Application: Presence Verification
Inspection
Challenge:
A manufacturer
needed to inspect automotive insulation panels. They wanted to check
that all the holes were in place, and needed to verify that the
area of the panel was correct within +/- 0.5mm. They were also checking
for rips in the material.
Need to verify
and assess:
- Check to see if there are the correct number of holes.
- Check for any missing material (rips).
- Measure the area.
Machine
Vision Solution:
The following
DT Vision Foundry Tools were added to the Point and Click Script
to solve this inspection challenge:
- Avi Player Tool – This tool shows a variety of images for display
purposes. It is ideal for rapid prototyping because it is fast
– in a run-time operation, it would be replaced with the more
sophisticated Picture Tool, which takes the image of the product
in order for the measurements to be processed.
- Blob Analysis Tool – The tool will be used to threshold the
image to check for the number of holes in the image. It is also
checking for the total perimeter of the image.
- If Then – This tool will determine if the product is a pass/fail.
In this case if the number of holes = 14 then it was classed
as a pass. If the number of holes is not equal to 14 then it
would be a fail as displayed on the screen shots below. This
also works for the perimeter. If the perimeter is over/under
a certain number then we know that a piece of material is missing
or there is a cut in the material.
- Text Tool – This tool visually displays the results of the test.
- Status Tool – This tool also displays the PASS/FAIL results
and will also show the pass/fail rate, variables and will also
save any images either passed or failed to a folder for later
failure analysis to be completed.
The
screen shot below shows that the image has been captured from a
camera and has been displayed upon the screen in a view port. The
screen first shows that the Blob AnalysisTool found the material
and performed a threshold, which has resulted in the number of holes
and the perimeter of the image being found. However, as can be seen,
the Blob Analysis Tool found more holes than the specifications
have allowed. In the center of the image, there is an extra hole.
The Blob Analysis Tool picked this up and reported back.
The information
was then passed to the If Then Tool, which will then let the system
know whether the panel is a Pass/Fail. As can be seen, the Text
Tool has shown that there is a “Hole Failure” but the panel has
the correct perimeter.
The
screen shot below shows the same program with another panel in front
of the camera. This time it is a perfect panel. The Machine Vision
System then completes the
The
screen below shows the user that there is a very good GUI (Graphical
User Interface) available within the package. This Status Tool shows
the user all the vital information that is needed for the quality
inspection of their product to be as efficient as possible. The
statistics shown are as follows:
- Pass or Fail sign (green or red respectively).
- Pass/Fail percentages.
- Variables that the user is looking for.
- The ability to save all the statistics and pass/failed images
for later failure analysis inspection.
- Warnings e.g. in case there are 5 failures consecutively.
The
screen above shows that the product has passed. The GREEN indicator
on the front of the Status Tool displays this.
The screen below
shows that the product has failed. The RED indicator on the front
of the Status Tool displays this.
As
can be seen, the system has found that there are too many holes.
From then on,
there are a number of scenarios that can be implemented. The Digital
I/O tool can signal the user’s PLC to operate a robot to discard
the failed articles and to let the passed articles carry on down
the production line.
The I/O tool
can even make the production line stop if there are any faults found
with the products that are being checked.
Result:
The Data Translation
machine vision solution automated the inspection process, resulting
in improved quality and efficiency for the manufacturer.
