Choosing The Right Machine Vision Applications Session2Choosingthe

Track, Trace & Control Solutions

Choosing the Right Machine

Vision Applications

Part 2 of a 3-part webinar series: Introduction to Machine Vision

About your Instructors

Dr. Jonathan Ludlow

Machine Vision Product Manager

Juan Worle

Technical Training Coordinator

Today’s Objectives

By the end of this webinar, you will know:

How to identify a good Machine Vision application

and which applications to avoid

Machine Vision hardware platforms and what to

consider when choosing one for an application

Today’s Topics

Today we will discuss:

Successful Machine Vision Applications

Challenging Machine Vision Applications

Application Examples

Machine Vision Hardware Platforms

Successful Machine Vision Applications

As a new user, you should choose an application that will not be overly complex.

Successful applications have the following attributes:

1. Looking for a single decision point

2. Clear application requirements

3. Application is consistent

4. Parts are high value or critical

5. Some false rejects are OK

1. Looking For Single Decision Point

The inspection will look for good and bad, rather than sorting through

parts.

Good vs. bad applications have a single decision point

Failures should be clearly visible

Some sorting is OK –(but not much)

GOOD vs. BAD: Reject defective product

SORTING: Identifying each

battery type and vendor by

shape, color, and text

2. Clear Application Requirements

The application requirements have been clearly defined.

The list of requirements is small, such as fitting on a single page

Samples of good and bad parts are available

The part to be inspected has a beginning and end, rather than continuous

Inspection requirements

should be one page

Avoid continuous web

inspection

Samples of good and bad

parts should be available

3. Application is Consistent

The parts are always positioned the same way, at the same distance

from the camera, with consistent lighting.

Designing tight application parameters allows a simple Machine Vision system.

Good applications include consistent

part shape, positioning, and lighting.

Organic items are inconsistent in

size and shape; items randomly

placed are difficult to locate.

4. Parts Are High Value or Critical

The value of the part is high, or the consequence of a flawed part is

high.

Low Consequence High Consequence

High Value

Low Value

5. Some False Rejects Are OK

The price for catching all the defects may be some false rejects. The

customer will need to make a decision on what will be the acceptable

level of rejects.

Ideally, there is a large separation

between good and bad parts.

As good and bad parts appear to be similar,

some false rejects must be acceptable to

catch all the bad parts

As good and bad parts become more

similar, the grey area becomes larger

Challenging Machine Vision Applications

Applications that are not impossible, but are specialized and time

consuming:

1. Non-industrial applications

2. Organic materials applications

ANYTHING IS PO$$IBLE!

Time consuming projects cost money

Consider the Return on Investment (ROI)

1. Non-Industrial Vision Applications

Machine Vision is a specific branch of Vision that is specialized for

industrial applications.

Pursue these applications: Industrial, Manufacturing

These types of applications typically follow the 5 guidelines we

discussed earlier.

Non-industrial applications include: Medical, Scientific, Security,

These applications have different requirements and use different

tools.

Security, Scientific and Medical applications have

specific challenges that take a lot of time to overcome.

2. Organic Materials Applications

Organic materials are inconsistent in size and shape -Difficult to

identify and inspect.

Avoid forest products, wood, vegetables, sorting trash

Watching vegetation grow

is not an ideal application

Sorting trash is

hard work!

Application examples

Ideal Machine Vision applications:

–There is a part handling solution in place

–Application can be replicated over 20 lines

–You are inspecting/gauging expensive parts

–There are good and bad parts available for evaluation

–The inspection/gauging criteria can be expressed in numbers

Challenging Machine Vision Applications:

–The application is inspecting plastic knives and forks

–The “spec” is a book with fuzzy pictures of bad parts

–The current process is manual

Ideal Machine Vision

applications have criteria

expressed in numbers

Ideal Machine Vision Applications

Here are a few examples of successful applications for new users.

These applications have the traits of a successful application:

1. Looking for a single decision point

2. Clear application requirements

3. Application is consistent

4. Parts are high value or critical

Read barcode and check label position Count that 3 bolts installed Validate 2D and OCR data

Measure part to tolerance

Machine Vision Hardware Platforms

Hardware Platforms for Machine Vision Applications

Smart camera:

Integrated Machine Vision

solution

PC Based:

PC-based image processing

using cameras for acquisition

Smart Cameras: Integrated Solution

Smart cameras can vary in processor power and capabilities. Be sure to match

the smart camera with the application.

Sometimes includes integral lighting and lens

Vision processing is done in the camera

Good for a single or few tasks with moderate processing speeds

Single camera operation, no multiple camera operations

Fewer I/O points, less sensor options

A computer is only required for programming. When programming is complete,

the smart camera can run on its own.

Benefits of a Smart Camera:

•No PC on the floor

•Compact

•Low cost

•All-in-one

Smart Cameras:

Includes lighting, lens,

sensor, Image processor,

and I/O

PC-Based Solutions

GigE Machine Vision uses a camera transporting the image over Gigabit

Ethernet to a PC for vision processing.

Fewer system components than frame grabbers

More processor power than smart cameras

Multiple cameras in a single inspection

More I/O points than smart cameras

PC required for operation

GigE:

Ethernet transports an image into a PC

Similar configurations: USB, IEEE1394, 10/100 Ethernet, Frame Grabbers

I/O Expansion:

PC-based Machine Vision like

GigE and frame grabbers allow

for more I/O

LIGHTS!

The Machine Vision platforms discussed today did not include Machine

Vision lighting.

To learn more about Machine Vision lighting, visit www.microscan.com

and select Training/Lighting.

Learn about:

–Geometry

–Feature analysis

Geometry

Feature Analysis

–Lighting types

–Effect of lighting

Introduction to Machine Vision for New Users

Conclusion

When entering the Machine Vision world, consider applications for:

Measuring, Decoding, Counting and Locating.

By following the guidelines discussed here, your first Machine Vision

applications will result in success and low maintenance.

Other types of applications are not impossible or unsuccessful, but they are

highly specialized and sometimes require specific equipment or other tools.

Selecting the right platform for an application is a balance between cost,

performance and portability.

Don’t forget to visit www.microscan.com to view training courses about

Machine Vision Lighting.

Let us help you define an application and hardware platform!

Thank you!

For More information

Website: www.microscan.com

–Online courses

–Spec sheets

– Technology Brochures

– Support Self-help and support request form

Instructors:

Juan Worle, Technical Training Coordinator

Email: jworle@microscan.com

Dr. Jonathan Ludlow, Machine Vision Product Manager

Email: jludlow@microscan.com

Feedback on this webinar: www.microscan.com/feedback

Additional contacts:

Additional product information: info@microscan.com

Training: training@microscan.com

Support: helpdesk@microscan.com

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