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Defect detection on painted surfaces

Defect detection on painted surfaces

17 November 2010

On 28 October 2010, Micro-Epsilon was proud to present a local workshop for the company’s robot-based system reflectCONTROL. This newly developed measurement technology monitors paint defects on car bodies following paint line processing. Forty well-known guests throughout the world registered for the presentation of the new system. Amongst others, Micro-Epsilon welcomed participants from BMW, Daimler, MAN, Toyota and VW. At the very beginning, Mr. Dipl.- Inform. Univ. Achim Sonntag, Managing Director of Micro-Epsilon Systemtechnik provided a brief introduction to the company and moved on to a live demonstration of a customer’s system, which was subject to preliminary acceptance. The way reflectCONTROL recognises defects and how it can be integrated into the production process was shown in detail. In the afternoon, Mr. Dipl.-Ing. Hannes Loferer (Product Manager Surface Technology) explained how the system works and its cost-effectiveness. This presentation also explained how costs can be significantly reduced as a result of minimised error frequency while achieving higher surface quality.

With its innovative, robot-based inspection system reflectCONTROL, Micro-Epsilon enables companies to recognise defects in painted surfaces. Furthermore, the system is able to record these defects, after which they can be marked on the vehicle. Compared to conventional visual inspections, the system shows very high defect recognition rates, whilst offering maximum reproducibility and availability. Even production volumes of 40-60 vehicles per hour, with paint defects down to 0,3mm in size, can be detected during inspection. In order to ensure these reliable results, reflectCONTROL is integrated to four robots, which work in parallel on a single production line. All systems are equipped with a large monitor and 4 cameras. However, inspection lasts less than 1s, each camera taking 8 pictures per measurement position. Therefore, in the case of normal robot operating speeds, approximately 30 positions can be detected within 60 seconds. By using 2 megapixel cameras, approximately 7 billion grey values are generated, which are then recorded for each vehicle and processed immediately. This process takes place in a separate system thanks to an optimised software application.

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