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3D vision automates seal integrity inspection

A major food processing company packages a number of different products in heat-sealed bags. The potential exists for food particles to be trapped in the seal. In some cases these particles can form micro channels large enough for bacteria to enter the package. Contaminants are tiny and are often hidden by the seal, which has made it difficult for successful inspections by 2D vision systems.

Cognex Figure 1
Cognex Figure 1

PFM Integrators addressed this challenge by developing a vision application in which a robot passes one bag every second in front of two Cognex DS1100 3D vision systems placed opposite to one another. The vision systems accurately measure the surface profile of each bag. These measurements are used to determine the thickness of the seal and identify any thickness variations that may indicate a failure in the integrity of the seal, such as contaminants stuck in the seal, for example. This application has helped the food processing company increase the safety of its products while reducing labor expenses by reducing the need for manual inspection.

Some food processors have experimented with conventional 2D machine vision to inspect the seals. “When this particular food processor tried inspecting the seals with 2D machine vision, the vision system either rejected every bag or let every bag pass depending on how the vision system was calibrated,” says Ken Baych, President of PFM Integrators. “The problem was that the contaminants trapped in the seal did not provide a sufficient visual signature to be detected by 2D vision systems. A couple of years ago we evaluated the use of 3D vision systems to inspect the seals but at that time the cost of 3D vision systems was so high that we felt they would not be able to provide a sufficient return on investment.”

Over the last few years a new generation of 3D vision systems has appeared on the scene that uses laser triangulation to extract 3D information from parts at a considerably lower cost than the 3D vision systems available in the past. “The vision systems used in this application cost only about one-half of the amount of those that we evaluated in the past,” Baych said. The new 3D vision systems use a laser range finder to project a beam onto the object to be measured. The image sensor captures a three dimensional point cloud of data to calculate the points of the object. This point cloud of data can be used to measure 3D and 2D features such as length, width, height, tilt, or volume. It can be used to detect defects, or presence or absence of features, or raised or embossed characters against a low-contrast background.

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