resubmit group project-final report

8/8/2019 Resubmit Group Project-Final Report

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INFO 6240Group Assignment

Emerging Technology

1.0 INTRODUCTION

1.1 Definition

Computer vision is the science and technology of machines

that see, where see in this case means that the machine is able to

extract information from an image that is necessary to solve some

task. As a scientific discipline, computer vision is concerned with the

theory behind artificial systems that extract information from images.

The image data can take many forms, such as video sequences,

views from multiple cameras, or multi-dimensional data from a

medical scanner.

1.2 Concept

Computers do not 'see' in the same way those human beings are

able to. Cameras are not equivalent to human optics and while

people can rely on inference systems and assumptions, computing

devices must 'see' by examining individual pixels of images,

processing them and attempting to develop conclusions with the

assistance of knowledge bases and features such as patternrecognition engines. Although some machine vision algorithms have

been developed to mimic human visual perception, a number of

unique processing methods have been developed to process images

and identify relevant image features in an effective and consistent

manner.

Machine vision and computer vision systems are capable of

processing images consistently, but computer-based image

processing systems are typically designed to perform single,

repetitive tasks, and despite significant improvements in the field, no

machine vision or computer vision system can yet match some

capabilities of human vision in terms of image comprehension,


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tolerance to lighting variations and image degradation, parts'

variability etc.

Two important specifications in any vision system are the

sensitivity and the resolution. Sensitivity is the ability of a machine to

see in dim light, or to detect weak impulses at invisible wavelengths.

Resolution is the extent to which a machine can differentiate

between objects. In general, the better the resolution, the more

confined the field of vision. Sensitivity and resolution are

interdependent. All other factors held constant, increasing the

sensitivity reduces the resolution, and improving the resolution

reduces the sensitivity.

1.3 General Application

All machine vision systems are designed to reduce or eliminate

the need for human observation of a particular task, and as their

price drops, the number of potential users that purchase a system

will increase. Machine vision applications generally fall into three

categories: measurement, inspection, and guidance. Measurement

systems determine the dimensions of an object in a camera's field ofview. Inspection systems determine whether an object matches a

predetermined description. Guidance systems cause a machine to

take certain courses of action based on visual queues.

Machine vision is used in various industrial and medical

applications. Examples of applications of computer vision include

systems for:

Controlling processes (e.g., an industrial robot or an autonomousvehicle).

Detecting events (e.g., for visual surveillance or people counting). Organizing information (e.g., for indexing databases of images and

image sequences). Modeling objects or environments (e.g., industrial inspection,

medical image analysis or topographical modeling).


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Interaction (e.g., as the input to a device for computer-humaninteraction).

2.0 TECHNOLOGIES USED/COMPONENTS OF MV SYSTEM

What is Machine Vision?

Machine vision (MV) is the application ofcomputer vision to industry

and manufacturing. It is an automated extraction of useful

information from digital images in an industrial setting. Examples of

useful information:

1. Confirmation of fill level

2. Confirmation that all components are assembled correctly

3. Part location and orientation for robot pickup

4. Part identification reading human or machine readable codes

2.2 About Machine Vision

100% quality control in manufacturing reduces costs and ensures a

high level of customer satisfaction. Machine vision inspection plays

an important role in achieving this goal. While human inspectors

working on assembly lines visually inspect parts to judge the quality

of workmanship, machine vision systems use cameras and image

processing software to perform similar inspections.

Machine vision system inspection consists of narrowly defined tasks

such as counting objects on a conveyor, reading serial numbers, and

searching for surface defects. Manufacturers often prefer machine

vision systems for visual inspections that require high speed, high

magnification, around-the-clock operation, and/or repeatability of

measurements.

For example, semiconductor fabrication depends greatly on vision

inspection technology, without which yields for computer chips would

be significantly reduced. Machine vision systems inspect silicon

wafers, processor chips, and sub-components such as resistors and

capacitors at high speeds with precision and accuracy.
http://en.wikipedia.org/wiki/Computer_visionhttp://en.wikipedia.org/wiki/Computer_vision


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2.3 Components of a Machine Vision System

Machine Vision is a subfield of engineering that is related to computer

science, optics, mechanical engineering, and industrial automation.

One of the most common applications of Machine Vision is the

inspection of manufactured goods such as semiconductor chips,

automobiles, food and pharmaceuticals.

While machine vision is best defined as a process of applying

computer vision to industrial application, it is useful to list commonly

utilized hardware and software components.

A typical machine vision solution will include several of the following

components:-

1. One or more digital or analog cameras (black-and-white or color) with

suitable optics for acquiring images.

2. Camera interface for making the images available for processing. For

analog cameras, this includes digitization of the images. When this

interface is a separate hardware device it is called a "frame grabber".

3. A processor (often a PC or embedded processor, such as a DSP).

4. Machine Vision Software which provides the tools to develop the

application-specific software program.

5. Input/Output hardware (e.g. digital I/O) or communication links (e.g.

network connection or RS-232) to report results.

6. A Smart Camera, a single device which includes all of the above

items.

7. Lenses to focus the desired field of view onto the image sensor.

8. Suitable, often very specialized, light sources (LED illuminators,

fluorescent or halogen lamps etc.).

9. An application-specific software program to process images anddetects relevant features.

10.A synchronizing sensor for part detection (often an optical or

magnetic sensor) to trigger image acquisition and processing.

11. Some form of actuators used to sort or reject defective parts.

2.4 Machine Vision for Camera
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The sync sensor determines when a part (often moving on a

conveyor) is in position to be inspected. The sensor triggers the

camera to take a picture of the part as it passes beneath the camera

and often synchronizes a lighting pulse to freeze a sharp image. The

lighting used to illuminate the part is designed to highlight features of

interest and obscure or minimize the appearance of features that are

not of interest (such as shadows or reflections). LED panels of

suitable sizes and arrangement are often used to this purpose.

The camera's image is captured by the frame grabber or by computer

memory in PC based systems where no frame grabber is utilized. A

frame grabber is a digitizing device (within a smart camera or as aseparate computer card) that converts the output of the camera to

digital format (typically a two dimensional array of numbers,

corresponding to the luminous intensity level of the corresponding

point in the field of view, called pixel) and places the image in

computer memory so that it may be processed by the machine vision

software.

The software will typically take several steps to process an image.

Often the image is first manipulated to reduce noise or to convert

many shades of gray to a simple combination of black and white.

Following the initial simplification, the software will count, measure,

and/or identify objects, dimensions, defects or other features in the

image. As a final step, the software passes or fails the part according

to programmed criteria. If a part fails, the software may signal a

mechanical device to reject the part; alternately, the system may

stop the production line and warn a human worker to fix the problem

that caused the failure.

Though most machine vision systems rely on "black-and-white" (gray

scale) cameras, the use of colour cameras is becoming more
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common. It is also increasingly common for Machine Vision systems

to include digital camera equipment for direct connection rather than

a camera and separate frame grabber, which reduces cost and

simplifies the system.

"Smart" cameras with built-in embedded processors are capturing an

increasing share of the machine vision market. The use of an

embedded (and often very optimized) processor eliminates the need

for a frame grabber card and external computer, thus reducing cost

and complexity of the system while providing dedicated processing

power to each camera.

Smart cameras are typically less expensive than systems comprising

a camera and a board and/or external computer, while the increasing

power of embedded processors and DSPs is often providing

comparable or higher performance and capabilities than conventional

PC-based systems.

2.5 Machine Vision in the Industry

Cognex is a manufacturer & supplier of machine vision systems &

vision inspection systems that are used to automate a wide range of

manufacturing processes where accurate visual inspection is

required. They offer vision sensors, modular vision systems &

camera-based surface inspection systems. Their vision systems

optimize product quality & control traceability while driving down

manufacturing costs.

National Instruments is a leading machine vision and scientific

imaging hardware and software tools provider. From inspecting

automotive parts to researching advanced medicines, engineers and
http://en.wikipedia.org/wiki/Digital_camerahttp://en.wikipedia.org/wiki/Smart_camerahttp://en.wikipedia.org/wiki/Smart_camerahttp://en.wikipedia.org/wiki/Digital_signal_processorhttp://en.wikipedia.org/wiki/Digital_camerahttp://en.wikipedia.org/wiki/Smart_camerahttp://en.wikipedia.org/wiki/Smart_camerahttp://en.wikipedia.org/wiki/Digital_signal_processor


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scientists use NI vision software and hardware to solve a diverse set

of application challenges, faster and at a lower cost.

Microscan holds one of the world's most robust patent portfolios for

machine vision systems technology, including hardware design,

software algorithms and machine vision illumination. Their

Visionscape brand of machine vision hardware and software is an

industry pioneer, improving automated technical inspection, gauging

and measurement capability to the benefit of manufacturers

worldwide.

Microscan is in continual development of their Visionscape hardware

and software as well as the NERLITE machine vision lighting

products, to ensure provides cutting edge technology and the most

complete offerings for machine vision applications.

Visionscape is a comprehensive line of machine vision system

solutions, with total scalability from smart camera systems to PC-

based solutions. Visionscape software provides all the elements

required for fast and efficient development and deployment ofadvanced machine vision applications in any industrial environment.

VIMATIC develop and build machine vision solution cater to the

semiconductor and electronic manufacturing industry. They welcome

enquiry from any companies that have requirement to integrate

vision system to their existing machines, or to replace existing

obsolete vision system. They are keen to joint venture with OEM

companies to incorporate vision system into their machines.

VIMATIC vision systems are installed to inspect a wide range of

packages like 2pSSP, 2pUSMM, 3pSSP, 3pUSMM, 3pMM, QFP, SOIC,
http://www.microscan.com/en-us/Products/ProductCategory.aspx?id=263http://www.microscan.com/en-us/Products/ProductCategory.aspx?id=2563http://www.microscan.com/en-us/Products/ProductCategory.aspx?id=263http://www.microscan.com/en-us/Products/ProductCategory.aspx?id=2563


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BGA, FlipChip and among others. The systems are checking products

for:

Leads quality and dimensional measurement.

Pads quality and dimensional measurement.

Marking specification.

Mold package quality.

Dye attach placement.

Dye wire bond placement.

Optical Character Recognition.

Machine vision software application development is carried out in-house by a team of experience engineers.We have products that cover the following market segment.

Vision System Integration

OEM Vision System

Stand Alone Vision System

2.6 Examples of Common Application

1. Colour matching

2. Sub Assembly verification

3. Die attach bond inspection

4. Location & alignment for pick and place

5. Ball grid array inspection

6. Measures solder paste levels

7. Wafer positioning

8. Robotic guidance


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2.7. Machine Vision Applications

Inspection

Gauging

Guidance

Identification

2.8 Component of Machine Vision


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Barcode Scannerand Reader

Camera Encoders

Filters Indicator LightsIndustrial Computers

Label Printers Lenses Lighting & Illuminations

Machine Safety

Measuring Solutions Sensors

Smart Camera Software

Support Systems

UID Vision Sensors Vision Systems

3.0 HOW THE MV WORKS/PROCESSING METHODS


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During the last 15 years, machine vision technology has matured

substantially, becoming a very important and in some cases,

indispensable tool for manufacturing automation. Today, machine

vision applications crop up in many industries, including

semiconductor, electronics, pharmaceuticals, packaging, medical

devices, automotive and consumer goods.

Machine vision systems offer a noncontact means of inspecting and

identifying parts, accurately measuring dimensions, or guiding robots

or other machines during pick-and-place and other assembly

operations.

Historically, machine vision has been most successful in applications

where it was integrated into the production process. For example,

guiding machines or closing a control loop. But, while vision guidance

has proved its worth in placing surface-mount components on printed

circuit boards, most users would hesitate before investing in a

machine vision inspection station to catch defective parts on an

existing production line.

However, continuous improvements in cost, performance, algorithmic

robustness and ease of use have encouraged vision systems' use in

general manufacturing automation. Further advances in these areas

will characterize the future of machine vision and result in more

vision systems on manufacturing floors during the next few years.

What characteristics will describe future vision systems? They must

include three characteristics in order to be useful in most

manufacturing industries. First, they must be fast enough to keep up

with ever-increasing production rates. Second, they must be intuitive


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and easy to use. Finally, they must be intelligent enough to deal with

part-to-part or other process variations.

While vision technology might not have reached this point yet, recent

advances in the vision industry have helped facilitate and accelerate

vision applications in manufacturing for the near future.

3.1 Faster hardware

Since its inception, the machine vision industry has been

characterized by continually improving price and performance ratios.

This trend has followed a similar one in the semiconductor industry,

which has seen desktop PCs move from yesterday's 8 MHz 8086 CPUs

to today's 300+ MHz Pentium IIs. The industry projects future 64-bit

processors that will run at clock rates in the gigahertz range.

Higher vision-processing hardware speeds have been key to both

faster parts-per-minute throughput and greater robustness in

individual vision tools. Even in manufacturing processes wheremechanical considerations limit production rates, higher-speed vision

processing means more processing power reserve. More reserve

means more intelligent vision tools that can help deal with process

variations and simplify a system's programming.

Formerly, machine vision systems allowed only binary processing of

low-resolution, black-and-white images. Today, sophisticated image

processing and analysis performed on high-resolution, grayscale

images is commonplace. Computationally intensive image-

preprocessing operations such as mathematical morphology are

widely used. In addition, vision hardware now allows not one but


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many processing passes through an image during a single frame

time.

Other advances have brought about process improvements. For

example, older systems' slow hardware couldn't rotate images to

compensate for part rotation. This could be performed only in very

expensive hardware or else required approximations that introduced

artifacts. State-of-the-art vision-processing hardware permits full-

frame image rotation within less than a frame time, which in turn

supports additional processing in real time.

Until recently, the standard broadcast TV frame rate of 30 Hz was

considered "real time." However, digital machine vision cameras,

which run at higher rates, require processing at a faster real-time

rate than conventional video. New vision-processing hardware readily

supports image acquisition from such nonstandard cameras. This

nimble hardware also can process the increased data contained in

higher-resolution images as well as conventional resolution images

that are acquired much faster.

Continuing advances in semiconductor technology during the last

decade have enabled custom vision-processing systems to shrink

continuously -- from board-filled cabinets to single boards to custom

silicon chips. In fact, during the last few years, VLSI design tools and

processes have matured to the point where vision vendors can

develop truly high-performance vision hardware.

Today, users perform vision-processing tasks at substantially faster

rates, using hardware that requires far less electrical power, while

paying a much lower unit cost than what conventional PC CPUs offer.

Custom vision-processing hardware also allows robust vision


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functionality, in less complex and lower cost configurations, closer to

the manufacturing process.

3.2 PC-based vision

During the last 10 years, PC-based vision systems have become more

widely accepted due to the ever-increasing speed of standard PC

CPUs.

Key advantages of PC-based vision systems include both the vision

supplier's and the user's abilities to leverage third-party hardware

and software. Also important is the PC's wide acceptance for both

desktops and factory floors. Today, PCs running under the Microsoft

Windows NT operating system are becoming a dominant platform for

delivering factory-floor monitoring and control applications.

Numerous low-cost frame grabbers and image-processing software

packages allow individual users to build vision applications

themselves. Although feasible, this option is not without potentialproblems, which include conventional multimedia frame grabbers'

limitations, nondeter-ministic performance and, occasionally,

excessive development, installation and support costs.

New technology that addresses current PC-based vision systems'

limitations includes next-generation, single-board, PC plug-in vision

engines and powerful, component-based software environments for

vision application development and deployment.

Plug-in vision engines

This latest generation of vision engines incorporates a complete

vision system in a single PCI board. Users can thus offload all vision-


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related processing from the host PC and use it for other tasks such as

production monitoring, control or user interfacing. Because all high-

bandwidth, image-capture operations are internal to the board, this

vision engine configuration offloads the host PCI bus in addition to

freeing up the CPU.

Furthermore, because the vision board fits completely inside a host

PC used for other purposes, plug-in vision engines offer a zero-

footprint solution -- a key consideration in many original equipment

manufacturer or clean-room applications. By plugging multiple boards

into a single PC, users can further leverage the single PC host over

multiple vision-engine boards, each dedicated to different inspection

tasks.

In addition to on-board, high-performance CPUs and custom vision-

processing hardware, such next-generation vision engines typically

run under a real-time multitasking operating system, which allows

deterministic performance in all image-acquisition, vision-processing

and input/output operations. This offers a distinct advantage over

conventional PC-based systems, which run under a nonreal-timeWindows operating system.

In contrast to multimedia frame grabbers, vision engine boards

support machine-vision input devices ranging from conventional

analog video to nonstandard digital cameras. Designed specifically

for machine vision applications, these products offer options such as

strobing and channel-switching between successive frames, which

conventional multimedia frame grabbers don't always do. On-board

display capabilities present images and graphics in a dedicated

optional display or in a picture-in-picture fashion on the host

PC/Windows display.


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With on-board input/output communications controlled by the on-

board, real-time operating system, plug-in systems also allow

straightforward integration with other equipment as well as control of

peripherals such as lighting without relying on the host PC and its

nonreal-time behavior.

Finally, on-board network connectivity simplifies deployment and

ensures participation in factory-floor networks and intranets. It also

supports innovative remote monitoring and diagnostics options.

3.3 Ease of use and deployment

Many users might be involved with the development, deployment and

day-to-day support of vision applications. Users range from factory-

floor operators and engineers -- who typically would set up, install or

modify vision applications -- to system integrators or OEMs, who

would create custom vision applications or even develop new vision

tools.

Ease of use no longer implies just a top-level, point-and-click

graphical user interface but also multilevel, comprehensive access for

all expected system users and skill levels. Newer systems'

intelligence reduces the need for inordinate vision-processing

expertise and minimizes application development and deployment

time.

Most state-of-the-art vision systems include built-in graphical user

interfaces and comprehensive run time or monitoring environments.

These allow systems to select jobs, start and stop inspections, adjust

inspection parameters, access reports and statistics, and capture and

log failed-part images or other data.


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At one level down, manufacturing engineers who set up or configure

vision applications do so in an intuitive environment, using high-level

tools as opposed to low-level image-processing and analysis

operations.

Describing a vision application program as a sequence of steps and

using high-level, application-oriented tools -- as opposed to low-level,

image-processing or analysis operations in a conventional

programming language -- is now a widely accepted approach.

Implementing such tools on high-performance platforms has

increased these tools' robustness and intelligence, while limiting the

need for users' vision expertise. This trend certainly will continue in

the future.

At the system's lowest level, system integrators or OEM users can

develop customized user interfaces quickly and, in some cases, add

to the system's functionality by working in industry-standard,

software-development environments. One recent development in this

area, which promises faster application deployment for system

integrators as well as faster time to market for OEMs, is component-based software. Such software encapsulates core vision system

functions required to develop and deploy vision applications.

In a Microsoft Windows environment, these components are

developed as ActiveX controls (formerly OCXs or OLE custom

controls). A vision application deployment component, for example,

would encapsulate all functions related to training or trying out a job.

Another deployment component would encapsulate all functions

related to loading a job, and starting, stopping and monitoring an

inspection. It's now possible to create or customize vision applications

without knowing much about vision system internals by dropping


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such basic building blocks inside a custom graphical user interface

developed using Visual Basic or Visual C++.

3.4 The future is now

The hardware and software trends highlighted above will continue

and even intensify in the future. Faster hardware, more intelligent

tools and better application software development and deployment

environments all will enable a broader and deeper proliferation of

machine vision in manufacturing.

However, through recent positive advances in price, performance,

robustness and ease of use, vision technology now has reached a

point very close to what the vision industry and marketplace

projected as a distant promise a few years ago.

At the same time, the last 15 or 20 years of vision applications on the

factory floor has educated manufacturers about optimal vision-

system uses, and these application boundaries continue to moveoutward. Manufacturers now consider machine vision not as a

research curiosity but rather a mature tool for manufacturing

automation.

Although potential users may want to wait for the future's inevitable

new technology -- including faster hardware and more intelligent

software -- the recent vision technology developments mentioned in

this article imply that the future is now, and it's an exciting time for

vision users and suppliers


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APPLICATIONS OF MACHINE VISION

4.0 Introduction

The applications of machine vision (MV) are diverse, covering areas

of endeavor including, but not limited to:

Large-scale industrial manufacture

Short-run unique object manufacture

Safety systems in industrial environments


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Inspection of pre-manufactured objects

Visual stock control and management systems

Control of automated guided vehicles

Quality control and refinement of food products

Retail automation

Machine vision systems are widely used in semiconductor fabrication

semiconductor fabrication indeed, without machine vision, yields for

computer chips would be significantly reduced. Machine vision

systems inspect silicon wafers, processor chips, and subcomponents

such as resistors and capacitors.

In the automotive industry, machine vision systems are used to guide

industrial robots, gauge the fit of stamped metal components, and

inspect the surface of the painted vehicle, weld seams, engine blocks

and many other components for defects.

Though machine vision techniques were developed for the visible

spectrum, the same processing techniques may be applied to images

captured using imagers sensitive to other forms of spectra such asinfrared light or x-ray emissions.

The following examples of specific applications indicate the diverse

nature to which machine vision technology can be applied. These

examples fall under the ambit of one of the above mentioned areas

4.2 Examples of MV Applications

Synergy between Solar Cell And Machine Vision Technologies

Machine vision inspection has been used to provide real-time process

feedback in the manufacture of solar cells, while solar cell technology


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has been used to develop a machine vision sensor which offers

exceptional dynamic range for demanding vision applications.

Machine Vision Gives Optometrists a Clear View

The international glasses manufacturer Rodenstock, Germany, has

developed an optometrist service terminal called ImpressionIST that

enables the adaptation of glasses regarding the individual

parameters and center data in an absolutely unstrained atmosphere.

Innovative 3D images (MV application) determine the facial

measurements, comfortably and accurately giving the optometrist

the information they require and the customer a view of themselves

in their new glasses.

Placing Of Foldable Plastic Spoons in Convenience Snacks

A specialist supplier of plastic injection moulded components for the

food industry approached RNA Automation Ltd. to automate a

production line for disposable plastic spoons. Some of the industries

largest food and snack manufacturers use this type of spoon in ready

meals and convenience snacks. For this particular project a foldable

spoon needed to be placed into a cap, the cap is supplied to a

manufacturer of milk based fast foods. A disposable plastic spoon is

very difficult to orient due to the design of the moulding especially at

120 parts per minute. The solution chosen was a vision guided

robotic system equipped with an RNA step feeder, (MV application) a

bulk storage hopper and a 6 axis robot.

Vision-Guided Robots Help Automate Vial and Syringe FillingAutomated Systems of Tacoma, Inc. (AST) was asked by a life science

research company to develop an alternative to conventional

pharmaceutical filling machinery having the capability to fill and

finish all their small-scale clinical trial products with a single flexible

platform. To solve this problem, AST had to develop a machine with


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the flexibility to be able to handle various sizes of prefilled syringes,

vials, cartridges and IV bags with minimal product changeover times.

The basic concept is a system that positions ready-to-use nests of a

particular container within the operating envelopes of two robots, the

Cognex In-Sight Micro vision system is used to precisely locate each

container and stopper and provide the robots these locations prior to

processing.

The Power in the Wind Using MV Technology

Larger and larger wind power turbines are bringing the forces of

nature under control. The main structures, the powerful tower and

rotors, are supported by parts that play a less obvious, but no lessimportant role: bolts. As simple as it may look, precision tightening of

bolts is an art form of its own. Intellifast GmbH is now ensuring

perfect support in any weather using ultrasound permanent sensors

and Data Matrix codes and reading the codes with the DataMan 100

from Cognex.

360 View Provides Extremely Fast Surface Check

In a strained economic situation, it is more important than ever to be

able to optimise processes and make them more efficient. The Expert

ETK inspection system, integrated with Cognex OmniView

technology, combines many different quality control requirements

into just one compact system.

There have been two key challenges to implementing machine vision

to aid in the quality control of labels on cylindrical objects. First,

vision systems require the bottles be consistently aligned within the

labelling machine, and second, labelling machines offer unfavourable

ambient conditions and lack appropriate space within to contain the

vision system. But now, the innovative OmniView vision technology


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from Cognex integrated in the Expert ETK inspection system from

Syscona Kontrollsysteme and Weber Systemtechnik has a 360

complete view of the bottle surface which provides new potential for

the inspection of bottle features with much greater reliability.

Vision Sensor Helps Automate High-Speed Loading Of

Transparent Cartons

A major beverage manufacturer uses transparent cartons to package

its bottled drinks so that their distinctive branded labels are visible to

consumers. However, the need to orient the bottles so that the right

part of the label is visible makes automated packaging a challenge. In

the past, bottles were filled on an automated line, and a team of 15

people were tasked with manually loading and orienting the bottles

into the transparent cartons. Recently, this beverage producer

became the first to successfully automate high-speed carton loading

with the use of a bucket autoload cartoner from AFA Nordale

Packaging Systems, which uses Cognex Checker vision sensors to

orient the bottles before they are placed in the cartons.

Cameras Sort Rice and Beans

A vision system will trigger air-jets at specific points to blast out the

unwanted beans or rice, broken beans or rice, or extraneous items

such as rocks or bugs. Since rice or beans are a consumable product

quality sorting is very important. Accuracy is paramount as no one

wants to bite into a rock or consume any bugs. Speed is very

important also since large volumes of product must be sorted

efficiently.


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Custom Cameras Classify Plastic Pellets Precisely

In the recycling of plastic products, incoming plastic is ground into

flakes, washed and dried, and, converted into pellets. These pellets

are manufactured by melting the plastic and then extruding and

cutting the plastic material into small, uniform pieces. Once

manufactured, these plastic pellets must be sorted before they are

sold to manufacturers to be made into new products, such as bottles

and trash bags.

Vision System Measures Scallops

Between July and August each year, the US National Oceanic and

Atmospheric Administration (NOAA) Fisheries Service conducts

surveys to determine the abundance and size distribution of deep-sea

scallops. To do this, sample height measurements from 125,000

scallops are taken from approximately 500 randomly selected

locations. To increase the accuracy and speed of these

measurements over current methods, William Kramer, an IT specialist

at the NOAA Woods Hole Laboratory on Cape Cod, obtained a Pioneer

Funding grant from the Chesapeake Bay Trust to develop a prototype

machine-vision system.

Inspecting Turbine Blades In Aircraft Engines

Turbines that are housed in aircraft engines are subjected to pretty

tough conditions. They must perform at speeds of 30 thousand rpm in

temperatures greater than 800C for hours at a time. The engine

manufacturers fully understand that even small surface defects can

reduce performance, increase maintenance costs, and reduce the

useful life of an aircraft engine. They need to inspect turbine blades


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very carefully to maintain the efficiency and reliability that the air

transport industry requires. One particular North American

manufacturer inspected its blades by hand and human eye. The

highly-trained inspectors measured hundreds of features and

checked for surface defects at depths in the order of thousandths of

an inch. Manual inspection was not only costly in terms of time and

labour, but subjective as well. Results were variable and even

differed between inspectors. Finally, because manual inspection was

so time consuming, there was no systematic inspection of every

blade; only a sampling of blades was inspected. The manufacturer

required an approach that would allow systematic inspections of the

blades, save time, and yield consistent and repeatable results.

Vision Automates Parking Surveillance

Instead of looking on parking fees and fines as a cash cow, some

enlightened cities attempt to balance their needs with those of

business owners and residents. Fredericksburg, VA is one city that

revolutionized the way it manages parking. By adopting an

automated parking system using a vehicle mounted vision system,

the city has enjoyed greater revenues, improved efficiency, and far

fewer complaints and repeat offenders.

Laser Marking and Image-Based Industrial ID Reader

An electronics manufacturer produces thousands of different part

numbers of electronic products intermixed on the same assembly

line. The difficulty in identifying parts, combined with the fast pace of

the line, resulted in a large amount of rework or scrap. The

manufacturer had experienced several hundred thousand dollars a

year in losses when incorrect parts were added to, and/or the wrong

operations were performed, on assemblies. The manufacturer asked

Claire Lasers for a solution. The manufacturer developed an


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application of the companys ClearMarka laser marking system that

added a motorized platform to move the Cognex DataMan ID reader

into position based on the location of the assembly.

5.0 CONCLUSION

Machine vision proves most successful in the controlled environment

of the factory floor, offering some important advantages over human

vision in terms of cost, speed, precision and physical demands.

Systems can:

Determine location or the position of an object.

Measure dimensions within thousandths-of-an-inch accuracy.

Count items such as pills in a bottle or cells in a petri dish.


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Identify or recognize an object.

Inspect objects and identify flaws in manufactured goods.

Verify that an object's quality meets standards.

Machine vision excels at locating and examining objects with hard,

well-defined edges and regular patterns. And its high-speed

processing capability gives it unquestioned superiority when it comes

to looking at parts on today's fast-paced production lines. Although

human inspectors can keep pace with visual inspection demands at a

rate of a few hundred items per minute, they also tend to get

fatigued and miss flaws. With machine vision, thousands of parts

often run past a camera per minute and resolve a dozen features on

each piece for product conformance -- all in a matter of milliseconds.

Machine vision systems ensure repeatable results and can run

continuously 24 hours a day, seven days a week.

The potential applications for machine vision reach far beyond even

those areas where human vision can be applied. These include

conditions where light levels are too low or too bright for human

vision, or where nonvisible electromagnetic radiation such as X-rays

or infrared is required. Machine vision systems can be applied in

manufacturing clean rooms and can survive environments too

hazardous for humans.

5.1 Cost Make or Buy Decision

Once manufacturers determine that machine vision can be an

effective tool for their application, they must decide the best path to

take in configuring a system. Larger companies with skilled

engineering staffs may pursue their own solution, assembling

components purchased from various vendors or even using new

technology. However, a steep learning curve, lack of industry


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standards and time-to-market pressures make the in-house approach

largely impractical. The vision system meant to add value to a

product can become a serious drain on time, energy and resources.

Expert help must be called in to solve the problem.

Outsourcing is a megatrend seen across all market segments as

companies find that purchasing a custom-engineered machine vision

system entails less risk than designing and manufacturing it

themselves. System integrators and value-added resellers have the

integration expertise necessary to provide application-specific

solutions based on a thorough review of the requirements. Many

specialize in serving a particular market niche such as foodprocessing or pharmaceutical manufacturing. This allows them to

focus their attention on a smaller range of needs.

Even then, putting together puzzle pieces from a variety of

component vendors remains a costly, time-consuming task, mainly

due to a lack of industry standards. According to industry analyst

Nello Zeuch of the Automated Imaging Association, the cost of

components accounts for less than one-third the cost of a machine

vision system. The rest goes toward custom development, system

integration and installation.

Moreover, the real costs of product development often hide in the

lost opportunity cost of not getting a product to market on time.

Studies show that, in today's fast-paced markets, the opportunity

cost of a six-month delay in product development can far exceed

both a 50-percent development cost overrun and a 10-percent

increase in manufacturing costs. With the help of an experienced

system integrator or VAR, schedules are more likely to be met.


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Having the support of an outside source -- long after a product

delivers -- adds another advantage. Many companies don't have the

in-house support required to get a system back up and running

should problems arise. Nor do they have the expertise necessary to

upgrade the system later with newer technology. A capable third-

party supplier may willingly take responsibility for the whole system,

providing an invaluable source of technical assistance and advice.

5.2 Future of MV

Historically, machine vision has been most successful in applications

where it was integrated into the production process. For example,

guiding machines or closing a control loop. But, while vision guidance

has proved its worth in placing surface-mount components on printed

circuit boards, most users would hesitate before investing in a

machine vision inspection station to catch defective parts on an

existing production line.

However, continuous improvements in cost, performance, algorithmic

robustness and ease of use have encouraged vision systems' use ingeneral manufacturing automation. Further advances in these areas

will characterize the future of machine vision and result in more

vision systems on manufacturing floors during the next few years.

What characteristics will describe future vision systems? They must

include three characteristics in order to be useful in most

manufacturing industries. First, they must be fast enough to keep up

with ever-increasing production rates. Second, they must be intuitive

and easy to use. Finally, they must be intelligent enough to deal with

part-to-part or other process variations.


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While vision technology might not have reached this point yet, recent

advances in the vision industry have helped facilitate and accelerate

vision applications in manufacturing for the near future.

The hardware and software trends highlighted above will continue

and even intensify in the future. Faster hardware, more intelligent

tools and better application software development and deployment

environments all will enable a broader and deeper proliferation of

machine vision in manufacturing.

However, through recent positive advances in price, performance,

robustness and ease of use, vision technology now has reached a

point very close to what the vision industry and marketplace

projected as a distant promise a few years ago.

At the same time, the last 15 or 20 years of vision applications on the

factory floor has educated manufacturers about optimal vision-

system uses, and these application boundaries continue to move

outward. Manufacturers now consider machine vision not as a

research curiosity but rather a mature tool for manufacturingautomation.

Although potential users may want to wait for the future's inevitable

new technology -- including faster hardware and more intelligent

software -- the recent vision technology developments mentioned in

this write-up imply that the future is now, and it's an exciting time for

vision users and suppliers.


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6.0 REFERENCES

http://whatis.techtarget.com/definition/0,,sid9_gci212508,00.html

http://www.answers.com/topic/computer-vision

http://en.wikipedia.org/wiki/Machine_vision

http://www.vimatic.com.my/machinevision

http://www.microscan.com

http://www.ni.com/vision
http://whatis.techtarget.com/definition/0,,sid9_gci212508,00.htmlhttp://www.answers.com/topic/computer-visionhttp://en.wikipedia.org/wiki/Machine_visionhttp://www.vimatic.com.my/machinevisionhttp://www.microscan.com/http://www.ni.com/visionhttp://whatis.techtarget.com/definition/0,,sid9_gci212508,00.htmlhttp://www.answers.com/topic/computer-visionhttp://en.wikipedia.org/wiki/Machine_visionhttp://www.vimatic.com.my/machinevisionhttp://www.microscan.com/http://www.ni.com/vision


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http://www.cognex.com

Article from: Product Line Card 2009 Microscan Systems, Inc. ML006A

05/09

Article from: Mechanical Engineering-CIME, Article date: July 1, 1992, Author:

Puttre, Michael, see http://www.highbeam.com/doc/1G1-12525307.html
http://www.cognex.com/http://www.highbeam.com/doc/1G1-12525307.htmlhttp://www.cognex.com/http://www.highbeam.com/doc/1G1-12525307.html

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