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Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

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Page 1: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Vision-Based Metrology

IET 405

Vision Based Metrology Project

Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Page 2: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Vision-Based Metrology History

• Vision-Based Metrology refers to the technology using optical sensors and digital image processing hardware and software to:– Identify

– Guide

– Inspect

– Measure objects

Page 3: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Vision-Based Metrology History

• Vision-Based Metrology inspection systems evolved from the combination of microscopes, cameras and optical comparators

Page 4: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Vision-Based Metrology History• Vision-Based Metrology is

extensively used in general industrial applications such as the manufacturing of:

– Electronics– Automotive– Aerospace– Pharmaceutical– Consumer products

• Vision-Based Metrology is being utilized in the automatic identification and data collection market as a complementary or alternative technology to traditional laser scanning devices for reading bar codes

Page 5: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Vision-Based Metrology History

• Early systems were integrated into packaging lines for optical character recognition and proved to be a reliable way to check the accuracy of product codes and label information.

• Today, high-resolution cameras, advances in software and imaging processors, and the availability of powerful, inexpensive compact computers have made vision systems faster and more reliable than ever.

Page 6: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

When does a company need a vision system?

• Some products require 100-percent product inspection with documented inspection results.

• In other cases a vision system may be needed for high production product inspection

• Vision systems provide a means of increasing yield-that is, the ratio of good parts to bad parts.

• When a serial defect is spotted, the system not only recognizes it but can stop the conveyor and inform the operator of the defect and its magnitude.

• The yield factor is particularly important in manufacturing industries that produce large volumes, as in the compact disc and pharmaceutical industries.

Page 7: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Vision-Based Metrology inAutomobile Wrecks

• Vision Based Metrology is now being used to focus on the movement of objects along with their deformation

• This is being used in many car wreck investigations

Page 8: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Vision-Based Metrology in Automobile Wrecks

• Two consecutive images were grabbed from a high speed video sequence

• A displacement field of a car at a certain moment is presented

Page 9: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Vision-Based Metrology in Automobile Wrecks

• The deformation pattern was obtained from the principle vector analysis.

• This analysis allows the representation of the deformation pattern.

Page 10: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Vision-Based Metrology in Weather Patterns

• Vision-Based Metrology has also been used to study weather patterns

• Flow information from a tornado is able to be extracted for scientists to attempt to learn more about them

Page 11: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Vision-Based Metrology in Companies

• There are many companies that use vision inspected systems today

• Some of the bigger ones are ICS/INEX and PPT Vision

Page 12: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

ICS/INEX• INEX can be traced all the way

back to the early 1900’s when they developed a system called OPTI-Tron which inspected bottle beverages

• The OPTI-Tron system would eventually become the OPTISCAN bottle inspector; a worldwide standard in container inspection with thousands of units installed.

• The introduction of the company's SuperInspector 1055 became the first commercial machine inspection system to integrate camera and computer technologies

Page 13: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

PPT Vision• Founded in 1982, PPT specializes in

industrial applications where accuracy, repeatability, high speed and flexibility are important requirements.

• They are the world leader in the design and manufacture of completely digital 2D machine vision systems.

• PPT's 2D machine vision product line is sold on a global basis to end-users, system integrators, and OEM's

• PPT is involved primarily in:– Electronics– Semiconductor components– Automotive– Medical devices– Pharmaceutical and packaged goods

Page 14: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Quality Inspection at Work

Polymer Membrane:Note texture defects

Machined Aluminum Bar:Note tool-chatter marks

Stamped Metal Package:Note scratch on grinded surface

Page 15: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Vision System PicturesMissing Fuse

Page 16: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Golf Ball Specifications

• Weight: Less than or equal to 1.620 Ounces

• Size: Greater than or equal to 1.680 Inches

• Shape: Must be symmetrical

Page 17: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

USGA Golf Ball Testing

• A ball passes USGA size inspection if it falls, under its own weight, through a 1.680 inch diameter ring gauge fewer than 25/100 times in randomly selected positions.– Temperature is constant at 23° C (73.4 ° F).– Humidity is held constant.

Page 18: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Test Outline

• Random sample testing for different brands of golf balls

• Determine diameter

• Analyze the results

Page 19: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Procedure• Place the ball on the test stand• Take a picture from a standard height for each golf

ball being tested• Analyze the image using National Instruments®

vision analysis software• Compare the image to the standard size for the

USGA ball specification• Compile and analyze the data from the testing

– Present information in graphical form

Page 20: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Test Device• Designed using Solidworks® CAD program

• Made of extruded aluminum

• Center positioned ball holder that provides consistent images for each ball tested

• Camera is secured using the tripod mount

Page 21: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Final Drawing

Page 22: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Test Device

Page 23: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Images from National Instruments® IMAQ Vision Builder

Page 24: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar
Page 25: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Images from the Vision Software

Horizontal Clamp Horizontal and Vertical Clamp

Page 26: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Golf Ball Analysis

Clamp Method

Ball #1 was standard of 1.681 inches

1 Precept MC 937.6 940.2 938.9 1.6812 Precept MC 937.7 938.8 938.3 1.6803 Precept MC 937.8 938.6 938.2 1.6804 Precept MC 937.8 939.8 938.8 1.6815 Precept MC 937.1 939.6 938.4 1.6806 Precept MC 938.2 939.5 938.9 1.6817 Precept MC 939.7 942.3 941.0 1.6858 Precept MC 938.3 940.2 939.3 1.6829 Precept MC 938.2 940.7 939.5 1.682

10 Precept MC 938.4 940.1 939.3 1.68211 Titleist 931.9 932.1 932.0 1.66912 Nike 933.8 932.4 933.1 1.67113 Nike 937.0 935.7 936.4 1.67614 Molitor 936.4 936.0 936.2 1.67615 Laser ACRA 945.2 942.3 943.8 1.69016 Top Flite Strata 936.9 939.4 938.2 1.68017 Top Flite XL 934.3 936.3 935.3 1.67518 Pinnacle 934.4 937.4 935.9 1.67619 Pinnacle 933.6 936.4 935.0 1.67420 Callaway Blue 935.6 936.0 935.8 1.67521 Tour Select UD 939.3 939.9 939.6 1.68222 ProStaff BiMetal 937.0 936.7 936.9 1.677

Average 937.1 938.2 937.7 1.679St. Dev. 2.694 2.752 2.604 0.005

3 s 8.083 8.256 7.812 0.014

USL 945.7 948.5 946.7 1.695LSL 929.5 931.9 931.1 1.667

Overall Diameter Average in pixels

Average Size in inchesBall # Ball TypeHorizontal Diameter in

pixelsVertical Diameter in

pixels

Page 27: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Ball Sizes

1.6551.6601.6651.6701.6751.6801.6851.6901.695

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Ball #

Siz

e in

In

ches

Page 28: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Deviation from 1.680

-0.015

-0.010

-0.005

0.000

0.005

0.010

0.015

Inch

es

Page 29: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Measurement Data

• Able to see variance between different golf balls

• Tolerance we detected was about 1.680 ± .010 inches

• The device performed as expected to allow us to complete the vision analysis

Page 30: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Conclusion

• Vision systems are a reliable way to accurately measure items

• A vision system can measure minute details to a precise and accurate level

• We were able to observe this with golf balls varying just a few pixels

• We now have a better understanding of vision systems and how they work

Page 31: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

http://www.cranfield.ac.uk/sme/amac/research/metrology/tornado.htmhttp://www.cranfield.ac.uk/sme/amac/research/metrology/carcrush.htmhttp://www.qualitydigest.com/mar98/html/vision.html http://www.rvsi.com/Pages/about.htmhttp://www.inexvision.comhttp://www.pptvision.comhttp://www.visionxinc.com

References

Page 32: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Acknowledgements

Alufab® located in Mt. Carmel, OhioDonated materials for the prototype

Donated their shop and tools for the construction

Special thanks to Dr. Allameh for allowing us to use his software and office for this project

Page 33: Vision-Based Metrology IET 405 Vision Based Metrology Project Bill Redman, Matt Herms, Matt Waldner, Brad Neufarth, Jason Marlar

Questions?