A

Seminar Report

0N

AUTOMATED OPTICAL INSPECTION

By

NITIKA JAIN

DEPARTMENT OF ELECTRONICS & COMMUNICATON ENGINEERING

GOVIND BALLABH PANT ENGINEERING COLLEGE

PAURI,GARHWAL(246001)

[2010-2011]

A

Seminar Report

On

AUTOMATED OPTICAL INSPECTION

In partial fulfillment of requirements for the degree of

Bachelor of Engineering

IN

ELECTRONICS & COMMUNICATION

ENGINEERING

SUBMITTED TO: SUBMITTED BY:

Dr.A.K.Gautam Nitika Jain

Associate Professor Roll No.:31

EEED, GBPEC ECE,IV Year

Pauri, Garhwal GBPEC,Pauri Garhwal

CERTIFICATE

This is to certify that the Seminar entitled “AUTOMATED OPTICAL INSPECTION”

has been submitted by NITIKA JAIN under my guidance in partial fulfillment of the

degree of

Bachelor of Engineering in Electronics & communication Engineering Technology

of G.B.Pant Engineering College during the academic year 2010-2011 (Semester)

Date: 1-09-2010

Place: Pauri,Garhwal

GUIDE HEAD OF DEPARTMENT

Dr.A.K.Gautam Dr.Y.Singh

Associate Professor Professor

EEED,GBPEC EEED,GBPEC

Pauri,Garhwal Pauri,Garhwal

I/C PRINCIPAL

COL(Dr.)Jasbir Singh Virk(Retd)

G.B.Pant Engg.College

ACKNOWLEDGEMENT

I would like to thank Mr. Y Singh, HOD ECE Department for providing us this valuable

opportunity of presenting the seminar on latest trends in electronics and communication

which has not only enhanced my knowledge about the subject but also increased my

confidence level.

I would like to convey my special thanks to Mr. A.K Gautam, Assistant Professor,

ECE Department for his valuable guidance and motivation. I express my sincere gratitude

to Mr. Manoj Kumar and Mr. Balraj for their co-operation.

I would also like to extend my cordial gratitude and regard to all my friends and

colleagues for their constant help and support. I am sincerely thankful to everyone who

has given me a part of his or her precious time for this seminar.

Nitika Jain

B.Tech (ECE - IV Year)

G.B.P.E.C., Pauri

PREFACE

This seminar is based on one of the latest trends in electronics,”Automated

Optical Inspection”. Automated Optical Inspection (AOI) is a powerful tool for assessing

workmanship compliance in Prototype as well as Production PCB assembly

environments. With advanced lighting, optics, and image processing capabilities, the

machines greatly enhance inspection repeatability, accuracy and throughput. AOI plays a

vital role in test strategies designed to ensure the highest possible quality throughout each

phase of a product’s life cycle.

Automated Optical Inspection (AOI) addresses ever-increasing density, diversity,

and quality requirements of PCBs by maximizing resources to increase production

efficiency in a competitive business that leaves little margin for error. AOI eliminates the

subjectivity and variability necessarily associated with manual visual inspection. Systems

are integrated into the automatic assembly processes to provide 100% visible component

and solder-joint inspection.

In this way AOI can be used to detect problems early in the production process.

Since faults cost more to fix later in the production process, it is essential to notice

problems early. For example, problems in the solder and assembly area of a PCB can be

seen early in the production process and information used to feedback quickly to previous

stages, avoiding the production of too many boards with the same problem.

Low costs and programming efforts make AOI a practical and powerful quality

tool for both prototypes and high-volume assembles. It is often paired with the testing

provided by boundary scan test, in-circuit test, x-ray test, and functional test. In many

cases, smaller circuit board designs are driving up the demand for AOI versus in-circuit

CONTENTS

Introduction-The Miniaturisation Era

Background

Evolution of AOI Power

Automated Optical Inspection

Process

I. Light Source

II. Capturing an Image

III. Programming

IV. Data Collection

V. System Memory

VI. System Speed

VII. System Accuracy

Axis

Lens Quality

Types Of AOI Machines

Inspection in Surface Mount Technology

Bare PCB Inspection

Applications Of AOI

AOI Repair Station

AOI Market

AOI Core Technologies

AOI Developing Strategies

Advances in applying AOI

The Zero Defect Production Line

Conclusion

References

INTRODUCTION

THE MINIATURISATION ERA

Over the past ten years, we have seen tremendous changes in our lives with the

introduction of a range of various portable devices for consumers such as mobile phones,

PDAs, MP3 players and GPS’, as well as the integration of more electronics in medical

devices like pacemakers or hearing aids. These devices integrate more and more

functions in smaller packages to satisfy our increasing demands for performance or

comfort. In this environment, The Electronics industry had to adapt to develop new PCBs

(Printed Circuit Boards) which could be integrated into these products. The race to build

smaller and smaller PCBs is long running, demanding the smallest component. The

smallest of these: 01005 component packages are now enabling further dramatic savings

of space and weight on the PCBs.

At first, 01005 components were predicted to be restricted principally to medical

applications where the key driver is size, not cost. Now, on reaching their production

stage, their cost has dramatically reduced and now they are widely integrated into many

consumer devices. Compared to their closest relative, the 0201 component packages,

which are 2.25 times bigger, they are only around 25 times more expensive, which makes

them more interesting now as their price drop down fourfold since their introduction.

Fig1. Evolution of passive packages size over the years

Almost invisible to the naked eye (0.2 mm x 0.4 mm) and extremely lightweight (0.004

mg), 01005 represent a real challenge for assembly. Qualified production sites are

capable of producing PCBs with 01005 passive components, but they all face increased

difficulties. The assembly process becomes a headache due to their extremely small size

where rework is near impossible.

In the past two decades, traditional industries have lost their competitiveness due to the

low profit rate. Meanwhile, due to the advent of emerging technologies, many hi-tech

new industries have replaced them, such as the IC, PC/NB, LCD, communication,

NEMS, etc. In those hi-tech industries, in addition to the main in-line fabrication

equipment, the off-line inspection equipment is also indispensable to guarantee product

quality. In order to detect the dimensions and the defects of the hi-tech components, in

accordance with the trend of high throughput and high resolution, the AOI equipment is

the necessary tool.

In most domestic hi-tech industries the AOI equipment is imported. In view of the

technology need, AOI consists of the integration of mechanical-electrical-optical-

information technologies. It is possible to promote a new AOI industry through the

integration of its strong background in mechatronic technology in positioning stages with

the optical image processing techniques. The market requirements are huge not only in

domestic need but also in global need. This is the main reason to promote the AOI

research for the coming years. Focused industrial applications will be in IC, PCB, LCD,

Communication, and MEMS parts.

BACKGROUND

The past half decade has seen Automated Optical Inspection, and to a lesser extent X Ray

Inspection, of printed circuit boards being adopted by a wide diversity of electronics

manufacturers worldwide. These companies are ranging from large multi national

organizations, initiating and leading the trend, to small and medium sized enterprises

more and more commonly following this lead. Both customer tiers are seeing knowledge

and insight of internal quality levels steadily rise as a result.

Prior to the commencement of this adoption process only manual, sample based and non

real time estimates of manufacturing quality levels and understanding of defect root

causes was possible. However, with AOI technology today it has become feasible to use

this type of sensor as an efficient tool for significant increase in defect coverage and also

as a source for providing reliable, real time information on process health and possible

existing, and future, line problems.

The versatility of AOI is impressive, seen in terms of its ability to provide efficient and

cost effective defect containment while in addition, at the same time, offer the possibility

to collect critical assembly data. This wide spectrum of assembly data in turn creates a

plethora of opportunities for line and process information to be derived and analyzed

thereof, finally to be used in the improvement procedures of end product quality and

process performance.

Today, despite a rapid and still accelerating adoption process of AOI in manufacturing

environments of very diverse profiles and characteristics, the use of AOI primarily as a

tool for the basic gauging of quality levels and simply providing test coverage still

dominates.

Undeniably, however, through technology advances by the same leading multi national

manufacturers once pioneers in implementing AOI, most of whom are predominantly

working with very challenging process and quality targets in terms of end product

performance, including complete assembly traceability, a new approach to using AOI is

gaining ground.

Remarkably accelerating is the use of AOI as a means of understanding where in a

manufacturing process defects are occurring, preferably before actual bad board build.

THE EVOLUTION OF AOI POWER

With Automated Optical Inspection equipment being able to leverage more powerful

hardware technology, as well as the progress in optics and processing power; full

advantage can now be taken also of software progress in technology since the late last

decade. Sophisticated, intelligent software tools were created to assist in the increasingly

refined use of AOI, as a superior process improvement tool.

Preconditions have indeed changed dramatically to open the doors for this kind of mature

and intelligent use of a cost effective, versatile, process sensor such as AOI.

With critical hardware building elements having undergone dramatic development in

terms of reliability, cost of goods and capability in the past decade, all possibilities exist

today for the AOI to advance equally dramatically in terms of potential and power as a

process improvement tool in manufacturing.

Also, with hardware power dramatically advancing, possibilities opened for the creation

of matching software tools – for the first time with the ambition and target to monitor the

manufacturing process itself, rather than merely offer information on how well, or indeed

poor, quality levels and end product yields actually were.

AUTOMATED OPTICAL INSPECTION

.Automated optical inspection (AOI) is an automated visual inspection of a wide range of

products, such as printed circuit boards (PCBs), LCDs, transistors, automotive parts, lids

and labels on product packages or agricultural products (seed corn or fruits). Visual

inspection is a common method of quality control, data acquisition, and data analysis.

Visual Inspection, used in maintenance of facilities, mean inspection of equipment and

structures using either or all of human senses such as vision, hearing, touch and smell.

Visual Inspection typically means inspection using raw human senses and/or any non-

specialized inspection equipment. Inspections requiring Ultrasonic, X-Ray equipment,

Infra-red, etc are not typically considered as Visual Inspection as these Inspection

methodologies require specialized equipment and training. In case of PCB-inspection, a

camera autonomously scans the device under test (DUT) for variety of surface feature

defects such as scratches and stains, open circuits, short circuits, thinning of the solder as

well as missing components, incorrect components, and incorrectly placed components.

Agricultural inspections might check for variations in part color, perhaps to find ripe

fruit. AOI is a type of white box testing. It is commonly used in the manufacturing

process because it is a non-contact test method. AOI is able to perform most of the visual

checks performed previously by manual operators, and far more swiftly and accurately.

AOI systems are implemented at many stages through the manufacturing process. They

are used for inspecting parts that have limited and known variations. For defect or flaw

detection, the AOI system looks for differences from a perfect part. There are systems

capable of bare board inspection, Solder Paste inspection (SPI), as well as inspecting the

component placement prior to reflow, the post-reflow component conditions, and post-

reflow solder joints. These inspection devices all have some common attributes that

affect capability, accuracy, and reliability. In this way AOI can be used to detect

problems early in the production process. Since faults cost more to fix later in the

production process, it is essential to notice problems early. For example, problems in the

solder and assembly area of a PCB can be seen early in the production process and

information used to feedback quickly to previous stages, avoiding the production of too

many boards with the same problem. Automated Optical Inspection (AOI) uses lighting,

cameras, and vision computers to make precise, repeatable, high-speed evaluations of a

wide range of products. Human vision has limited accuracy and is slow, but is very

flexible and easy to train. Mechanical gauging is accurate and precise but slow, and

cannot be used to evaluate changes in visual appearance – burn marks, for example.

A machine vision or AOI system can take millions of data points (pixels) in a fraction of

a second. These data points are used for visual inspection and for precision measurement.

With modest effort and cost, an AOI system can resolve about 25 microns. With

increasing effort and cost, measurement resolution can approach a micron.

Low costs and programming efforts make AOI a practical and powerful quality tool for

both prototypes and high-volume assembles. It is often paired with the testing provided

by boundary scan test, in-circuit test, x-ray test, and functional test. In many cases,

smaller circuit board designs are driving up the demand for AOI versus in-circuit test.

Fi

g.2Assembly line of SMT placement machines

PROCESS

A machine vision or an AOI system can acquire millions of data points (pixels) in a

fraction of a second. These data points are used for visual inspection and precision

measurement. AOI visually scans the surface of the PCB. The board is lit by several light

sources and observed by a scanner or by a number of high definition cameras. This

enables the monitoring of all areas of the board, even those hidden in one direction by

other components. It should be noted that each manufacturer of AOI systems utilizes

different inspection algorithms and lighting techniques, each of these systems may have

varying strengths and weaknesses depending upon the item/product it is inspecting.

LIGHT SOURCE

Lighting preprocesses the image to amplify features that need to be inspected and

suppress noise. Advances in lighting have improved the capabilities of vision systems, in

part by reducing the computation required by the vision computer. In essence this means

that the lighting combinations ideally will improve the image quality to improve the

efficiency of the AOI system's decision making process. Most AOI systems will have

predefined lighting combinations depending upon the mode of operation and type of

product being inspected, these combinations will require no user interaction and the

system software/algorithms will manipulate and choose the best image for analysis.

However some customization is often required and with that these systems will provide

interfacing for the end user. The test engineer has the option to choose which light source

to use for the lighting: a LED, fluorescent light, or in certain industries other light sources

such as IR or UV. This depends on the area to be inspected, industry, and other variables.

Some users believe that LED light measures post-print solder brick height more

accurately than a fluorescent light source. This accuracy also makes LED light a good

tool for post-reflow solder joint inspection. Fluorescent light, on the other hand is

excellent for inspection of component placement pre-reflow but is typically used for

location inspection only. The problem with it is that because of the frequent light changes

the fluorescent lamps can degrade quickly. For these above reasons LED lighting has

become very popular among most AOI companies in the PCB industry. The adoption of

standard LED-based lighting has improved AOI systems because it is very stable and

easily controlled when compared to older incandescent and fluorescent lighting. LEDs

are not perfect: they become darker with age, but this can be easily compensated for by

increasing the amperage to the LED or group of LEDs. Another lighting method projects

a pattern of light on an object, often by using a laser with a holographic lens or a white

light source with an attached projection grid. The distortions of this structured light

pattern can be measured and processed to recover the object's 3D structure. AOI systems

using structured light can, for example, compare complex objects such as engine blocks

or PCBs to the designed shape in CAD files. These techniques in the PCB industry are

referred to as laser triangulation and phase shift profilometry Profilometer respectively.

Both are valid techniques for acquiring three dimensional (3-D) information from the

PCB. The position of the light sources and laser inside the machine are important. Angles

of approach are calculated into the inspection algorithms providing enhanced accuracy of

the measurements. Also the angle of approach can be particularly important in certain

applications because surrounding objects may interfere with the light approach to the

target object. An example would be a tall component on a circuit board that blocks the

visual approach of the light/camera system to the target component or solder deposit for

example.

Lighting the part is critical for AOI. Obviously the AOI system has to be able to see the

parts and features to do the inspection. Beyond this, lighting is used to amplify features

(part structure) of interest and suppress visual features that are “noise”. For example,

many products reflect the light sources, causing bright highlights in the image. Highlights

can obscure features in the image that we want to inspect. The cameras are set at an angle

such that they can see both the top and sides of the part, but there is no highlight. This

allows the visualization and detection of fine cracks in the part as well as “chip outs”

along the top edge. Staging and lighting are critical for an AOI system because they

reduce variability in part images and act as pre-processors to select image data for the

vision computer. Without this pre-processing, the vision computer would be too slow or

unable to do the inspection. You may be able to use an AOI system that has built-in

staging and lighting, but often these have to be designed for your AOI task. A variety of

standard lights and mechanical components help with this task.

CAPTURING AN IMAGE

If a scanner is used it has to scan the surface of the PCB from above only once. If image

cameras are used, one must first determine the number of cameras needed. There are

systems with only one camera which scans the DUT from above and systems with a

couple of cameras from all sides. To be able to scan the device from all points of view,

the cameras should be able to move in both X- and Y-direction controlled by software.

To program this software the test engineer must have the CAD data. Then the type of

cameras must be chosen. There are several types in use today. Streaming video 2D frame

grabbers are common. They utilize a motion capture video camera that extracts one frame

from a streaming video and creates a still image. However, the system sacrifices image

quality for speed and efficiency. A second type of camera imaging system is the Line

Scan Still Image Camera. In this system, a still camera is placed relatively close to the

target. Because of this, this system requires a very good lighting system. Unfortunately,

the image can be distorted by subsystem imperfections such as transporter movement.

This makes obtaining precise positioning and measurements difficult when compared to

other types of systems. A benefit of the Line Scan Still Image Camera is the image

acquisition speed, which is faster than a CCD camera. Another camera imaging system is

the 2D Charge-coupled device or CCD. The CCD is used for high-end and special

applications such as space and military technologies. This system creates high precision

still images in color that are more accurate than other systems. Each industry is different

in how image acquisition signals are transferred to the camera. It can be hardware driven

via a mechanical signal such as a proximity sensor, laser interruption, drive system

encoder position, or software. Regardless of the signal the AOI system interprets the

signal which triggers the vision assembly (which could be a single frame grabber and

camera combination or more advanced as already discussed) that the object is in a known

location and to begin image acquisition. The vision computer then triggers the

camera/cameras to simultaneously acquire images of the device.

The camera’s lens forms an image of the bottle on the camera’s sensor, typically a CCD

or CMOS image array sensor. Inexpensive “machine vision” quality lenses are used in

this inspection, but inspecting small parts or high precision and accuracy measurements

requires more expensive lenses. Again, the optics may be included in the AOI system or

chosen for your specific task. The camera translates the pattern of light from the part into

an electronic image.

Cameras designed for AOI systems have square (1:1 aspect ratio) pixels to simplify

measurements, progressive scanning rather than interlaced scanning, a fast shutter and an

asynchronous trigger for acquiring images. The progressive scanning and fast shutter

reduce blurring of the part’s image due to movement of the part. The trigger is necessary

to synchronize the image acquisition with the presence of the part.

PROGRAMMING

The AOI system takes time to "learn" the object which in the PCB industry is typically a

circuit board. Several methods of learning exist but the two most common are image

matching and algorithm based. Image matching is when a "golden board" is introduced to

the system and the attributes of each component, solder deposit, etc are learned into the

system. This could include but not limited to color, white pixel count, dark pixel count,

transition points, and relative position of transition points. Image based systems require a

few example products typically to learn all possible variations. The other method is

algorithm based programming; this is where the user can apply rules and measurement

algorithms for inspection. Algorithm based programming typically also requires product

examples for programming but not usually as many as image based programming. There

are pros and cons for each technique which can include setup time, complexity of the

system, program transportability, time to generate a program, and call effectiveness. The

AOI system needs to be able to add the learned information acquired from the above

inspection techniques to its memory. It has to "remember" the different types of

components, their positions and also to check the quality of the soldered joints. It must be

able to recognize and adapt to differences in the appearances of the board resulting from

normal process variations, but must be able to recognize any that affect performance. To

achieve this it is normal to run a number of good boards (golden boards) through the

system before full production starts so that the system can "learn" the board. Currently

the best AOI machines can be set up relatively quickly and then they are reliably able to

inspect boards. This can be done by offline programming. This reduces production

downtime, and the programmer has time to enter accurate parameters without stopping an

assembly line. These systems also have a component database that saves data so that it

does not have to be entered every time a new board is produced. In case of automotive

parts inspection for example, the system should know what features to measure or for

sorting agricultural products the color of ripe fruit should be known.

DATA COLLECTION

To obtain the necessary data one can use 3D software imaging or LED light

measurements, which are common methods for measuring solder joint parameters.

Typical systems use both methods to obtain accurate measurements. These systems use a

directed light source or refracting light to measure height, area, and volume. The vision

computer and its software analyze data (images) and calculate statistical process control

(SPC) results in these areas. The results of the inspection are used to reject defective

parts. To reduce the computation required by the vision computer so that parts are

quickly inspected it is a good idea to use a type of mechanical restraint known as staging

or fixturing. The part is positioned in a known location and variability in where the parts

are and how they look is decreased. Other data collection concerns are factory software

integration of inspection results, how long to keep the data/measurements, and what data

is available. Each AOI system is going to vary in what is available and each industry and

customer will have varying needs. For example military and aerospace industries may

have the need to store data for years or until the expected end of life (EOL) of a product

while commercial manufacturing such as mobile phones may only require data for a few

weeks or possibly even just for that day or shift.

Using these new faster and more reliable methods leads us to the overall goal of what is

trying to be achieved by implementing vision. That is the collection of data both on the

machine for immediate process intervention, on the rework station for repair and analysis

of defects and even further, the implementation of a true SPC Statistical Process Control

of the line.

SYSTEM MEMORY

System memory is also important. Upgradeable systems that have the capacity for

expanded memory are desirable. Databases expand every day particularly with the

increase in lead-free components, solders, boards and assemblies that are rapidly entering

the industry.

SYSTEM SPEED

System speed is influenced largely by the size and complexity of the boards being

inspected and the level of inspection. Control over the pace of the production line can be

influenced by the AOI system. Since one hundred percent inspection is not always

necessary, valuable time can be saved by dialing in the appropriate inspection level.

SYSTEM ACCURACY

The accuracy for finding defects such as missing components, skewed components,

reversed components, or wrong valued components depends not only on the capability of

the inspection system but also on the accuracy of the program supplied by the user.

Accuracy of inspection is becoming even more important with the smaller devices

especially in the PCB industry devices such as 0201 and 01005 resistors and capacitors

are so small that the human eye can not detect their presence or absence on a PCB. The

accuracy of AOI obviously becomes more critical when inspecting 01005 components.

To minimize false calls, then the AOI must be able to measure position extremely

accurately, which in turn allows the use of small, precise search windows.

Further, to examine solder joints, then the AOI has to be intelligent enough to relocate the

solder joint search window following the measurement location of the component.

AXIS

Linear motors with high resolution optical encoders are bringing the required accuracy

enabling the system to place the centre of camera FOV on a precise position and then

measure component position deviation. Axes themselves must be mounted within a stable

framework to ensure consistent performance.

LENS QUALITY

Even when FOV centre is placed on the precise position, if the optic system includes too

much error in the image compared to the real object, accurate inspection is not going to

be possible.

As most of AOI use bigger FOV for 01005 inspection to maximize inspection speed,

more and more AOI started to implement low distortion lens trying to solve image

problems inside FOV.

One must be aware that the quality of commercially available telecentric lenses is not

high enough for 01005 inspections. In fact, telecentricity is an essential property in

metrology to determine the precise size of objects independently from their position

inside the FOV and even when their distance is affected by some degree of unknown

variations, such as PCB warpage or dilatation.

Fig.3 Telecentric lens eliminates perspective distortion

Example – Grading CornThe AOI task in Figure 4, is to find the ratio of bad (dark) corn kernels to the total of

good (yellow and orange) and bad kernels. This ratio is used to grade seed corn lots – lots

with fewer bad kernels sell for more. A typical AOI measurement task assumes ridged,

well defined parts, and that any variation beyond some tolerance is a defect. Here, the

parts are not well defined in size and shape, so trying to use a caliper tool to measure

kernel size would be useless and frustrating. Instead, we use the known colors of good

and bad kernels to approximate the desired ratio.

The staging and lighting consists of the operator taking a scoop of corn from a lot and

spreading the kernels on a light table, such that kernels are not overlapping. As this is

done on sample evaluation basis, automating the staging is not worth the cost and effort.

What is critical is that the ratio measurement be consistent over time and across

operators. So the evaluation task must apply objective standards to classifying bad and

good corn kernel, perhaps so customers can’t argue about the grading!

We teach the AOI system the color and color variation of know good and bad corn

kernels and the color (white) of the background. The ratio we want is approximated well

enough by taking the ratio of pixels with bad colors to the pixels with bad or good colors,

ignoring the background colors. While not as exact as if we had counted each kernel, it is

a lot faster and removes the operator’s subjective judgment from the evaluation.

Figure 4. Using the color of the corn kernels as the visual inspection feature, we can

estimate the proportion of bad (dark) corn kernels. The inset image shows image areas

that have colors corresponding to bad corn kernels.

TYPES OF AOI MACHINES

STAND-ALONE AND INLINE AOI SYSTEMS

When using Stand-alone machines the PCB has to be inserted into and after the test taken

out of the machine manually. Inline systems on the other hand are part of the production

line so the PCBs move into and go out of the machine automatically.

CLOSED- AND OPEN-TOP AOI SYSTEMS

Inside Open-top machines the artificial light is distracted by light sources different than

the ones used by the system itself (eg. sunlight). Closed-top machines eliminate any light

pollution because they are closed from all sides. In this way only artificial light is

available inside the machine making these type of systems much more efficient.

AOI AND COMBINED AOI/AXI SYSTEMS

Today's AOI systems have the capability to inspect visible solder joints on capacitors,

resistors, and other components. However, without additional capabilities such as

Automated x-ray inspection (AXI), ball grid array (BGA) and "J" leaded components are

limited to polarity, missing, and placement error detection. That is why Combined

AOI/AXI systems can provide the necessary mixture for high-performance and are

becoming more and more popular.

INSPECTION IN SURFACE-MOUNT TECHNOLOGY

The growing demand for Surface-mount technology equipment is reducing the need for

expensive rework and repair while increasing throughput. As PCB assembly

manufacturers aim for a zero-tolerance regime, the demand for pre-solder paste and pre-

reflow optical inspection equipment that detect faults such as poor quality solder joints,

tombstoning, and other post reflow defects is expected to rise significantly.

Technological improvements in AOI equipment have resulted in higher throughput,

repeatability, and reliability as well as increasing quality and production yields for the

PCB assembly manufacturers.

AOI's for a PCB board with components may inspect the following features:

• Area Defects

• Billboarding

• Component offset

• Component polarity

• Component presence/absence

• Component skew

• Excessive solder joints

• Flipped component

• Height Defects

• Insufficient paste around Leads

• Insufficient solder joints

• Lifted leads

• No-population tests

• Paste registration

• Severely damaged components

• Solder bridges

• Tombstoning

• Volume defects

• Wrong part

BARE PCB INSPECTION

AOI for a bare PCB board inspection may detect these features:

• Line width violations.

• Spacing violation.

• Access copper.

• Missing pad. I.e. a feature that should be on the board is missing.

• Shorts circuits.

• Cuts.

• Hole breakage. I.e. a drilled hole (via) is outside of its landing pad.

The triggering of a defects report may be either rule based (e.g. no lines on the board

should be smaller than 50μ) or

CAD based in which the board is locally compared with the intended design.

This inspection is much more reliable and repeatable than manual visual inspection.

APPLICATIONS OF AOI

Typical applications for AOI include:

Gauging the diameters and concentricity of holes in automotive parts.

Insuring that lids and labels are properly applied to food and pharmaceutical

products.

Evaluating molded parts against 3D CAD data.

Insuring that all parts are present in a product assembly

Checking for cracks, flaws, contamination, scratches and other defects

Reading barcodes or text (“Optical Character Recognition”)

Grading agricultural products such as seed corn or fruit

From these applications you see that AOI systems are used for inspecting parts that have

limited and known variations. For defect or flaw detection the AOI system “looks” for

differences from a perfect part. Agricultural inspections might look for variations in

“part” color, perhaps to find ripe fruit. To successfully apply AOI, you must set up the

AOI system for specific types of parts and limit the visual appearance of those parts.

An AOI system must also be set up or trained to inspect specific structures (visual

“features”) of the parts. For example, you must tell the AOI system what features to

measure on an automotive part or teach it the color of ripe fruit for sorting agricultural

products.

AOI REPAIR STATION

Finding defects and showing data is one thing, but supplying additional data and

graphical help to the repair station operator is a necessary part of the AOI software.

Information must be clearly shown which will help the operator to decide what repair

actions are necessary and to be able to log them for future reference.

AOI MARKET

According to the ITIS survey, the global AOI equipment market is about 3.7 billion US

dollars in year 2004, and it will gradually increase to 6.5 billion US dollars in 2006.

Some emerging industries take the major share of AOI market. It is known that there are

many OEM industries fabricating systems and components for many world leading

companies, such as IBM, HP, Dell, Motorola, Nokia, etc.The annual report shows that in

year 2004 the overall domestic made AOI equipment was less than 10% of the total

domestic market. It is expected that there will be a large space for local AOI industry in

the coming years.

AOI CORE TECHNOLOGIES

Fundamental AOI technology consists of the following subsystems:

(1) precision motion controlled XY-stage,

(2) optical–mechanical system,

(3) image capture and processing system, and

(4) image analysis and error detection system.

All applications relate to dimensional measurement and defect detection. There are also

some other important technologies, such as AXI (X-ray), OCT (optical coherence

tomography), spectrum microscopy, etc. to be noted.

AOI DEVELOPING STRATEGIES

The task force of each working group is to form a strategic alliance among several

relevant AOI equipment makers and users. Each alliance will propose an integral

proposal to apply the government R&D sponsorship. Some common core technologies

will subcontract to research institutes for in-depth long period development, such as in

image processing software, lighting analysis, and precision XY-stages. Industrial

applications are focused on the following subjects: (1) 2D measurements— such as

line/pin width/spacing, ball/hole diameter/position, mask alignment, and geometrical

analysis, etc.

(2) 2D defect inspection— such as pattern recognition and defect classification for all

areas,

(3) 3D measurement-- surface profile measurements for meso-, micro-, and nano-scales,

such as the thin film thickness, spacer or ball height, substrate warpage, micro optics,

grooves, and free-form shapes,

(4) 3D defect inspection—such as inner defects detection using X-ray, OCT, fluorescent

light, etc. techniques for PCB, solder, BGA, etc.

The government’s role is very important to promote the birth of a new AOI industry. The

annual program budget will be allocated by each related ministry. The Ministry of

Economic Affairs takes the responsibility to invite AOI users to provide a site test

environment. The Ministry of Education and the National Science Council will launch an

ad hoc committee to encourage university/industry collaboration.

ADVANCES IN APPLYING AOI

Many of the problems in applying AOI arise from the limited intelligence and flexibility

of an AOI system. We can pick up a part, examine it with various views and lighting, do

an amazing amount of neural processing, and draw conclusions based on our extensive

knowledge about objects and the materials they are made from. An AOI system has to

rely on staging to present the part and has a limited time to examine the part. An AOI

system doesn’t understand objects and materials and has very limited processing

capabilities. Improvements in lighting, computing capability, and vision software have

made AOI systems smarter and more flexible, though still far from human visual

intelligence. I mentioned that lighting pre-processes the image to amplify features you

want to inspect and suppress “noise”. Advances in lighting have therefore improved the

capabilities of vision systems, in part by reducing the computation required by the vision

computer. The adoption of standard, LED-based lighting has improved AOI systems

because LED lighting is very stable and easily controlled, compared to the older

incandescent and fluorescent lighting solutions. For example, we can strobe an LED light

source to give a brief and intense flash of light that “stops” part motion. This is difficult

to do with older lighting technology. Another lighting method is to project a pattern of

light on an object, often by using a laser with a holographic lens. The distortions of this

“structured light” pattern can be measured and processed to recover the object’s three-

dimensional structure, at least what we can see of it. AOI systems using structured light

can, for example, compare complex objects such as engine blocks to the designed shape

in CAD files.

Another major boost to AOI systems’ intelligence comes from the rapid improvement in

personal computers. AOI tasks that previously required special computing hardware are

now done with generic PC hardware along with hardware for image acquisition,

communications, and synchronization. This is approach is used in ipd’s VA-40 Vision

Appliance. Demanding inspection tasks, such as inspecting LCD flat panel screens, still

require the “horsepower” of a dedicated vision processor, such as the DALSA Coreco

“Anaconda” board. The biggest advance in applying AOI is the improvement in the

vision computer’s software. In the not-so-good old days, you could expect to spend many

months laboriously programming the vision computer for your task. The thrust of recent

software development is to make this task much easier by providing interfaces to hide the

nasty hardware details and to incorporate the specialized knowledge needed to do AOI

tasks.

The mantras AOI vision computer vendors are currently “ease of set-up” and “ease of

use.” With a specialized AOI system, perhaps for three-dimensional measurement using

structured light, the set up and operator interfaces can be very easy to use because the

task domain is very limited and well specified.

If you need a custom AOI system, then you, an integrator, or a vision component vendor

have to write the AOI software. Rapid application development (RAD) packages, such as

ipd’s Sherlock™, make this relatively easy. These packages typically have an easy-to-use

interface with features such as drag and drop selection of tools and operations and

extensive, on-line help. If you need extra computing power or find the RAD package

limiting, there are many “mature” software libraries. Just be prepared for a long learning

curve. Many AOI tasks can be solved with a good set of general vision tools. These tools

include visual search (find the part in the image or finding a reference point on a part),

measurement tools (calipers, concentricity, distance, etc.), defect detection, and barcode

and OCR reading. Vision computer vendors have developed packages that bundle these

tools inside a graphical user interface.

There is no programming required and most of the specialized knowledge needed to

solve an AOI task is incorporated in the software.

THE FUTURE ZERO DEFECT PRODUCTION LINE

In order to take all of this one step further, a concerted effort by both the AOI

manufacturers and the other equipment suppliers must be undertaken. If we are to use the

data collected by the AOI system to create a zero defect line which is able to take

corrective actions automatically, it is necessary for the production machines both

upstream and downstream to communicate in real time with the AOI system. Imagine the

future capabilities, when due to information received from the AOI system the screen

printer can be informed that the stencil needs to be cleaned or the pick & place machine

can carry out an automatic calibration of the pick up head or the camera to nozzle offset.

Other specific production goals could be implemented such as in the case of mobile

phone production. One issue today, is the placing of shields on boards that have

placement or solder paste defects. In the future, the AOI could instruct the downstream

machine not to place a particular screen and identify the board on a panel that needs

repair before the shield is placed.

CONCLUSION

The use of 01005 components in production is steadily increasing. All steps in the

assembly of these small packages have to be optimized: from board design, through

component placement to the reflow process. AOI is also challenged by the use of 01005

but the technology is ready and available to achieve accurate component location and

reliable defect detection. As visual inspection and rework are not possible, AOI is no

longer an option in these SMT lines it becomes absolutely essential. The ideal scenario is

to implement AOI at each of the fundamental steps of the SMT line: post-print & pre-

reflow as a process control tool and postreflow as a quality keeper. To be reliable in the

01005 process, an AOI must be of the highest capability and equipped with powerful

solutions to overcome resolution accuracy and inspection throughput, as well as having

the capability to return reliable data to control and improve 01005 process. It is no longer

satisfactory to find defects with only image correlation. This does not stand as a solution

to overcome line demands in terms of both speed and accuracy. A combination of state of

the art algorithms with high performance optics and reliable hardware is the only AOI

solution to give the expected performances.

AOI has many applications, but is limited to well-specified parts in well controlled

settings. It would be nice to have an AOI system as flexible and as easy to train as a

human, but with the speed, accuracy, and resolution of a computer vision system. Such

systems are many years off, but that doesn’t discourage us from continually improving

existing AOI systems.

The three major efforts in putting together an AOI system are building the part staging,

getting the right lighting, and programming the vision computer.

Improvements and standardization of lighting and mechanical fixtures have made the first

two tasks much easier. The improvement in computing power and vision software,

particularly the focus on easy-to-set-up and easy-to-use vision software continues to

make it easier and easier to program the vision computer.

REFERENCES

• AOI-IEEE Xplore(Digital Library)-IEEE.org

• AOI Imaging Challenges-K V Hari-ece.iisc.ernet.in

• AOI Technologies-http://iopscience.iop.org

• AOI-Vi Technology,France-Peter Grundy &Mats Magnell

• Applying AOI-Ben Dawson-DALSA Coreco Inc.,ipd Group