This document discusses the industrial application of machine vision. It begins with definitions of machine vision and descriptions of its key components like light sources, lenses, sensors, and processing units. It then explains the basic working principle of how a camera captures an image of an object, the computer analyzes the image characteristics, and communicates acceptance or rejection. Some common application fields are listed as automotive, electronics, food, and manufacturing. Specific applications like measurement, counting, location, and decoding are then described in more detail with examples. The document concludes that machine vision provides benefits like speed, consistency, reliability, and ability to operate in hazardous environments.

1. INDUSTRIAL APPLICATION OF
MACHINE VISION
BY
ANIL BADIGER
On
20 Feb 2016
UNDER GUIDENCE OF
Prof. MURALI M. AMBEKAR
Asst. Prof., Dept. of Mech. Engg.
KLECET, Chikodi
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2. CONTENTS
Definition
Components of machine vision
Working principle
Applications of machine vision
Advantages
Conclusion
Reference
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3. MACHINE VISION
The process of extracting information
from visual sensors to enable
machines to make intelligent decision.
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4. COMPONENTS OF MACHINE
VISION
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5. COMPONENTS OF MACHINE
VISION
Light source-LED, Fluorescent,
Halogen lamps
Lens – Telecentric , Macro lens
Sensors – Optic ,Magnetic type
Vision processing unit
Communication unit
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6. WORKING PRINCIPLE
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7. WORKING PRINCIPLE
1. A camera takes a picture of the object to be
tested in the presence of lens with suitable
intensity of light source, and sends it to a
computer for image processing.
2. The computer will define and analysis the
characteristics of image.
3. After analysis the computer system will
communicate with rejection unit if any
defects in the part, or else if it is defect free
it will send to the next station for
processing.
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8. APPICATION FIELDS
 Automotive
 Electronics
 Food
 Logistics
 Manufacturing
 Robotics
 Packaging
 Pharmaceutical
 Mining
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9. APPLICATIONS OF MACHINE
VISION SYSTEM
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10. MEASUREMENT
In measurement applications the purpose of the vision system
is to measure physical dimensions of the object. Examples of
physical dimensions are distance, diameter, curvature, area,
height, and volume.
Example: A camera measures multiple diameters of a
bottleneck
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11. COUNTING
 Counting is another typical machine vision application
 Basically counting means look for number of parts over
number of features on a part, this allows us to locate
missing part and ensure the products are assembled
properly.
Example 1: counting of holes on the aluminium
flange.
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12. COUNTING
Example 2: Identifying the presence or
absence of the part.
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13. LOCATION
Machine vision also used to report the
location and orientation of the parts.
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14. DECODING
 It is an identification application in which the
vision system reads various codes and alphanumeric
characters (text and numbers) and decodes the codes
to get the product features .It is used to record
information as historical data, track products
,validate data, verify correctness of data and verify
the product.
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15. ADVANTAGES
Machine vision system works more faster
than manual system.
Machine vision is consistent.
Perform beyond human vision
High repeatable in controlled environment
No fatigue – 24/7
Reliable
Good for unsafe and hazardous
environment
Operate well in space constrained
environments
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16. ADVANTAGES
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17. CONCLUSION
Machine vision is less risky, reliable to
use.
It enables high speed examination of
defects in products.
The quality products can be obtained
by
the incorporation of machine vision
system.
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18. REFERENCE
[1] Sathiyamoorthy, S (MAY 2014) “INDUSTRIAL APPLICATION
OF MACHINE VISION” Volume: 03 Special Issue: 07
Retrieved from
http://www.ijret.org
[2] Remigiusz Labudzki, Stanislaw Legutko (2009) “APPLICATION
OF MACHINE VISION” Retrieved from
http://www.fvt.tuke.sk/../2-pp-27.pdf
[3] Web link: http://www.microscan.com accessed on 15/2/2016
[4] Smith C J and Adendorff K (JUNE 1991) “ADVANTAGES AND
LIMITAIONS OF AN AUTOMATED VISUAL INSPECTION
SYSTEM”
Retrieved from
http//sajie.journals.ac.za
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19. THANK YOU
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