Using 3D Laser Scanning to Analyze Paint Defects on Metal Surfaces

A Midwest USA manufacturer produces roll-up doors and purchases pre-extruded metal strips, or slats, which are prepped and painted prior to assembly. The manufacturer approached Futura Automation, LLC 's Don Nedved looking for a solution to their quality concerns. The paint process consists of layers of paint and is finished with a clear coat. After the paint/clear coat process, the slats are assembled into a complete door and visually inspected by humans for paint defects and dents in the metal. #Paintdefects are typically dust particles in the clear coat and are observable to the human eye. But many times such defects at such a low height profile can barely be felt by the human touch.

These slight defects are now identified after assembly so in order to preserve the resources already expended on the finished assembly, the defects are wet sanded and polished manually. It’s no surprise this process is the bottleneck of daily finished product throughput. The customer is looking for a solution to inspect the painted surface and either A) remove defective slats from the assembly process for automated resurfacing, or B) use a robot or cobot to locate and re-surface the defective areas by sanding or buffing.

Futura Automation, in partnership with laser inspection expert, Jake Haefner, has designed a solution which can easily find and identify anomalies in the painted surface, both particles in the clear coat as well as dents. (It’s been proposed to scan for dents prior to any finishing process.) First, here are greyscale and height images of one of the painted pieces. We will be utilizing the #LJX8080 and 3D controller for this application. This model is accurate to 12.5 microns, or about 1/8th?of a human hair. All the tools and processing power needed for this application are contained within the controller. The system will only require a monitor for viewing the images and data.?

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Below is a zoomed in view of a defect as well as a 2D profile across the defect that shows the width and height measurement on a color-scale covering a span of 300 microns (-14.7mm to -14.4mm).

Our defect tool captures the height data and then converts it to shades of grey (typically illustrated as colors for better human understanding) so that we can identify contrast. It’s complex technology, but essentially the tool takes a height range, let’s say for example 0mm to 1mm, and assigns the lowest value, in this example 0mm, to shade “0” or fully black and assigns the highest value, 1mm, to shade “255” or fully white. The height data in between the lowest and highest height is then assigned to shades of grey between shade “0” and shade “255”. Based on this height data converted to shades of grey, the laser scanner can identify certain contrast changes to find defects like scratches, dents, and bulges, and foreign particles. Below is an image of a painted part a plus sign marking the defect we taught the system to identify. We can adjust the segment size (Defect size) and defect level (Defect depth) to only pickup defects that are considered to be unacceptable. We can also set limits on the size and quantity of defects on the part.

Below is a contrast view of the defect. This is representative of what the profiler actually sees when identifying the defect and judging it.

We have attached a few more images of various defects we scanned and their profile view. If you would like Futura Automation to scan your parts to find defects, we are happy to conduct a Proof of Concept prior to developing your production system.