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Vision Inspects Wall Plates in a Flash

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HANK HOGAN, CONTRIBUTING EDITOR

Wall plates are everywhere — covering electrical receptacles by the dozens in every home and by the hundreds in any moderately sized building. Therefore, wall plates are made in high volume and at low cost.

But these simple-seeming pieces of plastic can be a quality-control and inspection challenge. Wall plate dimensions for height, width, and thickness, for instance, must meet specifications.

There are also cosmetic aspects to consider, such as scratches. Since a wall plate can be highly visible, blemishes are a no-no in the high-end market targeted by SchoPlast Plastic GmbH. Based in Bischofswerda, Germany, the company makes 10 million wall plates a year, and it was manually inspecting them. SchoPlast has since deployed a machine vision-based automated system custom-developed by AUMO GmbH, a Dresden, Germany-based automation specialist.

The ‘cube’ hosts 10 Baumer CX cameras for quality inspection. The socket plates are picked from the bin and positioned on the conveyor belt (top left). According to the inspection result, the parts are then sorted into containers for ‘good’ or ‘bad.’ Courtesy of Baumer.

 
  The ‘cube’ hosts 10 Baumer CX cameras for quality inspection. The socket plates are picked from the bin and positioned on the conveyor belt (top left). According to the inspection result, the parts are then sorted into containers for ‘good’ or ‘bad.’ Courtesy of Baumer.

“The main intention in the system design was to detect exactly these cosmetic imperfections, which customers in the premium segment would not accept. Identification of functional defects, therefore, is secondary and a task easy to solve,” said AUMO managing director René Rösler.

Replacing manual inspection

SchoPlast had several reasons to move away from manual inspection. For one thing, there was the cost of the labor involved. Another issue was the error rate arising from assessing good parts as bad (a false negative) or classifying bad parts as good (a false positive).

Regarding the labor expense, the manual quality check used nine exper­ienced operators, three for each of the three shifts in SchoPlast’s 24-hour manufacturing. The inspectors had to be skilled because defects could be small, such as a barely visible scratch, or subtle, such as a discoloration.

As for inspection error rates, Rösler said each inspector tended to find a rather constant rate of parts not acceptable. The rate differed from one operator to the next. This inconsistency between individuals was a sign of subjectivity and possibly significant inspection errors.

In cases of false negatives, SchoPlast was throwing good wall plates away. But if the error was a false positive, the company was shipping less than optimum and possibly out-of-spec product to customers, potentially harming its reputation.

Seeking a solution to these problems, SchoPlast turned to AUMO. The automation company evaluated the situation, considering such aspects as the portion of the inspection that could be performed using machine vision, and under what kind of lighting.

“We elaborated solutions in theory, then prepared test setups for the individual testing tasks. The results obtained here underwent several cycles of evaluation and optimization,” Rösler said.

10 cameras, 2 PCs

After completing this development process, AUMO’s solution consisted of 10 VCXU-53M cameras from Baumer Ltd. of Friedberg, Germany. The cameras handled all the inspection tasks except for two performed by tactile sensors. The cameras can capture images at up to 73 fps and, importantly, are open systems without an integrated controller. This, Rösler said, enabled AUMO to tailor a solution for SchoPlast.

“We want to give our customer the opportunity to implement a solution in the existing environment, which will also meet possible future requirements,” he said.

Two industrial PCs controlled the cameras, lighting, and other aspects of the setup. The PCs also handled communications with SchoPlast’s plant IT network.

Cover plate type AS. Germany’s SchoPlast produces 10 million socket cover plates of various types per year. As of April 2018, quality inspection has been delegated to an automated inspection system developed by AUMO. Courtesy of Baumer.

 
  Cover plate type AS. Germany’s SchoPlast produces 10 million socket cover plates of various types per year. As of April 2018, quality inspection has been delegated to an automated inspection system developed by AUMO. Courtesy of Baumer.

While devising a manual inspection replacement, AUMO had to pay attention to interactions between elements of the solution. For instance, the final setup used both incident and transmitted light, illuminating the plates while they sat inside one of four measuring boxes. Ensuring that all defects could be picked up by vision systems meant brief but intense light inside the boxes. There was worry this would push the temperature above 65 °C, which would cause a problem for the cameras. However, testing showed a maximum temperature of 56 °C. Critically, this meant there was no need for active cooling, which would have driven up the solution’s expense and complexity.

Skilled operators have been freed up to perform tasks other than inspection, and quality control has improved.
Once completed and installed, the automated inspection setup sampled two plates from a bin every 3.67 s. Most of this time was spent handling the plates and moving them into position for a test. Evaluation by the PCs of the results ran about 600 ms, and exposure for the vision part of the testing ran less than half a millisecond, according to Rösler.

He said the 10-camera system has been in use for almost two years. Skilled operators have been freed up to perform tasks other than inspection, and quality control has improved. The exact bottom line impact is proprietary but the results are clear.

“SchoPlast’s expectations have been met,” Rösler said.

Vision Spectra
Spring 2020
GLOSSARY
machine vision
Interpretation of an image of an object or scene through the use of optical noncontact sensing mechanisms for the purpose of obtaining information and/or controlling machines or processes.
AUMO GmbHSchoPlast Plastics GmbHSensors & Detectorsmachine visionautomated inspection systemcamerasindustrialVision in Action

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