TECHNICAL SEMINAR ON

3D MACHINE VISION SYSTEM AS SHOP FLOOR METOLOGY TOOL

INTRODUCTION•Modern day durable goods manufacturing

have begun to embrace the concepts of digitization as a means to improve productivity and quality.

•This is the area where machine vision based tools start to excel.

•Machine vision in general has been used for everything from guiding the insertion of electronic chips on circuit boards to inspecting bottles at several per second in bottling lines.

WHAT IS MACHINE VISION?• A machine vision system consists of computer hardware and software working

together with cameras and lighting to capture images of objects for the purpose of making a quality control decision.

• When the image is captured and stored in memory, it is algorithmically compared to a predefined image or quality standard in an effort to detect defects or anomalies.

• Using machine vision technology for purposes of inspection and quality control enables manufacturing companies to prevent defective products from being shipped to customers and to improve their manufacturing processes and reduce costs.

• Machine vision systems at that time were complex in programming and maintaining, difficult to install, limited in performance and not cost-effective.

WHAT IS MACHINE VISION? Contd…..• Vision based smart camera solutions are primarily targeted at

providing manufacturers with 100% inspection in high speed, discrete part manufacturing applications.

• This typically replaces older off-line random sampling techniques or human vision inspection techniques as a means of monitoring quality.

• Therefore, our IMPACT machine vision based smart cameras are a key technology in enabling manufacturers to achieve zero defect production.

MACHINE VISION STAGES

Analog to digital conversion.

Remove noise/patterns, improve contrast.

Find Regions (objects) in the image.

Take measurements of object/relationship.

Match the above description with similar description of known objects.

Image Acquisitions (by

cameras, scanners etc)

Image segmentation

Image ProcessingImage

RestorationImage

Enhancement

Image Analysis(Binary Image

Processing)

Modern Matching Pattern

Recognition

DISCUSSION OF TECHNOLOGIES

There are currently three basic approaches to three-dimensional machine vision:

• Range finding including structured lighting

• Stereo or binocular vision

• Gray scale or range finding methods

1.Range finding including structured lightingTriangulation Method

Figure 1. A triangulation based system using a point of light to obtain distance. The effects that may be seen from a laser beam reflecting off a rough surface include:  Directional reflection due to surface ridge Expansion of the incident laser spot due to micro surface piping

A synchronized scanning system, limited the range of view

Active triangulation system, seeking laser point, providing extended range.

•2D V/S 3D MACHINE VISION

• 2D Machine Vision

2D vision systems use area scan or line scan cameras and appropriate lighting to measure the visible characteristics of an object such as:

• quality of surface appearance• edge based measurements• presence and location of features

2D Applications include:• food sorting of color, shape, and size• automotive parts needing location and presence

• 3D Machine Vision

3D vision systems use a specialized high speed camera and a projected laser line to measure the physical deviations of an objects surface such as:

• Volume• Flatness or shape• Density

3D Applications include:• Volume, size and shape measurements of baked goods or

produce• Completeness of molded parts• Flatness of stamped washers

APPLICATIONS

Adhesive Bead Inspection

High resolution, continuous inspection of height, width and volume of adhesive beads.•Control of shape and position of glue bead on the carrier part •Delivers robust, process-sure, reproducible measured data independent of ambient light effects and of exact positioning of carrier part Color/glance of adhesive or carrier surface has no influence on the measurement

Weld Seam Inspection

3D high resolution, continuous inspection of height, width and position of weld seams• Control of shape and position of seam •Delivers robust, process-sure, reproducible measured data independent of ambient light effects and of exact positioning of seam •Color/glance of seam has no influence on the measurement •Can be combined with an IR inspection system for extensive detection of faulty areas

Component Inspection

3D machine vision cameras for automatic quality control during the assembly steps in the production line.

Surface Inspection

3D Inspection of wood surfaces

•Wood knot detection •Inspection of wood geometry •Texture control

•Character recognition on railway rails

Tire and Rubber Inspection Using 3D Machine Vision

Industrial 3D machine vision on "difficult" materials such as tires and rubber.

•Simultaneous acquisition of intensity and height data •Uniform illumination of the measurement surface •Structures and patterns are clearly recognizable

These multi-camera vision systems are able to be customized and feature Vision Gauge On Line machine vision software which includes many tools to produce an inspection program that yields reliable results:

• Object Counting and Sizing / Blob Analysis • Part Identification • Defect / Flaw Detection • Presence / Absence Detection • Image Processing and Analysis • Automated Measurements • Optical Character Recognition and Verification • Pattern Matching and Part Location • Alignment and Registration • Color Verification

CONCLUSION

• As with any technology of this nature, the performance changes with the component technology.

• The primary advance that has made machine vision systems feasible for shop floor gauging applications has been the speed up in computing power.

• The other technologies that are influencing performance today include lower cost, digital cameras than provide better light range and pixel resolution with lower noise, and better light sources such as higher power laser diodes well as high

REFERENCES

• ASME Journal of Machine Design• "Machine Vision Based Gaging of Manufactured Parts," K.

Harding, Proc. SME Gaging '95, Detroit, Nov. 1995.• “The Promise of Machine Vision,” K. Harding, Optics and

Photonics News, p. 30 May 1996 Optical Society of America• "Light Source Design for Machine Vision", Eric J. Sieczka and

Kevin G. Harding, SPIE Proceedings Vol. 1614, Optics, Illumination and Image Sensing for Machine Vision VI, Boston, Nov. 1991.

• L. Bieman, "Three-Dimensional Machine Vision," Photonics Spectra, May 1988, p. 81.

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