision systems
whose results are attributive variables. Part 3
closes this gap and introduces indicators describ-
ing the classification capability of a machine
www.vdma.com/flawless – vision system.
The preparation of a requirement and system specification
ensures successful machine vision applications.
Part 4: Surface inspection systems in flat steel
production
The VDI/VDE/VDMA 2632 series of standards
structures the communication between supplier This standard describes concepts for continuous
and user. The standards help to avoid misunder- performance monitoring of surface inspection
systems. It is intended for manufacturers and
standings and to handle projects efficiently and
users of surface inspection systems and describes
successfully. procedures for stability testing. Although this
work is oriented towards the requirements of flat
steel production, it is expected that the results
Part 1: Basics, terms, and definitions can also be applied to other inspection tasks such
as aluminium, paper or foil.
Knowing what you are talking about is the start
of every successful project. The guideline Publisher of VDI/VDE/VDMA 2632 series is the
describes the principles and defines the terms VDI/VDE Society Measurement and Automatic
necessary for the use of image processing Control. The standards were elaborated in coop-
systems. It defines a consistent terminology for eration with VDMA Machine Vision. The docu-
all cooperation partners. ments are practice-oriented, thorough, and spe-
cifically address the requirements of machine
vision. They include both a German/English and
Part 2: Guideline for the preparation of a for part 2 an English/Chinese version, and can
requirement specification and a system therefore be applied in the communication with
specification customers worldwide.
The standard provides assistance in the prepa The VDI/VDE/VDMA 2632 standards can be
ration of specifications for industrial image purchased on:
processing systems. Particular emphasis was www.vdi.de/2632
placed on the representation and description of
influencing factors as well as on their effects.
The p roject partners are thus able to identify
influences at an early stage during planning and
to find optimised solutions.
www.vdma.com/flawless• In parallel to existing automation standards
tromagnetic waves Electromagnetic wavesvision Machine
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18 MACHINE VISION
Vision services
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The “Eye” of Industrie 4.0
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07.06.18 11:21
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Saule_MachineVison_Automatica2018.indd 1 07.06.18 11:21
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07.06.18 11:21
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07.06.18 11:21
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18 Machine Vision and OPC UA
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Interface 2MACHINE VISION 19
DUSTRIE 4.0
TANDARDS
OPC Machine Vision, part 1 OPC Machine Vision, part 2
ort The basic concept of OPCPart Vision is a subdivision
1 describes an abstraction into
of theseveral
generic Part 2 pertains to the Asset Management and
or all parts. Part 1 includes thevision
basissystem,
specification and describes
i.e. the representation anso
of the Condition Monitoring use cases. For the asset
ex infrastructure layer which provides basic services in a generic
called “digital twin” of the system. It handles management use case, one of the most impor-
tant requirements is to be able to successfully
of way. From part 2, a visiontheskill
management of recipes, configurations and
layer is addressed which provi-
results in a standardized way, whereas the con- identify the asset itself. The components that
ea des more specific vision services.
tents stay vendor-specific and are treated as black build up a machine vision system have also been
and boxes (1). It allows the control of a vision system considered as assets in this case. The condition
on for in a generalized way, abstracting the necessary monitoring use case forms a basis for business
behavior via a state Any production IT system
machine concept (2). cases like predictive and preventive maintenance.
Therefore, part 2 also defines the parameters for
the identified components of a machine vision
system, monitoring and analysing which can
Part 2 … n
Vision services provide us with useful information needed for
(Vision skills layer)
maintenance and diagnostics of the system and
its components.
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(Infrastructure layer)
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Part 1
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Part 3..n
proprietary input and output data black boxes
defined in Part 1 and to substitute them with
Basic services Vision system components
(focus on methodology) (identification, condition monitoring) standardized information structures and seman-
OPC Vision, part 1 tics. Currently a possibility to provide standard-
Part 1 describes an abstraction of the generic vision ized structures for the Result data black box is
Configu- Identification
Recipes Results Topology Components
ration & Monitoring
being discussed in the working group.
system, i.e. the representation of the so called "digital
ocess
twin" of the system. … It handles the management
… of recipes,
non-
configurations and results in a standardized way, whereas
o Part 1 (released) Part 2 (in progress)
the contents stay vendor-specific and are treated as black
ess
boxes (1). It allows the control of a vision system in a
t is Conceptual model for OPC Machine Vision
generalized way, abstracting the necessary behavior via a
ith
state machine concept (2).
er Configuration data
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black box 1
on to Data
1
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h
tput
Main scopes of OPC Machine Vision, part 1
ke
obot Future parts
In future parts, the generic basic information model will20 MACHINE VISION
Company profiles
Company profiles
21 Allied Vision Technologies GmbH
22 ASENTICS GmbH & Co. KG
24 Basler AG
26
Baumer GmbH / Baumer Inspection GmbH
28 Balluff GmbH
29 DVC Machinevision b.v.
30 EngRoTec-Solutions GmbH
31 i
nos Automationssoftware GmbH
32 I
DS Imaging Development Systems GmbH
34 ISRA VISION AG
36 iim AG
37 MATRIX VISION GmbH
38 LUCID Vision Labs GmbH
40 MVTec Software GmbH
41 NeuroCheck GmbH
42 OCTUM GmbH
43 Polytec GmbH
44 Vision Components GmbH
46 SVS-Vistek GmbH
47 VMT Vision Machine Technic
Bildverarbeitungssysteme GmbHAllied Vision 21
Focus on what counts –
digital industrial cameras for your application
For more than 30 years, Allied Vision has been We know how to help you find the best
helping people to reach their imaging goals. We camera solution for your application. That
don’t just develop cameras. We provide answers. includes a digital camera, but also the right lens,
the right connectivity hardware and the right
software interface. Our job is to reliably deliver
Allied Vision supplies camera technology and the image you need, when you need it and how
image capture solutions for factory automation, you need it.
industry and science, traffic monitoring and
many more application areas in digital imaging. To deliver the precision and reliability our custom-
By focusing on what counts for each customer, ers need, we manufacture our products according
Allied Vision finds solutions for every application, to the highest quality standards in state-of-the-
a practice which has made Allied Vision one of art clean room facilities. All our manufacturing
the leading camera manufacturers worldwide in sites are ISO 9001 certified and comply with the
the machine vision market. ISO 13485 quality standard for medical devices.
Our three-year warranty reflects our commitment
Our engineers design digital cameras with a large to quality.
scope of resolutions, frame rates, bandwidths,
interfaces, spectral sensitivities, sensor technolo- Our worldwide sales and support network allows
gies, and technical platforms. We have created a us to deliver first-class service before, during and
modular concept to ensure that your camera after your purchase. We have offices and sales
adapts to requirements of your application and representatives in Germany, the UK, France, the
not the other way around. USA, Singapore, and China and have teamed up
with selected distribution partners in more than
Allied Vision is at your side throughout the life 40 countries to ensure we are always there to
cycle of your image-processing project. help you whenever you need us.
Allied Vision Technologies GmbH • Allied Vision is a member of the TKH Group
Taschenweg 2a • 07646 Stadtroda • Germany
Phone +49 36428 677-230 • E-Mail info@alliedvision.com
Internet www.alliedvision.com22 ASENTICS
Providing solutions that ensure quality –
consistently, effectively and economically
ASENTICS – 360° inspection and 100% quality control using standardized OPC UA Interface (VDMA 40100-1) for Industrie 4.0 communication
By definition, quality is the match between ASENTICS is one of the leading application-
the expectations of a product and its properties. oriented image processing companies in Europe.
Producers in all markets are facing major We have been providing solutions for optical/
visual quality assurance in all fields of production
challenges because of our globalised world,
for more than 20 years, from small, intelligent
the desire for 100% quality is continuously stand-alone devices for simple tasks right
facing the demand for competitive prices. To through to universally applicable modular and
accomplish these tasks, ASENTICS has created scalable image processing systems for in-line
solutions that grow together with the monitoring.
demands and meet the highest standards
ASENTICS is excellently prepared for the
of the quality checks.
challenges of Industry 4.0. We consider machine
vision as not only a forerunner, but also a key
technology. The images have to be verified at
every stage of production, processed and made
available to the systems operating in the value
network. Apart from making a statement on
a good or bad part, ASENTICS machine vision
products also manage intelligent actions down
the line.You can also read
